openapi: 3.0.0
info:
  title: OpenAI API
  description: The OpenAI REST API. Please see https://platform.openai.com/docs/api-reference for more details.
  version: 2.3.0
  termsOfService: https://openai.com/policies/terms-of-use
  contact:
    name: OpenAI Support
    url: https://help.openai.com/
  license:
    name: MIT
    url: https://github.com/openai/openai-openapi/blob/master/LICENSE
servers:
  - url: https://api.openai.com/v1
security:
  - ApiKeyAuth: []
tags:
  - name: Assistants
    description: Build Assistants that can call models and use tools.
  - name: Audio
    description: Turn audio into text or text into audio.
  - name: Chat
    description: Given a list of messages comprising a conversation, the model will return a response.
  - name: Completions
    description: >-
      Given a prompt, the model will return one or more predicted completions, and can also return the
      probabilities of alternative tokens at each position.
  - name: Embeddings
    description: >-
      Get a vector representation of a given input that can be easily consumed by machine learning models and
      algorithms.
  - name: Evals
    description: Manage and run evals in the OpenAI platform.
  - name: Fine-tuning
    description: Manage fine-tuning jobs to tailor a model to your specific training data.
  - name: Graders
    description: Manage and run graders in the OpenAI platform.
  - name: Batch
    description: Create large batches of API requests to run asynchronously.
  - name: Files
    description: Files are used to upload documents that can be used with features like Assistants and Fine-tuning.
  - name: Uploads
    description: Use Uploads to upload large files in multiple parts.
  - name: Images
    description: Given a prompt and/or an input image, the model will generate a new image.
  - name: Models
    description: List and describe the various models available in the API.
  - name: Moderations
    description: Given text and/or image inputs, classifies if those inputs are potentially harmful.
  - name: Audit Logs
    description: List user actions and configuration changes within this organization.
paths:
  /assistants:
    get:
      operationId: listAssistants
      tags:
        - Assistants
      summary: Returns a list of assistants.
      parameters:
        - name: limit
          in: query
          description: >
            A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
            default is 20.
          required: false
          schema:
            type: integer
            default: 20
        - name: order
          in: query
          description: >
            Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for
            descending order.
          schema:
            type: string
            default: desc
            enum:
              - asc
              - desc
        - name: after
          in: query
          description: >
            A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
            instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
            call can include after=obj_foo in order to fetch the next page of the list.
          schema:
            type: string
        - name: before
          in: query
          description: >
            A cursor for use in pagination. `before` is an object ID that defines your place in the list. For
            instance, if you make a list request and receive 100 objects, starting with obj_foo, your
            subsequent call can include before=obj_foo in order to fetch the previous page of the list.
          schema:
            type: string
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ListAssistantsResponse'
      x-oaiMeta:
        name: List assistants
        group: assistants
        beta: true
        returns: A list of [assistant](/docs/api-reference/assistants/object) objects.
        examples:
          response: |
            {
              "object": "list",
              "data": [
                {
                  "id": "asst_abc123",
                  "object": "assistant",
                  "created_at": 1698982736,
                  "name": "Coding Tutor",
                  "description": null,
                  "model": "gpt-4o",
                  "instructions": "You are a helpful assistant designed to make me better at coding!",
                  "tools": [],
                  "tool_resources": {},
                  "metadata": {},
                  "top_p": 1.0,
                  "temperature": 1.0,
                  "response_format": "auto"
                },
                {
                  "id": "asst_abc456",
                  "object": "assistant",
                  "created_at": 1698982718,
                  "name": "My Assistant",
                  "description": null,
                  "model": "gpt-4o",
                  "instructions": "You are a helpful assistant designed to make me better at coding!",
                  "tools": [],
                  "tool_resources": {},
                  "metadata": {},
                  "top_p": 1.0,
                  "temperature": 1.0,
                  "response_format": "auto"
                },
                {
                  "id": "asst_abc789",
                  "object": "assistant",
                  "created_at": 1698982643,
                  "name": null,
                  "description": null,
                  "model": "gpt-4o",
                  "instructions": null,
                  "tools": [],
                  "tool_resources": {},
                  "metadata": {},
                  "top_p": 1.0,
                  "temperature": 1.0,
                  "response_format": "auto"
                }
              ],
              "first_id": "asst_abc123",
              "last_id": "asst_abc789",
              "has_more": false
            }
          request:
            curl: |
              curl "https://api.openai.com/v1/assistants?order=desc&limit=20" \
                -H "Content-Type: application/json" \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "OpenAI-Beta: assistants=v2"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              page = client.beta.assistants.list()
              page = page.data[0]
              print(page.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              // Automatically fetches more pages as needed.
              for await (const assistant of client.beta.assistants.list()) {
                console.log(assistant.id);
              }
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                page, err := client.Beta.Assistants.List(context.TODO(), openai.BetaAssistantListParams{

                })
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", page)
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.beta.assistants.AssistantListPage
              import com.openai.models.beta.assistants.AssistantListParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val page: AssistantListPage = client.beta().assistants().list()
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              page = openai.beta.assistants.list

              puts(page)
    post:
      operationId: createAssistant
      tags:
        - Assistants
      summary: Create an assistant with a model and instructions.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateAssistantRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/AssistantObject'
      x-oaiMeta:
        name: Create assistant
        group: assistants
        beta: true
        returns: An [assistant](/docs/api-reference/assistants/object) object.
        examples:
          - title: Code Interpreter
            request:
              curl: |
                curl "https://api.openai.com/v1/assistants" \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -H "OpenAI-Beta: assistants=v2" \
                  -d '{
                    "instructions": "You are a personal math tutor. When asked a question, write and run Python code to answer the question.",
                    "name": "Math Tutor",
                    "tools": [{"type": "code_interpreter"}],
                    "model": "gpt-4o"
                  }'
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                assistant = client.beta.assistants.create(
                    model="gpt-4o",
                )
                print(assistant.id)
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const assistant = await client.beta.assistants.create({ model: 'gpt-4o' });

                console.log(assistant.id);
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                  "github.com/openai/openai-go/shared"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  assistant, err := client.Beta.Assistants.New(context.TODO(), openai.BetaAssistantNewParams{
                    Model: shared.ChatModelGPT4_1,
                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", assistant.ID)
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.ChatModel
                import com.openai.models.beta.assistants.Assistant
                import com.openai.models.beta.assistants.AssistantCreateParams

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val params: AssistantCreateParams = AssistantCreateParams.builder()
                        .model(ChatModel.GPT_4_1)
                        .build()
                    val assistant: Assistant = client.beta().assistants().create(params)
                }
              ruby: |-
                require "openai"

                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )

                assistant = openai.beta.assistants.create(model: :"gpt-4.1")

                puts(assistant)
            response: |
              {
                "id": "asst_abc123",
                "object": "assistant",
                "created_at": 1698984975,
                "name": "Math Tutor",
                "description": null,
                "model": "gpt-4o",
                "instructions": "You are a personal math tutor. When asked a question, write and run Python code to answer the question.",
                "tools": [
                  {
                    "type": "code_interpreter"
                  }
                ],
                "metadata": {},
                "top_p": 1.0,
                "temperature": 1.0,
                "response_format": "auto"
              }
          - title: Files
            request:
              curl: |
                curl https://api.openai.com/v1/assistants \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -H "OpenAI-Beta: assistants=v2" \
                  -d '{
                    "instructions": "You are an HR bot, and you have access to files to answer employee questions about company policies.",
                    "tools": [{"type": "file_search"}],
                    "tool_resources": {"file_search": {"vector_store_ids": ["vs_123"]}},
                    "model": "gpt-4o"
                  }'
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                assistant = client.beta.assistants.create(
                    model="gpt-4o",
                )
                print(assistant.id)
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const assistant = await client.beta.assistants.create({ model: 'gpt-4o' });

                console.log(assistant.id);
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                  "github.com/openai/openai-go/shared"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  assistant, err := client.Beta.Assistants.New(context.TODO(), openai.BetaAssistantNewParams{
                    Model: shared.ChatModelGPT4_1,
                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", assistant.ID)
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.ChatModel
                import com.openai.models.beta.assistants.Assistant
                import com.openai.models.beta.assistants.AssistantCreateParams

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val params: AssistantCreateParams = AssistantCreateParams.builder()
                        .model(ChatModel.GPT_4_1)
                        .build()
                    val assistant: Assistant = client.beta().assistants().create(params)
                }
              ruby: |-
                require "openai"

                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )

                assistant = openai.beta.assistants.create(model: :"gpt-4.1")

                puts(assistant)
            response: |
              {
                "id": "asst_abc123",
                "object": "assistant",
                "created_at": 1699009403,
                "name": "HR Helper",
                "description": null,
                "model": "gpt-4o",
                "instructions": "You are an HR bot, and you have access to files to answer employee questions about company policies.",
                "tools": [
                  {
                    "type": "file_search"
                  }
                ],
                "tool_resources": {
                  "file_search": {
                    "vector_store_ids": ["vs_123"]
                  }
                },
                "metadata": {},
                "top_p": 1.0,
                "temperature": 1.0,
                "response_format": "auto"
              }
  /assistants/{assistant_id}:
    get:
      operationId: getAssistant
      tags:
        - Assistants
      summary: Retrieves an assistant.
      parameters:
        - in: path
          name: assistant_id
          required: true
          schema:
            type: string
          description: The ID of the assistant to retrieve.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/AssistantObject'
      x-oaiMeta:
        name: Retrieve assistant
        group: assistants
        beta: true
        returns: The [assistant](/docs/api-reference/assistants/object) object matching the specified ID.
        examples:
          response: |
            {
              "id": "asst_abc123",
              "object": "assistant",
              "created_at": 1699009709,
              "name": "HR Helper",
              "description": null,
              "model": "gpt-4o",
              "instructions": "You are an HR bot, and you have access to files to answer employee questions about company policies.",
              "tools": [
                {
                  "type": "file_search"
                }
              ],
              "metadata": {},
              "top_p": 1.0,
              "temperature": 1.0,
              "response_format": "auto"
            }
          request:
            curl: |
              curl https://api.openai.com/v1/assistants/asst_abc123 \
                -H "Content-Type: application/json" \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "OpenAI-Beta: assistants=v2"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              assistant = client.beta.assistants.retrieve(
                  "assistant_id",
              )
              print(assistant.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const assistant = await client.beta.assistants.retrieve('assistant_id');

              console.log(assistant.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                assistant, err := client.Beta.Assistants.Get(context.TODO(), "assistant_id")
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", assistant.ID)
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.beta.assistants.Assistant
              import com.openai.models.beta.assistants.AssistantRetrieveParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val assistant: Assistant = client.beta().assistants().retrieve("assistant_id")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              assistant = openai.beta.assistants.retrieve("assistant_id")

              puts(assistant)
    post:
      operationId: modifyAssistant
      tags:
        - Assistants
      summary: Modifies an assistant.
      parameters:
        - in: path
          name: assistant_id
          required: true
          schema:
            type: string
          description: The ID of the assistant to modify.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/ModifyAssistantRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/AssistantObject'
      x-oaiMeta:
        name: Modify assistant
        group: assistants
        beta: true
        returns: The modified [assistant](/docs/api-reference/assistants/object) object.
        examples:
          response: |
            {
              "id": "asst_123",
              "object": "assistant",
              "created_at": 1699009709,
              "name": "HR Helper",
              "description": null,
              "model": "gpt-4o",
              "instructions": "You are an HR bot, and you have access to files to answer employee questions about company policies. Always response with info from either of the files.",
              "tools": [
                {
                  "type": "file_search"
                }
              ],
              "tool_resources": {
                "file_search": {
                  "vector_store_ids": []
                }
              },
              "metadata": {},
              "top_p": 1.0,
              "temperature": 1.0,
              "response_format": "auto"
            }
          request:
            curl: |
              curl https://api.openai.com/v1/assistants/asst_abc123 \
                -H "Content-Type: application/json" \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "OpenAI-Beta: assistants=v2" \
                -d '{
                    "instructions": "You are an HR bot, and you have access to files to answer employee questions about company policies. Always response with info from either of the files.",
                    "tools": [{"type": "file_search"}],
                    "model": "gpt-4o"
                  }'
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              assistant = client.beta.assistants.update(
                  assistant_id="assistant_id",
              )
              print(assistant.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const assistant = await client.beta.assistants.update('assistant_id');

              console.log(assistant.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                assistant, err := client.Beta.Assistants.Update(
                  context.TODO(),
                  "assistant_id",
                  openai.BetaAssistantUpdateParams{

                  },
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", assistant.ID)
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.beta.assistants.Assistant
              import com.openai.models.beta.assistants.AssistantUpdateParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val assistant: Assistant = client.beta().assistants().update("assistant_id")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              assistant = openai.beta.assistants.update("assistant_id")

              puts(assistant)
    delete:
      operationId: deleteAssistant
      tags:
        - Assistants
      summary: Delete an assistant.
      parameters:
        - in: path
          name: assistant_id
          required: true
          schema:
            type: string
          description: The ID of the assistant to delete.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/DeleteAssistantResponse'
      x-oaiMeta:
        name: Delete assistant
        group: assistants
        beta: true
        returns: Deletion status
        examples:
          response: |
            {
              "id": "asst_abc123",
              "object": "assistant.deleted",
              "deleted": true
            }
          request:
            curl: |
              curl https://api.openai.com/v1/assistants/asst_abc123 \
                -H "Content-Type: application/json" \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "OpenAI-Beta: assistants=v2" \
                -X DELETE
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              assistant_deleted = client.beta.assistants.delete(
                  "assistant_id",
              )
              print(assistant_deleted.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const assistantDeleted = await client.beta.assistants.delete('assistant_id');

              console.log(assistantDeleted.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                assistantDeleted, err := client.Beta.Assistants.Delete(context.TODO(), "assistant_id")
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", assistantDeleted.ID)
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.beta.assistants.AssistantDeleteParams
              import com.openai.models.beta.assistants.AssistantDeleted

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val assistantDeleted: AssistantDeleted = client.beta().assistants().delete("assistant_id")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              assistant_deleted = openai.beta.assistants.delete("assistant_id")

              puts(assistant_deleted)
  /audio/speech:
    post:
      operationId: createSpeech
      tags:
        - Audio
      summary: Generates audio from the input text.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateSpeechRequest'
      responses:
        '200':
          description: OK
          headers:
            Transfer-Encoding:
              schema:
                type: string
              description: chunked
          content:
            application/octet-stream:
              schema:
                type: string
                format: binary
      x-oaiMeta:
        name: Create speech
        group: audio
        returns: The audio file content.
        examples:
          response: ''
          request:
            curl: |
              curl https://api.openai.com/v1/audio/speech \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
                -d '{
                  "model": "gpt-4o-mini-tts",
                  "input": "The quick brown fox jumped over the lazy dog.",
                  "voice": "alloy"
                }' \
                --output speech.mp3
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              speech = client.audio.speech.create(
                  input="input",
                  model="string",
                  voice="ash",
              )
              print(speech)
              content = speech.read()
              print(content)
            javascript: |
              import fs from "fs";
              import path from "path";
              import OpenAI from "openai";

              const openai = new OpenAI();

              const speechFile = path.resolve("./speech.mp3");

              async function main() {
                const mp3 = await openai.audio.speech.create({
                  model: "gpt-4o-mini-tts",
                  voice: "alloy",
                  input: "Today is a wonderful day to build something people love!",
                });
                console.log(speechFile);
                const buffer = Buffer.from(await mp3.arrayBuffer());
                await fs.promises.writeFile(speechFile, buffer);
              }
              main();
            csharp: |
              using System;
              using System.IO;

              using OpenAI.Audio;

              AudioClient client = new(
                  model: "gpt-4o-mini-tts",
                  apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
              );

              BinaryData speech = client.GenerateSpeech(
                  text: "The quick brown fox jumped over the lazy dog.",
                  voice: GeneratedSpeechVoice.Alloy
              );

              using FileStream stream = File.OpenWrite("speech.mp3");
              speech.ToStream().CopyTo(stream);
            node.js: >-
              import OpenAI from 'openai';


              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });


              const speech = await client.audio.speech.create({ input: 'input', model: 'string', voice: 'ash'
              });


              console.log(speech);


              const content = await speech.blob();

              console.log(content);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                speech, err := client.Audio.Speech.New(context.TODO(), openai.AudioSpeechNewParams{
                  Input: "input",
                  Model: openai.SpeechModelTTS1,
                  Voice: openai.AudioSpeechNewParamsVoiceAlloy,
                })
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", speech)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.core.http.HttpResponse;
              import com.openai.models.audio.speech.SpeechCreateParams;
              import com.openai.models.audio.speech.SpeechModel;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      SpeechCreateParams params = SpeechCreateParams.builder()
                          .input("input")
                          .model(SpeechModel.TTS_1)
                          .voice(SpeechCreateParams.Voice.ALLOY)
                          .build();
                      HttpResponse speech = client.audio().speech().create(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.core.http.HttpResponse
              import com.openai.models.audio.speech.SpeechCreateParams
              import com.openai.models.audio.speech.SpeechModel

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: SpeechCreateParams = SpeechCreateParams.builder()
                      .input("input")
                      .model(SpeechModel.TTS_1)
                      .voice(SpeechCreateParams.Voice.ALLOY)
                      .build()
                  val speech: HttpResponse = client.audio().speech().create(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              speech = openai.audio.speech.create(input: "input", model: :"tts-1", voice: :alloy)

              puts(speech)
  /audio/transcriptions:
    post:
      operationId: createTranscription
      tags:
        - Audio
      summary: Transcribes audio into the input language.
      requestBody:
        required: true
        content:
          multipart/form-data:
            schema:
              $ref: '#/components/schemas/CreateTranscriptionRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                oneOf:
                  - $ref: '#/components/schemas/CreateTranscriptionResponseJson'
                  - $ref: '#/components/schemas/CreateTranscriptionResponseVerboseJson'
            text/event-stream:
              schema:
                $ref: '#/components/schemas/CreateTranscriptionResponseStreamEvent'
      x-oaiMeta:
        name: Create transcription
        group: audio
        returns: >-
          The [transcription object](/docs/api-reference/audio/json-object), a [verbose transcription
          object](/docs/api-reference/audio/verbose-json-object) or a [stream of transcript
          events](/docs/api-reference/audio/transcript-text-delta-event).
        examples:
          - title: Default
            request:
              curl: |
                curl https://api.openai.com/v1/audio/transcriptions \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -H "Content-Type: multipart/form-data" \
                  -F file="@/path/to/file/audio.mp3" \
                  -F model="gpt-4o-transcribe"
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                transcription = client.audio.transcriptions.create(
                    file=b"raw file contents",
                    model="gpt-4o-transcribe",
                )
                print(transcription)
              javascript: |
                import fs from "fs";
                import OpenAI from "openai";

                const openai = new OpenAI();

                async function main() {
                  const transcription = await openai.audio.transcriptions.create({
                    file: fs.createReadStream("audio.mp3"),
                    model: "gpt-4o-transcribe",
                  });

                  console.log(transcription.text);
                }
                main();
              csharp: |
                using System;

                using OpenAI.Audio;
                string audioFilePath = "audio.mp3";

                AudioClient client = new(
                    model: "gpt-4o-transcribe",
                    apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
                );

                AudioTranscription transcription = client.TranscribeAudio(audioFilePath);

                Console.WriteLine($"{transcription.Text}");
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const transcription = await client.audio.transcriptions.create({
                  file: fs.createReadStream('speech.mp3'),
                  model: 'gpt-4o-transcribe',
                });

                console.log(transcription);
              go: |
                package main

                import (
                  "bytes"
                  "context"
                  "fmt"
                  "io"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  transcription, err := client.Audio.Transcriptions.New(context.TODO(), openai.AudioTranscriptionNewParams{
                    File: io.Reader(bytes.NewBuffer([]byte("some file contents"))),
                    Model: openai.AudioModelWhisper1,
                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", transcription)
                }
              java: |-
                package com.openai.example;

                import com.openai.client.OpenAIClient;
                import com.openai.client.okhttp.OpenAIOkHttpClient;
                import com.openai.models.audio.AudioModel;
                import com.openai.models.audio.transcriptions.TranscriptionCreateParams;
                import com.openai.models.audio.transcriptions.TranscriptionCreateResponse;
                import java.io.ByteArrayInputStream;

                public final class Main {
                    private Main() {}

                    public static void main(String[] args) {
                        // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                        TranscriptionCreateParams params = TranscriptionCreateParams.builder()
                            .file(ByteArrayInputStream("some content".getBytes()))
                            .model(AudioModel.WHISPER_1)
                            .build();
                        TranscriptionCreateResponse transcription = client.audio().transcriptions().create(params);
                    }
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.audio.AudioModel
                import com.openai.models.audio.transcriptions.TranscriptionCreateParams
                import com.openai.models.audio.transcriptions.TranscriptionCreateResponse
                import java.io.ByteArrayInputStream

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val params: TranscriptionCreateParams = TranscriptionCreateParams.builder()
                        .file("some content".byteInputStream())
                        .model(AudioModel.WHISPER_1)
                        .build()
                    val transcription: TranscriptionCreateResponse = client.audio().transcriptions().create(params)
                }
              ruby: >-
                require "openai"


                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )


                transcription = openai.audio.transcriptions.create(file: Pathname(__FILE__), model:
                :"whisper-1")


                puts(transcription)
            response: |
              {
                "text": "Imagine the wildest idea that you've ever had, and you're curious about how it might scale to something that's a 100, a 1,000 times bigger. This is a place where you can get to do that."
              }
          - title: Streaming
            request:
              curl: |
                curl https://api.openai.com/v1/audio/transcriptions \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -H "Content-Type: multipart/form-data" \
                  -F file="@/path/to/file/audio.mp3" \
                  -F model="gpt-4o-mini-transcribe" \
                  -F stream=true
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                transcription = client.audio.transcriptions.create(
                    file=b"raw file contents",
                    model="gpt-4o-transcribe",
                )
                print(transcription)
              javascript: |
                import fs from "fs";
                import OpenAI from "openai";

                const openai = new OpenAI();

                const stream = await openai.audio.transcriptions.create({
                  file: fs.createReadStream("audio.mp3"),
                  model: "gpt-4o-mini-transcribe",
                  stream: true,
                });

                for await (const event of stream) {
                  console.log(event);
                }
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const transcription = await client.audio.transcriptions.create({
                  file: fs.createReadStream('speech.mp3'),
                  model: 'gpt-4o-transcribe',
                });

                console.log(transcription);
              go: |
                package main

                import (
                  "bytes"
                  "context"
                  "fmt"
                  "io"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  transcription, err := client.Audio.Transcriptions.New(context.TODO(), openai.AudioTranscriptionNewParams{
                    File: io.Reader(bytes.NewBuffer([]byte("some file contents"))),
                    Model: openai.AudioModelWhisper1,
                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", transcription)
                }
              java: |-
                package com.openai.example;

                import com.openai.client.OpenAIClient;
                import com.openai.client.okhttp.OpenAIOkHttpClient;
                import com.openai.models.audio.AudioModel;
                import com.openai.models.audio.transcriptions.TranscriptionCreateParams;
                import com.openai.models.audio.transcriptions.TranscriptionCreateResponse;
                import java.io.ByteArrayInputStream;

                public final class Main {
                    private Main() {}

                    public static void main(String[] args) {
                        // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                        TranscriptionCreateParams params = TranscriptionCreateParams.builder()
                            .file(ByteArrayInputStream("some content".getBytes()))
                            .model(AudioModel.WHISPER_1)
                            .build();
                        TranscriptionCreateResponse transcription = client.audio().transcriptions().create(params);
                    }
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.audio.AudioModel
                import com.openai.models.audio.transcriptions.TranscriptionCreateParams
                import com.openai.models.audio.transcriptions.TranscriptionCreateResponse
                import java.io.ByteArrayInputStream

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val params: TranscriptionCreateParams = TranscriptionCreateParams.builder()
                        .file("some content".byteInputStream())
                        .model(AudioModel.WHISPER_1)
                        .build()
                    val transcription: TranscriptionCreateResponse = client.audio().transcriptions().create(params)
                }
              ruby: >-
                require "openai"


                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )


                transcription = openai.audio.transcriptions.create(file: Pathname(__FILE__), model:
                :"whisper-1")


                puts(transcription)
            response: >
              data:
              {"type":"transcript.text.delta","delta":"I","logprobs":[{"token":"I","logprob":-0.00007588794,"bytes":[73]}]}


              data: {"type":"transcript.text.delta","delta":" see","logprobs":[{"token":"
              see","logprob":-3.1281633e-7,"bytes":[32,115,101,101]}]}


              data: {"type":"transcript.text.delta","delta":" skies","logprobs":[{"token":"
              skies","logprob":-2.3392786e-6,"bytes":[32,115,107,105,101,115]}]}


              data: {"type":"transcript.text.delta","delta":" of","logprobs":[{"token":"
              of","logprob":-3.1281633e-7,"bytes":[32,111,102]}]}


              data: {"type":"transcript.text.delta","delta":" blue","logprobs":[{"token":"
              blue","logprob":-1.0280384e-6,"bytes":[32,98,108,117,101]}]}


              data: {"type":"transcript.text.delta","delta":" and","logprobs":[{"token":"
              and","logprob":-0.0005108566,"bytes":[32,97,110,100]}]}


              data: {"type":"transcript.text.delta","delta":" clouds","logprobs":[{"token":"
              clouds","logprob":-1.9361265e-7,"bytes":[32,99,108,111,117,100,115]}]}


              data: {"type":"transcript.text.delta","delta":" of","logprobs":[{"token":"
              of","logprob":-1.9361265e-7,"bytes":[32,111,102]}]}


              data: {"type":"transcript.text.delta","delta":" white","logprobs":[{"token":"
              white","logprob":-7.89631e-7,"bytes":[32,119,104,105,116,101]}]}


              data:
              {"type":"transcript.text.delta","delta":",","logprobs":[{"token":",","logprob":-0.0014890312,"bytes":[44]}]}


              data: {"type":"transcript.text.delta","delta":" the","logprobs":[{"token":"
              the","logprob":-0.0110956915,"bytes":[32,116,104,101]}]}


              data: {"type":"transcript.text.delta","delta":" bright","logprobs":[{"token":"
              bright","logprob":0.0,"bytes":[32,98,114,105,103,104,116]}]}


              data: {"type":"transcript.text.delta","delta":" blessed","logprobs":[{"token":"
              blessed","logprob":-0.000045848617,"bytes":[32,98,108,101,115,115,101,100]}]}


              data: {"type":"transcript.text.delta","delta":" days","logprobs":[{"token":"
              days","logprob":-0.000010802739,"bytes":[32,100,97,121,115]}]}


              data:
              {"type":"transcript.text.delta","delta":",","logprobs":[{"token":",","logprob":-0.00001700133,"bytes":[44]}]}


              data: {"type":"transcript.text.delta","delta":" the","logprobs":[{"token":"
              the","logprob":-0.0000118755715,"bytes":[32,116,104,101]}]}


              data: {"type":"transcript.text.delta","delta":" dark","logprobs":[{"token":"
              dark","logprob":-5.5122365e-7,"bytes":[32,100,97,114,107]}]}


              data: {"type":"transcript.text.delta","delta":" sacred","logprobs":[{"token":"
              sacred","logprob":-5.4385737e-6,"bytes":[32,115,97,99,114,101,100]}]}


              data: {"type":"transcript.text.delta","delta":" nights","logprobs":[{"token":"
              nights","logprob":-4.00813e-6,"bytes":[32,110,105,103,104,116,115]}]}


              data:
              {"type":"transcript.text.delta","delta":",","logprobs":[{"token":",","logprob":-0.0036910512,"bytes":[44]}]}


              data: {"type":"transcript.text.delta","delta":" and","logprobs":[{"token":"
              and","logprob":-0.0031903093,"bytes":[32,97,110,100]}]}


              data: {"type":"transcript.text.delta","delta":" I","logprobs":[{"token":"
              I","logprob":-1.504853e-6,"bytes":[32,73]}]}


              data: {"type":"transcript.text.delta","delta":" think","logprobs":[{"token":"
              think","logprob":-4.3202e-7,"bytes":[32,116,104,105,110,107]}]}


              data: {"type":"transcript.text.delta","delta":" to","logprobs":[{"token":"
              to","logprob":-1.9361265e-7,"bytes":[32,116,111]}]}


              data: {"type":"transcript.text.delta","delta":" myself","logprobs":[{"token":"
              myself","logprob":-1.7432603e-6,"bytes":[32,109,121,115,101,108,102]}]}


              data:
              {"type":"transcript.text.delta","delta":",","logprobs":[{"token":",","logprob":-0.29254505,"bytes":[44]}]}


              data: {"type":"transcript.text.delta","delta":" what","logprobs":[{"token":"
              what","logprob":-0.016815351,"bytes":[32,119,104,97,116]}]}


              data: {"type":"transcript.text.delta","delta":" a","logprobs":[{"token":"
              a","logprob":-3.1281633e-7,"bytes":[32,97]}]}


              data: {"type":"transcript.text.delta","delta":" wonderful","logprobs":[{"token":"
              wonderful","logprob":-2.1008714e-6,"bytes":[32,119,111,110,100,101,114,102,117,108]}]}


              data: {"type":"transcript.text.delta","delta":" world","logprobs":[{"token":"
              world","logprob":-8.180258e-6,"bytes":[32,119,111,114,108,100]}]}


              data:
              {"type":"transcript.text.delta","delta":".","logprobs":[{"token":".","logprob":-0.014231676,"bytes":[46]}]}


              data: {"type":"transcript.text.done","text":"I see skies of blue and clouds of white, the bright
              blessed days, the dark sacred nights, and I think to myself, what a wonderful
              world.","logprobs":[{"token":"I","logprob":-0.00007588794,"bytes":[73]},{"token":"
              see","logprob":-3.1281633e-7,"bytes":[32,115,101,101]},{"token":"
              skies","logprob":-2.3392786e-6,"bytes":[32,115,107,105,101,115]},{"token":"
              of","logprob":-3.1281633e-7,"bytes":[32,111,102]},{"token":"
              blue","logprob":-1.0280384e-6,"bytes":[32,98,108,117,101]},{"token":"
              and","logprob":-0.0005108566,"bytes":[32,97,110,100]},{"token":"
              clouds","logprob":-1.9361265e-7,"bytes":[32,99,108,111,117,100,115]},{"token":"
              of","logprob":-1.9361265e-7,"bytes":[32,111,102]},{"token":"
              white","logprob":-7.89631e-7,"bytes":[32,119,104,105,116,101]},{"token":",","logprob":-0.0014890312,"bytes":[44]},{"token":"
              the","logprob":-0.0110956915,"bytes":[32,116,104,101]},{"token":"
              bright","logprob":0.0,"bytes":[32,98,114,105,103,104,116]},{"token":"
              blessed","logprob":-0.000045848617,"bytes":[32,98,108,101,115,115,101,100]},{"token":"
              days","logprob":-0.000010802739,"bytes":[32,100,97,121,115]},{"token":",","logprob":-0.00001700133,"bytes":[44]},{"token":"
              the","logprob":-0.0000118755715,"bytes":[32,116,104,101]},{"token":"
              dark","logprob":-5.5122365e-7,"bytes":[32,100,97,114,107]},{"token":"
              sacred","logprob":-5.4385737e-6,"bytes":[32,115,97,99,114,101,100]},{"token":"
              nights","logprob":-4.00813e-6,"bytes":[32,110,105,103,104,116,115]},{"token":",","logprob":-0.0036910512,"bytes":[44]},{"token":"
              and","logprob":-0.0031903093,"bytes":[32,97,110,100]},{"token":"
              I","logprob":-1.504853e-6,"bytes":[32,73]},{"token":"
              think","logprob":-4.3202e-7,"bytes":[32,116,104,105,110,107]},{"token":"
              to","logprob":-1.9361265e-7,"bytes":[32,116,111]},{"token":"
              myself","logprob":-1.7432603e-6,"bytes":[32,109,121,115,101,108,102]},{"token":",","logprob":-0.29254505,"bytes":[44]},{"token":"
              what","logprob":-0.016815351,"bytes":[32,119,104,97,116]},{"token":"
              a","logprob":-3.1281633e-7,"bytes":[32,97]},{"token":"
              wonderful","logprob":-2.1008714e-6,"bytes":[32,119,111,110,100,101,114,102,117,108]},{"token":"
              world","logprob":-8.180258e-6,"bytes":[32,119,111,114,108,100]},{"token":".","logprob":-0.014231676,"bytes":[46]}]}
          - title: Logprobs
            request:
              curl: |
                curl https://api.openai.com/v1/audio/transcriptions \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -H "Content-Type: multipart/form-data" \
                  -F file="@/path/to/file/audio.mp3" \
                  -F "include[]=logprobs" \
                  -F model="gpt-4o-transcribe" \
                  -F response_format="json"
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                transcription = client.audio.transcriptions.create(
                    file=b"raw file contents",
                    model="gpt-4o-transcribe",
                )
                print(transcription)
              javascript: |
                import fs from "fs";
                import OpenAI from "openai";

                const openai = new OpenAI();

                async function main() {
                  const transcription = await openai.audio.transcriptions.create({
                    file: fs.createReadStream("audio.mp3"),
                    model: "gpt-4o-transcribe",
                    response_format: "json",
                    include: ["logprobs"]
                  });

                  console.log(transcription);
                }
                main();
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const transcription = await client.audio.transcriptions.create({
                  file: fs.createReadStream('speech.mp3'),
                  model: 'gpt-4o-transcribe',
                });

                console.log(transcription);
              go: |
                package main

                import (
                  "bytes"
                  "context"
                  "fmt"
                  "io"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  transcription, err := client.Audio.Transcriptions.New(context.TODO(), openai.AudioTranscriptionNewParams{
                    File: io.Reader(bytes.NewBuffer([]byte("some file contents"))),
                    Model: openai.AudioModelWhisper1,
                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", transcription)
                }
              java: |-
                package com.openai.example;

                import com.openai.client.OpenAIClient;
                import com.openai.client.okhttp.OpenAIOkHttpClient;
                import com.openai.models.audio.AudioModel;
                import com.openai.models.audio.transcriptions.TranscriptionCreateParams;
                import com.openai.models.audio.transcriptions.TranscriptionCreateResponse;
                import java.io.ByteArrayInputStream;

                public final class Main {
                    private Main() {}

                    public static void main(String[] args) {
                        // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                        TranscriptionCreateParams params = TranscriptionCreateParams.builder()
                            .file(ByteArrayInputStream("some content".getBytes()))
                            .model(AudioModel.WHISPER_1)
                            .build();
                        TranscriptionCreateResponse transcription = client.audio().transcriptions().create(params);
                    }
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.audio.AudioModel
                import com.openai.models.audio.transcriptions.TranscriptionCreateParams
                import com.openai.models.audio.transcriptions.TranscriptionCreateResponse
                import java.io.ByteArrayInputStream

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val params: TranscriptionCreateParams = TranscriptionCreateParams.builder()
                        .file("some content".byteInputStream())
                        .model(AudioModel.WHISPER_1)
                        .build()
                    val transcription: TranscriptionCreateResponse = client.audio().transcriptions().create(params)
                }
              ruby: >-
                require "openai"


                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )


                transcription = openai.audio.transcriptions.create(file: Pathname(__FILE__), model:
                :"whisper-1")


                puts(transcription)
            response: |
              {
                "text": "Hey, my knee is hurting and I want to see the doctor tomorrow ideally.",
                "logprobs": [
                  { "token": "Hey", "logprob": -1.0415299, "bytes": [72, 101, 121] },
                  { "token": ",", "logprob": -9.805982e-5, "bytes": [44] },
                  { "token": " my", "logprob": -0.00229799, "bytes": [32, 109, 121] },
                  {
                    "token": " knee",
                    "logprob": -4.7159858e-5,
                    "bytes": [32, 107, 110, 101, 101]
                  },
                  { "token": " is", "logprob": -0.043909557, "bytes": [32, 105, 115] },
                  {
                    "token": " hurting",
                    "logprob": -1.1041146e-5,
                    "bytes": [32, 104, 117, 114, 116, 105, 110, 103]
                  },
                  { "token": " and", "logprob": -0.011076359, "bytes": [32, 97, 110, 100] },
                  { "token": " I", "logprob": -5.3193703e-6, "bytes": [32, 73] },
                  {
                    "token": " want",
                    "logprob": -0.0017156356,
                    "bytes": [32, 119, 97, 110, 116]
                  },
                  { "token": " to", "logprob": -7.89631e-7, "bytes": [32, 116, 111] },
                  { "token": " see", "logprob": -5.5122365e-7, "bytes": [32, 115, 101, 101] },
                  { "token": " the", "logprob": -0.0040786397, "bytes": [32, 116, 104, 101] },
                  {
                    "token": " doctor",
                    "logprob": -2.3392786e-6,
                    "bytes": [32, 100, 111, 99, 116, 111, 114]
                  },
                  {
                    "token": " tomorrow",
                    "logprob": -7.89631e-7,
                    "bytes": [32, 116, 111, 109, 111, 114, 114, 111, 119]
                  },
                  {
                    "token": " ideally",
                    "logprob": -0.5800861,
                    "bytes": [32, 105, 100, 101, 97, 108, 108, 121]
                  },
                  { "token": ".", "logprob": -0.00011093382, "bytes": [46] }
                ]
              }
          - title: Word timestamps
            request:
              curl: |
                curl https://api.openai.com/v1/audio/transcriptions \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -H "Content-Type: multipart/form-data" \
                  -F file="@/path/to/file/audio.mp3" \
                  -F "timestamp_granularities[]=word" \
                  -F model="whisper-1" \
                  -F response_format="verbose_json"
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                transcription = client.audio.transcriptions.create(
                    file=b"raw file contents",
                    model="gpt-4o-transcribe",
                )
                print(transcription)
              javascript: |
                import fs from "fs";
                import OpenAI from "openai";

                const openai = new OpenAI();

                async function main() {
                  const transcription = await openai.audio.transcriptions.create({
                    file: fs.createReadStream("audio.mp3"),
                    model: "whisper-1",
                    response_format: "verbose_json",
                    timestamp_granularities: ["word"]
                  });

                  console.log(transcription.text);
                }
                main();
              csharp: |
                using System;

                using OpenAI.Audio;

                string audioFilePath = "audio.mp3";

                AudioClient client = new(
                    model: "whisper-1",
                    apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
                );

                AudioTranscriptionOptions options = new()
                {
                    ResponseFormat = AudioTranscriptionFormat.Verbose,
                    TimestampGranularities = AudioTimestampGranularities.Word,
                };

                AudioTranscription transcription = client.TranscribeAudio(audioFilePath, options);

                Console.WriteLine($"{transcription.Text}");
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const transcription = await client.audio.transcriptions.create({
                  file: fs.createReadStream('speech.mp3'),
                  model: 'gpt-4o-transcribe',
                });

                console.log(transcription);
              go: |
                package main

                import (
                  "bytes"
                  "context"
                  "fmt"
                  "io"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  transcription, err := client.Audio.Transcriptions.New(context.TODO(), openai.AudioTranscriptionNewParams{
                    File: io.Reader(bytes.NewBuffer([]byte("some file contents"))),
                    Model: openai.AudioModelWhisper1,
                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", transcription)
                }
              java: |-
                package com.openai.example;

                import com.openai.client.OpenAIClient;
                import com.openai.client.okhttp.OpenAIOkHttpClient;
                import com.openai.models.audio.AudioModel;
                import com.openai.models.audio.transcriptions.TranscriptionCreateParams;
                import com.openai.models.audio.transcriptions.TranscriptionCreateResponse;
                import java.io.ByteArrayInputStream;

                public final class Main {
                    private Main() {}

                    public static void main(String[] args) {
                        // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                        TranscriptionCreateParams params = TranscriptionCreateParams.builder()
                            .file(ByteArrayInputStream("some content".getBytes()))
                            .model(AudioModel.WHISPER_1)
                            .build();
                        TranscriptionCreateResponse transcription = client.audio().transcriptions().create(params);
                    }
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.audio.AudioModel
                import com.openai.models.audio.transcriptions.TranscriptionCreateParams
                import com.openai.models.audio.transcriptions.TranscriptionCreateResponse
                import java.io.ByteArrayInputStream

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val params: TranscriptionCreateParams = TranscriptionCreateParams.builder()
                        .file("some content".byteInputStream())
                        .model(AudioModel.WHISPER_1)
                        .build()
                    val transcription: TranscriptionCreateResponse = client.audio().transcriptions().create(params)
                }
              ruby: >-
                require "openai"


                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )


                transcription = openai.audio.transcriptions.create(file: Pathname(__FILE__), model:
                :"whisper-1")


                puts(transcription)
            response: |
              {
                "task": "transcribe",
                "language": "english",
                "duration": 8.470000267028809,
                "text": "The beach was a popular spot on a hot summer day. People were swimming in the ocean, building sandcastles, and playing beach volleyball.",
                "words": [
                  {
                    "word": "The",
                    "start": 0.0,
                    "end": 0.23999999463558197
                  },
                  ...
                  {
                    "word": "volleyball",
                    "start": 7.400000095367432,
                    "end": 7.900000095367432
                  }
                ]
              }
          - title: Segment timestamps
            request:
              curl: |
                curl https://api.openai.com/v1/audio/transcriptions \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -H "Content-Type: multipart/form-data" \
                  -F file="@/path/to/file/audio.mp3" \
                  -F "timestamp_granularities[]=segment" \
                  -F model="whisper-1" \
                  -F response_format="verbose_json"
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                transcription = client.audio.transcriptions.create(
                    file=b"raw file contents",
                    model="gpt-4o-transcribe",
                )
                print(transcription)
              javascript: |
                import fs from "fs";
                import OpenAI from "openai";

                const openai = new OpenAI();

                async function main() {
                  const transcription = await openai.audio.transcriptions.create({
                    file: fs.createReadStream("audio.mp3"),
                    model: "whisper-1",
                    response_format: "verbose_json",
                    timestamp_granularities: ["segment"]
                  });

                  console.log(transcription.text);
                }
                main();
              csharp: |
                using System;

                using OpenAI.Audio;

                string audioFilePath = "audio.mp3";

                AudioClient client = new(
                    model: "whisper-1",
                    apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
                );

                AudioTranscriptionOptions options = new()
                {
                    ResponseFormat = AudioTranscriptionFormat.Verbose,
                    TimestampGranularities = AudioTimestampGranularities.Segment,
                };

                AudioTranscription transcription = client.TranscribeAudio(audioFilePath, options);

                Console.WriteLine($"{transcription.Text}");
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const transcription = await client.audio.transcriptions.create({
                  file: fs.createReadStream('speech.mp3'),
                  model: 'gpt-4o-transcribe',
                });

                console.log(transcription);
              go: |
                package main

                import (
                  "bytes"
                  "context"
                  "fmt"
                  "io"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  transcription, err := client.Audio.Transcriptions.New(context.TODO(), openai.AudioTranscriptionNewParams{
                    File: io.Reader(bytes.NewBuffer([]byte("some file contents"))),
                    Model: openai.AudioModelWhisper1,
                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", transcription)
                }
              java: |-
                package com.openai.example;

                import com.openai.client.OpenAIClient;
                import com.openai.client.okhttp.OpenAIOkHttpClient;
                import com.openai.models.audio.AudioModel;
                import com.openai.models.audio.transcriptions.TranscriptionCreateParams;
                import com.openai.models.audio.transcriptions.TranscriptionCreateResponse;
                import java.io.ByteArrayInputStream;

                public final class Main {
                    private Main() {}

                    public static void main(String[] args) {
                        // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                        TranscriptionCreateParams params = TranscriptionCreateParams.builder()
                            .file(ByteArrayInputStream("some content".getBytes()))
                            .model(AudioModel.WHISPER_1)
                            .build();
                        TranscriptionCreateResponse transcription = client.audio().transcriptions().create(params);
                    }
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.audio.AudioModel
                import com.openai.models.audio.transcriptions.TranscriptionCreateParams
                import com.openai.models.audio.transcriptions.TranscriptionCreateResponse
                import java.io.ByteArrayInputStream

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val params: TranscriptionCreateParams = TranscriptionCreateParams.builder()
                        .file("some content".byteInputStream())
                        .model(AudioModel.WHISPER_1)
                        .build()
                    val transcription: TranscriptionCreateResponse = client.audio().transcriptions().create(params)
                }
              ruby: >-
                require "openai"


                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )


                transcription = openai.audio.transcriptions.create(file: Pathname(__FILE__), model:
                :"whisper-1")


                puts(transcription)
            response: |
              {
                "task": "transcribe",
                "language": "english",
                "duration": 8.470000267028809,
                "text": "The beach was a popular spot on a hot summer day. People were swimming in the ocean, building sandcastles, and playing beach volleyball.",
                "segments": [
                  {
                    "id": 0,
                    "seek": 0,
                    "start": 0.0,
                    "end": 3.319999933242798,
                    "text": " The beach was a popular spot on a hot summer day.",
                    "tokens": [
                      50364, 440, 7534, 390, 257, 3743, 4008, 322, 257, 2368, 4266, 786, 13, 50530
                    ],
                    "temperature": 0.0,
                    "avg_logprob": -0.2860786020755768,
                    "compression_ratio": 1.2363636493682861,
                    "no_speech_prob": 0.00985979475080967
                  },
                  ...
                ]
              }
  /audio/translations:
    post:
      operationId: createTranslation
      tags:
        - Audio
      summary: Translates audio into English.
      requestBody:
        required: true
        content:
          multipart/form-data:
            schema:
              $ref: '#/components/schemas/CreateTranslationRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                oneOf:
                  - $ref: '#/components/schemas/CreateTranslationResponseJson'
                  - $ref: '#/components/schemas/CreateTranslationResponseVerboseJson'
      x-oaiMeta:
        name: Create translation
        group: audio
        returns: The translated text.
        examples:
          response: |
            {
              "text": "Hello, my name is Wolfgang and I come from Germany. Where are you heading today?"
            }
          request:
            curl: |
              curl https://api.openai.com/v1/audio/translations \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: multipart/form-data" \
                -F file="@/path/to/file/german.m4a" \
                -F model="whisper-1"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              translation = client.audio.translations.create(
                  file=b"raw file contents",
                  model="whisper-1",
              )
              print(translation)
            javascript: |
              import fs from "fs";
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                  const translation = await openai.audio.translations.create({
                      file: fs.createReadStream("speech.mp3"),
                      model: "whisper-1",
                  });

                  console.log(translation.text);
              }
              main();
            csharp: |
              using System;

              using OpenAI.Audio;

              string audioFilePath = "audio.mp3";

              AudioClient client = new(
                  model: "whisper-1",
                  apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
              );

              AudioTranscription transcription = client.TranscribeAudio(audioFilePath);

              Console.WriteLine($"{transcription.Text}");
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const translation = await client.audio.translations.create({
                file: fs.createReadStream('speech.mp3'),
                model: 'whisper-1',
              });

              console.log(translation);
            go: |
              package main

              import (
                "bytes"
                "context"
                "fmt"
                "io"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                translation, err := client.Audio.Translations.New(context.TODO(), openai.AudioTranslationNewParams{
                  File: io.Reader(bytes.NewBuffer([]byte("some file contents"))),
                  Model: openai.AudioModelWhisper1,
                })
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", translation)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.audio.AudioModel;
              import com.openai.models.audio.translations.TranslationCreateParams;
              import com.openai.models.audio.translations.TranslationCreateResponse;
              import java.io.ByteArrayInputStream;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      TranslationCreateParams params = TranslationCreateParams.builder()
                          .file(ByteArrayInputStream("some content".getBytes()))
                          .model(AudioModel.WHISPER_1)
                          .build();
                      TranslationCreateResponse translation = client.audio().translations().create(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.audio.AudioModel
              import com.openai.models.audio.translations.TranslationCreateParams
              import com.openai.models.audio.translations.TranslationCreateResponse
              import java.io.ByteArrayInputStream

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: TranslationCreateParams = TranslationCreateParams.builder()
                      .file("some content".byteInputStream())
                      .model(AudioModel.WHISPER_1)
                      .build()
                  val translation: TranslationCreateResponse = client.audio().translations().create(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              translation = openai.audio.translations.create(file: Pathname(__FILE__), model: :"whisper-1")

              puts(translation)
  /batches:
    post:
      summary: Creates and executes a batch from an uploaded file of requests
      operationId: createBatch
      tags:
        - Batch
      requestBody:
        required: true
        content:
          application/json:
            schema:
              type: object
              required:
                - input_file_id
                - endpoint
                - completion_window
              properties:
                input_file_id:
                  type: string
                  description: >
                    The ID of an uploaded file that contains requests for the new batch.


                    See [upload file](/docs/api-reference/files/create) for how to upload a file.


                    Your input file must be formatted as a [JSONL
                    file](/docs/api-reference/batch/request-input), and must be uploaded with the purpose
                    `batch`. The file can contain up to 50,000 requests, and can be up to 200 MB in size.
                endpoint:
                  type: string
                  enum:
                    - /v1/responses
                    - /v1/chat/completions
                    - /v1/embeddings
                    - /v1/completions
                  description: >-
                    The endpoint to be used for all requests in the batch. Currently `/v1/responses`,
                    `/v1/chat/completions`, `/v1/embeddings`, and `/v1/completions` are supported. Note that
                    `/v1/embeddings` batches are also restricted to a maximum of 50,000 embedding inputs
                    across all requests in the batch.
                completion_window:
                  type: string
                  enum:
                    - 24h
                  description: >-
                    The time frame within which the batch should be processed. Currently only `24h` is
                    supported.
                metadata:
                  $ref: '#/components/schemas/Metadata'
      responses:
        '200':
          description: Batch created successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Batch'
      x-oaiMeta:
        name: Create batch
        group: batch
        returns: The created [Batch](/docs/api-reference/batch/object) object.
        examples:
          response: |
            {
              "id": "batch_abc123",
              "object": "batch",
              "endpoint": "/v1/chat/completions",
              "errors": null,
              "input_file_id": "file-abc123",
              "completion_window": "24h",
              "status": "validating",
              "output_file_id": null,
              "error_file_id": null,
              "created_at": 1711471533,
              "in_progress_at": null,
              "expires_at": null,
              "finalizing_at": null,
              "completed_at": null,
              "failed_at": null,
              "expired_at": null,
              "cancelling_at": null,
              "cancelled_at": null,
              "request_counts": {
                "total": 0,
                "completed": 0,
                "failed": 0
              },
              "metadata": {
                "customer_id": "user_123456789",
                "batch_description": "Nightly eval job",
              }
            }
          request:
            curl: |
              curl https://api.openai.com/v1/batches \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
                -d '{
                  "input_file_id": "file-abc123",
                  "endpoint": "/v1/chat/completions",
                  "completion_window": "24h"
                }'
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              batch = client.batches.create(
                  completion_window="24h",
                  endpoint="/v1/responses",
                  input_file_id="input_file_id",
              )
              print(batch.id)
            node: |
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const batch = await openai.batches.create({
                  input_file_id: "file-abc123",
                  endpoint: "/v1/chat/completions",
                  completion_window: "24h"
                });

                console.log(batch);
              }

              main();
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const batch = await client.batches.create({
                completion_window: '24h',
                endpoint: '/v1/responses',
                input_file_id: 'input_file_id',
              });

              console.log(batch.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                batch, err := client.Batches.New(context.TODO(), openai.BatchNewParams{
                  CompletionWindow: openai.BatchNewParamsCompletionWindow24h,
                  Endpoint: openai.BatchNewParamsEndpointV1Responses,
                  InputFileID: "input_file_id",
                })
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", batch.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.batches.Batch;
              import com.openai.models.batches.BatchCreateParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      BatchCreateParams params = BatchCreateParams.builder()
                          .completionWindow(BatchCreateParams.CompletionWindow._24H)
                          .endpoint(BatchCreateParams.Endpoint.V1_RESPONSES)
                          .inputFileId("input_file_id")
                          .build();
                      Batch batch = client.batches().create(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.batches.Batch
              import com.openai.models.batches.BatchCreateParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: BatchCreateParams = BatchCreateParams.builder()
                      .completionWindow(BatchCreateParams.CompletionWindow._24H)
                      .endpoint(BatchCreateParams.Endpoint.V1_RESPONSES)
                      .inputFileId("input_file_id")
                      .build()
                  val batch: Batch = client.batches().create(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              batch = openai.batches.create(
                completion_window: :"24h",
                endpoint: :"/v1/responses",
                input_file_id: "input_file_id"
              )

              puts(batch)
    get:
      operationId: listBatches
      tags:
        - Batch
      summary: List your organization's batches.
      parameters:
        - in: query
          name: after
          required: false
          schema:
            type: string
          description: >
            A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
            instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
            call can include after=obj_foo in order to fetch the next page of the list.
        - name: limit
          in: query
          description: >
            A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
            default is 20.
          required: false
          schema:
            type: integer
            default: 20
      responses:
        '200':
          description: Batch listed successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ListBatchesResponse'
      x-oaiMeta:
        name: List batch
        group: batch
        returns: A list of paginated [Batch](/docs/api-reference/batch/object) objects.
        examples:
          response: |
            {
              "object": "list",
              "data": [
                {
                  "id": "batch_abc123",
                  "object": "batch",
                  "endpoint": "/v1/chat/completions",
                  "errors": null,
                  "input_file_id": "file-abc123",
                  "completion_window": "24h",
                  "status": "completed",
                  "output_file_id": "file-cvaTdG",
                  "error_file_id": "file-HOWS94",
                  "created_at": 1711471533,
                  "in_progress_at": 1711471538,
                  "expires_at": 1711557933,
                  "finalizing_at": 1711493133,
                  "completed_at": 1711493163,
                  "failed_at": null,
                  "expired_at": null,
                  "cancelling_at": null,
                  "cancelled_at": null,
                  "request_counts": {
                    "total": 100,
                    "completed": 95,
                    "failed": 5
                  },
                  "metadata": {
                    "customer_id": "user_123456789",
                    "batch_description": "Nightly job",
                  }
                },
                { ... },
              ],
              "first_id": "batch_abc123",
              "last_id": "batch_abc456",
              "has_more": true
            }
          request:
            curl: |
              curl https://api.openai.com/v1/batches?limit=2 \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              page = client.batches.list()
              page = page.data[0]
              print(page.id)
            node: |
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const list = await openai.batches.list();

                for await (const batch of list) {
                  console.log(batch);
                }
              }

              main();
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              // Automatically fetches more pages as needed.
              for await (const batch of client.batches.list()) {
                console.log(batch.id);
              }
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                page, err := client.Batches.List(context.TODO(), openai.BatchListParams{

                })
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", page)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.batches.BatchListPage;
              import com.openai.models.batches.BatchListParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      BatchListPage page = client.batches().list();
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.batches.BatchListPage
              import com.openai.models.batches.BatchListParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val page: BatchListPage = client.batches().list()
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              page = openai.batches.list

              puts(page)
  /batches/{batch_id}:
    get:
      operationId: retrieveBatch
      tags:
        - Batch
      summary: Retrieves a batch.
      parameters:
        - in: path
          name: batch_id
          required: true
          schema:
            type: string
          description: The ID of the batch to retrieve.
      responses:
        '200':
          description: Batch retrieved successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Batch'
      x-oaiMeta:
        name: Retrieve batch
        group: batch
        returns: The [Batch](/docs/api-reference/batch/object) object matching the specified ID.
        examples:
          response: |
            {
              "id": "batch_abc123",
              "object": "batch",
              "endpoint": "/v1/completions",
              "errors": null,
              "input_file_id": "file-abc123",
              "completion_window": "24h",
              "status": "completed",
              "output_file_id": "file-cvaTdG",
              "error_file_id": "file-HOWS94",
              "created_at": 1711471533,
              "in_progress_at": 1711471538,
              "expires_at": 1711557933,
              "finalizing_at": 1711493133,
              "completed_at": 1711493163,
              "failed_at": null,
              "expired_at": null,
              "cancelling_at": null,
              "cancelled_at": null,
              "request_counts": {
                "total": 100,
                "completed": 95,
                "failed": 5
              },
              "metadata": {
                "customer_id": "user_123456789",
                "batch_description": "Nightly eval job",
              }
            }
          request:
            curl: |
              curl https://api.openai.com/v1/batches/batch_abc123 \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              batch = client.batches.retrieve(
                  "batch_id",
              )
              print(batch.id)
            node: |
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const batch = await openai.batches.retrieve("batch_abc123");

                console.log(batch);
              }

              main();
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const batch = await client.batches.retrieve('batch_id');

              console.log(batch.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                batch, err := client.Batches.Get(context.TODO(), "batch_id")
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", batch.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.batches.Batch;
              import com.openai.models.batches.BatchRetrieveParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      Batch batch = client.batches().retrieve("batch_id");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.batches.Batch
              import com.openai.models.batches.BatchRetrieveParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val batch: Batch = client.batches().retrieve("batch_id")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              batch = openai.batches.retrieve("batch_id")

              puts(batch)
  /batches/{batch_id}/cancel:
    post:
      operationId: cancelBatch
      tags:
        - Batch
      summary: >-
        Cancels an in-progress batch. The batch will be in status `cancelling` for up to 10 minutes, before
        changing to `cancelled`, where it will have partial results (if any) available in the output file.
      parameters:
        - in: path
          name: batch_id
          required: true
          schema:
            type: string
          description: The ID of the batch to cancel.
      responses:
        '200':
          description: Batch is cancelling. Returns the cancelling batch's details.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Batch'
      x-oaiMeta:
        name: Cancel batch
        group: batch
        returns: The [Batch](/docs/api-reference/batch/object) object matching the specified ID.
        examples:
          response: |
            {
              "id": "batch_abc123",
              "object": "batch",
              "endpoint": "/v1/chat/completions",
              "errors": null,
              "input_file_id": "file-abc123",
              "completion_window": "24h",
              "status": "cancelling",
              "output_file_id": null,
              "error_file_id": null,
              "created_at": 1711471533,
              "in_progress_at": 1711471538,
              "expires_at": 1711557933,
              "finalizing_at": null,
              "completed_at": null,
              "failed_at": null,
              "expired_at": null,
              "cancelling_at": 1711475133,
              "cancelled_at": null,
              "request_counts": {
                "total": 100,
                "completed": 23,
                "failed": 1
              },
              "metadata": {
                "customer_id": "user_123456789",
                "batch_description": "Nightly eval job",
              }
            }
          request:
            curl: |
              curl https://api.openai.com/v1/batches/batch_abc123/cancel \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
                -X POST
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              batch = client.batches.cancel(
                  "batch_id",
              )
              print(batch.id)
            node: |
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const batch = await openai.batches.cancel("batch_abc123");

                console.log(batch);
              }

              main();
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const batch = await client.batches.cancel('batch_id');

              console.log(batch.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                batch, err := client.Batches.Cancel(context.TODO(), "batch_id")
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", batch.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.batches.Batch;
              import com.openai.models.batches.BatchCancelParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      Batch batch = client.batches().cancel("batch_id");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.batches.Batch
              import com.openai.models.batches.BatchCancelParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val batch: Batch = client.batches().cancel("batch_id")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              batch = openai.batches.cancel("batch_id")

              puts(batch)
  /chat/completions:
    get:
      operationId: listChatCompletions
      tags:
        - Chat
      summary: |
        List stored Chat Completions. Only Chat Completions that have been stored
        with the `store` parameter set to `true` will be returned.
      parameters:
        - name: model
          in: query
          description: The model used to generate the Chat Completions.
          required: false
          schema:
            type: string
        - name: metadata
          in: query
          description: |
            A list of metadata keys to filter the Chat Completions by. Example:

            `metadata[key1]=value1&metadata[key2]=value2`
          required: false
          schema:
            $ref: '#/components/schemas/Metadata'
        - name: after
          in: query
          description: Identifier for the last chat completion from the previous pagination request.
          required: false
          schema:
            type: string
        - name: limit
          in: query
          description: Number of Chat Completions to retrieve.
          required: false
          schema:
            type: integer
            default: 20
        - name: order
          in: query
          description: >-
            Sort order for Chat Completions by timestamp. Use `asc` for ascending order or `desc` for
            descending order. Defaults to `asc`.
          required: false
          schema:
            type: string
            enum:
              - asc
              - desc
            default: asc
      responses:
        '200':
          description: A list of Chat Completions
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ChatCompletionList'
      x-oaiMeta:
        name: List Chat Completions
        group: chat
        returns: A list of [Chat Completions](/docs/api-reference/chat/list-object) matching the specified filters.
        path: list
        examples:
          response: |
            {
              "object": "list",
              "data": [
                {
                  "object": "chat.completion",
                  "id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2",
                  "model": "gpt-4.1-2025-04-14",
                  "created": 1738960610,
                  "request_id": "req_ded8ab984ec4bf840f37566c1011c417",
                  "tool_choice": null,
                  "usage": {
                    "total_tokens": 31,
                    "completion_tokens": 18,
                    "prompt_tokens": 13
                  },
                  "seed": 4944116822809979520,
                  "top_p": 1.0,
                  "temperature": 1.0,
                  "presence_penalty": 0.0,
                  "frequency_penalty": 0.0,
                  "system_fingerprint": "fp_50cad350e4",
                  "input_user": null,
                  "service_tier": "default",
                  "tools": null,
                  "metadata": {},
                  "choices": [
                    {
                      "index": 0,
                      "message": {
                        "content": "Mind of circuits hum,  \nLearning patterns in silence—  \nFuture's quiet spark.",
                        "role": "assistant",
                        "tool_calls": null,
                        "function_call": null
                      },
                      "finish_reason": "stop",
                      "logprobs": null
                    }
                  ],
                  "response_format": null
                }
              ],
              "first_id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2",
              "last_id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2",
              "has_more": false
            }
          request:
            curl: |
              curl https://api.openai.com/v1/chat/completions \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              page = client.chat.completions.list()
              page = page.data[0]
              print(page.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              // Automatically fetches more pages as needed.
              for await (const chatCompletion of client.chat.completions.list()) {
                console.log(chatCompletion.id);
              }
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                page, err := client.Chat.Completions.List(context.TODO(), openai.ChatCompletionListParams{

                })
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", page)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.chat.completions.ChatCompletionListPage;
              import com.openai.models.chat.completions.ChatCompletionListParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      ChatCompletionListPage page = client.chat().completions().list();
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.chat.completions.ChatCompletionListPage
              import com.openai.models.chat.completions.ChatCompletionListParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val page: ChatCompletionListPage = client.chat().completions().list()
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              page = openai.chat.completions.list

              puts(page)
    post:
      operationId: createChatCompletion
      tags:
        - Chat
      summary: |
        **Starting a new project?** We recommend trying [Responses](/docs/api-reference/responses) 
        to take advantage of the latest OpenAI platform features. Compare
        [Chat Completions with Responses](/docs/guides/responses-vs-chat-completions?api-mode=responses).

        ---

        Creates a model response for the given chat conversation. Learn more in the
        [text generation](/docs/guides/text-generation), [vision](/docs/guides/vision),
        and [audio](/docs/guides/audio) guides.

        Parameter support can differ depending on the model used to generate the
        response, particularly for newer reasoning models. Parameters that are only
        supported for reasoning models are noted below. For the current state of 
        unsupported parameters in reasoning models, 
        [refer to the reasoning guide](/docs/guides/reasoning).
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateChatCompletionRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/CreateChatCompletionResponse'
            text/event-stream:
              schema:
                $ref: '#/components/schemas/CreateChatCompletionStreamResponse'
      x-oaiMeta:
        name: Create chat completion
        group: chat
        returns: >
          Returns a [chat completion](/docs/api-reference/chat/object) object, or a streamed sequence of [chat
          completion chunk](/docs/api-reference/chat/streaming) objects if the request is streamed.
        path: create
        examples:
          - title: Default
            request:
              curl: |
                curl https://api.openai.com/v1/chat/completions \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -d '{
                    "model": "VAR_chat_model_id",
                    "messages": [
                      {
                        "role": "developer",
                        "content": "You are a helpful assistant."
                      },
                      {
                        "role": "user",
                        "content": "Hello!"
                      }
                    ]
                  }'
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                chat_completion = client.chat.completions.create(
                    messages=[{
                        "content": "string",
                        "role": "developer",
                    }],
                    model="gpt-4o",
                )
                print(chat_completion)
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const chatCompletion = await client.chat.completions.create({
                  messages: [{ content: 'string', role: 'developer' }],
                  model: 'gpt-4o',
                });

                console.log(chatCompletion);
              csharp: |
                using System;
                using System.Collections.Generic;

                using OpenAI.Chat;

                ChatClient client = new(
                    model: "gpt-4.1",
                    apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
                );

                List<ChatMessage> messages =
                [
                    new SystemChatMessage("You are a helpful assistant."),
                    new UserChatMessage("Hello!")
                ];

                ChatCompletion completion = client.CompleteChat(messages);

                Console.WriteLine(completion.Content[0].Text);
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                  "github.com/openai/openai-go/shared"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  chatCompletion, err := client.Chat.Completions.New(context.TODO(), openai.ChatCompletionNewParams{
                    Messages: []openai.ChatCompletionMessageParamUnion{openai.ChatCompletionMessageParamUnion{
                      OfDeveloper: &openai.ChatCompletionDeveloperMessageParam{
                        Content: openai.ChatCompletionDeveloperMessageParamContentUnion{
                          OfString: openai.String("string"),
                        },
                      },
                    }},
                    Model: shared.ChatModelGPT4_1,
                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", chatCompletion)
                }
              java: |-
                package com.openai.example;

                import com.openai.client.OpenAIClient;
                import com.openai.client.okhttp.OpenAIOkHttpClient;
                import com.openai.models.ChatModel;
                import com.openai.models.chat.completions.ChatCompletion;
                import com.openai.models.chat.completions.ChatCompletionCreateParams;

                public final class Main {
                    private Main() {}

                    public static void main(String[] args) {
                        // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                        ChatCompletionCreateParams params = ChatCompletionCreateParams.builder()
                            .addDeveloperMessage("string")
                            .model(ChatModel.GPT_4_1)
                            .build();
                        ChatCompletion chatCompletion = client.chat().completions().create(params);
                    }
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.ChatModel
                import com.openai.models.chat.completions.ChatCompletion
                import com.openai.models.chat.completions.ChatCompletionCreateParams

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val params: ChatCompletionCreateParams = ChatCompletionCreateParams.builder()
                        .addDeveloperMessage("string")
                        .model(ChatModel.GPT_4_1)
                        .build()
                    val chatCompletion: ChatCompletion = client.chat().completions().create(params)
                }
              ruby: >-
                require "openai"


                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )


                chat_completion = openai.chat.completions.create(messages: [{content: "string", role:
                :developer}], model: :"gpt-4.1")


                puts(chat_completion)
            response: |
              {
                "id": "chatcmpl-B9MBs8CjcvOU2jLn4n570S5qMJKcT",
                "object": "chat.completion",
                "created": 1741569952,
                "model": "gpt-4.1-2025-04-14",
                "choices": [
                  {
                    "index": 0,
                    "message": {
                      "role": "assistant",
                      "content": "Hello! How can I assist you today?",
                      "refusal": null,
                      "annotations": []
                    },
                    "logprobs": null,
                    "finish_reason": "stop"
                  }
                ],
                "usage": {
                  "prompt_tokens": 19,
                  "completion_tokens": 10,
                  "total_tokens": 29,
                  "prompt_tokens_details": {
                    "cached_tokens": 0,
                    "audio_tokens": 0
                  },
                  "completion_tokens_details": {
                    "reasoning_tokens": 0,
                    "audio_tokens": 0,
                    "accepted_prediction_tokens": 0,
                    "rejected_prediction_tokens": 0
                  }
                },
                "service_tier": "default"
              }
          - title: Image input
            request:
              curl: |
                curl https://api.openai.com/v1/chat/completions \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -d '{
                    "model": "gpt-4.1",
                    "messages": [
                      {
                        "role": "user",
                        "content": [
                          {
                            "type": "text",
                            "text": "What is in this image?"
                          },
                          {
                            "type": "image_url",
                            "image_url": {
                              "url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
                            }
                          }
                        ]
                      }
                    ],
                    "max_tokens": 300
                  }'
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                chat_completion = client.chat.completions.create(
                    messages=[{
                        "content": "string",
                        "role": "developer",
                    }],
                    model="gpt-4o",
                )
                print(chat_completion)
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const chatCompletion = await client.chat.completions.create({
                  messages: [{ content: 'string', role: 'developer' }],
                  model: 'gpt-4o',
                });

                console.log(chatCompletion);
              csharp: |
                using System;
                using System.Collections.Generic;

                using OpenAI.Chat;

                ChatClient client = new(
                    model: "gpt-4.1",
                    apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
                );

                List<ChatMessage> messages =
                [
                    new UserChatMessage(
                    [
                        ChatMessageContentPart.CreateTextPart("What's in this image?"),
                        ChatMessageContentPart.CreateImagePart(new Uri("https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"))
                    ])
                ];

                ChatCompletion completion = client.CompleteChat(messages);

                Console.WriteLine(completion.Content[0].Text);
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                  "github.com/openai/openai-go/shared"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  chatCompletion, err := client.Chat.Completions.New(context.TODO(), openai.ChatCompletionNewParams{
                    Messages: []openai.ChatCompletionMessageParamUnion{openai.ChatCompletionMessageParamUnion{
                      OfDeveloper: &openai.ChatCompletionDeveloperMessageParam{
                        Content: openai.ChatCompletionDeveloperMessageParamContentUnion{
                          OfString: openai.String("string"),
                        },
                      },
                    }},
                    Model: shared.ChatModelGPT4_1,
                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", chatCompletion)
                }
              java: |-
                package com.openai.example;

                import com.openai.client.OpenAIClient;
                import com.openai.client.okhttp.OpenAIOkHttpClient;
                import com.openai.models.ChatModel;
                import com.openai.models.chat.completions.ChatCompletion;
                import com.openai.models.chat.completions.ChatCompletionCreateParams;

                public final class Main {
                    private Main() {}

                    public static void main(String[] args) {
                        // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                        ChatCompletionCreateParams params = ChatCompletionCreateParams.builder()
                            .addDeveloperMessage("string")
                            .model(ChatModel.GPT_4_1)
                            .build();
                        ChatCompletion chatCompletion = client.chat().completions().create(params);
                    }
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.ChatModel
                import com.openai.models.chat.completions.ChatCompletion
                import com.openai.models.chat.completions.ChatCompletionCreateParams

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val params: ChatCompletionCreateParams = ChatCompletionCreateParams.builder()
                        .addDeveloperMessage("string")
                        .model(ChatModel.GPT_4_1)
                        .build()
                    val chatCompletion: ChatCompletion = client.chat().completions().create(params)
                }
              ruby: >-
                require "openai"


                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )


                chat_completion = openai.chat.completions.create(messages: [{content: "string", role:
                :developer}], model: :"gpt-4.1")


                puts(chat_completion)
            response: |
              {
                "id": "chatcmpl-B9MHDbslfkBeAs8l4bebGdFOJ6PeG",
                "object": "chat.completion",
                "created": 1741570283,
                "model": "gpt-4.1-2025-04-14",
                "choices": [
                  {
                    "index": 0,
                    "message": {
                      "role": "assistant",
                      "content": "The image shows a wooden boardwalk path running through a lush green field or meadow. The sky is bright blue with some scattered clouds, giving the scene a serene and peaceful atmosphere. Trees and shrubs are visible in the background.",
                      "refusal": null,
                      "annotations": []
                    },
                    "logprobs": null,
                    "finish_reason": "stop"
                  }
                ],
                "usage": {
                  "prompt_tokens": 1117,
                  "completion_tokens": 46,
                  "total_tokens": 1163,
                  "prompt_tokens_details": {
                    "cached_tokens": 0,
                    "audio_tokens": 0
                  },
                  "completion_tokens_details": {
                    "reasoning_tokens": 0,
                    "audio_tokens": 0,
                    "accepted_prediction_tokens": 0,
                    "rejected_prediction_tokens": 0
                  }
                },
                "service_tier": "default"
              }
          - title: Streaming
            request:
              curl: |
                curl https://api.openai.com/v1/chat/completions \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -d '{
                    "model": "VAR_chat_model_id",
                    "messages": [
                      {
                        "role": "developer",
                        "content": "You are a helpful assistant."
                      },
                      {
                        "role": "user",
                        "content": "Hello!"
                      }
                    ],
                    "stream": true
                  }'
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                chat_completion = client.chat.completions.create(
                    messages=[{
                        "content": "string",
                        "role": "developer",
                    }],
                    model="gpt-4o",
                )
                print(chat_completion)
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const chatCompletion = await client.chat.completions.create({
                  messages: [{ content: 'string', role: 'developer' }],
                  model: 'gpt-4o',
                });

                console.log(chatCompletion);
              csharp: >
                using System;

                using System.ClientModel;

                using System.Collections.Generic;

                using System.Threading.Tasks;


                using OpenAI.Chat;


                ChatClient client = new(
                    model: "gpt-4.1",
                    apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
                );


                List<ChatMessage> messages =

                [
                    new SystemChatMessage("You are a helpful assistant."),
                    new UserChatMessage("Hello!")
                ];


                AsyncCollectionResult<StreamingChatCompletionUpdate> completionUpdates =
                client.CompleteChatStreamingAsync(messages);


                await foreach (StreamingChatCompletionUpdate completionUpdate in completionUpdates)

                {
                    if (completionUpdate.ContentUpdate.Count > 0)
                    {
                        Console.Write(completionUpdate.ContentUpdate[0].Text);
                    }
                }
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                  "github.com/openai/openai-go/shared"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  chatCompletion, err := client.Chat.Completions.New(context.TODO(), openai.ChatCompletionNewParams{
                    Messages: []openai.ChatCompletionMessageParamUnion{openai.ChatCompletionMessageParamUnion{
                      OfDeveloper: &openai.ChatCompletionDeveloperMessageParam{
                        Content: openai.ChatCompletionDeveloperMessageParamContentUnion{
                          OfString: openai.String("string"),
                        },
                      },
                    }},
                    Model: shared.ChatModelGPT4_1,
                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", chatCompletion)
                }
              java: |-
                package com.openai.example;

                import com.openai.client.OpenAIClient;
                import com.openai.client.okhttp.OpenAIOkHttpClient;
                import com.openai.models.ChatModel;
                import com.openai.models.chat.completions.ChatCompletion;
                import com.openai.models.chat.completions.ChatCompletionCreateParams;

                public final class Main {
                    private Main() {}

                    public static void main(String[] args) {
                        // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                        ChatCompletionCreateParams params = ChatCompletionCreateParams.builder()
                            .addDeveloperMessage("string")
                            .model(ChatModel.GPT_4_1)
                            .build();
                        ChatCompletion chatCompletion = client.chat().completions().create(params);
                    }
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.ChatModel
                import com.openai.models.chat.completions.ChatCompletion
                import com.openai.models.chat.completions.ChatCompletionCreateParams

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val params: ChatCompletionCreateParams = ChatCompletionCreateParams.builder()
                        .addDeveloperMessage("string")
                        .model(ChatModel.GPT_4_1)
                        .build()
                    val chatCompletion: ChatCompletion = client.chat().completions().create(params)
                }
              ruby: >-
                require "openai"


                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )


                chat_completion = openai.chat.completions.create(messages: [{content: "string", role:
                :developer}], model: :"gpt-4.1")


                puts(chat_completion)
            response: >
              {"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"gpt-4o-mini",
              "system_fingerprint": "fp_44709d6fcb",
              "choices":[{"index":0,"delta":{"role":"assistant","content":""},"logprobs":null,"finish_reason":null}]}


              {"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"gpt-4o-mini",
              "system_fingerprint": "fp_44709d6fcb",
              "choices":[{"index":0,"delta":{"content":"Hello"},"logprobs":null,"finish_reason":null}]}


              ....


              {"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"gpt-4o-mini",
              "system_fingerprint": "fp_44709d6fcb",
              "choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}]}
          - title: Functions
            request:
              curl: |
                curl https://api.openai.com/v1/chat/completions \
                -H "Content-Type: application/json" \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -d '{
                  "model": "gpt-4.1",
                  "messages": [
                    {
                      "role": "user",
                      "content": "What is the weather like in Boston today?"
                    }
                  ],
                  "tools": [
                    {
                      "type": "function",
                      "function": {
                        "name": "get_current_weather",
                        "description": "Get the current weather in a given location",
                        "parameters": {
                          "type": "object",
                          "properties": {
                            "location": {
                              "type": "string",
                              "description": "The city and state, e.g. San Francisco, CA"
                            },
                            "unit": {
                              "type": "string",
                              "enum": ["celsius", "fahrenheit"]
                            }
                          },
                          "required": ["location"]
                        }
                      }
                    }
                  ],
                  "tool_choice": "auto"
                }'
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                chat_completion = client.chat.completions.create(
                    messages=[{
                        "content": "string",
                        "role": "developer",
                    }],
                    model="gpt-4o",
                )
                print(chat_completion)
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const chatCompletion = await client.chat.completions.create({
                  messages: [{ content: 'string', role: 'developer' }],
                  model: 'gpt-4o',
                });

                console.log(chatCompletion);
              csharp: |
                using System;
                using System.Collections.Generic;

                using OpenAI.Chat;

                ChatClient client = new(
                    model: "gpt-4.1",
                    apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
                );

                ChatTool getCurrentWeatherTool = ChatTool.CreateFunctionTool(
                    functionName: "get_current_weather",
                    functionDescription: "Get the current weather in a given location",
                    functionParameters: BinaryData.FromString("""
                        {
                            "type": "object",
                            "properties": {
                                "location": {
                                    "type": "string",
                                    "description": "The city and state, e.g. San Francisco, CA"
                                },
                                "unit": {
                                    "type": "string",
                                    "enum": [ "celsius", "fahrenheit" ]
                                }
                            },
                            "required": [ "location" ]
                        }
                    """)
                );

                List<ChatMessage> messages =
                [
                    new UserChatMessage("What's the weather like in Boston today?"),
                ];

                ChatCompletionOptions options = new()
                {
                    Tools =
                    {
                        getCurrentWeatherTool
                    },
                    ToolChoice = ChatToolChoice.CreateAutoChoice(),
                };

                ChatCompletion completion = client.CompleteChat(messages, options);
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                  "github.com/openai/openai-go/shared"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  chatCompletion, err := client.Chat.Completions.New(context.TODO(), openai.ChatCompletionNewParams{
                    Messages: []openai.ChatCompletionMessageParamUnion{openai.ChatCompletionMessageParamUnion{
                      OfDeveloper: &openai.ChatCompletionDeveloperMessageParam{
                        Content: openai.ChatCompletionDeveloperMessageParamContentUnion{
                          OfString: openai.String("string"),
                        },
                      },
                    }},
                    Model: shared.ChatModelGPT4_1,
                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", chatCompletion)
                }
              java: |-
                package com.openai.example;

                import com.openai.client.OpenAIClient;
                import com.openai.client.okhttp.OpenAIOkHttpClient;
                import com.openai.models.ChatModel;
                import com.openai.models.chat.completions.ChatCompletion;
                import com.openai.models.chat.completions.ChatCompletionCreateParams;

                public final class Main {
                    private Main() {}

                    public static void main(String[] args) {
                        // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                        ChatCompletionCreateParams params = ChatCompletionCreateParams.builder()
                            .addDeveloperMessage("string")
                            .model(ChatModel.GPT_4_1)
                            .build();
                        ChatCompletion chatCompletion = client.chat().completions().create(params);
                    }
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.ChatModel
                import com.openai.models.chat.completions.ChatCompletion
                import com.openai.models.chat.completions.ChatCompletionCreateParams

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val params: ChatCompletionCreateParams = ChatCompletionCreateParams.builder()
                        .addDeveloperMessage("string")
                        .model(ChatModel.GPT_4_1)
                        .build()
                    val chatCompletion: ChatCompletion = client.chat().completions().create(params)
                }
              ruby: >-
                require "openai"


                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )


                chat_completion = openai.chat.completions.create(messages: [{content: "string", role:
                :developer}], model: :"gpt-4.1")


                puts(chat_completion)
            response: |
              {
                "id": "chatcmpl-abc123",
                "object": "chat.completion",
                "created": 1699896916,
                "model": "gpt-4o-mini",
                "choices": [
                  {
                    "index": 0,
                    "message": {
                      "role": "assistant",
                      "content": null,
                      "tool_calls": [
                        {
                          "id": "call_abc123",
                          "type": "function",
                          "function": {
                            "name": "get_current_weather",
                            "arguments": "{\n\"location\": \"Boston, MA\"\n}"
                          }
                        }
                      ]
                    },
                    "logprobs": null,
                    "finish_reason": "tool_calls"
                  }
                ],
                "usage": {
                  "prompt_tokens": 82,
                  "completion_tokens": 17,
                  "total_tokens": 99,
                  "completion_tokens_details": {
                    "reasoning_tokens": 0,
                    "accepted_prediction_tokens": 0,
                    "rejected_prediction_tokens": 0
                  }
                }
              }
          - title: Logprobs
            request:
              curl: |
                curl https://api.openai.com/v1/chat/completions \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -d '{
                    "model": "VAR_chat_model_id",
                    "messages": [
                      {
                        "role": "user",
                        "content": "Hello!"
                      }
                    ],
                    "logprobs": true,
                    "top_logprobs": 2
                  }'
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                chat_completion = client.chat.completions.create(
                    messages=[{
                        "content": "string",
                        "role": "developer",
                    }],
                    model="gpt-4o",
                )
                print(chat_completion)
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const chatCompletion = await client.chat.completions.create({
                  messages: [{ content: 'string', role: 'developer' }],
                  model: 'gpt-4o',
                });

                console.log(chatCompletion);
              csharp: |
                using System;
                using System.Collections.Generic;

                using OpenAI.Chat;

                ChatClient client = new(
                    model: "gpt-4.1",
                    apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
                );

                List<ChatMessage> messages =
                [
                    new UserChatMessage("Hello!")
                ];

                ChatCompletionOptions options = new()
                {
                    IncludeLogProbabilities = true,
                    TopLogProbabilityCount = 2
                };

                ChatCompletion completion = client.CompleteChat(messages, options);

                Console.WriteLine(completion.Content[0].Text);
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                  "github.com/openai/openai-go/shared"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  chatCompletion, err := client.Chat.Completions.New(context.TODO(), openai.ChatCompletionNewParams{
                    Messages: []openai.ChatCompletionMessageParamUnion{openai.ChatCompletionMessageParamUnion{
                      OfDeveloper: &openai.ChatCompletionDeveloperMessageParam{
                        Content: openai.ChatCompletionDeveloperMessageParamContentUnion{
                          OfString: openai.String("string"),
                        },
                      },
                    }},
                    Model: shared.ChatModelGPT4_1,
                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", chatCompletion)
                }
              java: |-
                package com.openai.example;

                import com.openai.client.OpenAIClient;
                import com.openai.client.okhttp.OpenAIOkHttpClient;
                import com.openai.models.ChatModel;
                import com.openai.models.chat.completions.ChatCompletion;
                import com.openai.models.chat.completions.ChatCompletionCreateParams;

                public final class Main {
                    private Main() {}

                    public static void main(String[] args) {
                        // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                        ChatCompletionCreateParams params = ChatCompletionCreateParams.builder()
                            .addDeveloperMessage("string")
                            .model(ChatModel.GPT_4_1)
                            .build();
                        ChatCompletion chatCompletion = client.chat().completions().create(params);
                    }
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.ChatModel
                import com.openai.models.chat.completions.ChatCompletion
                import com.openai.models.chat.completions.ChatCompletionCreateParams

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val params: ChatCompletionCreateParams = ChatCompletionCreateParams.builder()
                        .addDeveloperMessage("string")
                        .model(ChatModel.GPT_4_1)
                        .build()
                    val chatCompletion: ChatCompletion = client.chat().completions().create(params)
                }
              ruby: >-
                require "openai"


                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )


                chat_completion = openai.chat.completions.create(messages: [{content: "string", role:
                :developer}], model: :"gpt-4.1")


                puts(chat_completion)
            response: |
              {
                "id": "chatcmpl-123",
                "object": "chat.completion",
                "created": 1702685778,
                "model": "gpt-4o-mini",
                "choices": [
                  {
                    "index": 0,
                    "message": {
                      "role": "assistant",
                      "content": "Hello! How can I assist you today?"
                    },
                    "logprobs": {
                      "content": [
                        {
                          "token": "Hello",
                          "logprob": -0.31725305,
                          "bytes": [72, 101, 108, 108, 111],
                          "top_logprobs": [
                            {
                              "token": "Hello",
                              "logprob": -0.31725305,
                              "bytes": [72, 101, 108, 108, 111]
                            },
                            {
                              "token": "Hi",
                              "logprob": -1.3190403,
                              "bytes": [72, 105]
                            }
                          ]
                        },
                        {
                          "token": "!",
                          "logprob": -0.02380986,
                          "bytes": [
                            33
                          ],
                          "top_logprobs": [
                            {
                              "token": "!",
                              "logprob": -0.02380986,
                              "bytes": [33]
                            },
                            {
                              "token": " there",
                              "logprob": -3.787621,
                              "bytes": [32, 116, 104, 101, 114, 101]
                            }
                          ]
                        },
                        {
                          "token": " How",
                          "logprob": -0.000054669687,
                          "bytes": [32, 72, 111, 119],
                          "top_logprobs": [
                            {
                              "token": " How",
                              "logprob": -0.000054669687,
                              "bytes": [32, 72, 111, 119]
                            },
                            {
                              "token": "<|end|>",
                              "logprob": -10.953937,
                              "bytes": null
                            }
                          ]
                        },
                        {
                          "token": " can",
                          "logprob": -0.015801601,
                          "bytes": [32, 99, 97, 110],
                          "top_logprobs": [
                            {
                              "token": " can",
                              "logprob": -0.015801601,
                              "bytes": [32, 99, 97, 110]
                            },
                            {
                              "token": " may",
                              "logprob": -4.161023,
                              "bytes": [32, 109, 97, 121]
                            }
                          ]
                        },
                        {
                          "token": " I",
                          "logprob": -3.7697225e-6,
                          "bytes": [
                            32,
                            73
                          ],
                          "top_logprobs": [
                            {
                              "token": " I",
                              "logprob": -3.7697225e-6,
                              "bytes": [32, 73]
                            },
                            {
                              "token": " assist",
                              "logprob": -13.596657,
                              "bytes": [32, 97, 115, 115, 105, 115, 116]
                            }
                          ]
                        },
                        {
                          "token": " assist",
                          "logprob": -0.04571125,
                          "bytes": [32, 97, 115, 115, 105, 115, 116],
                          "top_logprobs": [
                            {
                              "token": " assist",
                              "logprob": -0.04571125,
                              "bytes": [32, 97, 115, 115, 105, 115, 116]
                            },
                            {
                              "token": " help",
                              "logprob": -3.1089056,
                              "bytes": [32, 104, 101, 108, 112]
                            }
                          ]
                        },
                        {
                          "token": " you",
                          "logprob": -5.4385737e-6,
                          "bytes": [32, 121, 111, 117],
                          "top_logprobs": [
                            {
                              "token": " you",
                              "logprob": -5.4385737e-6,
                              "bytes": [32, 121, 111, 117]
                            },
                            {
                              "token": " today",
                              "logprob": -12.807695,
                              "bytes": [32, 116, 111, 100, 97, 121]
                            }
                          ]
                        },
                        {
                          "token": " today",
                          "logprob": -0.0040071653,
                          "bytes": [32, 116, 111, 100, 97, 121],
                          "top_logprobs": [
                            {
                              "token": " today",
                              "logprob": -0.0040071653,
                              "bytes": [32, 116, 111, 100, 97, 121]
                            },
                            {
                              "token": "?",
                              "logprob": -5.5247097,
                              "bytes": [63]
                            }
                          ]
                        },
                        {
                          "token": "?",
                          "logprob": -0.0008108172,
                          "bytes": [63],
                          "top_logprobs": [
                            {
                              "token": "?",
                              "logprob": -0.0008108172,
                              "bytes": [63]
                            },
                            {
                              "token": "?\n",
                              "logprob": -7.184561,
                              "bytes": [63, 10]
                            }
                          ]
                        }
                      ]
                    },
                    "finish_reason": "stop"
                  }
                ],
                "usage": {
                  "prompt_tokens": 9,
                  "completion_tokens": 9,
                  "total_tokens": 18,
                  "completion_tokens_details": {
                    "reasoning_tokens": 0,
                    "accepted_prediction_tokens": 0,
                    "rejected_prediction_tokens": 0
                  }
                },
                "system_fingerprint": null
              }
  /chat/completions/{completion_id}:
    get:
      operationId: getChatCompletion
      tags:
        - Chat
      summary: |
        Get a stored chat completion. Only Chat Completions that have been created
        with the `store` parameter set to `true` will be returned.
      parameters:
        - in: path
          name: completion_id
          required: true
          schema:
            type: string
          description: The ID of the chat completion to retrieve.
      responses:
        '200':
          description: A chat completion
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/CreateChatCompletionResponse'
      x-oaiMeta:
        name: Get chat completion
        group: chat
        returns: The [ChatCompletion](/docs/api-reference/chat/object) object matching the specified ID.
        examples:
          response: |
            {
              "object": "chat.completion",
              "id": "chatcmpl-abc123",
              "model": "gpt-4o-2024-08-06",
              "created": 1738960610,
              "request_id": "req_ded8ab984ec4bf840f37566c1011c417",
              "tool_choice": null,
              "usage": {
                "total_tokens": 31,
                "completion_tokens": 18,
                "prompt_tokens": 13
              },
              "seed": 4944116822809979520,
              "top_p": 1.0,
              "temperature": 1.0,
              "presence_penalty": 0.0,
              "frequency_penalty": 0.0,
              "system_fingerprint": "fp_50cad350e4",
              "input_user": null,
              "service_tier": "default",
              "tools": null,
              "metadata": {},
              "choices": [
                {
                  "index": 0,
                  "message": {
                    "content": "Mind of circuits hum,  \nLearning patterns in silence—  \nFuture's quiet spark.",
                    "role": "assistant",
                    "tool_calls": null,
                    "function_call": null
                  },
                  "finish_reason": "stop",
                  "logprobs": null
                }
              ],
              "response_format": null
            }
          request:
            curl: |
              curl https://api.openai.com/v1/chat/completions/chatcmpl-abc123 \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              chat_completion = client.chat.completions.retrieve(
                  "completion_id",
              )
              print(chat_completion.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const chatCompletion = await client.chat.completions.retrieve('completion_id');

              console.log(chatCompletion.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                chatCompletion, err := client.Chat.Completions.Get(context.TODO(), "completion_id")
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", chatCompletion.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.chat.completions.ChatCompletion;
              import com.openai.models.chat.completions.ChatCompletionRetrieveParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      ChatCompletion chatCompletion = client.chat().completions().retrieve("completion_id");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.chat.completions.ChatCompletion
              import com.openai.models.chat.completions.ChatCompletionRetrieveParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val chatCompletion: ChatCompletion = client.chat().completions().retrieve("completion_id")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              chat_completion = openai.chat.completions.retrieve("completion_id")

              puts(chat_completion)
    post:
      operationId: updateChatCompletion
      tags:
        - Chat
      summary: |
        Modify a stored chat completion. Only Chat Completions that have been
        created with the `store` parameter set to `true` can be modified. Currently,
        the only supported modification is to update the `metadata` field.
      parameters:
        - in: path
          name: completion_id
          required: true
          schema:
            type: string
          description: The ID of the chat completion to update.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              type: object
              required:
                - metadata
              properties:
                metadata:
                  $ref: '#/components/schemas/Metadata'
      responses:
        '200':
          description: A chat completion
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/CreateChatCompletionResponse'
      x-oaiMeta:
        name: Update chat completion
        group: chat
        returns: The [ChatCompletion](/docs/api-reference/chat/object) object matching the specified ID.
        examples:
          response: |
            {
              "object": "chat.completion",
              "id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2",
              "model": "gpt-4o-2024-08-06",
              "created": 1738960610,
              "request_id": "req_ded8ab984ec4bf840f37566c1011c417",
              "tool_choice": null,
              "usage": {
                "total_tokens": 31,
                "completion_tokens": 18,
                "prompt_tokens": 13
              },
              "seed": 4944116822809979520,
              "top_p": 1.0,
              "temperature": 1.0,
              "presence_penalty": 0.0,
              "frequency_penalty": 0.0,
              "system_fingerprint": "fp_50cad350e4",
              "input_user": null,
              "service_tier": "default",
              "tools": null,
              "metadata": {
                "foo": "bar"
              },
              "choices": [
                {
                  "index": 0,
                  "message": {
                    "content": "Mind of circuits hum,  \nLearning patterns in silence—  \nFuture's quiet spark.",
                    "role": "assistant",
                    "tool_calls": null,
                    "function_call": null
                  },
                  "finish_reason": "stop",
                  "logprobs": null
                }
              ],
              "response_format": null
            }
          request:
            curl: |
              curl -X POST https://api.openai.com/v1/chat/completions/chat_abc123 \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
                -d '{"metadata": {"foo": "bar"}}'
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              chat_completion = client.chat.completions.update(
                  completion_id="completion_id",
                  metadata={
                      "foo": "string"
                  },
              )
              print(chat_completion.id)
            node.js: >-
              import OpenAI from 'openai';


              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });


              const chatCompletion = await client.chat.completions.update('completion_id', { metadata: { foo:
              'string' } });


              console.log(chatCompletion.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
                "github.com/openai/openai-go/shared"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                chatCompletion, err := client.Chat.Completions.Update(
                  context.TODO(),
                  "completion_id",
                  openai.ChatCompletionUpdateParams{
                    Metadata: shared.Metadata{
                    "foo": "string",
                    },
                  },
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", chatCompletion.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.core.JsonValue;
              import com.openai.models.chat.completions.ChatCompletion;
              import com.openai.models.chat.completions.ChatCompletionUpdateParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      ChatCompletionUpdateParams params = ChatCompletionUpdateParams.builder()
                          .completionId("completion_id")
                          .metadata(ChatCompletionUpdateParams.Metadata.builder()
                              .putAdditionalProperty("foo", JsonValue.from("string"))
                              .build())
                          .build();
                      ChatCompletion chatCompletion = client.chat().completions().update(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.core.JsonValue
              import com.openai.models.chat.completions.ChatCompletion
              import com.openai.models.chat.completions.ChatCompletionUpdateParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: ChatCompletionUpdateParams = ChatCompletionUpdateParams.builder()
                      .completionId("completion_id")
                      .metadata(ChatCompletionUpdateParams.Metadata.builder()
                          .putAdditionalProperty("foo", JsonValue.from("string"))
                          .build())
                      .build()
                  val chatCompletion: ChatCompletion = client.chat().completions().update(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              chat_completion = openai.chat.completions.update("completion_id", metadata: {foo: "string"})

              puts(chat_completion)
    delete:
      operationId: deleteChatCompletion
      tags:
        - Chat
      summary: |
        Delete a stored chat completion. Only Chat Completions that have been
        created with the `store` parameter set to `true` can be deleted.
      parameters:
        - in: path
          name: completion_id
          required: true
          schema:
            type: string
          description: The ID of the chat completion to delete.
      responses:
        '200':
          description: The chat completion was deleted successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ChatCompletionDeleted'
      x-oaiMeta:
        name: Delete chat completion
        group: chat
        returns: A deletion confirmation object.
        examples:
          response: |
            {
              "object": "chat.completion.deleted",
              "id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2",
              "deleted": true
            }
          request:
            curl: |
              curl -X DELETE https://api.openai.com/v1/chat/completions/chat_abc123 \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              chat_completion_deleted = client.chat.completions.delete(
                  "completion_id",
              )
              print(chat_completion_deleted.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const chatCompletionDeleted = await client.chat.completions.delete('completion_id');

              console.log(chatCompletionDeleted.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                chatCompletionDeleted, err := client.Chat.Completions.Delete(context.TODO(), "completion_id")
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", chatCompletionDeleted.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.chat.completions.ChatCompletionDeleteParams;
              import com.openai.models.chat.completions.ChatCompletionDeleted;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      ChatCompletionDeleted chatCompletionDeleted = client.chat().completions().delete("completion_id");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.chat.completions.ChatCompletionDeleteParams
              import com.openai.models.chat.completions.ChatCompletionDeleted

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val chatCompletionDeleted: ChatCompletionDeleted = client.chat().completions().delete("completion_id")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              chat_completion_deleted = openai.chat.completions.delete("completion_id")

              puts(chat_completion_deleted)
  /chat/completions/{completion_id}/messages:
    get:
      operationId: getChatCompletionMessages
      tags:
        - Chat
      summary: |
        Get the messages in a stored chat completion. Only Chat Completions that
        have been created with the `store` parameter set to `true` will be
        returned.
      parameters:
        - in: path
          name: completion_id
          required: true
          schema:
            type: string
          description: The ID of the chat completion to retrieve messages from.
        - name: after
          in: query
          description: Identifier for the last message from the previous pagination request.
          required: false
          schema:
            type: string
        - name: limit
          in: query
          description: Number of messages to retrieve.
          required: false
          schema:
            type: integer
            default: 20
        - name: order
          in: query
          description: >-
            Sort order for messages by timestamp. Use `asc` for ascending order or `desc` for descending
            order. Defaults to `asc`.
          required: false
          schema:
            type: string
            enum:
              - asc
              - desc
            default: asc
      responses:
        '200':
          description: A list of messages
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ChatCompletionMessageList'
      x-oaiMeta:
        name: Get chat messages
        group: chat
        returns: A list of [messages](/docs/api-reference/chat/message-list) for the specified chat completion.
        examples:
          response: |
            {
              "object": "list",
              "data": [
                {
                  "id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2-0",
                  "role": "user",
                  "content": "write a haiku about ai",
                  "name": null,
                  "content_parts": null
                }
              ],
              "first_id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2-0",
              "last_id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2-0",
              "has_more": false
            }
          request:
            curl: |
              curl https://api.openai.com/v1/chat/completions/chat_abc123/messages \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              page = client.chat.completions.messages.list(
                  completion_id="completion_id",
              )
              page = page.data[0]
              print(page)
            node.js: >-
              import OpenAI from 'openai';


              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });


              // Automatically fetches more pages as needed.

              for await (const chatCompletionStoreMessage of
              client.chat.completions.messages.list('completion_id')) {
                console.log(chatCompletionStoreMessage);
              }
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                page, err := client.Chat.Completions.Messages.List(
                  context.TODO(),
                  "completion_id",
                  openai.ChatCompletionMessageListParams{

                  },
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", page)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.chat.completions.messages.MessageListPage;
              import com.openai.models.chat.completions.messages.MessageListParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      MessageListPage page = client.chat().completions().messages().list("completion_id");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.chat.completions.messages.MessageListPage
              import com.openai.models.chat.completions.messages.MessageListParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val page: MessageListPage = client.chat().completions().messages().list("completion_id")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              page = openai.chat.completions.messages.list("completion_id")

              puts(page)
  /completions:
    post:
      operationId: createCompletion
      tags:
        - Completions
      summary: Creates a completion for the provided prompt and parameters.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateCompletionRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/CreateCompletionResponse'
      x-oaiMeta:
        name: Create completion
        group: completions
        returns: >
          Returns a [completion](/docs/api-reference/completions/object) object, or a sequence of completion
          objects if the request is streamed.
        legacy: true
        examples:
          - title: No streaming
            request:
              curl: |
                curl https://api.openai.com/v1/completions \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -d '{
                    "model": "VAR_completion_model_id",
                    "prompt": "Say this is a test",
                    "max_tokens": 7,
                    "temperature": 0
                  }'
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                completion = client.completions.create(
                    model="string",
                    prompt="This is a test.",
                )
                print(completion)
              node.js: >-
                import OpenAI from 'openai';


                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });


                const completion = await client.completions.create({ model: 'string', prompt: 'This is a
                test.' });


                console.log(completion);
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  completion, err := client.Completions.New(context.TODO(), openai.CompletionNewParams{
                    Model: openai.CompletionNewParamsModelGPT3_5TurboInstruct,
                    Prompt: openai.CompletionNewParamsPromptUnion{
                      OfString: openai.String("This is a test."),
                    },
                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", completion)
                }
              java: |-
                package com.openai.example;

                import com.openai.client.OpenAIClient;
                import com.openai.client.okhttp.OpenAIOkHttpClient;
                import com.openai.models.completions.Completion;
                import com.openai.models.completions.CompletionCreateParams;

                public final class Main {
                    private Main() {}

                    public static void main(String[] args) {
                        // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                        CompletionCreateParams params = CompletionCreateParams.builder()
                            .model(CompletionCreateParams.Model.GPT_3_5_TURBO_INSTRUCT)
                            .prompt("This is a test.")
                            .build();
                        Completion completion = client.completions().create(params);
                    }
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.completions.Completion
                import com.openai.models.completions.CompletionCreateParams

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val params: CompletionCreateParams = CompletionCreateParams.builder()
                        .model(CompletionCreateParams.Model.GPT_3_5_TURBO_INSTRUCT)
                        .prompt("This is a test.")
                        .build()
                    val completion: Completion = client.completions().create(params)
                }
              ruby: >-
                require "openai"


                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )


                completion = openai.completions.create(model: :"gpt-3.5-turbo-instruct", prompt: "This is a
                test.")


                puts(completion)
            response: |
              {
                "id": "cmpl-uqkvlQyYK7bGYrRHQ0eXlWi7",
                "object": "text_completion",
                "created": 1589478378,
                "model": "VAR_completion_model_id",
                "system_fingerprint": "fp_44709d6fcb",
                "choices": [
                  {
                    "text": "\n\nThis is indeed a test",
                    "index": 0,
                    "logprobs": null,
                    "finish_reason": "length"
                  }
                ],
                "usage": {
                  "prompt_tokens": 5,
                  "completion_tokens": 7,
                  "total_tokens": 12
                }
              }
          - title: Streaming
            request:
              curl: |
                curl https://api.openai.com/v1/completions \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -d '{
                    "model": "VAR_completion_model_id",
                    "prompt": "Say this is a test",
                    "max_tokens": 7,
                    "temperature": 0,
                    "stream": true
                  }'
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                completion = client.completions.create(
                    model="string",
                    prompt="This is a test.",
                )
                print(completion)
              node.js: >-
                import OpenAI from 'openai';


                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });


                const completion = await client.completions.create({ model: 'string', prompt: 'This is a
                test.' });


                console.log(completion);
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  completion, err := client.Completions.New(context.TODO(), openai.CompletionNewParams{
                    Model: openai.CompletionNewParamsModelGPT3_5TurboInstruct,
                    Prompt: openai.CompletionNewParamsPromptUnion{
                      OfString: openai.String("This is a test."),
                    },
                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", completion)
                }
              java: |-
                package com.openai.example;

                import com.openai.client.OpenAIClient;
                import com.openai.client.okhttp.OpenAIOkHttpClient;
                import com.openai.models.completions.Completion;
                import com.openai.models.completions.CompletionCreateParams;

                public final class Main {
                    private Main() {}

                    public static void main(String[] args) {
                        // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                        CompletionCreateParams params = CompletionCreateParams.builder()
                            .model(CompletionCreateParams.Model.GPT_3_5_TURBO_INSTRUCT)
                            .prompt("This is a test.")
                            .build();
                        Completion completion = client.completions().create(params);
                    }
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.completions.Completion
                import com.openai.models.completions.CompletionCreateParams

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val params: CompletionCreateParams = CompletionCreateParams.builder()
                        .model(CompletionCreateParams.Model.GPT_3_5_TURBO_INSTRUCT)
                        .prompt("This is a test.")
                        .build()
                    val completion: Completion = client.completions().create(params)
                }
              ruby: >-
                require "openai"


                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )


                completion = openai.completions.create(model: :"gpt-3.5-turbo-instruct", prompt: "This is a
                test.")


                puts(completion)
            response: |
              {
                "id": "cmpl-7iA7iJjj8V2zOkCGvWF2hAkDWBQZe",
                "object": "text_completion",
                "created": 1690759702,
                "choices": [
                  {
                    "text": "This",
                    "index": 0,
                    "logprobs": null,
                    "finish_reason": null
                  }
                ],
                "model": "gpt-3.5-turbo-instruct"
                "system_fingerprint": "fp_44709d6fcb",
              }
  /containers:
    get:
      summary: List Containers
      description: Lists containers.
      operationId: ListContainers
      parameters:
        - name: limit
          in: query
          description: >
            A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
            default is 20.
          required: false
          schema:
            type: integer
            default: 20
        - name: order
          in: query
          description: >
            Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for
            descending order.
          schema:
            type: string
            default: desc
            enum:
              - asc
              - desc
        - name: after
          in: query
          description: >
            A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
            instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
            call can include after=obj_foo in order to fetch the next page of the list.
          schema:
            type: string
      responses:
        '200':
          description: Success
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ContainerListResource'
      x-oaiMeta:
        name: List containers
        group: containers
        returns: a list of [container](/docs/api-reference/containers/object) objects.
        path: get
        examples:
          response: |
            {
              "object": "list",
              "data": [
                {
                    "id": "cntr_682dfebaacac8198bbfe9c2474fb6f4a085685cbe3cb5863",
                    "object": "container",
                    "created_at": 1747844794,
                    "status": "running",
                    "expires_after": {
                        "anchor": "last_active_at",
                        "minutes": 20
                    },
                    "last_active_at": 1747844794,
                    "name": "My Container"
                }
              ],
              "first_id": "container_123",
              "last_id": "container_123",
              "has_more": false
            }
          request:
            curl: |
              curl https://api.openai.com/v1/containers \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              // Automatically fetches more pages as needed.
              for await (const containerListResponse of client.containers.list()) {
                console.log(containerListResponse.id);
              }
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              page = client.containers.list()
              page = page.data[0]
              print(page.id)
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                page, err := client.Containers.List(context.TODO(), openai.ContainerListParams{

                })
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", page)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.containers.ContainerListPage;
              import com.openai.models.containers.ContainerListParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      ContainerListPage page = client.containers().list();
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.containers.ContainerListPage
              import com.openai.models.containers.ContainerListParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val page: ContainerListPage = client.containers().list()
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              page = openai.containers.list

              puts(page)
    post:
      summary: Create Container
      description: Creates a container.
      operationId: CreateContainer
      parameters: []
      requestBody:
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateContainerBody'
      responses:
        '200':
          description: Success
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ContainerResource'
      x-oaiMeta:
        name: Create container
        group: containers
        returns: The created [container](/docs/api-reference/containers/object) object.
        path: post
        examples:
          response: |
            {
                "id": "cntr_682e30645a488191b6363a0cbefc0f0a025ec61b66250591",
                "object": "container",
                "created_at": 1747857508,
                "status": "running",
                "expires_after": {
                    "anchor": "last_active_at",
                    "minutes": 20
                },
                "last_active_at": 1747857508,
                "name": "My Container"
            }
          request:
            curl: |
              curl https://api.openai.com/v1/containers \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
                -d '{
                      "name": "My Container"
                    }'
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const container = await client.containers.create({ name: 'name' });

              console.log(container.id);
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              container = client.containers.create(
                  name="name",
              )
              print(container.id)
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                container, err := client.Containers.New(context.TODO(), openai.ContainerNewParams{
                  Name: "name",
                })
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", container.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.containers.ContainerCreateParams;
              import com.openai.models.containers.ContainerCreateResponse;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      ContainerCreateParams params = ContainerCreateParams.builder()
                          .name("name")
                          .build();
                      ContainerCreateResponse container = client.containers().create(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.containers.ContainerCreateParams
              import com.openai.models.containers.ContainerCreateResponse

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: ContainerCreateParams = ContainerCreateParams.builder()
                      .name("name")
                      .build()
                  val container: ContainerCreateResponse = client.containers().create(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              container = openai.containers.create(name: "name")

              puts(container)
  /containers/{container_id}:
    get:
      summary: Retrieve Container
      description: Retrieves a container.
      operationId: RetrieveContainer
      parameters:
        - name: container_id
          in: path
          required: true
          schema:
            type: string
      responses:
        '200':
          description: Success
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ContainerResource'
      x-oaiMeta:
        name: Retrieve container
        group: containers
        returns: The [container](/docs/api-reference/containers/object) object.
        path: get
        examples:
          response: |
            {
                "id": "cntr_682dfebaacac8198bbfe9c2474fb6f4a085685cbe3cb5863",
                "object": "container",
                "created_at": 1747844794,
                "status": "running",
                "expires_after": {
                    "anchor": "last_active_at",
                    "minutes": 20
                },
                "last_active_at": 1747844794,
                "name": "My Container"
            }
          request:
            curl: >
              curl https://api.openai.com/v1/containers/cntr_682dfebaacac8198bbfe9c2474fb6f4a085685cbe3cb5863
              \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const container = await client.containers.retrieve('container_id');

              console.log(container.id);
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              container = client.containers.retrieve(
                  "container_id",
              )
              print(container.id)
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                container, err := client.Containers.Get(context.TODO(), "container_id")
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", container.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.containers.ContainerRetrieveParams;
              import com.openai.models.containers.ContainerRetrieveResponse;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      ContainerRetrieveResponse container = client.containers().retrieve("container_id");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.containers.ContainerRetrieveParams
              import com.openai.models.containers.ContainerRetrieveResponse

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val container: ContainerRetrieveResponse = client.containers().retrieve("container_id")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              container = openai.containers.retrieve("container_id")

              puts(container)
    delete:
      operationId: DeleteContainer
      summary: Delete Container
      description: Delete a container.
      parameters:
        - name: container_id
          in: path
          description: The ID of the container to delete.
          required: true
          schema:
            type: string
      responses:
        '200':
          description: OK
      x-oaiMeta:
        name: Delete a container
        group: containers
        returns: Deletion Status
        path: delete
        examples:
          response: |
            {
                "id": "cntr_682dfebaacac8198bbfe9c2474fb6f4a085685cbe3cb5863",
                "object": "container.deleted",
                "deleted": true
            }
          request:
            curl: >
              curl -X DELETE
              https://api.openai.com/v1/containers/cntr_682dfebaacac8198bbfe9c2474fb6f4a085685cbe3cb5863 \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              await client.containers.delete('container_id');
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              client.containers.delete(
                  "container_id",
              )
            go: |
              package main

              import (
                "context"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                err := client.Containers.Delete(context.TODO(), "container_id")
                if err != nil {
                  panic(err.Error())
                }
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.containers.ContainerDeleteParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      client.containers().delete("container_id");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.containers.ContainerDeleteParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  client.containers().delete("container_id")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              result = openai.containers.delete("container_id")

              puts(result)
  /containers/{container_id}/files:
    post:
      summary: >
        Create a Container File


        You can send either a multipart/form-data request with the raw file content, or a JSON request with a
        file ID.
      description: |
        Creates a container file.
      operationId: CreateContainerFile
      parameters:
        - name: container_id
          in: path
          required: true
          schema:
            type: string
      requestBody:
        required: true
        content:
          multipart/form-data:
            schema:
              $ref: '#/components/schemas/CreateContainerFileBody'
      responses:
        '200':
          description: Success
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ContainerFileResource'
      x-oaiMeta:
        name: Create container file
        group: containers
        returns: The created [container file](/docs/api-reference/container-files/object) object.
        path: post
        examples:
          response: |
            {
              "id": "cfile_682e0e8a43c88191a7978f477a09bdf5",
              "object": "container.file",
              "created_at": 1747848842,
              "bytes": 880,
              "container_id": "cntr_682e0e7318108198aa783fd921ff305e08e78805b9fdbb04",
              "path": "/mnt/data/88e12fa445d32636f190a0b33daed6cb-tsconfig.json",
              "source": "user"
            }
          request:
            curl: >
              curl
              https://api.openai.com/v1/containers/cntr_682e0e7318108198aa783fd921ff305e08e78805b9fdbb04/files
              \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -F file="@example.txt"
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const file = await client.containers.files.create('container_id');

              console.log(file.id);
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              file = client.containers.files.create(
                  container_id="container_id",
              )
              print(file.id)
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                file, err := client.Containers.Files.New(
                  context.TODO(),
                  "container_id",
                  openai.ContainerFileNewParams{

                  },
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", file.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.containers.files.FileCreateParams;
              import com.openai.models.containers.files.FileCreateResponse;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      FileCreateResponse file = client.containers().files().create("container_id");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.containers.files.FileCreateParams
              import com.openai.models.containers.files.FileCreateResponse

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val file: FileCreateResponse = client.containers().files().create("container_id")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              file = openai.containers.files.create("container_id")

              puts(file)
    get:
      summary: List Container files
      description: Lists container files.
      operationId: ListContainerFiles
      parameters:
        - name: container_id
          in: path
          required: true
          schema:
            type: string
        - name: limit
          in: query
          description: >
            A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
            default is 20.
          required: false
          schema:
            type: integer
            default: 20
        - name: order
          in: query
          description: >
            Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for
            descending order.
          schema:
            type: string
            default: desc
            enum:
              - asc
              - desc
        - name: after
          in: query
          description: >
            A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
            instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
            call can include after=obj_foo in order to fetch the next page of the list.
          schema:
            type: string
      responses:
        '200':
          description: Success
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ContainerFileListResource'
      x-oaiMeta:
        name: List container files
        group: containers
        returns: a list of [container file](/docs/api-reference/container-files/object) objects.
        path: get
        examples:
          response: |
            {
                "object": "list",
                "data": [
                    {
                        "id": "cfile_682e0e8a43c88191a7978f477a09bdf5",
                        "object": "container.file",
                        "created_at": 1747848842,
                        "bytes": 880,
                        "container_id": "cntr_682e0e7318108198aa783fd921ff305e08e78805b9fdbb04",
                        "path": "/mnt/data/88e12fa445d32636f190a0b33daed6cb-tsconfig.json",
                        "source": "user"
                    }
                ],
                "first_id": "cfile_682e0e8a43c88191a7978f477a09bdf5",
                "has_more": false,
                "last_id": "cfile_682e0e8a43c88191a7978f477a09bdf5"
            }
          request:
            curl: >
              curl
              https://api.openai.com/v1/containers/cntr_682e0e7318108198aa783fd921ff305e08e78805b9fdbb04/files
              \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              // Automatically fetches more pages as needed.
              for await (const fileListResponse of client.containers.files.list('container_id')) {
                console.log(fileListResponse.id);
              }
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              page = client.containers.files.list(
                  container_id="container_id",
              )
              page = page.data[0]
              print(page.id)
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                page, err := client.Containers.Files.List(
                  context.TODO(),
                  "container_id",
                  openai.ContainerFileListParams{

                  },
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", page)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.containers.files.FileListPage;
              import com.openai.models.containers.files.FileListParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      FileListPage page = client.containers().files().list("container_id");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.containers.files.FileListPage
              import com.openai.models.containers.files.FileListParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val page: FileListPage = client.containers().files().list("container_id")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              page = openai.containers.files.list("container_id")

              puts(page)
  /containers/{container_id}/files/{file_id}:
    get:
      summary: Retrieve Container File
      description: Retrieves a container file.
      operationId: RetrieveContainerFile
      parameters:
        - name: container_id
          in: path
          required: true
          schema:
            type: string
        - name: file_id
          in: path
          required: true
          schema:
            type: string
      responses:
        '200':
          description: Success
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ContainerFileResource'
      x-oaiMeta:
        name: Retrieve container file
        group: containers
        returns: The [container file](/docs/api-reference/container-files/object) object.
        path: get
        examples:
          response: |
            {
                "id": "cfile_682e0e8a43c88191a7978f477a09bdf5",
                "object": "container.file",
                "created_at": 1747848842,
                "bytes": 880,
                "container_id": "cntr_682e0e7318108198aa783fd921ff305e08e78805b9fdbb04",
                "path": "/mnt/data/88e12fa445d32636f190a0b33daed6cb-tsconfig.json",
                "source": "user"
            }
          request:
            curl: |
              curl https://api.openai.com/v1/containers/container_123/files/file_456 \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            node.js: >-
              import OpenAI from 'openai';


              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });


              const file = await client.containers.files.retrieve('file_id', { container_id: 'container_id'
              });


              console.log(file.id);
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              file = client.containers.files.retrieve(
                  file_id="file_id",
                  container_id="container_id",
              )
              print(file.id)
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                file, err := client.Containers.Files.Get(
                  context.TODO(),
                  "container_id",
                  "file_id",
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", file.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.containers.files.FileRetrieveParams;
              import com.openai.models.containers.files.FileRetrieveResponse;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      FileRetrieveParams params = FileRetrieveParams.builder()
                          .containerId("container_id")
                          .fileId("file_id")
                          .build();
                      FileRetrieveResponse file = client.containers().files().retrieve(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.containers.files.FileRetrieveParams
              import com.openai.models.containers.files.FileRetrieveResponse

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: FileRetrieveParams = FileRetrieveParams.builder()
                      .containerId("container_id")
                      .fileId("file_id")
                      .build()
                  val file: FileRetrieveResponse = client.containers().files().retrieve(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              file = openai.containers.files.retrieve("file_id", container_id: "container_id")

              puts(file)
    delete:
      operationId: DeleteContainerFile
      summary: Delete Container File
      description: Delete a container file.
      parameters:
        - name: container_id
          in: path
          required: true
          schema:
            type: string
        - name: file_id
          in: path
          required: true
          schema:
            type: string
      responses:
        '200':
          description: OK
      x-oaiMeta:
        name: Delete a container file
        group: containers
        returns: Deletion Status
        path: delete
        examples:
          response: |
            {
                "id": "cfile_682e0e8a43c88191a7978f477a09bdf5",
                "object": "container.file.deleted",
                "deleted": true
            }
          request:
            curl: >
              curl -X DELETE
              https://api.openai.com/v1/containers/cntr_682dfebaacac8198bbfe9c2474fb6f4a085685cbe3cb5863/files/cfile_682e0e8a43c88191a7978f477a09bdf5
              \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              await client.containers.files.delete('file_id', { container_id: 'container_id' });
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              client.containers.files.delete(
                  file_id="file_id",
                  container_id="container_id",
              )
            go: |
              package main

              import (
                "context"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                err := client.Containers.Files.Delete(
                  context.TODO(),
                  "container_id",
                  "file_id",
                )
                if err != nil {
                  panic(err.Error())
                }
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.containers.files.FileDeleteParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      FileDeleteParams params = FileDeleteParams.builder()
                          .containerId("container_id")
                          .fileId("file_id")
                          .build();
                      client.containers().files().delete(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.containers.files.FileDeleteParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: FileDeleteParams = FileDeleteParams.builder()
                      .containerId("container_id")
                      .fileId("file_id")
                      .build()
                  client.containers().files().delete(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              result = openai.containers.files.delete("file_id", container_id: "container_id")

              puts(result)
  /containers/{container_id}/files/{file_id}/content:
    get:
      summary: Retrieve Container File Content
      description: Retrieves a container file content.
      operationId: RetrieveContainerFileContent
      parameters:
        - name: container_id
          in: path
          required: true
          schema:
            type: string
        - name: file_id
          in: path
          required: true
          schema:
            type: string
      responses:
        '200':
          description: Success
      x-oaiMeta:
        name: Retrieve container file content
        group: containers
        returns: The contents of the container file.
        path: get
        examples:
          response: |
            <binary content of the file>
          request:
            curl: |
              curl https://api.openai.com/v1/containers/container_123/files/cfile_456/content \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            node.js: >-
              import OpenAI from 'openai';


              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });


              const content = await client.containers.files.content.retrieve('file_id', { container_id:
              'container_id' });


              console.log(content);


              const data = await content.blob();

              console.log(data);
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              content = client.containers.files.content.retrieve(
                  file_id="file_id",
                  container_id="container_id",
              )
              print(content)
              data = content.read()
              print(data)
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                content, err := client.Containers.Files.Content.Get(
                  context.TODO(),
                  "container_id",
                  "file_id",
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", content)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.core.http.HttpResponse;
              import com.openai.models.containers.files.content.ContentRetrieveParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      ContentRetrieveParams params = ContentRetrieveParams.builder()
                          .containerId("container_id")
                          .fileId("file_id")
                          .build();
                      HttpResponse content = client.containers().files().content().retrieve(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.core.http.HttpResponse
              import com.openai.models.containers.files.content.ContentRetrieveParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: ContentRetrieveParams = ContentRetrieveParams.builder()
                      .containerId("container_id")
                      .fileId("file_id")
                      .build()
                  val content: HttpResponse = client.containers().files().content().retrieve(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              content = openai.containers.files.content.retrieve("file_id", container_id: "container_id")

              puts(content)
  /embeddings:
    post:
      operationId: createEmbedding
      tags:
        - Embeddings
      summary: Creates an embedding vector representing the input text.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateEmbeddingRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/CreateEmbeddingResponse'
      x-oaiMeta:
        name: Create embeddings
        group: embeddings
        returns: A list of [embedding](/docs/api-reference/embeddings/object) objects.
        examples:
          response: |
            {
              "object": "list",
              "data": [
                {
                  "object": "embedding",
                  "embedding": [
                    0.0023064255,
                    -0.009327292,
                    .... (1536 floats total for ada-002)
                    -0.0028842222,
                  ],
                  "index": 0
                }
              ],
              "model": "text-embedding-ada-002",
              "usage": {
                "prompt_tokens": 8,
                "total_tokens": 8
              }
            }
          request:
            curl: |
              curl https://api.openai.com/v1/embeddings \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
                -d '{
                  "input": "The food was delicious and the waiter...",
                  "model": "text-embedding-ada-002",
                  "encoding_format": "float"
                }'
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              create_embedding_response = client.embeddings.create(
                  input="The quick brown fox jumped over the lazy dog",
                  model="text-embedding-3-small",
              )
              print(create_embedding_response.data)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const createEmbeddingResponse = await client.embeddings.create({
                input: 'The quick brown fox jumped over the lazy dog',
                model: 'text-embedding-3-small',
              });

              console.log(createEmbeddingResponse.data);
            csharp: >
              using System;


              using OpenAI.Embeddings;


              EmbeddingClient client = new(
                  model: "text-embedding-3-small",
                  apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
              );


              OpenAIEmbedding embedding = client.GenerateEmbedding(input: "The quick brown fox jumped over the
              lazy dog");

              ReadOnlyMemory<float> vector = embedding.ToFloats();


              for (int i = 0; i < vector.Length; i++)

              {
                  Console.WriteLine($"  [{i,4}] = {vector.Span[i]}");
              }
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                createEmbeddingResponse, err := client.Embeddings.New(context.TODO(), openai.EmbeddingNewParams{
                  Input: openai.EmbeddingNewParamsInputUnion{
                    OfString: openai.String("The quick brown fox jumped over the lazy dog"),
                  },
                  Model: openai.EmbeddingModelTextEmbeddingAda002,
                })
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", createEmbeddingResponse.Data)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.embeddings.CreateEmbeddingResponse;
              import com.openai.models.embeddings.EmbeddingCreateParams;
              import com.openai.models.embeddings.EmbeddingModel;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      EmbeddingCreateParams params = EmbeddingCreateParams.builder()
                          .input("The quick brown fox jumped over the lazy dog")
                          .model(EmbeddingModel.TEXT_EMBEDDING_ADA_002)
                          .build();
                      CreateEmbeddingResponse createEmbeddingResponse = client.embeddings().create(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.embeddings.CreateEmbeddingResponse
              import com.openai.models.embeddings.EmbeddingCreateParams
              import com.openai.models.embeddings.EmbeddingModel

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: EmbeddingCreateParams = EmbeddingCreateParams.builder()
                      .input("The quick brown fox jumped over the lazy dog")
                      .model(EmbeddingModel.TEXT_EMBEDDING_ADA_002)
                      .build()
                  val createEmbeddingResponse: CreateEmbeddingResponse = client.embeddings().create(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              create_embedding_response = openai.embeddings.create(
                input: "The quick brown fox jumped over the lazy dog",
                model: :"text-embedding-ada-002"
              )

              puts(create_embedding_response)
  /evals:
    get:
      operationId: listEvals
      tags:
        - Evals
      summary: |
        List evaluations for a project.
      parameters:
        - name: after
          in: query
          description: Identifier for the last eval from the previous pagination request.
          required: false
          schema:
            type: string
        - name: limit
          in: query
          description: Number of evals to retrieve.
          required: false
          schema:
            type: integer
            default: 20
        - name: order
          in: query
          description: Sort order for evals by timestamp. Use `asc` for ascending order or `desc` for descending order.
          required: false
          schema:
            type: string
            enum:
              - asc
              - desc
            default: asc
        - name: order_by
          in: query
          description: |
            Evals can be ordered by creation time or last updated time. Use
            `created_at` for creation time or `updated_at` for last updated time.
          required: false
          schema:
            type: string
            enum:
              - created_at
              - updated_at
            default: created_at
      responses:
        '200':
          description: A list of evals
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/EvalList'
      x-oaiMeta:
        name: List evals
        group: evals
        returns: A list of [evals](/docs/api-reference/evals/object) matching the specified filters.
        path: list
        examples:
          response: |
            {
              "object": "list",
              "data": [
                {
                  "id": "eval_67abd54d9b0081909a86353f6fb9317a",
                  "object": "eval",
                  "data_source_config": {
                    "type": "stored_completions",
                    "metadata": {
                      "usecase": "push_notifications_summarizer"
                    },
                    "schema": {
                      "type": "object",
                      "properties": {
                        "item": {
                          "type": "object"
                        },
                        "sample": {
                          "type": "object"
                        }
                      },
                      "required": [
                        "item",
                        "sample"
                      ]
                    }
                  },
                  "testing_criteria": [
                    {
                      "name": "Push Notification Summary Grader",
                      "id": "Push Notification Summary Grader-9b876f24-4762-4be9-aff4-db7a9b31c673",
                      "type": "label_model",
                      "model": "o3-mini",
                      "input": [
                        {
                          "type": "message",
                          "role": "developer",
                          "content": {
                            "type": "input_text",
                            "text": "\nLabel the following push notification summary as either correct or incorrect.\nThe push notification and the summary will be provided below.\nA good push notificiation summary is concise and snappy.\nIf it is good, then label it as correct, if not, then incorrect.\n"
                          }
                        },
                        {
                          "type": "message",
                          "role": "user",
                          "content": {
                            "type": "input_text",
                            "text": "\nPush notifications: {{item.input}}\nSummary: {{sample.output_text}}\n"
                          }
                        }
                      ],
                      "passing_labels": [
                        "correct"
                      ],
                      "labels": [
                        "correct",
                        "incorrect"
                      ],
                      "sampling_params": null
                    }
                  ],
                  "name": "Push Notification Summary Grader",
                  "created_at": 1739314509,
                  "metadata": {
                    "description": "A stored completions eval for push notification summaries"
                  }
                }
              ],
              "first_id": "eval_67abd54d9b0081909a86353f6fb9317a",
              "last_id": "eval_67aa884cf6688190b58f657d4441c8b7",
              "has_more": true
            }
          request:
            curl: |
              curl https://api.openai.com/v1/evals?limit=1 \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              page = client.evals.list()
              page = page.data[0]
              print(page.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              // Automatically fetches more pages as needed.
              for await (const evalListResponse of client.evals.list()) {
                console.log(evalListResponse.id);
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.evals.EvalListPage;
              import com.openai.models.evals.EvalListParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      EvalListPage page = client.evals().list();
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.evals.EvalListPage
              import com.openai.models.evals.EvalListParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val page: EvalListPage = client.evals().list()
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              page = openai.evals.list

              puts(page)
    post:
      operationId: createEval
      tags:
        - Evals
      summary: >
        Create the structure of an evaluation that can be used to test a model's performance.

        An evaluation is a set of testing criteria and the config for a data source, which dictates the schema
        of the data used in the evaluation. After creating an evaluation, you can run it on different models
        and model parameters. We support several types of graders and datasources.

        For more information, see the [Evals guide](/docs/guides/evals).
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateEvalRequest'
      responses:
        '201':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Eval'
      x-oaiMeta:
        name: Create eval
        group: evals
        returns: The created [Eval](/docs/api-reference/evals/object) object.
        path: post
        examples:
          response: |
            {
              "object": "eval",
              "id": "eval_67b7fa9a81a88190ab4aa417e397ea21",
              "data_source_config": {
                "type": "stored_completions",
                "metadata": {
                  "usecase": "chatbot"
                },
                "schema": {
                  "type": "object",
                  "properties": {
                    "item": {
                      "type": "object"
                    },
                    "sample": {
                      "type": "object"
                    }
                  },
                  "required": [
                    "item",
                    "sample"
                  ]
              },
              "testing_criteria": [
                {
                  "name": "Example label grader",
                  "type": "label_model",
                  "model": "o3-mini",
                  "input": [
                    {
                      "type": "message",
                      "role": "developer",
                      "content": {
                        "type": "input_text",
                        "text": "Classify the sentiment of the following statement as one of positive, neutral, or negative"
                      }
                    },
                    {
                      "type": "message",
                      "role": "user",
                      "content": {
                        "type": "input_text",
                        "text": "Statement: {{item.input}}"
                      }
                    }
                  ],
                  "passing_labels": [
                    "positive"
                  ],
                  "labels": [
                    "positive",
                    "neutral",
                    "negative"
                  ]
                }
              ],
              "name": "Sentiment",
              "created_at": 1740110490,
              "metadata": {
                "description": "An eval for sentiment analysis"
              }
            }
          request:
            curl: |
              curl https://api.openai.com/v1/evals \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
                -d '{
                      "name": "Sentiment",
                      "data_source_config": {
                        "type": "stored_completions",
                        "metadata": {
                            "usecase": "chatbot"
                        }
                      },
                      "testing_criteria": [
                        {
                          "type": "label_model",
                          "model": "o3-mini",
                          "input": [
                            {
                              "role": "developer",
                              "content": "Classify the sentiment of the following statement as one of 'positive', 'neutral', or 'negative'"
                            },
                            {
                              "role": "user",
                              "content": "Statement: {{item.input}}"
                            }
                          ],
                          "passing_labels": [
                            "positive"
                          ],
                          "labels": [
                            "positive",
                            "neutral",
                            "negative"
                          ],
                          "name": "Example label grader"
                        }
                      ]
                    }'
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              eval = client.evals.create(
                  data_source_config={
                      "item_schema": {
                          "foo": "bar"
                      },
                      "type": "custom",
                  },
                  testing_criteria=[{
                      "input": [{
                          "content": "content",
                          "role": "role",
                      }],
                      "labels": ["string"],
                      "model": "model",
                      "name": "name",
                      "passing_labels": ["string"],
                      "type": "label_model",
                  }],
              )
              print(eval.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const _eval = await client.evals.create({
                data_source_config: { item_schema: { foo: 'bar' }, type: 'custom' },
                testing_criteria: [
                  {
                    input: [{ content: 'content', role: 'role' }],
                    labels: ['string'],
                    model: 'model',
                    name: 'name',
                    passing_labels: ['string'],
                    type: 'label_model',
                  },
                ],
              });

              console.log(_eval.id);
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.core.JsonValue;
              import com.openai.models.evals.EvalCreateParams;
              import com.openai.models.evals.EvalCreateResponse;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      EvalCreateParams params = EvalCreateParams.builder()
                          .customDataSourceConfig(EvalCreateParams.DataSourceConfig.Custom.ItemSchema.builder()
                              .putAdditionalProperty("foo", JsonValue.from("bar"))
                              .build())
                          .addTestingCriterion(EvalCreateParams.TestingCriterion.LabelModel.builder()
                              .addInput(EvalCreateParams.TestingCriterion.LabelModel.Input.SimpleInputMessage.builder()
                                  .content("content")
                                  .role("role")
                                  .build())
                              .addLabel("string")
                              .model("model")
                              .name("name")
                              .addPassingLabel("string")
                              .build())
                          .build();
                      EvalCreateResponse eval = client.evals().create(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.core.JsonValue
              import com.openai.models.evals.EvalCreateParams
              import com.openai.models.evals.EvalCreateResponse

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: EvalCreateParams = EvalCreateParams.builder()
                      .customDataSourceConfig(EvalCreateParams.DataSourceConfig.Custom.ItemSchema.builder()
                          .putAdditionalProperty("foo", JsonValue.from("bar"))
                          .build())
                      .addTestingCriterion(EvalCreateParams.TestingCriterion.LabelModel.builder()
                          .addInput(EvalCreateParams.TestingCriterion.LabelModel.Input.SimpleInputMessage.builder()
                              .content("content")
                              .role("role")
                              .build())
                          .addLabel("string")
                          .model("model")
                          .name("name")
                          .addPassingLabel("string")
                          .build())
                      .build()
                  val eval: EvalCreateResponse = client.evals().create(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              eval_ = openai.evals.create(
                data_source_config: {item_schema: {foo: "bar"}, type: :custom},
                testing_criteria: [
                  {
                    input: [{content: "content", role: "role"}],
                    labels: ["string"],
                    model: "model",
                    name: "name",
                    passing_labels: ["string"],
                    type: :label_model
                  }
                ]
              )

              puts(eval_)
  /evals/{eval_id}:
    get:
      operationId: getEval
      tags:
        - Evals
      summary: |
        Get an evaluation by ID.
      parameters:
        - name: eval_id
          in: path
          required: true
          schema:
            type: string
          description: The ID of the evaluation to retrieve.
      responses:
        '200':
          description: The evaluation
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Eval'
      x-oaiMeta:
        name: Get an eval
        group: evals
        returns: The [Eval](/docs/api-reference/evals/object) object matching the specified ID.
        path: get
        examples:
          response: |
            {
              "object": "eval",
              "id": "eval_67abd54d9b0081909a86353f6fb9317a",
              "data_source_config": {
                "type": "custom",
                "schema": {
                  "type": "object",
                  "properties": {
                    "item": {
                      "type": "object",
                      "properties": {
                        "input": {
                          "type": "string"
                        },
                        "ground_truth": {
                          "type": "string"
                        }
                      },
                      "required": [
                        "input",
                        "ground_truth"
                      ]
                    }
                  },
                  "required": [
                    "item"
                  ]
                }
              },
              "testing_criteria": [
                {
                  "name": "String check",
                  "id": "String check-2eaf2d8d-d649-4335-8148-9535a7ca73c2",
                  "type": "string_check",
                  "input": "{{item.input}}",
                  "reference": "{{item.ground_truth}}",
                  "operation": "eq"
                }
              ],
              "name": "External Data Eval",
              "created_at": 1739314509,
              "metadata": {},
            }
          request:
            curl: |
              curl https://api.openai.com/v1/evals/eval_67abd54d9b0081909a86353f6fb9317a \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              eval = client.evals.retrieve(
                  "eval_id",
              )
              print(eval.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const _eval = await client.evals.retrieve('eval_id');

              console.log(_eval.id);
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.evals.EvalRetrieveParams;
              import com.openai.models.evals.EvalRetrieveResponse;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      EvalRetrieveResponse eval = client.evals().retrieve("eval_id");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.evals.EvalRetrieveParams
              import com.openai.models.evals.EvalRetrieveResponse

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val eval: EvalRetrieveResponse = client.evals().retrieve("eval_id")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              eval_ = openai.evals.retrieve("eval_id")

              puts(eval_)
    post:
      operationId: updateEval
      tags:
        - Evals
      summary: |
        Update certain properties of an evaluation.
      parameters:
        - name: eval_id
          in: path
          required: true
          schema:
            type: string
          description: The ID of the evaluation to update.
      requestBody:
        description: Request to update an evaluation
        required: true
        content:
          application/json:
            schema:
              type: object
              properties:
                name:
                  type: string
                  description: Rename the evaluation.
                metadata:
                  $ref: '#/components/schemas/Metadata'
      responses:
        '200':
          description: The updated evaluation
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Eval'
      x-oaiMeta:
        name: Update an eval
        group: evals
        returns: The [Eval](/docs/api-reference/evals/object) object matching the updated version.
        path: update
        examples:
          response: |
            {
              "object": "eval",
              "id": "eval_67abd54d9b0081909a86353f6fb9317a",
              "data_source_config": {
                "type": "custom",
                "schema": {
                  "type": "object",
                  "properties": {
                    "item": {
                      "type": "object",
                      "properties": {
                        "input": {
                          "type": "string"
                        },
                        "ground_truth": {
                          "type": "string"
                        }
                      },
                      "required": [
                        "input",
                        "ground_truth"
                      ]
                    }
                  },
                  "required": [
                    "item"
                  ]
                }
              },
              "testing_criteria": [
                {
                  "name": "String check",
                  "id": "String check-2eaf2d8d-d649-4335-8148-9535a7ca73c2",
                  "type": "string_check",
                  "input": "{{item.input}}",
                  "reference": "{{item.ground_truth}}",
                  "operation": "eq"
                }
              ],
              "name": "Updated Eval",
              "created_at": 1739314509,
              "metadata": {"description": "Updated description"},
            }
          request:
            curl: |
              curl https://api.openai.com/v1/evals/eval_67abd54d9b0081909a86353f6fb9317a \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
                -d '{"name": "Updated Eval", "metadata": {"description": "Updated description"}}'
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              eval = client.evals.update(
                  eval_id="eval_id",
              )
              print(eval.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const _eval = await client.evals.update('eval_id');

              console.log(_eval.id);
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.evals.EvalUpdateParams;
              import com.openai.models.evals.EvalUpdateResponse;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      EvalUpdateResponse eval = client.evals().update("eval_id");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.evals.EvalUpdateParams
              import com.openai.models.evals.EvalUpdateResponse

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val eval: EvalUpdateResponse = client.evals().update("eval_id")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              eval_ = openai.evals.update("eval_id")

              puts(eval_)
    delete:
      operationId: deleteEval
      tags:
        - Evals
      summary: |
        Delete an evaluation.
      parameters:
        - name: eval_id
          in: path
          required: true
          schema:
            type: string
          description: The ID of the evaluation to delete.
      responses:
        '200':
          description: Successfully deleted the evaluation.
          content:
            application/json:
              schema:
                type: object
                properties:
                  object:
                    type: string
                    example: eval.deleted
                  deleted:
                    type: boolean
                    example: true
                  eval_id:
                    type: string
                    example: eval_abc123
                required:
                  - object
                  - deleted
                  - eval_id
        '404':
          description: Evaluation not found.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Error'
      x-oaiMeta:
        name: Delete an eval
        group: evals
        returns: A deletion confirmation object.
        examples:
          response: |
            {
              "object": "eval.deleted",
              "deleted": true,
              "eval_id": "eval_abc123"
            }
          request:
            curl: |
              curl https://api.openai.com/v1/evals/eval_abc123 \
                -X DELETE \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              eval = client.evals.delete(
                  "eval_id",
              )
              print(eval.eval_id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const _eval = await client.evals.delete('eval_id');

              console.log(_eval.eval_id);
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.evals.EvalDeleteParams;
              import com.openai.models.evals.EvalDeleteResponse;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      EvalDeleteResponse eval = client.evals().delete("eval_id");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.evals.EvalDeleteParams
              import com.openai.models.evals.EvalDeleteResponse

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val eval: EvalDeleteResponse = client.evals().delete("eval_id")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              eval_ = openai.evals.delete("eval_id")

              puts(eval_)
  /evals/{eval_id}/runs:
    get:
      operationId: getEvalRuns
      tags:
        - Evals
      summary: |
        Get a list of runs for an evaluation.
      parameters:
        - name: eval_id
          in: path
          required: true
          schema:
            type: string
          description: The ID of the evaluation to retrieve runs for.
        - name: after
          in: query
          description: Identifier for the last run from the previous pagination request.
          required: false
          schema:
            type: string
        - name: limit
          in: query
          description: Number of runs to retrieve.
          required: false
          schema:
            type: integer
            default: 20
        - name: order
          in: query
          description: >-
            Sort order for runs by timestamp. Use `asc` for ascending order or `desc` for descending order.
            Defaults to `asc`.
          required: false
          schema:
            type: string
            enum:
              - asc
              - desc
            default: asc
        - name: status
          in: query
          description: Filter runs by status. One of `queued` | `in_progress` | `failed` | `completed` | `canceled`.
          required: false
          schema:
            type: string
            enum:
              - queued
              - in_progress
              - completed
              - canceled
              - failed
      responses:
        '200':
          description: A list of runs for the evaluation
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/EvalRunList'
      x-oaiMeta:
        name: Get eval runs
        group: evals
        returns: A list of [EvalRun](/docs/api-reference/evals/run-object) objects matching the specified ID.
        path: get-runs
        examples:
          response: |
            {
              "object": "list",
              "data": [
                {
                  "object": "eval.run",
                  "id": "evalrun_67e0c7d31560819090d60c0780591042",
                  "eval_id": "eval_67e0c726d560819083f19a957c4c640b",
                  "report_url": "https://platform.openai.com/evaluations/eval_67e0c726d560819083f19a957c4c640b",
                  "status": "completed",
                  "model": "o3-mini",
                  "name": "bulk_with_negative_examples_o3-mini",
                  "created_at": 1742784467,
                  "result_counts": {
                    "total": 1,
                    "errored": 0,
                    "failed": 0,
                    "passed": 1
                  },
                  "per_model_usage": [
                    {
                      "model_name": "o3-mini",
                      "invocation_count": 1,
                      "prompt_tokens": 563,
                      "completion_tokens": 874,
                      "total_tokens": 1437,
                      "cached_tokens": 0
                    }
                  ],
                  "per_testing_criteria_results": [
                    {
                      "testing_criteria": "Push Notification Summary Grader-1808cd0b-eeec-4e0b-a519-337e79f4f5d1",
                      "passed": 1,
                      "failed": 0
                    }
                  ],
                  "data_source": {
                    "type": "completions",
                    "source": {
                      "type": "file_content",
                      "content": [
                        {
                          "item": {
                            "notifications": "\n- New message from Sarah: \"Can you call me later?\"\n- Your package has been delivered!\n- Flash sale: 20% off electronics for the next 2 hours!\n"
                          }
                        }
                      ]
                    },
                    "input_messages": {
                      "type": "template",
                      "template": [
                        {
                          "type": "message",
                          "role": "developer",
                          "content": {
                            "type": "input_text",
                            "text": "\n\n\n\nYou are a helpful assistant that takes in an array of push notifications and returns a collapsed summary of them.\nThe push notification will be provided as follows:\n<push_notifications>\n...notificationlist...\n</push_notifications>\n\nYou should return just the summary and nothing else.\n\n\nYou should return a summary that is concise and snappy.\n\n\nHere is an example of a good summary:\n<push_notifications>\n- Traffic alert: Accident reported on Main Street.- Package out for delivery: Expected by 5 PM.- New friend suggestion: Connect with Emma.\n</push_notifications>\n<summary>\nTraffic alert, package expected by 5pm, suggestion for new friend (Emily).\n</summary>\n\n\nHere is an example of a bad summary:\n<push_notifications>\n- Traffic alert: Accident reported on Main Street.- Package out for delivery: Expected by 5 PM.- New friend suggestion: Connect with Emma.\n</push_notifications>\n<summary>\nTraffic alert reported on main street. You have a package that will arrive by 5pm, Emily is a new friend suggested for you.\n</summary>\n"
                          }
                        },
                        {
                          "type": "message",
                          "role": "user",
                          "content": {
                            "type": "input_text",
                            "text": "<push_notifications>{{item.notifications}}</push_notifications>"
                          }
                        }
                      ]
                    },
                    "model": "o3-mini",
                    "sampling_params": null
                  },
                  "error": null,
                  "metadata": {}
                }
              ],
              "first_id": "evalrun_67e0c7d31560819090d60c0780591042",
              "last_id": "evalrun_67e0c7d31560819090d60c0780591042",
              "has_more": true
            }
          request:
            curl: |
              curl https://api.openai.com/v1/evals/egroup_67abd54d9b0081909a86353f6fb9317a/runs \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              page = client.evals.runs.list(
                  eval_id="eval_id",
              )
              page = page.data[0]
              print(page.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              // Automatically fetches more pages as needed.
              for await (const runListResponse of client.evals.runs.list('eval_id')) {
                console.log(runListResponse.id);
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.evals.runs.RunListPage;
              import com.openai.models.evals.runs.RunListParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      RunListPage page = client.evals().runs().list("eval_id");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.evals.runs.RunListPage
              import com.openai.models.evals.runs.RunListParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val page: RunListPage = client.evals().runs().list("eval_id")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              page = openai.evals.runs.list("eval_id")

              puts(page)
    post:
      operationId: createEvalRun
      tags:
        - Evals
      summary: >
        Kicks off a new run for a given evaluation, specifying the data source, and what model configuration
        to use to test. The datasource will be validated against the schema specified in the config of the
        evaluation.
      parameters:
        - in: path
          name: eval_id
          required: true
          schema:
            type: string
          description: The ID of the evaluation to create a run for.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateEvalRunRequest'
      responses:
        '201':
          description: Successfully created a run for the evaluation
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/EvalRun'
        '400':
          description: Bad request (for example, missing eval object)
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Error'
      x-oaiMeta:
        name: Create eval run
        group: evals
        returns: The [EvalRun](/docs/api-reference/evals/run-object) object matching the specified ID.
        examples:
          response: |
            {
              "object": "eval.run",
              "id": "evalrun_67e57965b480819094274e3a32235e4c",
              "eval_id": "eval_67e579652b548190aaa83ada4b125f47",
              "report_url": "https://platform.openai.com/evaluations/eval_67e579652b548190aaa83ada4b125f47&run_id=evalrun_67e57965b480819094274e3a32235e4c",
              "status": "queued",
              "model": "gpt-4o-mini",
              "name": "gpt-4o-mini",
              "created_at": 1743092069,
              "result_counts": {
                "total": 0,
                "errored": 0,
                "failed": 0,
                "passed": 0
              },
              "per_model_usage": null,
              "per_testing_criteria_results": null,
              "data_source": {
                "type": "completions",
                "source": {
                  "type": "file_content",
                  "content": [
                    {
                      "item": {
                        "input": "Tech Company Launches Advanced Artificial Intelligence Platform",
                        "ground_truth": "Technology"
                      }
                    }
                  ]
                },
                "input_messages": {
                  "type": "template",
                  "template": [
                    {
                      "type": "message",
                      "role": "developer",
                      "content": {
                        "type": "input_text",
                        "text": "Categorize a given news headline into one of the following topics: Technology, Markets, World, Business, or Sports.\n\n# Steps\n\n1. Analyze the content of the news headline to understand its primary focus.\n2. Extract the subject matter, identifying any key indicators or keywords.\n3. Use the identified indicators to determine the most suitable category out of the five options: Technology, Markets, World, Business, or Sports.\n4. Ensure only one category is selected per headline.\n\n# Output Format\n\nRespond with the chosen category as a single word. For instance: \"Technology\", \"Markets\", \"World\", \"Business\", or \"Sports\".\n\n# Examples\n\n**Input**: \"Apple Unveils New iPhone Model, Featuring Advanced AI Features\"  \n**Output**: \"Technology\"\n\n**Input**: \"Global Stocks Mixed as Investors Await Central Bank Decisions\"  \n**Output**: \"Markets\"\n\n**Input**: \"War in Ukraine: Latest Updates on Negotiation Status\"  \n**Output**: \"World\"\n\n**Input**: \"Microsoft in Talks to Acquire Gaming Company for $2 Billion\"  \n**Output**: \"Business\"\n\n**Input**: \"Manchester United Secures Win in Premier League Football Match\"  \n**Output**: \"Sports\" \n\n# Notes\n\n- If the headline appears to fit into more than one category, choose the most dominant theme.\n- Keywords or phrases such as \"stocks\", \"company acquisition\", \"match\", or technological brands can be good indicators for classification.\n"
                      }
                    },
                    {
                      "type": "message",
                      "role": "user",
                      "content": {
                        "type": "input_text",
                        "text": "{{item.input}}"
                      }
                    }
                  ]
                },
                "model": "gpt-4o-mini",
                "sampling_params": {
                  "seed": 42,
                  "temperature": 1.0,
                  "top_p": 1.0,
                  "max_completions_tokens": 2048
                }
              },
              "error": null,
              "metadata": {}
            }
          request:
            curl: |
              curl https://api.openai.com/v1/evals/eval_67e579652b548190aaa83ada4b125f47/runs \
                -X POST \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
                -d '{"name":"gpt-4o-mini","data_source":{"type":"completions","input_messages":{"type":"template","template":[{"role":"developer","content":"Categorize a given news headline into one of the following topics: Technology, Markets, World, Business, or Sports.\n\n# Steps\n\n1. Analyze the content of the news headline to understand its primary focus.\n2. Extract the subject matter, identifying any key indicators or keywords.\n3. Use the identified indicators to determine the most suitable category out of the five options: Technology, Markets, World, Business, or Sports.\n4. Ensure only one category is selected per headline.\n\n# Output Format\n\nRespond with the chosen category as a single word. For instance: \"Technology\", \"Markets\", \"World\", \"Business\", or \"Sports\".\n\n# Examples\n\n**Input**: \"Apple Unveils New iPhone Model, Featuring Advanced AI Features\"  \n**Output**: \"Technology\"\n\n**Input**: \"Global Stocks Mixed as Investors Await Central Bank Decisions\"  \n**Output**: \"Markets\"\n\n**Input**: \"War in Ukraine: Latest Updates on Negotiation Status\"  \n**Output**: \"World\"\n\n**Input**: \"Microsoft in Talks to Acquire Gaming Company for $2 Billion\"  \n**Output**: \"Business\"\n\n**Input**: \"Manchester United Secures Win in Premier League Football Match\"  \n**Output**: \"Sports\" \n\n# Notes\n\n- If the headline appears to fit into more than one category, choose the most dominant theme.\n- Keywords or phrases such as \"stocks\", \"company acquisition\", \"match\", or technological brands can be good indicators for classification.\n"} , {"role":"user","content":"{{item.input}}"}]} ,"sampling_params":{"temperature":1,"max_completions_tokens":2048,"top_p":1,"seed":42},"model":"gpt-4o-mini","source":{"type":"file_content","content":[{"item":{"input":"Tech Company Launches Advanced Artificial Intelligence Platform","ground_truth":"Technology"}}]}}'
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              run = client.evals.runs.create(
                  eval_id="eval_id",
                  data_source={
                      "source": {
                          "content": [{
                              "item": {
                                  "foo": "bar"
                              }
                          }],
                          "type": "file_content",
                      },
                      "type": "jsonl",
                  },
              )
              print(run.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const run = await client.evals.runs.create('eval_id', {
                data_source: { source: { content: [{ item: { foo: 'bar' } }], type: 'file_content' }, type: 'jsonl' },
              });

              console.log(run.id);
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.core.JsonValue;
              import com.openai.models.evals.runs.CreateEvalJsonlRunDataSource;
              import com.openai.models.evals.runs.RunCreateParams;
              import com.openai.models.evals.runs.RunCreateResponse;
              import java.util.List;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      RunCreateParams params = RunCreateParams.builder()
                          .evalId("eval_id")
                          .dataSource(CreateEvalJsonlRunDataSource.builder()
                              .fileContentSource(List.of(CreateEvalJsonlRunDataSource.Source.FileContent.Content.builder()
                                  .item(CreateEvalJsonlRunDataSource.Source.FileContent.Content.Item.builder()
                                      .putAdditionalProperty("foo", JsonValue.from("bar"))
                                      .build())
                                  .build()))
                              .build())
                          .build();
                      RunCreateResponse run = client.evals().runs().create(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.core.JsonValue
              import com.openai.models.evals.runs.CreateEvalJsonlRunDataSource
              import com.openai.models.evals.runs.RunCreateParams
              import com.openai.models.evals.runs.RunCreateResponse

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: RunCreateParams = RunCreateParams.builder()
                      .evalId("eval_id")
                      .dataSource(CreateEvalJsonlRunDataSource.builder()
                          .fileContentSource(listOf(CreateEvalJsonlRunDataSource.Source.FileContent.Content.builder()
                              .item(CreateEvalJsonlRunDataSource.Source.FileContent.Content.Item.builder()
                                  .putAdditionalProperty("foo", JsonValue.from("bar"))
                                  .build())
                              .build()))
                          .build())
                      .build()
                  val run: RunCreateResponse = client.evals().runs().create(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              run = openai.evals.runs.create(
                "eval_id",
                data_source: {source: {content: [{item: {foo: "bar"}}], type: :file_content}, type: :jsonl}
              )

              puts(run)
  /evals/{eval_id}/runs/{run_id}:
    get:
      operationId: getEvalRun
      tags:
        - Evals
      summary: |
        Get an evaluation run by ID.
      parameters:
        - name: eval_id
          in: path
          required: true
          schema:
            type: string
          description: The ID of the evaluation to retrieve runs for.
        - name: run_id
          in: path
          required: true
          schema:
            type: string
          description: The ID of the run to retrieve.
      responses:
        '200':
          description: The evaluation run
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/EvalRun'
      x-oaiMeta:
        name: Get an eval run
        group: evals
        returns: The [EvalRun](/docs/api-reference/evals/run-object) object matching the specified ID.
        path: get
        examples:
          response: |
            {
              "object": "eval.run",
              "id": "evalrun_67abd54d60ec8190832b46859da808f7",
              "eval_id": "eval_67abd54d9b0081909a86353f6fb9317a",
              "report_url": "https://platform.openai.com/evaluations/eval_67abd54d9b0081909a86353f6fb9317a?run_id=evalrun_67abd54d60ec8190832b46859da808f7",
              "status": "queued",
              "model": "gpt-4o-mini",
              "name": "gpt-4o-mini",
              "created_at": 1743092069,
              "result_counts": {
                "total": 0,
                "errored": 0,
                "failed": 0,
                "passed": 0
              },
              "per_model_usage": null,
              "per_testing_criteria_results": null,
              "data_source": {
                "type": "completions",
                "source": {
                  "type": "file_content",
                  "content": [
                    {
                      "item": {
                        "input": "Tech Company Launches Advanced Artificial Intelligence Platform",
                        "ground_truth": "Technology"
                      }
                    },
                    {
                      "item": {
                        "input": "Central Bank Increases Interest Rates Amid Inflation Concerns",
                        "ground_truth": "Markets"
                      }
                    },
                    {
                      "item": {
                        "input": "International Summit Addresses Climate Change Strategies",
                        "ground_truth": "World"
                      }
                    },
                    {
                      "item": {
                        "input": "Major Retailer Reports Record-Breaking Holiday Sales",
                        "ground_truth": "Business"
                      }
                    },
                    {
                      "item": {
                        "input": "National Team Qualifies for World Championship Finals",
                        "ground_truth": "Sports"
                      }
                    },
                    {
                      "item": {
                        "input": "Stock Markets Rally After Positive Economic Data Released",
                        "ground_truth": "Markets"
                      }
                    },
                    {
                      "item": {
                        "input": "Global Manufacturer Announces Merger with Competitor",
                        "ground_truth": "Business"
                      }
                    },
                    {
                      "item": {
                        "input": "Breakthrough in Renewable Energy Technology Unveiled",
                        "ground_truth": "Technology"
                      }
                    },
                    {
                      "item": {
                        "input": "World Leaders Sign Historic Climate Agreement",
                        "ground_truth": "World"
                      }
                    },
                    {
                      "item": {
                        "input": "Professional Athlete Sets New Record in Championship Event",
                        "ground_truth": "Sports"
                      }
                    },
                    {
                      "item": {
                        "input": "Financial Institutions Adapt to New Regulatory Requirements",
                        "ground_truth": "Business"
                      }
                    },
                    {
                      "item": {
                        "input": "Tech Conference Showcases Advances in Artificial Intelligence",
                        "ground_truth": "Technology"
                      }
                    },
                    {
                      "item": {
                        "input": "Global Markets Respond to Oil Price Fluctuations",
                        "ground_truth": "Markets"
                      }
                    },
                    {
                      "item": {
                        "input": "International Cooperation Strengthened Through New Treaty",
                        "ground_truth": "World"
                      }
                    },
                    {
                      "item": {
                        "input": "Sports League Announces Revised Schedule for Upcoming Season",
                        "ground_truth": "Sports"
                      }
                    }
                  ]
                },
                "input_messages": {
                  "type": "template",
                  "template": [
                    {
                      "type": "message",
                      "role": "developer",
                      "content": {
                        "type": "input_text",
                        "text": "Categorize a given news headline into one of the following topics: Technology, Markets, World, Business, or Sports.\n\n# Steps\n\n1. Analyze the content of the news headline to understand its primary focus.\n2. Extract the subject matter, identifying any key indicators or keywords.\n3. Use the identified indicators to determine the most suitable category out of the five options: Technology, Markets, World, Business, or Sports.\n4. Ensure only one category is selected per headline.\n\n# Output Format\n\nRespond with the chosen category as a single word. For instance: \"Technology\", \"Markets\", \"World\", \"Business\", or \"Sports\".\n\n# Examples\n\n**Input**: \"Apple Unveils New iPhone Model, Featuring Advanced AI Features\"  \n**Output**: \"Technology\"\n\n**Input**: \"Global Stocks Mixed as Investors Await Central Bank Decisions\"  \n**Output**: \"Markets\"\n\n**Input**: \"War in Ukraine: Latest Updates on Negotiation Status\"  \n**Output**: \"World\"\n\n**Input**: \"Microsoft in Talks to Acquire Gaming Company for $2 Billion\"  \n**Output**: \"Business\"\n\n**Input**: \"Manchester United Secures Win in Premier League Football Match\"  \n**Output**: \"Sports\" \n\n# Notes\n\n- If the headline appears to fit into more than one category, choose the most dominant theme.\n- Keywords or phrases such as \"stocks\", \"company acquisition\", \"match\", or technological brands can be good indicators for classification.\n"
                      }
                    },
                    {
                      "type": "message",
                      "role": "user",
                      "content": {
                        "type": "input_text",
                        "text": "{{item.input}}"
                      }
                    }
                  ]
                },
                "model": "gpt-4o-mini",
                "sampling_params": {
                  "seed": 42,
                  "temperature": 1.0,
                  "top_p": 1.0,
                  "max_completions_tokens": 2048
                }
              },
              "error": null,
              "metadata": {}
            }
          request:
            curl: >
              curl
              https://api.openai.com/v1/evals/eval_67abd54d9b0081909a86353f6fb9317a/runs/evalrun_67abd54d60ec8190832b46859da808f7
              \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              run = client.evals.runs.retrieve(
                  run_id="run_id",
                  eval_id="eval_id",
              )
              print(run.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const run = await client.evals.runs.retrieve('run_id', { eval_id: 'eval_id' });

              console.log(run.id);
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.evals.runs.RunRetrieveParams;
              import com.openai.models.evals.runs.RunRetrieveResponse;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      RunRetrieveParams params = RunRetrieveParams.builder()
                          .evalId("eval_id")
                          .runId("run_id")
                          .build();
                      RunRetrieveResponse run = client.evals().runs().retrieve(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.evals.runs.RunRetrieveParams
              import com.openai.models.evals.runs.RunRetrieveResponse

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: RunRetrieveParams = RunRetrieveParams.builder()
                      .evalId("eval_id")
                      .runId("run_id")
                      .build()
                  val run: RunRetrieveResponse = client.evals().runs().retrieve(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              run = openai.evals.runs.retrieve("run_id", eval_id: "eval_id")

              puts(run)
    post:
      operationId: cancelEvalRun
      tags:
        - Evals
      summary: |
        Cancel an ongoing evaluation run.
      parameters:
        - name: eval_id
          in: path
          required: true
          schema:
            type: string
          description: The ID of the evaluation whose run you want to cancel.
        - name: run_id
          in: path
          required: true
          schema:
            type: string
          description: The ID of the run to cancel.
      responses:
        '200':
          description: The canceled eval run object
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/EvalRun'
      x-oaiMeta:
        name: Cancel eval run
        group: evals
        returns: >-
          The updated [EvalRun](/docs/api-reference/evals/run-object) object reflecting that the run is
          canceled.
        path: post
        examples:
          response: |
            {
              "object": "eval.run",
              "id": "evalrun_67abd54d60ec8190832b46859da808f7",
              "eval_id": "eval_67abd54d9b0081909a86353f6fb9317a",
              "report_url": "https://platform.openai.com/evaluations/eval_67abd54d9b0081909a86353f6fb9317a?run_id=evalrun_67abd54d60ec8190832b46859da808f7",
              "status": "canceled",
              "model": "gpt-4o-mini",
              "name": "gpt-4o-mini",
              "created_at": 1743092069,
              "result_counts": {
                "total": 0,
                "errored": 0,
                "failed": 0,
                "passed": 0
              },
              "per_model_usage": null,
              "per_testing_criteria_results": null,
              "data_source": {
                "type": "completions",
                "source": {
                  "type": "file_content",
                  "content": [
                    {
                      "item": {
                        "input": "Tech Company Launches Advanced Artificial Intelligence Platform",
                        "ground_truth": "Technology"
                      }
                    },
                    {
                      "item": {
                        "input": "Central Bank Increases Interest Rates Amid Inflation Concerns",
                        "ground_truth": "Markets"
                      }
                    },
                    {
                      "item": {
                        "input": "International Summit Addresses Climate Change Strategies",
                        "ground_truth": "World"
                      }
                    },
                    {
                      "item": {
                        "input": "Major Retailer Reports Record-Breaking Holiday Sales",
                        "ground_truth": "Business"
                      }
                    },
                    {
                      "item": {
                        "input": "National Team Qualifies for World Championship Finals",
                        "ground_truth": "Sports"
                      }
                    },
                    {
                      "item": {
                        "input": "Stock Markets Rally After Positive Economic Data Released",
                        "ground_truth": "Markets"
                      }
                    },
                    {
                      "item": {
                        "input": "Global Manufacturer Announces Merger with Competitor",
                        "ground_truth": "Business"
                      }
                    },
                    {
                      "item": {
                        "input": "Breakthrough in Renewable Energy Technology Unveiled",
                        "ground_truth": "Technology"
                      }
                    },
                    {
                      "item": {
                        "input": "World Leaders Sign Historic Climate Agreement",
                        "ground_truth": "World"
                      }
                    },
                    {
                      "item": {
                        "input": "Professional Athlete Sets New Record in Championship Event",
                        "ground_truth": "Sports"
                      }
                    },
                    {
                      "item": {
                        "input": "Financial Institutions Adapt to New Regulatory Requirements",
                        "ground_truth": "Business"
                      }
                    },
                    {
                      "item": {
                        "input": "Tech Conference Showcases Advances in Artificial Intelligence",
                        "ground_truth": "Technology"
                      }
                    },
                    {
                      "item": {
                        "input": "Global Markets Respond to Oil Price Fluctuations",
                        "ground_truth": "Markets"
                      }
                    },
                    {
                      "item": {
                        "input": "International Cooperation Strengthened Through New Treaty",
                        "ground_truth": "World"
                      }
                    },
                    {
                      "item": {
                        "input": "Sports League Announces Revised Schedule for Upcoming Season",
                        "ground_truth": "Sports"
                      }
                    }
                  ]
                },
                "input_messages": {
                  "type": "template",
                  "template": [
                    {
                      "type": "message",
                      "role": "developer",
                      "content": {
                        "type": "input_text",
                        "text": "Categorize a given news headline into one of the following topics: Technology, Markets, World, Business, or Sports.\n\n# Steps\n\n1. Analyze the content of the news headline to understand its primary focus.\n2. Extract the subject matter, identifying any key indicators or keywords.\n3. Use the identified indicators to determine the most suitable category out of the five options: Technology, Markets, World, Business, or Sports.\n4. Ensure only one category is selected per headline.\n\n# Output Format\n\nRespond with the chosen category as a single word. For instance: \"Technology\", \"Markets\", \"World\", \"Business\", or \"Sports\".\n\n# Examples\n\n**Input**: \"Apple Unveils New iPhone Model, Featuring Advanced AI Features\"  \n**Output**: \"Technology\"\n\n**Input**: \"Global Stocks Mixed as Investors Await Central Bank Decisions\"  \n**Output**: \"Markets\"\n\n**Input**: \"War in Ukraine: Latest Updates on Negotiation Status\"  \n**Output**: \"World\"\n\n**Input**: \"Microsoft in Talks to Acquire Gaming Company for $2 Billion\"  \n**Output**: \"Business\"\n\n**Input**: \"Manchester United Secures Win in Premier League Football Match\"  \n**Output**: \"Sports\" \n\n# Notes\n\n- If the headline appears to fit into more than one category, choose the most dominant theme.\n- Keywords or phrases such as \"stocks\", \"company acquisition\", \"match\", or technological brands can be good indicators for classification.\n"
                      }
                    },
                    {
                      "type": "message",
                      "role": "user",
                      "content": {
                        "type": "input_text",
                        "text": "{{item.input}}"
                      }
                    }
                  ]
                },
                "model": "gpt-4o-mini",
                "sampling_params": {
                  "seed": 42,
                  "temperature": 1.0,
                  "top_p": 1.0,
                  "max_completions_tokens": 2048
                }
              },
              "error": null,
              "metadata": {}
            }
          request:
            curl: >
              curl
              https://api.openai.com/v1/evals/eval_67abd54d9b0081909a86353f6fb9317a/runs/evalrun_67abd54d60ec8190832b46859da808f7/cancel
              \
                -X POST \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              response = client.evals.runs.cancel(
                  run_id="run_id",
                  eval_id="eval_id",
              )
              print(response.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const response = await client.evals.runs.cancel('run_id', { eval_id: 'eval_id' });

              console.log(response.id);
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.evals.runs.RunCancelParams;
              import com.openai.models.evals.runs.RunCancelResponse;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      RunCancelParams params = RunCancelParams.builder()
                          .evalId("eval_id")
                          .runId("run_id")
                          .build();
                      RunCancelResponse response = client.evals().runs().cancel(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.evals.runs.RunCancelParams
              import com.openai.models.evals.runs.RunCancelResponse

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: RunCancelParams = RunCancelParams.builder()
                      .evalId("eval_id")
                      .runId("run_id")
                      .build()
                  val response: RunCancelResponse = client.evals().runs().cancel(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              response = openai.evals.runs.cancel("run_id", eval_id: "eval_id")

              puts(response)
    delete:
      operationId: deleteEvalRun
      tags:
        - Evals
      summary: |
        Delete an eval run.
      parameters:
        - name: eval_id
          in: path
          required: true
          schema:
            type: string
          description: The ID of the evaluation to delete the run from.
        - name: run_id
          in: path
          required: true
          schema:
            type: string
          description: The ID of the run to delete.
      responses:
        '200':
          description: Successfully deleted the eval run
          content:
            application/json:
              schema:
                type: object
                properties:
                  object:
                    type: string
                    example: eval.run.deleted
                  deleted:
                    type: boolean
                    example: true
                  run_id:
                    type: string
                    example: evalrun_677469f564d48190807532a852da3afb
        '404':
          description: Run not found
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Error'
      x-oaiMeta:
        name: Delete eval run
        group: evals
        returns: An object containing the status of the delete operation.
        path: delete
        examples:
          response: |
            {
              "object": "eval.run.deleted",
              "deleted": true,
              "run_id": "evalrun_abc456"
            }
          request:
            curl: |
              curl https://api.openai.com/v1/evals/eval_123abc/runs/evalrun_abc456 \
                -X DELETE \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              run = client.evals.runs.delete(
                  run_id="run_id",
                  eval_id="eval_id",
              )
              print(run.run_id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const run = await client.evals.runs.delete('run_id', { eval_id: 'eval_id' });

              console.log(run.run_id);
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.evals.runs.RunDeleteParams;
              import com.openai.models.evals.runs.RunDeleteResponse;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      RunDeleteParams params = RunDeleteParams.builder()
                          .evalId("eval_id")
                          .runId("run_id")
                          .build();
                      RunDeleteResponse run = client.evals().runs().delete(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.evals.runs.RunDeleteParams
              import com.openai.models.evals.runs.RunDeleteResponse

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: RunDeleteParams = RunDeleteParams.builder()
                      .evalId("eval_id")
                      .runId("run_id")
                      .build()
                  val run: RunDeleteResponse = client.evals().runs().delete(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              run = openai.evals.runs.delete("run_id", eval_id: "eval_id")

              puts(run)
  /evals/{eval_id}/runs/{run_id}/output_items:
    get:
      operationId: getEvalRunOutputItems
      tags:
        - Evals
      summary: |
        Get a list of output items for an evaluation run.
      parameters:
        - name: eval_id
          in: path
          required: true
          schema:
            type: string
          description: The ID of the evaluation to retrieve runs for.
        - name: run_id
          in: path
          required: true
          schema:
            type: string
          description: The ID of the run to retrieve output items for.
        - name: after
          in: query
          description: Identifier for the last output item from the previous pagination request.
          required: false
          schema:
            type: string
        - name: limit
          in: query
          description: Number of output items to retrieve.
          required: false
          schema:
            type: integer
            default: 20
        - name: status
          in: query
          description: |
            Filter output items by status. Use `failed` to filter by failed output
            items or `pass` to filter by passed output items.
          required: false
          schema:
            type: string
            enum:
              - fail
              - pass
        - name: order
          in: query
          description: >-
            Sort order for output items by timestamp. Use `asc` for ascending order or `desc` for descending
            order. Defaults to `asc`.
          required: false
          schema:
            type: string
            enum:
              - asc
              - desc
            default: asc
      responses:
        '200':
          description: A list of output items for the evaluation run
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/EvalRunOutputItemList'
      x-oaiMeta:
        name: Get eval run output items
        group: evals
        returns: >-
          A list of [EvalRunOutputItem](/docs/api-reference/evals/run-output-item-object) objects matching the
          specified ID.
        path: get
        examples:
          response: |
            {
              "object": "list",
              "data": [
                {
                  "object": "eval.run.output_item",
                  "id": "outputitem_67e5796c28e081909917bf79f6e6214d",
                  "created_at": 1743092076,
                  "run_id": "evalrun_67abd54d60ec8190832b46859da808f7",
                  "eval_id": "eval_67abd54d9b0081909a86353f6fb9317a",
                  "status": "pass",
                  "datasource_item_id": 5,
                  "datasource_item": {
                    "input": "Stock Markets Rally After Positive Economic Data Released",
                    "ground_truth": "Markets"
                  },
                  "results": [
                    {
                      "name": "String check-a2486074-d803-4445-b431-ad2262e85d47",
                      "sample": null,
                      "passed": true,
                      "score": 1.0
                    }
                  ],
                  "sample": {
                    "input": [
                      {
                        "role": "developer",
                        "content": "Categorize a given news headline into one of the following topics: Technology, Markets, World, Business, or Sports.\n\n# Steps\n\n1. Analyze the content of the news headline to understand its primary focus.\n2. Extract the subject matter, identifying any key indicators or keywords.\n3. Use the identified indicators to determine the most suitable category out of the five options: Technology, Markets, World, Business, or Sports.\n4. Ensure only one category is selected per headline.\n\n# Output Format\n\nRespond with the chosen category as a single word. For instance: \"Technology\", \"Markets\", \"World\", \"Business\", or \"Sports\".\n\n# Examples\n\n**Input**: \"Apple Unveils New iPhone Model, Featuring Advanced AI Features\"  \n**Output**: \"Technology\"\n\n**Input**: \"Global Stocks Mixed as Investors Await Central Bank Decisions\"  \n**Output**: \"Markets\"\n\n**Input**: \"War in Ukraine: Latest Updates on Negotiation Status\"  \n**Output**: \"World\"\n\n**Input**: \"Microsoft in Talks to Acquire Gaming Company for $2 Billion\"  \n**Output**: \"Business\"\n\n**Input**: \"Manchester United Secures Win in Premier League Football Match\"  \n**Output**: \"Sports\" \n\n# Notes\n\n- If the headline appears to fit into more than one category, choose the most dominant theme.\n- Keywords or phrases such as \"stocks\", \"company acquisition\", \"match\", or technological brands can be good indicators for classification.\n",
                        "tool_call_id": null,
                        "tool_calls": null,
                        "function_call": null
                      },
                      {
                        "role": "user",
                        "content": "Stock Markets Rally After Positive Economic Data Released",
                        "tool_call_id": null,
                        "tool_calls": null,
                        "function_call": null
                      }
                    ],
                    "output": [
                      {
                        "role": "assistant",
                        "content": "Markets",
                        "tool_call_id": null,
                        "tool_calls": null,
                        "function_call": null
                      }
                    ],
                    "finish_reason": "stop",
                    "model": "gpt-4o-mini-2024-07-18",
                    "usage": {
                      "total_tokens": 325,
                      "completion_tokens": 2,
                      "prompt_tokens": 323,
                      "cached_tokens": 0
                    },
                    "error": null,
                    "temperature": 1.0,
                    "max_completion_tokens": 2048,
                    "top_p": 1.0,
                    "seed": 42
                  }
                }
              ],
              "first_id": "outputitem_67e5796c28e081909917bf79f6e6214d",
              "last_id": "outputitem_67e5796c28e081909917bf79f6e6214d",
              "has_more": true
            }
          request:
            curl: >
              curl
              https://api.openai.com/v1/evals/egroup_67abd54d9b0081909a86353f6fb9317a/runs/erun_67abd54d60ec8190832b46859da808f7/output_items
              \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              page = client.evals.runs.output_items.list(
                  run_id="run_id",
                  eval_id="eval_id",
              )
              page = page.data[0]
              print(page.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              // Automatically fetches more pages as needed.
              for await (const outputItemListResponse of client.evals.runs.outputItems.list('run_id', {
                eval_id: 'eval_id',
              })) {
                console.log(outputItemListResponse.id);
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.evals.runs.outputitems.OutputItemListPage;
              import com.openai.models.evals.runs.outputitems.OutputItemListParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      OutputItemListParams params = OutputItemListParams.builder()
                          .evalId("eval_id")
                          .runId("run_id")
                          .build();
                      OutputItemListPage page = client.evals().runs().outputItems().list(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.evals.runs.outputitems.OutputItemListPage
              import com.openai.models.evals.runs.outputitems.OutputItemListParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: OutputItemListParams = OutputItemListParams.builder()
                      .evalId("eval_id")
                      .runId("run_id")
                      .build()
                  val page: OutputItemListPage = client.evals().runs().outputItems().list(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              page = openai.evals.runs.output_items.list("run_id", eval_id: "eval_id")

              puts(page)
  /evals/{eval_id}/runs/{run_id}/output_items/{output_item_id}:
    get:
      operationId: getEvalRunOutputItem
      tags:
        - Evals
      summary: |
        Get an evaluation run output item by ID.
      parameters:
        - name: eval_id
          in: path
          required: true
          schema:
            type: string
          description: The ID of the evaluation to retrieve runs for.
        - name: run_id
          in: path
          required: true
          schema:
            type: string
          description: The ID of the run to retrieve.
        - name: output_item_id
          in: path
          required: true
          schema:
            type: string
          description: The ID of the output item to retrieve.
      responses:
        '200':
          description: The evaluation run output item
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/EvalRunOutputItem'
      x-oaiMeta:
        name: Get an output item of an eval run
        group: evals
        returns: >-
          The [EvalRunOutputItem](/docs/api-reference/evals/run-output-item-object) object matching the
          specified ID.
        path: get
        examples:
          response: |
            {
              "object": "eval.run.output_item",
              "id": "outputitem_67e5796c28e081909917bf79f6e6214d",
              "created_at": 1743092076,
              "run_id": "evalrun_67abd54d60ec8190832b46859da808f7",
              "eval_id": "eval_67abd54d9b0081909a86353f6fb9317a",
              "status": "pass",
              "datasource_item_id": 5,
              "datasource_item": {
                "input": "Stock Markets Rally After Positive Economic Data Released",
                "ground_truth": "Markets"
              },
              "results": [
                {
                  "name": "String check-a2486074-d803-4445-b431-ad2262e85d47",
                  "sample": null,
                  "passed": true,
                  "score": 1.0
                }
              ],
              "sample": {
                "input": [
                  {
                    "role": "developer",
                    "content": "Categorize a given news headline into one of the following topics: Technology, Markets, World, Business, or Sports.\n\n# Steps\n\n1. Analyze the content of the news headline to understand its primary focus.\n2. Extract the subject matter, identifying any key indicators or keywords.\n3. Use the identified indicators to determine the most suitable category out of the five options: Technology, Markets, World, Business, or Sports.\n4. Ensure only one category is selected per headline.\n\n# Output Format\n\nRespond with the chosen category as a single word. For instance: \"Technology\", \"Markets\", \"World\", \"Business\", or \"Sports\".\n\n# Examples\n\n**Input**: \"Apple Unveils New iPhone Model, Featuring Advanced AI Features\"  \n**Output**: \"Technology\"\n\n**Input**: \"Global Stocks Mixed as Investors Await Central Bank Decisions\"  \n**Output**: \"Markets\"\n\n**Input**: \"War in Ukraine: Latest Updates on Negotiation Status\"  \n**Output**: \"World\"\n\n**Input**: \"Microsoft in Talks to Acquire Gaming Company for $2 Billion\"  \n**Output**: \"Business\"\n\n**Input**: \"Manchester United Secures Win in Premier League Football Match\"  \n**Output**: \"Sports\" \n\n# Notes\n\n- If the headline appears to fit into more than one category, choose the most dominant theme.\n- Keywords or phrases such as \"stocks\", \"company acquisition\", \"match\", or technological brands can be good indicators for classification.\n",
                    "tool_call_id": null,
                    "tool_calls": null,
                    "function_call": null
                  },
                  {
                    "role": "user",
                    "content": "Stock Markets Rally After Positive Economic Data Released",
                    "tool_call_id": null,
                    "tool_calls": null,
                    "function_call": null
                  }
                ],
                "output": [
                  {
                    "role": "assistant",
                    "content": "Markets",
                    "tool_call_id": null,
                    "tool_calls": null,
                    "function_call": null
                  }
                ],
                "finish_reason": "stop",
                "model": "gpt-4o-mini-2024-07-18",
                "usage": {
                  "total_tokens": 325,
                  "completion_tokens": 2,
                  "prompt_tokens": 323,
                  "cached_tokens": 0
                },
                "error": null,
                "temperature": 1.0,
                "max_completion_tokens": 2048,
                "top_p": 1.0,
                "seed": 42
              }
            }
          request:
            curl: >
              curl
              https://api.openai.com/v1/evals/eval_67abd54d9b0081909a86353f6fb9317a/runs/evalrun_67abd54d60ec8190832b46859da808f7/output_items/outputitem_67abd55eb6548190bb580745d5644a33
              \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              output_item = client.evals.runs.output_items.retrieve(
                  output_item_id="output_item_id",
                  eval_id="eval_id",
                  run_id="run_id",
              )
              print(output_item.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const outputItem = await client.evals.runs.outputItems.retrieve('output_item_id', {
                eval_id: 'eval_id',
                run_id: 'run_id',
              });

              console.log(outputItem.id);
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.evals.runs.outputitems.OutputItemRetrieveParams;
              import com.openai.models.evals.runs.outputitems.OutputItemRetrieveResponse;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      OutputItemRetrieveParams params = OutputItemRetrieveParams.builder()
                          .evalId("eval_id")
                          .runId("run_id")
                          .outputItemId("output_item_id")
                          .build();
                      OutputItemRetrieveResponse outputItem = client.evals().runs().outputItems().retrieve(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.evals.runs.outputitems.OutputItemRetrieveParams
              import com.openai.models.evals.runs.outputitems.OutputItemRetrieveResponse

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: OutputItemRetrieveParams = OutputItemRetrieveParams.builder()
                      .evalId("eval_id")
                      .runId("run_id")
                      .outputItemId("output_item_id")
                      .build()
                  val outputItem: OutputItemRetrieveResponse = client.evals().runs().outputItems().retrieve(params)
              }
            ruby: >-
              require "openai"


              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )


              output_item = openai.evals.runs.output_items.retrieve("output_item_id", eval_id: "eval_id",
              run_id: "run_id")


              puts(output_item)
  /files:
    get:
      operationId: listFiles
      tags:
        - Files
      summary: Returns a list of files.
      parameters:
        - in: query
          name: purpose
          required: false
          schema:
            type: string
          description: Only return files with the given purpose.
        - name: limit
          in: query
          description: >
            A limit on the number of objects to be returned. Limit can range between 1 and 10,000, and the
            default is 10,000.
          required: false
          schema:
            type: integer
            default: 10000
        - name: order
          in: query
          description: >
            Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for
            descending order.
          schema:
            type: string
            default: desc
            enum:
              - asc
              - desc
        - name: after
          in: query
          description: >
            A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
            instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
            call can include after=obj_foo in order to fetch the next page of the list.
          schema:
            type: string
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ListFilesResponse'
      x-oaiMeta:
        name: List files
        group: files
        returns: A list of [File](/docs/api-reference/files/object) objects.
        examples:
          response: |
            {
              "data": [
                {
                  "id": "file-abc123",
                  "object": "file",
                  "bytes": 175,
                  "created_at": 1613677385,
                  "filename": "salesOverview.pdf",
                  "purpose": "assistants",
                },
                {
                  "id": "file-abc123",
                  "object": "file",
                  "bytes": 140,
                  "created_at": 1613779121,
                  "filename": "puppy.jsonl",
                  "purpose": "fine-tune",
                }
              ],
              "object": "list"
            }
          request:
            curl: |
              curl https://api.openai.com/v1/files \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              page = client.files.list()
              page = page.data[0]
              print(page)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              // Automatically fetches more pages as needed.
              for await (const fileObject of client.files.list()) {
                console.log(fileObject);
              }
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                page, err := client.Files.List(context.TODO(), openai.FileListParams{

                })
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", page)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.files.FileListPage;
              import com.openai.models.files.FileListParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      FileListPage page = client.files().list();
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.files.FileListPage
              import com.openai.models.files.FileListParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val page: FileListPage = client.files().list()
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              page = openai.files.list

              puts(page)
    post:
      operationId: createFile
      tags:
        - Files
      summary: >
        Upload a file that can be used across various endpoints. Individual files can be up to 512 MB, and the
        size of all files uploaded by one organization can be up to 100 GB.


        The Assistants API supports files up to 2 million tokens and of specific file types. See the
        [Assistants Tools guide](/docs/assistants/tools) for details.


        The Fine-tuning API only supports `.jsonl` files. The input also has certain required formats for
        fine-tuning [chat](/docs/api-reference/fine-tuning/chat-input) or
        [completions](/docs/api-reference/fine-tuning/completions-input) models.


        The Batch API only supports `.jsonl` files up to 200 MB in size. The input also has a specific
        required [format](/docs/api-reference/batch/request-input).


        Please [contact us](https://help.openai.com/) if you need to increase these storage limits.
      requestBody:
        required: true
        content:
          multipart/form-data:
            schema:
              $ref: '#/components/schemas/CreateFileRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/OpenAIFile'
      x-oaiMeta:
        name: Upload file
        group: files
        returns: The uploaded [File](/docs/api-reference/files/object) object.
        examples:
          response: |
            {
              "id": "file-abc123",
              "object": "file",
              "bytes": 120000,
              "created_at": 1677610602,
              "filename": "mydata.jsonl",
              "purpose": "fine-tune",
            }
          request:
            curl: |
              curl https://api.openai.com/v1/files \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -F purpose="fine-tune" \
                -F file="@mydata.jsonl"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              file_object = client.files.create(
                  file=b"raw file contents",
                  purpose="assistants",
              )
              print(file_object.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const fileObject = await client.files.create({
                file: fs.createReadStream('fine-tune.jsonl'),
                purpose: 'assistants',
              });

              console.log(fileObject.id);
            go: |
              package main

              import (
                "bytes"
                "context"
                "fmt"
                "io"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                fileObject, err := client.Files.New(context.TODO(), openai.FileNewParams{
                  File: io.Reader(bytes.NewBuffer([]byte("some file contents"))),
                  Purpose: openai.FilePurposeAssistants,
                })
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", fileObject.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.files.FileCreateParams;
              import com.openai.models.files.FileObject;
              import com.openai.models.files.FilePurpose;
              import java.io.ByteArrayInputStream;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      FileCreateParams params = FileCreateParams.builder()
                          .file(ByteArrayInputStream("some content".getBytes()))
                          .purpose(FilePurpose.ASSISTANTS)
                          .build();
                      FileObject fileObject = client.files().create(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.files.FileCreateParams
              import com.openai.models.files.FileObject
              import com.openai.models.files.FilePurpose
              import java.io.ByteArrayInputStream

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: FileCreateParams = FileCreateParams.builder()
                      .file("some content".byteInputStream())
                      .purpose(FilePurpose.ASSISTANTS)
                      .build()
                  val fileObject: FileObject = client.files().create(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              file_object = openai.files.create(file: Pathname(__FILE__), purpose: :assistants)

              puts(file_object)
  /files/{file_id}:
    delete:
      operationId: deleteFile
      tags:
        - Files
      summary: Delete a file.
      parameters:
        - in: path
          name: file_id
          required: true
          schema:
            type: string
          description: The ID of the file to use for this request.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/DeleteFileResponse'
      x-oaiMeta:
        name: Delete file
        group: files
        returns: Deletion status.
        examples:
          response: |
            {
              "id": "file-abc123",
              "object": "file",
              "deleted": true
            }
          request:
            curl: |
              curl https://api.openai.com/v1/files/file-abc123 \
                -X DELETE \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              file_deleted = client.files.delete(
                  "file_id",
              )
              print(file_deleted.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const fileDeleted = await client.files.delete('file_id');

              console.log(fileDeleted.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                fileDeleted, err := client.Files.Delete(context.TODO(), "file_id")
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", fileDeleted.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.files.FileDeleteParams;
              import com.openai.models.files.FileDeleted;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      FileDeleted fileDeleted = client.files().delete("file_id");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.files.FileDeleteParams
              import com.openai.models.files.FileDeleted

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val fileDeleted: FileDeleted = client.files().delete("file_id")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              file_deleted = openai.files.delete("file_id")

              puts(file_deleted)
    get:
      operationId: retrieveFile
      tags:
        - Files
      summary: Returns information about a specific file.
      parameters:
        - in: path
          name: file_id
          required: true
          schema:
            type: string
          description: The ID of the file to use for this request.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/OpenAIFile'
      x-oaiMeta:
        name: Retrieve file
        group: files
        returns: The [File](/docs/api-reference/files/object) object matching the specified ID.
        examples:
          response: |
            {
              "id": "file-abc123",
              "object": "file",
              "bytes": 120000,
              "created_at": 1677610602,
              "filename": "mydata.jsonl",
              "purpose": "fine-tune",
            }
          request:
            curl: |
              curl https://api.openai.com/v1/files/file-abc123 \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              file_object = client.files.retrieve(
                  "file_id",
              )
              print(file_object.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const fileObject = await client.files.retrieve('file_id');

              console.log(fileObject.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                fileObject, err := client.Files.Get(context.TODO(), "file_id")
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", fileObject.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.files.FileObject;
              import com.openai.models.files.FileRetrieveParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      FileObject fileObject = client.files().retrieve("file_id");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.files.FileObject
              import com.openai.models.files.FileRetrieveParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val fileObject: FileObject = client.files().retrieve("file_id")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              file_object = openai.files.retrieve("file_id")

              puts(file_object)
  /files/{file_id}/content:
    get:
      operationId: downloadFile
      tags:
        - Files
      summary: Returns the contents of the specified file.
      parameters:
        - in: path
          name: file_id
          required: true
          schema:
            type: string
          description: The ID of the file to use for this request.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                type: string
      x-oaiMeta:
        name: Retrieve file content
        group: files
        returns: The file content.
        examples:
          response: ''
          request:
            curl: |
              curl https://api.openai.com/v1/files/file-abc123/content \
                -H "Authorization: Bearer $OPENAI_API_KEY" > file.jsonl
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              response = client.files.content(
                  "file_id",
              )
              print(response)
              content = response.read()
              print(content)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const response = await client.files.content('file_id');

              console.log(response);

              const content = await response.blob();
              console.log(content);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                response, err := client.Files.Content(context.TODO(), "file_id")
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", response)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.core.http.HttpResponse;
              import com.openai.models.files.FileContentParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      HttpResponse response = client.files().content("file_id");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.core.http.HttpResponse
              import com.openai.models.files.FileContentParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val response: HttpResponse = client.files().content("file_id")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              response = openai.files.content("file_id")

              puts(response)
  /fine_tuning/alpha/graders/run:
    post:
      operationId: runGrader
      tags:
        - Fine-tuning
      summary: |
        Run a grader.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/RunGraderRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/RunGraderResponse'
      x-oaiMeta:
        name: Run grader
        beta: true
        group: graders
        returns: The results from the grader run.
        examples:
          response: |
            {
              "reward": 1.0,
              "metadata": {
                "name": "Example score model grader",
                "type": "score_model",
                "errors": {
                  "formula_parse_error": false,
                  "sample_parse_error": false,
                  "truncated_observation_error": false,
                  "unresponsive_reward_error": false,
                  "invalid_variable_error": false,
                  "other_error": false,
                  "python_grader_server_error": false,
                  "python_grader_server_error_type": null,
                  "python_grader_runtime_error": false,
                  "python_grader_runtime_error_details": null,
                  "model_grader_server_error": false,
                  "model_grader_refusal_error": false,
                  "model_grader_parse_error": false,
                  "model_grader_server_error_details": null
                },
                "execution_time": 4.365238428115845,
                "scores": {},
                "token_usage": {
                  "prompt_tokens": 190,
                  "total_tokens": 324,
                  "completion_tokens": 134,
                  "cached_tokens": 0
                },
                "sampled_model_name": "gpt-4o-2024-08-06"
              },
              "sub_rewards": {},
              "model_grader_token_usage_per_model": {
                "gpt-4o-2024-08-06": {
                  "prompt_tokens": 190,
                  "total_tokens": 324,
                  "completion_tokens": 134,
                  "cached_tokens": 0
                }
              }
            }
          request:
            curl: |
              curl -X POST https://api.openai.com/v1/fine_tuning/alpha/graders/run \
                -H "Content-Type: application/json" \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -d '{
                  "grader": {
                    "type": "score_model",
                    "name": "Example score model grader",
                    "input": [
                      {
                        "role": "user",
                        "content": "Score how close the reference answer is to the model answer. Score 1.0 if they are the same and 0.0 if they are different. Return just a floating point score\n\nReference answer: {{item.reference_answer}}\n\nModel answer: {{sample.output_text}}"
                      }
                    ],
                    "model": "gpt-4o-2024-08-06",
                    "sampling_params": {
                      "temperature": 1,
                      "top_p": 1,
                      "seed": 42
                    }
                  },
                  "item": {
                    "reference_answer": "fuzzy wuzzy was a bear"
                  },
                  "model_sample": "fuzzy wuzzy was a bear"
                }'
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const response = await client.fineTuning.alpha.graders.run({
                grader: { input: 'input', name: 'name', operation: 'eq', reference: 'reference', type: 'string_check' },
                model_sample: 'model_sample',
              });

              console.log(response.metadata);
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              response = client.fine_tuning.alpha.graders.run(
                  grader={
                      "input": "input",
                      "name": "name",
                      "operation": "eq",
                      "reference": "reference",
                      "type": "string_check",
                  },
                  model_sample="model_sample",
              )
              print(response.metadata)
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                response, err := client.FineTuning.Alpha.Graders.Run(context.TODO(), openai.FineTuningAlphaGraderRunParams{
                  Grader: openai.FineTuningAlphaGraderRunParamsGraderUnion{
                    OfStringCheck: &openai.StringCheckGraderParam{
                      Input: "input",
                      Name: "name",
                      Operation: openai.StringCheckGraderOperationEq,
                      Reference: "reference",
                    },
                  },
                  ModelSample: "model_sample",
                })
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", response.Metadata)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.finetuning.alpha.graders.GraderRunParams;
              import com.openai.models.finetuning.alpha.graders.GraderRunResponse;
              import com.openai.models.graders.gradermodels.StringCheckGrader;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      GraderRunParams params = GraderRunParams.builder()
                          .grader(StringCheckGrader.builder()
                              .input("input")
                              .name("name")
                              .operation(StringCheckGrader.Operation.EQ)
                              .reference("reference")
                              .build())
                          .modelSample("model_sample")
                          .build();
                      GraderRunResponse response = client.fineTuning().alpha().graders().run(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.finetuning.alpha.graders.GraderRunParams
              import com.openai.models.finetuning.alpha.graders.GraderRunResponse
              import com.openai.models.graders.gradermodels.StringCheckGrader

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: GraderRunParams = GraderRunParams.builder()
                      .grader(StringCheckGrader.builder()
                          .input("input")
                          .name("name")
                          .operation(StringCheckGrader.Operation.EQ)
                          .reference("reference")
                          .build())
                      .modelSample("model_sample")
                      .build()
                  val response: GraderRunResponse = client.fineTuning().alpha().graders().run(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              response = openai.fine_tuning.alpha.graders.run(
                grader: {input: "input", name: "name", operation: :eq, reference: "reference", type: :string_check},
                model_sample: "model_sample"
              )

              puts(response)
  /fine_tuning/alpha/graders/validate:
    post:
      operationId: validateGrader
      tags:
        - Fine-tuning
      summary: |
        Validate a grader.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/ValidateGraderRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ValidateGraderResponse'
      x-oaiMeta:
        name: Validate grader
        beta: true
        group: graders
        returns: The validated grader object.
        examples:
          response: |
            {
              "grader": {
                "type": "string_check",
                "name": "Example string check grader",
                "input": "{{sample.output_text}}",
                "reference": "{{item.label}}",
                "operation": "eq"
              }
            }
          request:
            curl: |
              curl https://api.openai.com/v1/fine_tuning/alpha/graders/validate \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
                -d '{
                  "grader": {
                    "type": "string_check",
                    "name": "Example string check grader",
                    "input": "{{sample.output_text}}",
                    "reference": "{{item.label}}",
                    "operation": "eq"
                  }
                }'
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const response = await client.fineTuning.alpha.graders.validate({
                grader: { input: 'input', name: 'name', operation: 'eq', reference: 'reference', type: 'string_check' },
              });

              console.log(response.grader);
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              response = client.fine_tuning.alpha.graders.validate(
                  grader={
                      "input": "input",
                      "name": "name",
                      "operation": "eq",
                      "reference": "reference",
                      "type": "string_check",
                  },
              )
              print(response.grader)
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                response, err := client.FineTuning.Alpha.Graders.Validate(context.TODO(), openai.FineTuningAlphaGraderValidateParams{
                  Grader: openai.FineTuningAlphaGraderValidateParamsGraderUnion{
                    OfStringCheckGrader: &openai.StringCheckGraderParam{
                      Input: "input",
                      Name: "name",
                      Operation: openai.StringCheckGraderOperationEq,
                      Reference: "reference",
                    },
                  },
                })
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", response.Grader)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.finetuning.alpha.graders.GraderValidateParams;
              import com.openai.models.finetuning.alpha.graders.GraderValidateResponse;
              import com.openai.models.graders.gradermodels.StringCheckGrader;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      GraderValidateParams params = GraderValidateParams.builder()
                          .grader(StringCheckGrader.builder()
                              .input("input")
                              .name("name")
                              .operation(StringCheckGrader.Operation.EQ)
                              .reference("reference")
                              .build())
                          .build();
                      GraderValidateResponse response = client.fineTuning().alpha().graders().validate(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.finetuning.alpha.graders.GraderValidateParams
              import com.openai.models.finetuning.alpha.graders.GraderValidateResponse
              import com.openai.models.graders.gradermodels.StringCheckGrader

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: GraderValidateParams = GraderValidateParams.builder()
                      .grader(StringCheckGrader.builder()
                          .input("input")
                          .name("name")
                          .operation(StringCheckGrader.Operation.EQ)
                          .reference("reference")
                          .build())
                      .build()
                  val response: GraderValidateResponse = client.fineTuning().alpha().graders().validate(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              response = openai.fine_tuning.alpha.graders.validate(
                grader: {input: "input", name: "name", operation: :eq, reference: "reference", type: :string_check}
              )

              puts(response)
  /fine_tuning/checkpoints/{fine_tuned_model_checkpoint}/permissions:
    get:
      operationId: listFineTuningCheckpointPermissions
      tags:
        - Fine-tuning
      summary: |
        **NOTE:** This endpoint requires an [admin API key](../admin-api-keys).

        Organization owners can use this endpoint to view all permissions for a fine-tuned model checkpoint.
      parameters:
        - in: path
          name: fine_tuned_model_checkpoint
          required: true
          schema:
            type: string
            example: ft-AF1WoRqd3aJAHsqc9NY7iL8F
          description: |
            The ID of the fine-tuned model checkpoint to get permissions for.
        - name: project_id
          in: query
          description: The ID of the project to get permissions for.
          required: false
          schema:
            type: string
        - name: after
          in: query
          description: Identifier for the last permission ID from the previous pagination request.
          required: false
          schema:
            type: string
        - name: limit
          in: query
          description: Number of permissions to retrieve.
          required: false
          schema:
            type: integer
            default: 10
        - name: order
          in: query
          description: The order in which to retrieve permissions.
          required: false
          schema:
            type: string
            enum:
              - ascending
              - descending
            default: descending
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ListFineTuningCheckpointPermissionResponse'
      x-oaiMeta:
        name: List checkpoint permissions
        group: fine-tuning
        returns: >-
          A list of fine-tuned model checkpoint [permission
          objects](/docs/api-reference/fine-tuning/permission-object) for a fine-tuned model checkpoint.
        examples:
          response: |
            {
              "object": "list",
              "data": [
                {
                  "object": "checkpoint.permission",
                  "id": "cp_zc4Q7MP6XxulcVzj4MZdwsAB",
                  "created_at": 1721764867,
                  "project_id": "proj_abGMw1llN8IrBb6SvvY5A1iH"
                },
                {
                  "object": "checkpoint.permission",
                  "id": "cp_enQCFmOTGj3syEpYVhBRLTSy",
                  "created_at": 1721764800,
                  "project_id": "proj_iqGMw1llN8IrBb6SvvY5A1oF"
                },
              ],
              "first_id": "cp_zc4Q7MP6XxulcVzj4MZdwsAB",
              "last_id": "cp_enQCFmOTGj3syEpYVhBRLTSy",
              "has_more": false
            }
          request:
            curl: >
              curl
              https://api.openai.com/v1/fine_tuning/checkpoints/ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd/permissions
              \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            node.js: >-
              import OpenAI from 'openai';


              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });


              // Automatically fetches more pages as needed.

              for await (const permissionRetrieveResponse of
              client.fineTuning.checkpoints.permissions.retrieve(
                'ft-AF1WoRqd3aJAHsqc9NY7iL8F',
              )) {
                console.log(permissionRetrieveResponse.id);
              }
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              page = client.fine_tuning.checkpoints.permissions.retrieve(
                  fine_tuned_model_checkpoint="ft-AF1WoRqd3aJAHsqc9NY7iL8F",
              )
              page = page.data[0]
              print(page.id)
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                page, err := client.FineTuning.Checkpoints.Permissions.Get(
                  context.TODO(),
                  "ft-AF1WoRqd3aJAHsqc9NY7iL8F",
                  openai.FineTuningCheckpointPermissionGetParams{

                  },
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", page)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.finetuning.checkpoints.permissions.PermissionRetrievePage;
              import com.openai.models.finetuning.checkpoints.permissions.PermissionRetrieveParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      PermissionRetrievePage page = client.fineTuning().checkpoints().permissions().retrieve("ft-AF1WoRqd3aJAHsqc9NY7iL8F");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.finetuning.checkpoints.permissions.PermissionRetrievePage
              import com.openai.models.finetuning.checkpoints.permissions.PermissionRetrieveParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val page: PermissionRetrievePage = client.fineTuning().checkpoints().permissions().retrieve("ft-AF1WoRqd3aJAHsqc9NY7iL8F")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              page = openai.fine_tuning.checkpoints.permissions.retrieve("ft-AF1WoRqd3aJAHsqc9NY7iL8F")

              puts(page)
    post:
      operationId: createFineTuningCheckpointPermission
      tags:
        - Fine-tuning
      summary: |
        **NOTE:** Calling this endpoint requires an [admin API key](../admin-api-keys).

        This enables organization owners to share fine-tuned models with other projects in their organization.
      parameters:
        - in: path
          name: fine_tuned_model_checkpoint
          required: true
          schema:
            type: string
            example: ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd
          description: |
            The ID of the fine-tuned model checkpoint to create a permission for.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateFineTuningCheckpointPermissionRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ListFineTuningCheckpointPermissionResponse'
      x-oaiMeta:
        name: Create checkpoint permissions
        group: fine-tuning
        returns: >-
          A list of fine-tuned model checkpoint [permission
          objects](/docs/api-reference/fine-tuning/permission-object) for a fine-tuned model checkpoint.
        examples:
          response: |
            {
              "object": "list",
              "data": [
                {
                  "object": "checkpoint.permission",
                  "id": "cp_zc4Q7MP6XxulcVzj4MZdwsAB",
                  "created_at": 1721764867,
                  "project_id": "proj_abGMw1llN8IrBb6SvvY5A1iH"
                }
              ],
              "first_id": "cp_zc4Q7MP6XxulcVzj4MZdwsAB",
              "last_id": "cp_zc4Q7MP6XxulcVzj4MZdwsAB",
              "has_more": false
            }
          request:
            curl: >
              curl
              https://api.openai.com/v1/fine_tuning/checkpoints/ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd/permissions
              \
                -H "Authorization: Bearer $OPENAI_API_KEY"
                -d '{"project_ids": ["proj_abGMw1llN8IrBb6SvvY5A1iH"]}'
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              // Automatically fetches more pages as needed.
              for await (const permissionCreateResponse of client.fineTuning.checkpoints.permissions.create(
                'ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd',
                { project_ids: ['string'] },
              )) {
                console.log(permissionCreateResponse.id);
              }
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              page = client.fine_tuning.checkpoints.permissions.create(
                  fine_tuned_model_checkpoint="ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd",
                  project_ids=["string"],
              )
              page = page.data[0]
              print(page.id)
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                page, err := client.FineTuning.Checkpoints.Permissions.New(
                  context.TODO(),
                  "ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd",
                  openai.FineTuningCheckpointPermissionNewParams{
                    ProjectIDs: []string{"string"},
                  },
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", page)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.finetuning.checkpoints.permissions.PermissionCreatePage;
              import com.openai.models.finetuning.checkpoints.permissions.PermissionCreateParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      PermissionCreateParams params = PermissionCreateParams.builder()
                          .fineTunedModelCheckpoint("ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd")
                          .addProjectId("string")
                          .build();
                      PermissionCreatePage page = client.fineTuning().checkpoints().permissions().create(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.finetuning.checkpoints.permissions.PermissionCreatePage
              import com.openai.models.finetuning.checkpoints.permissions.PermissionCreateParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: PermissionCreateParams = PermissionCreateParams.builder()
                      .fineTunedModelCheckpoint("ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd")
                      .addProjectId("string")
                      .build()
                  val page: PermissionCreatePage = client.fineTuning().checkpoints().permissions().create(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              page = openai.fine_tuning.checkpoints.permissions.create(
                "ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd",
                project_ids: ["string"]
              )

              puts(page)
  /fine_tuning/checkpoints/{fine_tuned_model_checkpoint}/permissions/{permission_id}:
    delete:
      operationId: deleteFineTuningCheckpointPermission
      tags:
        - Fine-tuning
      summary: |
        **NOTE:** This endpoint requires an [admin API key](../admin-api-keys).

        Organization owners can use this endpoint to delete a permission for a fine-tuned model checkpoint.
      parameters:
        - in: path
          name: fine_tuned_model_checkpoint
          required: true
          schema:
            type: string
            example: ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd
          description: |
            The ID of the fine-tuned model checkpoint to delete a permission for.
        - in: path
          name: permission_id
          required: true
          schema:
            type: string
            example: cp_zc4Q7MP6XxulcVzj4MZdwsAB
          description: |
            The ID of the fine-tuned model checkpoint permission to delete.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/DeleteFineTuningCheckpointPermissionResponse'
      x-oaiMeta:
        name: Delete checkpoint permission
        group: fine-tuning
        returns: >-
          The deletion status of the fine-tuned model checkpoint [permission
          object](/docs/api-reference/fine-tuning/permission-object).
        examples:
          response: |
            {
              "object": "checkpoint.permission",
              "id": "cp_zc4Q7MP6XxulcVzj4MZdwsAB",
              "deleted": true
            }
          request:
            curl: >
              curl
              https://api.openai.com/v1/fine_tuning/checkpoints/ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd/permissions/cp_zc4Q7MP6XxulcVzj4MZdwsAB
              \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            node.js: >-
              import OpenAI from 'openai';


              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });


              const permission = await
              client.fineTuning.checkpoints.permissions.delete('cp_zc4Q7MP6XxulcVzj4MZdwsAB', {
                fine_tuned_model_checkpoint: 'ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd',
              });


              console.log(permission.id);
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              permission = client.fine_tuning.checkpoints.permissions.delete(
                  permission_id="cp_zc4Q7MP6XxulcVzj4MZdwsAB",
                  fine_tuned_model_checkpoint="ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd",
              )
              print(permission.id)
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                permission, err := client.FineTuning.Checkpoints.Permissions.Delete(
                  context.TODO(),
                  "ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd",
                  "cp_zc4Q7MP6XxulcVzj4MZdwsAB",
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", permission.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.finetuning.checkpoints.permissions.PermissionDeleteParams;
              import com.openai.models.finetuning.checkpoints.permissions.PermissionDeleteResponse;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      PermissionDeleteParams params = PermissionDeleteParams.builder()
                          .fineTunedModelCheckpoint("ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd")
                          .permissionId("cp_zc4Q7MP6XxulcVzj4MZdwsAB")
                          .build();
                      PermissionDeleteResponse permission = client.fineTuning().checkpoints().permissions().delete(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.finetuning.checkpoints.permissions.PermissionDeleteParams
              import com.openai.models.finetuning.checkpoints.permissions.PermissionDeleteResponse

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: PermissionDeleteParams = PermissionDeleteParams.builder()
                      .fineTunedModelCheckpoint("ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd")
                      .permissionId("cp_zc4Q7MP6XxulcVzj4MZdwsAB")
                      .build()
                  val permission: PermissionDeleteResponse = client.fineTuning().checkpoints().permissions().delete(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              permission = openai.fine_tuning.checkpoints.permissions.delete(
                "cp_zc4Q7MP6XxulcVzj4MZdwsAB",
                fine_tuned_model_checkpoint: "ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd"
              )

              puts(permission)
  /fine_tuning/jobs:
    post:
      operationId: createFineTuningJob
      tags:
        - Fine-tuning
      summary: >
        Creates a fine-tuning job which begins the process of creating a new model from a given dataset.


        Response includes details of the enqueued job including job status and the name of the fine-tuned
        models once complete.


        [Learn more about fine-tuning](/docs/guides/model-optimization)
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateFineTuningJobRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/FineTuningJob'
      x-oaiMeta:
        name: Create fine-tuning job
        group: fine-tuning
        returns: A [fine-tuning.job](/docs/api-reference/fine-tuning/object) object.
        examples:
          - title: Default
            request:
              curl: |
                curl https://api.openai.com/v1/fine_tuning/jobs \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -d '{
                    "training_file": "file-BK7bzQj3FfZFXr7DbL6xJwfo",
                    "model": "gpt-4o-mini"
                  }'
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                fine_tuning_job = client.fine_tuning.jobs.create(
                    model="gpt-4o-mini",
                    training_file="file-abc123",
                )
                print(fine_tuning_job.id)
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const fineTuningJob = await client.fineTuning.jobs.create({
                  model: 'gpt-4o-mini',
                  training_file: 'file-abc123',
                });

                console.log(fineTuningJob.id);
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  fineTuningJob, err := client.FineTuning.Jobs.New(context.TODO(), openai.FineTuningJobNewParams{
                    Model: openai.FineTuningJobNewParamsModelBabbage002,
                    TrainingFile: "file-abc123",
                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", fineTuningJob.ID)
                }
              java: |-
                package com.openai.example;

                import com.openai.client.OpenAIClient;
                import com.openai.client.okhttp.OpenAIOkHttpClient;
                import com.openai.models.finetuning.jobs.FineTuningJob;
                import com.openai.models.finetuning.jobs.JobCreateParams;

                public final class Main {
                    private Main() {}

                    public static void main(String[] args) {
                        // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                        JobCreateParams params = JobCreateParams.builder()
                            .model(JobCreateParams.Model.BABBAGE_002)
                            .trainingFile("file-abc123")
                            .build();
                        FineTuningJob fineTuningJob = client.fineTuning().jobs().create(params);
                    }
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.finetuning.jobs.FineTuningJob
                import com.openai.models.finetuning.jobs.JobCreateParams

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val params: JobCreateParams = JobCreateParams.builder()
                        .model(JobCreateParams.Model.BABBAGE_002)
                        .trainingFile("file-abc123")
                        .build()
                    val fineTuningJob: FineTuningJob = client.fineTuning().jobs().create(params)
                }
              ruby: >-
                require "openai"


                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )


                fine_tuning_job = openai.fine_tuning.jobs.create(model: :"babbage-002", training_file:
                "file-abc123")


                puts(fine_tuning_job)
            response: |
              {
                "object": "fine_tuning.job",
                "id": "ftjob-abc123",
                "model": "gpt-4o-mini-2024-07-18",
                "created_at": 1721764800,
                "fine_tuned_model": null,
                "organization_id": "org-123",
                "result_files": [],
                "status": "queued",
                "validation_file": null,
                "training_file": "file-abc123",
                "method": {
                  "type": "supervised",
                  "supervised": {
                    "hyperparameters": {
                      "batch_size": "auto",
                      "learning_rate_multiplier": "auto",
                      "n_epochs": "auto",
                    }
                  }
                },
                "metadata": null
              }
          - title: Epochs
            request:
              curl: |
                curl https://api.openai.com/v1/fine_tuning/jobs \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -d '{
                    "training_file": "file-abc123",
                    "model": "gpt-4o-mini",
                    "method": {
                      "type": "supervised",
                      "supervised": {
                        "hyperparameters": {
                          "n_epochs": 2
                        }
                      }
                    }
                  }'
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                fine_tuning_job = client.fine_tuning.jobs.create(
                    model="gpt-4o-mini",
                    training_file="file-abc123",
                )
                print(fine_tuning_job.id)
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const fineTuningJob = await client.fineTuning.jobs.create({
                  model: 'gpt-4o-mini',
                  training_file: 'file-abc123',
                });

                console.log(fineTuningJob.id);
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  fineTuningJob, err := client.FineTuning.Jobs.New(context.TODO(), openai.FineTuningJobNewParams{
                    Model: openai.FineTuningJobNewParamsModelBabbage002,
                    TrainingFile: "file-abc123",
                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", fineTuningJob.ID)
                }
              java: |-
                package com.openai.example;

                import com.openai.client.OpenAIClient;
                import com.openai.client.okhttp.OpenAIOkHttpClient;
                import com.openai.models.finetuning.jobs.FineTuningJob;
                import com.openai.models.finetuning.jobs.JobCreateParams;

                public final class Main {
                    private Main() {}

                    public static void main(String[] args) {
                        // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                        JobCreateParams params = JobCreateParams.builder()
                            .model(JobCreateParams.Model.BABBAGE_002)
                            .trainingFile("file-abc123")
                            .build();
                        FineTuningJob fineTuningJob = client.fineTuning().jobs().create(params);
                    }
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.finetuning.jobs.FineTuningJob
                import com.openai.models.finetuning.jobs.JobCreateParams

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val params: JobCreateParams = JobCreateParams.builder()
                        .model(JobCreateParams.Model.BABBAGE_002)
                        .trainingFile("file-abc123")
                        .build()
                    val fineTuningJob: FineTuningJob = client.fineTuning().jobs().create(params)
                }
              ruby: >-
                require "openai"


                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )


                fine_tuning_job = openai.fine_tuning.jobs.create(model: :"babbage-002", training_file:
                "file-abc123")


                puts(fine_tuning_job)
            response: |
              {
                "object": "fine_tuning.job",
                "id": "ftjob-abc123",
                "model": "gpt-4o-mini",
                "created_at": 1721764800,
                "fine_tuned_model": null,
                "organization_id": "org-123",
                "result_files": [],
                "status": "queued",
                "validation_file": null,
                "training_file": "file-abc123",
                "hyperparameters": {
                  "batch_size": "auto",
                  "learning_rate_multiplier": "auto",
                  "n_epochs": 2
                },
                "method": {
                  "type": "supervised",
                  "supervised": {
                    "hyperparameters": {
                      "batch_size": "auto",
                      "learning_rate_multiplier": "auto",
                      "n_epochs": 2
                    }
                  }
                },
                "metadata": null,
                "error": {
                  "code": null,
                  "message": null,
                  "param": null
                },
                "finished_at": null,
                "seed": 683058546,
                "trained_tokens": null,
                "estimated_finish": null,
                "integrations": [],
                "user_provided_suffix": null,
                "usage_metrics": null,
                "shared_with_openai": false
              }
          - title: DPO
            request:
              curl: |
                curl https://api.openai.com/v1/fine_tuning/jobs \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -d '{
                    "training_file": "file-abc123",
                    "validation_file": "file-abc123",
                    "model": "gpt-4o-mini",
                    "method": {
                      "type": "dpo",
                      "dpo": {
                        "hyperparameters": {
                          "beta": 0.1
                        }
                      }
                    }
                  }'
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const fineTuningJob = await client.fineTuning.jobs.create({
                  model: 'gpt-4o-mini',
                  training_file: 'file-abc123',
                });

                console.log(fineTuningJob.id);
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                fine_tuning_job = client.fine_tuning.jobs.create(
                    model="gpt-4o-mini",
                    training_file="file-abc123",
                )
                print(fine_tuning_job.id)
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  fineTuningJob, err := client.FineTuning.Jobs.New(context.TODO(), openai.FineTuningJobNewParams{
                    Model: openai.FineTuningJobNewParamsModelBabbage002,
                    TrainingFile: "file-abc123",
                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", fineTuningJob.ID)
                }
              java: |-
                package com.openai.example;

                import com.openai.client.OpenAIClient;
                import com.openai.client.okhttp.OpenAIOkHttpClient;
                import com.openai.models.finetuning.jobs.FineTuningJob;
                import com.openai.models.finetuning.jobs.JobCreateParams;

                public final class Main {
                    private Main() {}

                    public static void main(String[] args) {
                        // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                        JobCreateParams params = JobCreateParams.builder()
                            .model(JobCreateParams.Model.BABBAGE_002)
                            .trainingFile("file-abc123")
                            .build();
                        FineTuningJob fineTuningJob = client.fineTuning().jobs().create(params);
                    }
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.finetuning.jobs.FineTuningJob
                import com.openai.models.finetuning.jobs.JobCreateParams

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val params: JobCreateParams = JobCreateParams.builder()
                        .model(JobCreateParams.Model.BABBAGE_002)
                        .trainingFile("file-abc123")
                        .build()
                    val fineTuningJob: FineTuningJob = client.fineTuning().jobs().create(params)
                }
              ruby: >-
                require "openai"


                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )


                fine_tuning_job = openai.fine_tuning.jobs.create(model: :"babbage-002", training_file:
                "file-abc123")


                puts(fine_tuning_job)
            python: |
              from openai import OpenAI
              from openai.types.fine_tuning import DpoMethod, DpoHyperparameters

              client = OpenAI()

              client.fine_tuning.jobs.create(
                training_file="file-abc",
                validation_file="file-123",
                model="gpt-4o-mini",
                method={
                  "type": "dpo",
                  "dpo": DpoMethod(
                    hyperparameters=DpoHyperparameters(beta=0.1)
                  )
                }
              )
            response: |
              {
                "object": "fine_tuning.job",
                "id": "ftjob-abc",
                "model": "gpt-4o-mini",
                "created_at": 1746130590,
                "fine_tuned_model": null,
                "organization_id": "org-abc",
                "result_files": [],
                "status": "queued",
                "validation_file": "file-123",
                "training_file": "file-abc",
                "method": {
                  "type": "dpo",
                  "dpo": {
                    "hyperparameters": {
                      "beta": 0.1,
                      "batch_size": "auto",
                      "learning_rate_multiplier": "auto",
                      "n_epochs": "auto"
                    }
                  }
                },
                "metadata": null,
                "error": {
                  "code": null,
                  "message": null,
                  "param": null
                },
                "finished_at": null,
                "hyperparameters": null,
                "seed": 1036326793,
                "estimated_finish": null,
                "integrations": [],
                "user_provided_suffix": null,
                "usage_metrics": null,
                "shared_with_openai": false
              }
          - title: Reinforcement
            request:
              curl: |
                curl https://api.openai.com/v1/fine_tuning/jobs \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -d '{
                    "training_file": "file-abc",
                    "validation_file": "file-123",
                    "model": "o4-mini",
                    "method": {
                      "type": "reinforcement",
                      "reinforcement": {
                        "grader": {
                          "type": "string_check",
                          "name": "Example string check grader",
                          "input": "{{sample.output_text}}",
                          "reference": "{{item.label}}",
                          "operation": "eq"
                        },
                        "hyperparameters": {
                          "reasoning_effort": "medium"
                        }
                      }
                    }
                  }'
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                fine_tuning_job = client.fine_tuning.jobs.create(
                    model="gpt-4o-mini",
                    training_file="file-abc123",
                )
                print(fine_tuning_job.id)
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const fineTuningJob = await client.fineTuning.jobs.create({
                  model: 'gpt-4o-mini',
                  training_file: 'file-abc123',
                });

                console.log(fineTuningJob.id);
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  fineTuningJob, err := client.FineTuning.Jobs.New(context.TODO(), openai.FineTuningJobNewParams{
                    Model: openai.FineTuningJobNewParamsModelBabbage002,
                    TrainingFile: "file-abc123",
                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", fineTuningJob.ID)
                }
              java: |-
                package com.openai.example;

                import com.openai.client.OpenAIClient;
                import com.openai.client.okhttp.OpenAIOkHttpClient;
                import com.openai.models.finetuning.jobs.FineTuningJob;
                import com.openai.models.finetuning.jobs.JobCreateParams;

                public final class Main {
                    private Main() {}

                    public static void main(String[] args) {
                        // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                        JobCreateParams params = JobCreateParams.builder()
                            .model(JobCreateParams.Model.BABBAGE_002)
                            .trainingFile("file-abc123")
                            .build();
                        FineTuningJob fineTuningJob = client.fineTuning().jobs().create(params);
                    }
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.finetuning.jobs.FineTuningJob
                import com.openai.models.finetuning.jobs.JobCreateParams

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val params: JobCreateParams = JobCreateParams.builder()
                        .model(JobCreateParams.Model.BABBAGE_002)
                        .trainingFile("file-abc123")
                        .build()
                    val fineTuningJob: FineTuningJob = client.fineTuning().jobs().create(params)
                }
              ruby: >-
                require "openai"


                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )


                fine_tuning_job = openai.fine_tuning.jobs.create(model: :"babbage-002", training_file:
                "file-abc123")


                puts(fine_tuning_job)
            response: |
              {
                "object": "fine_tuning.job",
                "id": "ftjob-abc123",
                "model": "o4-mini",
                "created_at": 1721764800,
                "finished_at": null,
                "fine_tuned_model": null,
                "organization_id": "org-123",
                "result_files": [],
                "status": "validating_files",
                "validation_file": "file-123",
                "training_file": "file-abc",
                "trained_tokens": null,
                "error": {},
                "user_provided_suffix": null,
                "seed": 950189191,
                "estimated_finish": null,
                "integrations": [],
                "method": {
                  "type": "reinforcement",
                  "reinforcement": {
                    "hyperparameters": {
                      "batch_size": "auto",
                      "learning_rate_multiplier": "auto",
                      "n_epochs": "auto",
                      "eval_interval": "auto",
                      "eval_samples": "auto",
                      "compute_multiplier": "auto",
                      "reasoning_effort": "medium"
                    },
                    "grader": {
                      "type": "string_check",
                      "name": "Example string check grader",
                      "input": "{{sample.output_text}}",
                      "reference": "{{item.label}}",
                      "operation": "eq"
                    },
                    "response_format": null
                  }
                },
                "metadata": null,
                "usage_metrics": null,
                "shared_with_openai": false
              }
                    
          - title: Validation file
            request:
              curl: |
                curl https://api.openai.com/v1/fine_tuning/jobs \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -d '{
                    "training_file": "file-abc123",
                    "validation_file": "file-abc123",
                    "model": "gpt-4o-mini"
                  }'
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                fine_tuning_job = client.fine_tuning.jobs.create(
                    model="gpt-4o-mini",
                    training_file="file-abc123",
                )
                print(fine_tuning_job.id)
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const fineTuningJob = await client.fineTuning.jobs.create({
                  model: 'gpt-4o-mini',
                  training_file: 'file-abc123',
                });

                console.log(fineTuningJob.id);
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  fineTuningJob, err := client.FineTuning.Jobs.New(context.TODO(), openai.FineTuningJobNewParams{
                    Model: openai.FineTuningJobNewParamsModelBabbage002,
                    TrainingFile: "file-abc123",
                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", fineTuningJob.ID)
                }
              java: |-
                package com.openai.example;

                import com.openai.client.OpenAIClient;
                import com.openai.client.okhttp.OpenAIOkHttpClient;
                import com.openai.models.finetuning.jobs.FineTuningJob;
                import com.openai.models.finetuning.jobs.JobCreateParams;

                public final class Main {
                    private Main() {}

                    public static void main(String[] args) {
                        // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                        JobCreateParams params = JobCreateParams.builder()
                            .model(JobCreateParams.Model.BABBAGE_002)
                            .trainingFile("file-abc123")
                            .build();
                        FineTuningJob fineTuningJob = client.fineTuning().jobs().create(params);
                    }
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.finetuning.jobs.FineTuningJob
                import com.openai.models.finetuning.jobs.JobCreateParams

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val params: JobCreateParams = JobCreateParams.builder()
                        .model(JobCreateParams.Model.BABBAGE_002)
                        .trainingFile("file-abc123")
                        .build()
                    val fineTuningJob: FineTuningJob = client.fineTuning().jobs().create(params)
                }
              ruby: >-
                require "openai"


                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )


                fine_tuning_job = openai.fine_tuning.jobs.create(model: :"babbage-002", training_file:
                "file-abc123")


                puts(fine_tuning_job)
            response: |
              {
                "object": "fine_tuning.job",
                "id": "ftjob-abc123",
                "model": "gpt-4o-mini-2024-07-18",
                "created_at": 1721764800,
                "fine_tuned_model": null,
                "organization_id": "org-123",
                "result_files": [],
                "status": "queued",
                "validation_file": "file-abc123",
                "training_file": "file-abc123",
                "method": {
                  "type": "supervised",
                  "supervised": {
                    "hyperparameters": {
                      "batch_size": "auto",
                      "learning_rate_multiplier": "auto",
                      "n_epochs": "auto",
                    }
                  }
                },
                "metadata": null
              }
          - title: W&B Integration
            request:
              curl: |
                curl https://api.openai.com/v1/fine_tuning/jobs \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -d '{
                    "training_file": "file-abc123",
                    "validation_file": "file-abc123",
                    "model": "gpt-4o-mini",
                    "integrations": [
                      {
                        "type": "wandb",
                        "wandb": {
                          "project": "my-wandb-project",
                          "name": "ft-run-display-name"
                          "tags": [
                            "first-experiment", "v2"
                          ]
                        }
                      }
                    ]
                  }'
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const fineTuningJob = await client.fineTuning.jobs.create({
                  model: 'gpt-4o-mini',
                  training_file: 'file-abc123',
                });

                console.log(fineTuningJob.id);
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                fine_tuning_job = client.fine_tuning.jobs.create(
                    model="gpt-4o-mini",
                    training_file="file-abc123",
                )
                print(fine_tuning_job.id)
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  fineTuningJob, err := client.FineTuning.Jobs.New(context.TODO(), openai.FineTuningJobNewParams{
                    Model: openai.FineTuningJobNewParamsModelBabbage002,
                    TrainingFile: "file-abc123",
                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", fineTuningJob.ID)
                }
              java: |-
                package com.openai.example;

                import com.openai.client.OpenAIClient;
                import com.openai.client.okhttp.OpenAIOkHttpClient;
                import com.openai.models.finetuning.jobs.FineTuningJob;
                import com.openai.models.finetuning.jobs.JobCreateParams;

                public final class Main {
                    private Main() {}

                    public static void main(String[] args) {
                        // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                        JobCreateParams params = JobCreateParams.builder()
                            .model(JobCreateParams.Model.BABBAGE_002)
                            .trainingFile("file-abc123")
                            .build();
                        FineTuningJob fineTuningJob = client.fineTuning().jobs().create(params);
                    }
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.finetuning.jobs.FineTuningJob
                import com.openai.models.finetuning.jobs.JobCreateParams

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val params: JobCreateParams = JobCreateParams.builder()
                        .model(JobCreateParams.Model.BABBAGE_002)
                        .trainingFile("file-abc123")
                        .build()
                    val fineTuningJob: FineTuningJob = client.fineTuning().jobs().create(params)
                }
              ruby: >-
                require "openai"


                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )


                fine_tuning_job = openai.fine_tuning.jobs.create(model: :"babbage-002", training_file:
                "file-abc123")


                puts(fine_tuning_job)
            response: |
              {
                "object": "fine_tuning.job",
                "id": "ftjob-abc123",
                "model": "gpt-4o-mini-2024-07-18",
                "created_at": 1721764800,
                "fine_tuned_model": null,
                "organization_id": "org-123",
                "result_files": [],
                "status": "queued",
                "validation_file": "file-abc123",
                "training_file": "file-abc123",
                "integrations": [
                  {
                    "type": "wandb",
                    "wandb": {
                      "project": "my-wandb-project",
                      "entity": None,
                      "run_id": "ftjob-abc123"
                    }
                  }
                ],
                "method": {
                  "type": "supervised",
                  "supervised": {
                    "hyperparameters": {
                      "batch_size": "auto",
                      "learning_rate_multiplier": "auto",
                      "n_epochs": "auto",
                    }
                  }
                },
                "metadata": null
              }
    get:
      operationId: listPaginatedFineTuningJobs
      tags:
        - Fine-tuning
      summary: |
        List your organization's fine-tuning jobs
      parameters:
        - name: after
          in: query
          description: Identifier for the last job from the previous pagination request.
          required: false
          schema:
            type: string
        - name: limit
          in: query
          description: Number of fine-tuning jobs to retrieve.
          required: false
          schema:
            type: integer
            default: 20
        - in: query
          name: metadata
          required: false
          schema:
            type: object
            nullable: true
            additionalProperties:
              type: string
          style: deepObject
          explode: true
          description: >
            Optional metadata filter. To filter, use the syntax `metadata[k]=v`. Alternatively, set
            `metadata=null` to indicate no metadata.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ListPaginatedFineTuningJobsResponse'
      x-oaiMeta:
        name: List fine-tuning jobs
        group: fine-tuning
        returns: A list of paginated [fine-tuning job](/docs/api-reference/fine-tuning/object) objects.
        examples:
          response: |
            {
              "object": "list",
              "data": [
                {
                  "object": "fine_tuning.job",
                  "id": "ftjob-abc123",
                  "model": "gpt-4o-mini-2024-07-18",
                  "created_at": 1721764800,
                  "fine_tuned_model": null,
                  "organization_id": "org-123",
                  "result_files": [],
                  "status": "queued",
                  "validation_file": null,
                  "training_file": "file-abc123",
                  "metadata": {
                    "key": "value"
                  }
                },
                { ... },
                { ... }
              ], "has_more": true
            }
          request:
            curl: |
              curl https://api.openai.com/v1/fine_tuning/jobs?limit=2&metadata[key]=value \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              page = client.fine_tuning.jobs.list()
              page = page.data[0]
              print(page.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              // Automatically fetches more pages as needed.
              for await (const fineTuningJob of client.fineTuning.jobs.list()) {
                console.log(fineTuningJob.id);
              }
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                page, err := client.FineTuning.Jobs.List(context.TODO(), openai.FineTuningJobListParams{

                })
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", page)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.finetuning.jobs.JobListPage;
              import com.openai.models.finetuning.jobs.JobListParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      JobListPage page = client.fineTuning().jobs().list();
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.finetuning.jobs.JobListPage
              import com.openai.models.finetuning.jobs.JobListParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val page: JobListPage = client.fineTuning().jobs().list()
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              page = openai.fine_tuning.jobs.list

              puts(page)
  /fine_tuning/jobs/{fine_tuning_job_id}:
    get:
      operationId: retrieveFineTuningJob
      tags:
        - Fine-tuning
      summary: |
        Get info about a fine-tuning job.

        [Learn more about fine-tuning](/docs/guides/model-optimization)
      parameters:
        - in: path
          name: fine_tuning_job_id
          required: true
          schema:
            type: string
            example: ft-AF1WoRqd3aJAHsqc9NY7iL8F
          description: |
            The ID of the fine-tuning job.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/FineTuningJob'
      x-oaiMeta:
        name: Retrieve fine-tuning job
        group: fine-tuning
        returns: The [fine-tuning](/docs/api-reference/fine-tuning/object) object with the given ID.
        examples:
          response: |
            {
              "object": "fine_tuning.job",
              "id": "ftjob-abc123",
              "model": "davinci-002",
              "created_at": 1692661014,
              "finished_at": 1692661190,
              "fine_tuned_model": "ft:davinci-002:my-org:custom_suffix:7q8mpxmy",
              "organization_id": "org-123",
              "result_files": [
                  "file-abc123"
              ],
              "status": "succeeded",
              "validation_file": null,
              "training_file": "file-abc123",
              "hyperparameters": {
                  "n_epochs": 4,
                  "batch_size": 1,
                  "learning_rate_multiplier": 1.0
              },
              "trained_tokens": 5768,
              "integrations": [],
              "seed": 0,
              "estimated_finish": 0,
              "method": {
                "type": "supervised",
                "supervised": {
                  "hyperparameters": {
                    "n_epochs": 4,
                    "batch_size": 1,
                    "learning_rate_multiplier": 1.0
                  }
                }
              }
            }
          request:
            curl: |
              curl https://api.openai.com/v1/fine_tuning/jobs/ft-AF1WoRqd3aJAHsqc9NY7iL8F \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              fine_tuning_job = client.fine_tuning.jobs.retrieve(
                  "ft-AF1WoRqd3aJAHsqc9NY7iL8F",
              )
              print(fine_tuning_job.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const fineTuningJob = await client.fineTuning.jobs.retrieve('ft-AF1WoRqd3aJAHsqc9NY7iL8F');

              console.log(fineTuningJob.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                fineTuningJob, err := client.FineTuning.Jobs.Get(context.TODO(), "ft-AF1WoRqd3aJAHsqc9NY7iL8F")
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", fineTuningJob.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.finetuning.jobs.FineTuningJob;
              import com.openai.models.finetuning.jobs.JobRetrieveParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      FineTuningJob fineTuningJob = client.fineTuning().jobs().retrieve("ft-AF1WoRqd3aJAHsqc9NY7iL8F");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.finetuning.jobs.FineTuningJob
              import com.openai.models.finetuning.jobs.JobRetrieveParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val fineTuningJob: FineTuningJob = client.fineTuning().jobs().retrieve("ft-AF1WoRqd3aJAHsqc9NY7iL8F")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              fine_tuning_job = openai.fine_tuning.jobs.retrieve("ft-AF1WoRqd3aJAHsqc9NY7iL8F")

              puts(fine_tuning_job)
  /fine_tuning/jobs/{fine_tuning_job_id}/cancel:
    post:
      operationId: cancelFineTuningJob
      tags:
        - Fine-tuning
      summary: |
        Immediately cancel a fine-tune job.
      parameters:
        - in: path
          name: fine_tuning_job_id
          required: true
          schema:
            type: string
            example: ft-AF1WoRqd3aJAHsqc9NY7iL8F
          description: |
            The ID of the fine-tuning job to cancel.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/FineTuningJob'
      x-oaiMeta:
        name: Cancel fine-tuning
        group: fine-tuning
        returns: The cancelled [fine-tuning](/docs/api-reference/fine-tuning/object) object.
        examples:
          response: |
            {
              "object": "fine_tuning.job",
              "id": "ftjob-abc123",
              "model": "gpt-4o-mini-2024-07-18",
              "created_at": 1721764800,
              "fine_tuned_model": null,
              "organization_id": "org-123",
              "result_files": [],
              "status": "cancelled",
              "validation_file": "file-abc123",
              "training_file": "file-abc123"
            }
          request:
            curl: |
              curl -X POST https://api.openai.com/v1/fine_tuning/jobs/ftjob-abc123/cancel \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              fine_tuning_job = client.fine_tuning.jobs.cancel(
                  "ft-AF1WoRqd3aJAHsqc9NY7iL8F",
              )
              print(fine_tuning_job.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const fineTuningJob = await client.fineTuning.jobs.cancel('ft-AF1WoRqd3aJAHsqc9NY7iL8F');

              console.log(fineTuningJob.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                fineTuningJob, err := client.FineTuning.Jobs.Cancel(context.TODO(), "ft-AF1WoRqd3aJAHsqc9NY7iL8F")
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", fineTuningJob.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.finetuning.jobs.FineTuningJob;
              import com.openai.models.finetuning.jobs.JobCancelParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      FineTuningJob fineTuningJob = client.fineTuning().jobs().cancel("ft-AF1WoRqd3aJAHsqc9NY7iL8F");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.finetuning.jobs.FineTuningJob
              import com.openai.models.finetuning.jobs.JobCancelParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val fineTuningJob: FineTuningJob = client.fineTuning().jobs().cancel("ft-AF1WoRqd3aJAHsqc9NY7iL8F")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              fine_tuning_job = openai.fine_tuning.jobs.cancel("ft-AF1WoRqd3aJAHsqc9NY7iL8F")

              puts(fine_tuning_job)
  /fine_tuning/jobs/{fine_tuning_job_id}/checkpoints:
    get:
      operationId: listFineTuningJobCheckpoints
      tags:
        - Fine-tuning
      summary: |
        List checkpoints for a fine-tuning job.
      parameters:
        - in: path
          name: fine_tuning_job_id
          required: true
          schema:
            type: string
            example: ft-AF1WoRqd3aJAHsqc9NY7iL8F
          description: |
            The ID of the fine-tuning job to get checkpoints for.
        - name: after
          in: query
          description: Identifier for the last checkpoint ID from the previous pagination request.
          required: false
          schema:
            type: string
        - name: limit
          in: query
          description: Number of checkpoints to retrieve.
          required: false
          schema:
            type: integer
            default: 10
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ListFineTuningJobCheckpointsResponse'
      x-oaiMeta:
        name: List fine-tuning checkpoints
        group: fine-tuning
        returns: >-
          A list of fine-tuning [checkpoint objects](/docs/api-reference/fine-tuning/checkpoint-object) for a
          fine-tuning job.
        examples:
          response: |
            {
              "object": "list"
              "data": [
                {
                  "object": "fine_tuning.job.checkpoint",
                  "id": "ftckpt_zc4Q7MP6XxulcVzj4MZdwsAB",
                  "created_at": 1721764867,
                  "fine_tuned_model_checkpoint": "ft:gpt-4o-mini-2024-07-18:my-org:custom-suffix:96olL566:ckpt-step-2000",
                  "metrics": {
                    "full_valid_loss": 0.134,
                    "full_valid_mean_token_accuracy": 0.874
                  },
                  "fine_tuning_job_id": "ftjob-abc123",
                  "step_number": 2000,
                },
                {
                  "object": "fine_tuning.job.checkpoint",
                  "id": "ftckpt_enQCFmOTGj3syEpYVhBRLTSy",
                  "created_at": 1721764800,
                  "fine_tuned_model_checkpoint": "ft:gpt-4o-mini-2024-07-18:my-org:custom-suffix:7q8mpxmy:ckpt-step-1000",
                  "metrics": {
                    "full_valid_loss": 0.167,
                    "full_valid_mean_token_accuracy": 0.781
                  },
                  "fine_tuning_job_id": "ftjob-abc123",
                  "step_number": 1000,
                },
              ],
              "first_id": "ftckpt_zc4Q7MP6XxulcVzj4MZdwsAB",
              "last_id": "ftckpt_enQCFmOTGj3syEpYVhBRLTSy",
              "has_more": true
            }
          request:
            curl: |
              curl https://api.openai.com/v1/fine_tuning/jobs/ftjob-abc123/checkpoints \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              // Automatically fetches more pages as needed.
              for await (const fineTuningJobCheckpoint of client.fineTuning.jobs.checkpoints.list(
                'ft-AF1WoRqd3aJAHsqc9NY7iL8F',
              )) {
                console.log(fineTuningJobCheckpoint.id);
              }
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              page = client.fine_tuning.jobs.checkpoints.list(
                  fine_tuning_job_id="ft-AF1WoRqd3aJAHsqc9NY7iL8F",
              )
              page = page.data[0]
              print(page.id)
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                page, err := client.FineTuning.Jobs.Checkpoints.List(
                  context.TODO(),
                  "ft-AF1WoRqd3aJAHsqc9NY7iL8F",
                  openai.FineTuningJobCheckpointListParams{

                  },
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", page)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.finetuning.jobs.checkpoints.CheckpointListPage;
              import com.openai.models.finetuning.jobs.checkpoints.CheckpointListParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      CheckpointListPage page = client.fineTuning().jobs().checkpoints().list("ft-AF1WoRqd3aJAHsqc9NY7iL8F");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.finetuning.jobs.checkpoints.CheckpointListPage
              import com.openai.models.finetuning.jobs.checkpoints.CheckpointListParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val page: CheckpointListPage = client.fineTuning().jobs().checkpoints().list("ft-AF1WoRqd3aJAHsqc9NY7iL8F")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              page = openai.fine_tuning.jobs.checkpoints.list("ft-AF1WoRqd3aJAHsqc9NY7iL8F")

              puts(page)
  /fine_tuning/jobs/{fine_tuning_job_id}/events:
    get:
      operationId: listFineTuningEvents
      tags:
        - Fine-tuning
      summary: |
        Get status updates for a fine-tuning job.
      parameters:
        - in: path
          name: fine_tuning_job_id
          required: true
          schema:
            type: string
            example: ft-AF1WoRqd3aJAHsqc9NY7iL8F
          description: |
            The ID of the fine-tuning job to get events for.
        - name: after
          in: query
          description: Identifier for the last event from the previous pagination request.
          required: false
          schema:
            type: string
        - name: limit
          in: query
          description: Number of events to retrieve.
          required: false
          schema:
            type: integer
            default: 20
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ListFineTuningJobEventsResponse'
      x-oaiMeta:
        name: List fine-tuning events
        group: fine-tuning
        returns: A list of fine-tuning event objects.
        examples:
          response: |
            {
              "object": "list",
              "data": [
                {
                  "object": "fine_tuning.job.event",
                  "id": "ft-event-ddTJfwuMVpfLXseO0Am0Gqjm",
                  "created_at": 1721764800,
                  "level": "info",
                  "message": "Fine tuning job successfully completed",
                  "data": null,
                  "type": "message"
                },
                {
                  "object": "fine_tuning.job.event",
                  "id": "ft-event-tyiGuB72evQncpH87xe505Sv",
                  "created_at": 1721764800,
                  "level": "info",
                  "message": "New fine-tuned model created: ft:gpt-4o-mini:openai::7p4lURel",
                  "data": null,
                  "type": "message"
                }
              ],
              "has_more": true
            }
          request:
            curl: |
              curl https://api.openai.com/v1/fine_tuning/jobs/ftjob-abc123/events \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              page = client.fine_tuning.jobs.list_events(
                  fine_tuning_job_id="ft-AF1WoRqd3aJAHsqc9NY7iL8F",
              )
              page = page.data[0]
              print(page.id)
            node.js: >-
              import OpenAI from 'openai';


              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });


              // Automatically fetches more pages as needed.

              for await (const fineTuningJobEvent of
              client.fineTuning.jobs.listEvents('ft-AF1WoRqd3aJAHsqc9NY7iL8F')) {
                console.log(fineTuningJobEvent.id);
              }
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                page, err := client.FineTuning.Jobs.ListEvents(
                  context.TODO(),
                  "ft-AF1WoRqd3aJAHsqc9NY7iL8F",
                  openai.FineTuningJobListEventsParams{

                  },
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", page)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.finetuning.jobs.JobListEventsPage;
              import com.openai.models.finetuning.jobs.JobListEventsParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      JobListEventsPage page = client.fineTuning().jobs().listEvents("ft-AF1WoRqd3aJAHsqc9NY7iL8F");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.finetuning.jobs.JobListEventsPage
              import com.openai.models.finetuning.jobs.JobListEventsParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val page: JobListEventsPage = client.fineTuning().jobs().listEvents("ft-AF1WoRqd3aJAHsqc9NY7iL8F")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              page = openai.fine_tuning.jobs.list_events("ft-AF1WoRqd3aJAHsqc9NY7iL8F")

              puts(page)
  /fine_tuning/jobs/{fine_tuning_job_id}/pause:
    post:
      operationId: pauseFineTuningJob
      tags:
        - Fine-tuning
      summary: |
        Pause a fine-tune job.
      parameters:
        - in: path
          name: fine_tuning_job_id
          required: true
          schema:
            type: string
            example: ft-AF1WoRqd3aJAHsqc9NY7iL8F
          description: |
            The ID of the fine-tuning job to pause.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/FineTuningJob'
      x-oaiMeta:
        name: Pause fine-tuning
        group: fine-tuning
        returns: The paused [fine-tuning](/docs/api-reference/fine-tuning/object) object.
        examples:
          response: |
            {
              "object": "fine_tuning.job",
              "id": "ftjob-abc123",
              "model": "gpt-4o-mini-2024-07-18",
              "created_at": 1721764800,
              "fine_tuned_model": null,
              "organization_id": "org-123",
              "result_files": [],
              "status": "paused",
              "validation_file": "file-abc123",
              "training_file": "file-abc123"
            }
          request:
            curl: |
              curl -X POST https://api.openai.com/v1/fine_tuning/jobs/ftjob-abc123/pause \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              fine_tuning_job = client.fine_tuning.jobs.pause(
                  "ft-AF1WoRqd3aJAHsqc9NY7iL8F",
              )
              print(fine_tuning_job.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const fineTuningJob = await client.fineTuning.jobs.pause('ft-AF1WoRqd3aJAHsqc9NY7iL8F');

              console.log(fineTuningJob.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                fineTuningJob, err := client.FineTuning.Jobs.Pause(context.TODO(), "ft-AF1WoRqd3aJAHsqc9NY7iL8F")
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", fineTuningJob.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.finetuning.jobs.FineTuningJob;
              import com.openai.models.finetuning.jobs.JobPauseParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      FineTuningJob fineTuningJob = client.fineTuning().jobs().pause("ft-AF1WoRqd3aJAHsqc9NY7iL8F");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.finetuning.jobs.FineTuningJob
              import com.openai.models.finetuning.jobs.JobPauseParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val fineTuningJob: FineTuningJob = client.fineTuning().jobs().pause("ft-AF1WoRqd3aJAHsqc9NY7iL8F")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              fine_tuning_job = openai.fine_tuning.jobs.pause("ft-AF1WoRqd3aJAHsqc9NY7iL8F")

              puts(fine_tuning_job)
  /fine_tuning/jobs/{fine_tuning_job_id}/resume:
    post:
      operationId: resumeFineTuningJob
      tags:
        - Fine-tuning
      summary: |
        Resume a fine-tune job.
      parameters:
        - in: path
          name: fine_tuning_job_id
          required: true
          schema:
            type: string
            example: ft-AF1WoRqd3aJAHsqc9NY7iL8F
          description: |
            The ID of the fine-tuning job to resume.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/FineTuningJob'
      x-oaiMeta:
        name: Resume fine-tuning
        group: fine-tuning
        returns: The resumed [fine-tuning](/docs/api-reference/fine-tuning/object) object.
        examples:
          response: |
            {
              "object": "fine_tuning.job",
              "id": "ftjob-abc123",
              "model": "gpt-4o-mini-2024-07-18",
              "created_at": 1721764800,
              "fine_tuned_model": null,
              "organization_id": "org-123",
              "result_files": [],
              "status": "queued",
              "validation_file": "file-abc123",
              "training_file": "file-abc123"
            }
          request:
            curl: |
              curl -X POST https://api.openai.com/v1/fine_tuning/jobs/ftjob-abc123/resume \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              fine_tuning_job = client.fine_tuning.jobs.resume(
                  "ft-AF1WoRqd3aJAHsqc9NY7iL8F",
              )
              print(fine_tuning_job.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const fineTuningJob = await client.fineTuning.jobs.resume('ft-AF1WoRqd3aJAHsqc9NY7iL8F');

              console.log(fineTuningJob.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                fineTuningJob, err := client.FineTuning.Jobs.Resume(context.TODO(), "ft-AF1WoRqd3aJAHsqc9NY7iL8F")
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", fineTuningJob.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.finetuning.jobs.FineTuningJob;
              import com.openai.models.finetuning.jobs.JobResumeParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      FineTuningJob fineTuningJob = client.fineTuning().jobs().resume("ft-AF1WoRqd3aJAHsqc9NY7iL8F");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.finetuning.jobs.FineTuningJob
              import com.openai.models.finetuning.jobs.JobResumeParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val fineTuningJob: FineTuningJob = client.fineTuning().jobs().resume("ft-AF1WoRqd3aJAHsqc9NY7iL8F")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              fine_tuning_job = openai.fine_tuning.jobs.resume("ft-AF1WoRqd3aJAHsqc9NY7iL8F")

              puts(fine_tuning_job)
  /images/edits:
    post:
      operationId: createImageEdit
      tags:
        - Images
      summary: >-
        Creates an edited or extended image given one or more source images and a prompt. This endpoint only
        supports `gpt-image-1` and `dall-e-2`.
      requestBody:
        required: true
        content:
          multipart/form-data:
            schema:
              $ref: '#/components/schemas/CreateImageEditRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ImagesResponse'
      x-oaiMeta:
        name: Create image edit
        group: images
        returns: Returns a list of [image](/docs/api-reference/images/object) objects.
        examples:
          response: |
            {
              "created": 1713833628,
              "data": [
                {
                  "b64_json": "..."
                }
              ],
              "usage": {
                "total_tokens": 100,
                "input_tokens": 50,
                "output_tokens": 50,
                "input_tokens_details": {
                  "text_tokens": 10,
                  "image_tokens": 40
                }
              }
            }
          request:
            curl: |
              curl -s -D >(grep -i x-request-id >&2) \
                -o >(jq -r '.data[0].b64_json' | base64 --decode > gift-basket.png) \
                -X POST "https://api.openai.com/v1/images/edits" \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -F "model=gpt-image-1" \
                -F "image[]=@body-lotion.png" \
                -F "image[]=@bath-bomb.png" \
                -F "image[]=@incense-kit.png" \
                -F "image[]=@soap.png" \
                -F 'prompt=Create a lovely gift basket with these four items in it'
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              images_response = client.images.edit(
                  image=b"raw file contents",
                  prompt="A cute baby sea otter wearing a beret",
              )
              print(images_response)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const imagesResponse = await client.images.edit({
                image: fs.createReadStream('path/to/file'),
                prompt: 'A cute baby sea otter wearing a beret',
              });

              console.log(imagesResponse);
            go: |
              package main

              import (
                "bytes"
                "context"
                "fmt"
                "io"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                imagesResponse, err := client.Images.Edit(context.TODO(), openai.ImageEditParams{
                  Image: openai.ImageEditParamsImageUnion{
                    OfFile: io.Reader(bytes.NewBuffer([]byte("some file contents"))),
                  },
                  Prompt: "A cute baby sea otter wearing a beret",
                })
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", imagesResponse)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.images.ImageEditParams;
              import com.openai.models.images.ImagesResponse;
              import java.io.ByteArrayInputStream;
              import java.io.InputStream;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      ImageEditParams params = ImageEditParams.builder()
                          .image(ByteArrayInputStream("some content".getBytes()))
                          .prompt("A cute baby sea otter wearing a beret")
                          .build();
                      ImagesResponse imagesResponse = client.images().edit(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.images.ImageEditParams
              import com.openai.models.images.ImagesResponse
              import java.io.ByteArrayInputStream
              import java.io.InputStream

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: ImageEditParams = ImageEditParams.builder()
                      .image("some content".byteInputStream())
                      .prompt("A cute baby sea otter wearing a beret")
                      .build()
                  val imagesResponse: ImagesResponse = client.images().edit(params)
              }
            ruby: >-
              require "openai"


              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )


              images_response = openai.images.edit(image: Pathname(__FILE__), prompt: "A cute baby sea otter
              wearing a beret")


              puts(images_response)
  /images/generations:
    post:
      operationId: createImage
      tags:
        - Images
      summary: |
        Creates an image given a prompt. [Learn more](/docs/guides/images).
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateImageRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ImagesResponse'
      x-oaiMeta:
        name: Create image
        group: images
        returns: Returns a list of [image](/docs/api-reference/images/object) objects.
        examples:
          response: |
            {
              "created": 1713833628,
              "data": [
                {
                  "b64_json": "..."
                }
              ],
              "usage": {
                "total_tokens": 100,
                "input_tokens": 50,
                "output_tokens": 50,
                "input_tokens_details": {
                  "text_tokens": 10,
                  "image_tokens": 40
                }
              }
            }
          request:
            curl: |
              curl https://api.openai.com/v1/images/generations \
                -H "Content-Type: application/json" \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -d '{
                  "model": "gpt-image-1",
                  "prompt": "A cute baby sea otter",
                  "n": 1,
                  "size": "1024x1024"
                }'
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              images_response = client.images.generate(
                  prompt="A cute baby sea otter",
              )
              print(images_response)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const imagesResponse = await client.images.generate({ prompt: 'A cute baby sea otter' });

              console.log(imagesResponse);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                imagesResponse, err := client.Images.Generate(context.TODO(), openai.ImageGenerateParams{
                  Prompt: "A cute baby sea otter",
                })
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", imagesResponse)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.images.ImageGenerateParams;
              import com.openai.models.images.ImagesResponse;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      ImageGenerateParams params = ImageGenerateParams.builder()
                          .prompt("A cute baby sea otter")
                          .build();
                      ImagesResponse imagesResponse = client.images().generate(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.images.ImageGenerateParams
              import com.openai.models.images.ImagesResponse

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: ImageGenerateParams = ImageGenerateParams.builder()
                      .prompt("A cute baby sea otter")
                      .build()
                  val imagesResponse: ImagesResponse = client.images().generate(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              images_response = openai.images.generate(prompt: "A cute baby sea otter")

              puts(images_response)
  /images/variations:
    post:
      operationId: createImageVariation
      tags:
        - Images
      summary: Creates a variation of a given image. This endpoint only supports `dall-e-2`.
      requestBody:
        required: true
        content:
          multipart/form-data:
            schema:
              $ref: '#/components/schemas/CreateImageVariationRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ImagesResponse'
      x-oaiMeta:
        name: Create image variation
        group: images
        returns: Returns a list of [image](/docs/api-reference/images/object) objects.
        examples:
          response: |
            {
              "created": 1589478378,
              "data": [
                {
                  "url": "https://..."
                },
                {
                  "url": "https://..."
                }
              ]
            }
          request:
            curl: |
              curl https://api.openai.com/v1/images/variations \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -F image="@otter.png" \
                -F n=2 \
                -F size="1024x1024"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              images_response = client.images.create_variation(
                  image=b"raw file contents",
              )
              print(images_response.created)
            node.js: >-
              import OpenAI from 'openai';


              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });


              const imagesResponse = await client.images.createVariation({ image:
              fs.createReadStream('otter.png') });


              console.log(imagesResponse.created);
            csharp: |
              using System;

              using OpenAI.Images;

              ImageClient client = new(
                  model: "dall-e-2",
                  apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
              );

              GeneratedImage image = client.GenerateImageVariation(imageFilePath: "otter.png");

              Console.WriteLine(image.ImageUri);
            go: |
              package main

              import (
                "bytes"
                "context"
                "fmt"
                "io"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                imagesResponse, err := client.Images.NewVariation(context.TODO(), openai.ImageNewVariationParams{
                  Image: io.Reader(bytes.NewBuffer([]byte("some file contents"))),
                })
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", imagesResponse.Created)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.images.ImageCreateVariationParams;
              import com.openai.models.images.ImagesResponse;
              import java.io.ByteArrayInputStream;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      ImageCreateVariationParams params = ImageCreateVariationParams.builder()
                          .image(ByteArrayInputStream("some content".getBytes()))
                          .build();
                      ImagesResponse imagesResponse = client.images().createVariation(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.images.ImageCreateVariationParams
              import com.openai.models.images.ImagesResponse
              import java.io.ByteArrayInputStream

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: ImageCreateVariationParams = ImageCreateVariationParams.builder()
                      .image("some content".byteInputStream())
                      .build()
                  val imagesResponse: ImagesResponse = client.images().createVariation(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              images_response = openai.images.create_variation(image: Pathname(__FILE__))

              puts(images_response)
  /models:
    get:
      operationId: listModels
      tags:
        - Models
      summary: >-
        Lists the currently available models, and provides basic information about each one such as the owner
        and availability.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ListModelsResponse'
      x-oaiMeta:
        name: List models
        group: models
        returns: A list of [model](/docs/api-reference/models/object) objects.
        examples:
          response: |
            {
              "object": "list",
              "data": [
                {
                  "id": "model-id-0",
                  "object": "model",
                  "created": 1686935002,
                  "owned_by": "organization-owner"
                },
                {
                  "id": "model-id-1",
                  "object": "model",
                  "created": 1686935002,
                  "owned_by": "organization-owner",
                },
                {
                  "id": "model-id-2",
                  "object": "model",
                  "created": 1686935002,
                  "owned_by": "openai"
                },
              ],
              "object": "list"
            }
          request:
            curl: |
              curl https://api.openai.com/v1/models \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              page = client.models.list()
              page = page.data[0]
              print(page.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              // Automatically fetches more pages as needed.
              for await (const model of client.models.list()) {
                console.log(model.id);
              }
            csharp: |
              using System;

              using OpenAI.Models;

              OpenAIModelClient client = new(
                  apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
              );

              foreach (var model in client.GetModels().Value)
              {
                  Console.WriteLine(model.Id);
              }
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                page, err := client.Models.List(context.TODO())
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", page)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.models.ModelListPage;
              import com.openai.models.models.ModelListParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      ModelListPage page = client.models().list();
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.models.ModelListPage
              import com.openai.models.models.ModelListParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val page: ModelListPage = client.models().list()
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              page = openai.models.list

              puts(page)
  /models/{model}:
    get:
      operationId: retrieveModel
      tags:
        - Models
      summary: >-
        Retrieves a model instance, providing basic information about the model such as the owner and
        permissioning.
      parameters:
        - in: path
          name: model
          required: true
          schema:
            type: string
            example: gpt-4o-mini
          description: The ID of the model to use for this request
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Model'
      x-oaiMeta:
        name: Retrieve model
        group: models
        returns: The [model](/docs/api-reference/models/object) object matching the specified ID.
        examples:
          response: |
            {
              "id": "VAR_chat_model_id",
              "object": "model",
              "created": 1686935002,
              "owned_by": "openai"
            }
          request:
            curl: |
              curl https://api.openai.com/v1/models/VAR_chat_model_id \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              model = client.models.retrieve(
                  "gpt-4o-mini",
              )
              print(model.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const model = await client.models.retrieve('gpt-4o-mini');

              console.log(model.id);
            csharp: |
              using System;
              using System.ClientModel;

              using OpenAI.Models;

                OpenAIModelClient client = new(
                  apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
              );

              ClientResult<OpenAIModel> model = client.GetModel("babbage-002");
              Console.WriteLine(model.Value.Id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                model, err := client.Models.Get(context.TODO(), "gpt-4o-mini")
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", model.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.models.Model;
              import com.openai.models.models.ModelRetrieveParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      Model model = client.models().retrieve("gpt-4o-mini");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.models.Model
              import com.openai.models.models.ModelRetrieveParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val model: Model = client.models().retrieve("gpt-4o-mini")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              model = openai.models.retrieve("gpt-4o-mini")

              puts(model)
    delete:
      operationId: deleteModel
      tags:
        - Models
      summary: Delete a fine-tuned model. You must have the Owner role in your organization to delete a model.
      parameters:
        - in: path
          name: model
          required: true
          schema:
            type: string
            example: ft:gpt-4o-mini:acemeco:suffix:abc123
          description: The model to delete
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/DeleteModelResponse'
      x-oaiMeta:
        name: Delete a fine-tuned model
        group: models
        returns: Deletion status.
        examples:
          response: |
            {
              "id": "ft:gpt-4o-mini:acemeco:suffix:abc123",
              "object": "model",
              "deleted": true
            }
          request:
            curl: |
              curl https://api.openai.com/v1/models/ft:gpt-4o-mini:acemeco:suffix:abc123 \
                -X DELETE \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              model_deleted = client.models.delete(
                  "ft:gpt-4o-mini:acemeco:suffix:abc123",
              )
              print(model_deleted.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const modelDeleted = await client.models.delete('ft:gpt-4o-mini:acemeco:suffix:abc123');

              console.log(modelDeleted.id);
            csharp: |
              using System;
              using System.ClientModel;

              using OpenAI.Models;

              OpenAIModelClient client = new(
                  apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
              );

              ClientResult success = client.DeleteModel("ft:gpt-4o-mini:acemeco:suffix:abc123");
              Console.WriteLine(success);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                modelDeleted, err := client.Models.Delete(context.TODO(), "ft:gpt-4o-mini:acemeco:suffix:abc123")
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", modelDeleted.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.models.ModelDeleteParams;
              import com.openai.models.models.ModelDeleted;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      ModelDeleted modelDeleted = client.models().delete("ft:gpt-4o-mini:acemeco:suffix:abc123");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.models.ModelDeleteParams
              import com.openai.models.models.ModelDeleted

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val modelDeleted: ModelDeleted = client.models().delete("ft:gpt-4o-mini:acemeco:suffix:abc123")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              model_deleted = openai.models.delete("ft:gpt-4o-mini:acemeco:suffix:abc123")

              puts(model_deleted)
  /moderations:
    post:
      operationId: createModeration
      tags:
        - Moderations
      summary: |
        Classifies if text and/or image inputs are potentially harmful. Learn
        more in the [moderation guide](/docs/guides/moderation).
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateModerationRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/CreateModerationResponse'
      x-oaiMeta:
        name: Create moderation
        group: moderations
        returns: A [moderation](/docs/api-reference/moderations/object) object.
        examples:
          - title: Single string
            request:
              curl: |
                curl https://api.openai.com/v1/moderations \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -d '{
                    "input": "I want to kill them."
                  }'
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                moderation = client.moderations.create(
                    input="I want to kill them.",
                )
                print(moderation.id)
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const moderation = await client.moderations.create({ input: 'I want to kill them.' });

                console.log(moderation.id);
              csharp: |
                using System;
                using System.ClientModel;

                using OpenAI.Moderations;

                ModerationClient client = new(
                    model: "omni-moderation-latest",
                    apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
                );

                ClientResult<ModerationResult> moderation = client.ClassifyText("I want to kill them.");
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  moderation, err := client.Moderations.New(context.TODO(), openai.ModerationNewParams{
                    Input: openai.ModerationNewParamsInputUnion{
                      OfString: openai.String("I want to kill them."),
                    },
                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", moderation.ID)
                }
              java: |-
                package com.openai.example;

                import com.openai.client.OpenAIClient;
                import com.openai.client.okhttp.OpenAIOkHttpClient;
                import com.openai.models.moderations.ModerationCreateParams;
                import com.openai.models.moderations.ModerationCreateResponse;

                public final class Main {
                    private Main() {}

                    public static void main(String[] args) {
                        // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                        ModerationCreateParams params = ModerationCreateParams.builder()
                            .input("I want to kill them.")
                            .build();
                        ModerationCreateResponse moderation = client.moderations().create(params);
                    }
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.moderations.ModerationCreateParams
                import com.openai.models.moderations.ModerationCreateResponse

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val params: ModerationCreateParams = ModerationCreateParams.builder()
                        .input("I want to kill them.")
                        .build()
                    val moderation: ModerationCreateResponse = client.moderations().create(params)
                }
              ruby: |-
                require "openai"

                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )

                moderation = openai.moderations.create(input: "I want to kill them.")

                puts(moderation)
            response: |
              {
                "id": "modr-AB8CjOTu2jiq12hp1AQPfeqFWaORR",
                "model": "text-moderation-007",
                "results": [
                  {
                    "flagged": true,
                    "categories": {
                      "sexual": false,
                      "hate": false,
                      "harassment": true,
                      "self-harm": false,
                      "sexual/minors": false,
                      "hate/threatening": false,
                      "violence/graphic": false,
                      "self-harm/intent": false,
                      "self-harm/instructions": false,
                      "harassment/threatening": true,
                      "violence": true
                    },
                    "category_scores": {
                      "sexual": 0.000011726012417057063,
                      "hate": 0.22706663608551025,
                      "harassment": 0.5215635299682617,
                      "self-harm": 2.227119921371923e-6,
                      "sexual/minors": 7.107352217872176e-8,
                      "hate/threatening": 0.023547329008579254,
                      "violence/graphic": 0.00003391829886822961,
                      "self-harm/intent": 1.646940972932498e-6,
                      "self-harm/instructions": 1.1198755256458526e-9,
                      "harassment/threatening": 0.5694745779037476,
                      "violence": 0.9971134662628174
                    }
                  }
                ]
              }
          - title: Image and text
            request:
              curl: |
                curl https://api.openai.com/v1/moderations \
                  -X POST \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -d '{
                    "model": "omni-moderation-latest",
                    "input": [
                      { "type": "text", "text": "...text to classify goes here..." },
                      {
                        "type": "image_url",
                        "image_url": {
                          "url": "https://example.com/image.png"
                        }
                      }
                    ]
                  }'
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                moderation = client.moderations.create(
                    input="I want to kill them.",
                )
                print(moderation.id)
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const moderation = await client.moderations.create({ input: 'I want to kill them.' });

                console.log(moderation.id);
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  moderation, err := client.Moderations.New(context.TODO(), openai.ModerationNewParams{
                    Input: openai.ModerationNewParamsInputUnion{
                      OfString: openai.String("I want to kill them."),
                    },
                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", moderation.ID)
                }
              java: |-
                package com.openai.example;

                import com.openai.client.OpenAIClient;
                import com.openai.client.okhttp.OpenAIOkHttpClient;
                import com.openai.models.moderations.ModerationCreateParams;
                import com.openai.models.moderations.ModerationCreateResponse;

                public final class Main {
                    private Main() {}

                    public static void main(String[] args) {
                        // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                        ModerationCreateParams params = ModerationCreateParams.builder()
                            .input("I want to kill them.")
                            .build();
                        ModerationCreateResponse moderation = client.moderations().create(params);
                    }
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.moderations.ModerationCreateParams
                import com.openai.models.moderations.ModerationCreateResponse

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val params: ModerationCreateParams = ModerationCreateParams.builder()
                        .input("I want to kill them.")
                        .build()
                    val moderation: ModerationCreateResponse = client.moderations().create(params)
                }
              ruby: |-
                require "openai"

                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )

                moderation = openai.moderations.create(input: "I want to kill them.")

                puts(moderation)
            response: |
              {
                "id": "modr-0d9740456c391e43c445bf0f010940c7",
                "model": "omni-moderation-latest",
                "results": [
                  {
                    "flagged": true,
                    "categories": {
                      "harassment": true,
                      "harassment/threatening": true,
                      "sexual": false,
                      "hate": false,
                      "hate/threatening": false,
                      "illicit": false,
                      "illicit/violent": false,
                      "self-harm/intent": false,
                      "self-harm/instructions": false,
                      "self-harm": false,
                      "sexual/minors": false,
                      "violence": true,
                      "violence/graphic": true
                    },
                    "category_scores": {
                      "harassment": 0.8189693396524255,
                      "harassment/threatening": 0.804985420696006,
                      "sexual": 1.573112165348997e-6,
                      "hate": 0.007562942636942845,
                      "hate/threatening": 0.004208854591835476,
                      "illicit": 0.030535955153511665,
                      "illicit/violent": 0.008925306722380033,
                      "self-harm/intent": 0.00023023930975076432,
                      "self-harm/instructions": 0.0002293869201073356,
                      "self-harm": 0.012598046106750154,
                      "sexual/minors": 2.212566909570261e-8,
                      "violence": 0.9999992735124786,
                      "violence/graphic": 0.843064871157054
                    },
                    "category_applied_input_types": {
                      "harassment": [
                        "text"
                      ],
                      "harassment/threatening": [
                        "text"
                      ],
                      "sexual": [
                        "text",
                        "image"
                      ],
                      "hate": [
                        "text"
                      ],
                      "hate/threatening": [
                        "text"
                      ],
                      "illicit": [
                        "text"
                      ],
                      "illicit/violent": [
                        "text"
                      ],
                      "self-harm/intent": [
                        "text",
                        "image"
                      ],
                      "self-harm/instructions": [
                        "text",
                        "image"
                      ],
                      "self-harm": [
                        "text",
                        "image"
                      ],
                      "sexual/minors": [
                        "text"
                      ],
                      "violence": [
                        "text",
                        "image"
                      ],
                      "violence/graphic": [
                        "text",
                        "image"
                      ]
                    }
                  }
                ]
              }
  /organization/admin_api_keys:
    get:
      summary: List organization API keys
      operationId: admin-api-keys-list
      description: Retrieve a paginated list of organization admin API keys.
      parameters:
        - in: query
          name: after
          required: false
          schema:
            type: string
            nullable: true
            description: Return keys with IDs that come after this ID in the pagination order.
        - in: query
          name: order
          required: false
          schema:
            type: string
            enum:
              - asc
              - desc
            default: asc
            description: Order results by creation time, ascending or descending.
        - in: query
          name: limit
          required: false
          schema:
            type: integer
            default: 20
            description: Maximum number of keys to return.
      responses:
        '200':
          description: A list of organization API keys.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ApiKeyList'
      x-oaiMeta:
        name: List all organization and project API keys.
        group: administration
        returns: A list of admin and project API key objects.
        examples:
          response: |
            {
              "object": "list",
              "data": [
                {
                  "object": "organization.admin_api_key",
                  "id": "key_abc",
                  "name": "Main Admin Key",
                  "redacted_value": "sk-admin...def",
                  "created_at": 1711471533,
                  "last_used_at": 1711471534,
                  "owner": {
                    "type": "service_account",
                    "object": "organization.service_account",
                    "id": "sa_456",
                    "name": "My Service Account",
                    "created_at": 1711471533,
                    "role": "member"
                  }
                }
              ],
              "first_id": "key_abc",
              "last_id": "key_abc",
              "has_more": false
            }
          request:
            curl: |
              curl https://api.openai.com/v1/organization/admin_api_keys?after=key_abc&limit=20 \
                -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
                -H "Content-Type: application/json"
    post:
      summary: Create an organization admin API key
      operationId: admin-api-keys-create
      description: Create a new admin-level API key for the organization.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              type: object
              required:
                - name
              properties:
                name:
                  type: string
                  example: New Admin Key
      responses:
        '200':
          description: The newly created admin API key.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/AdminApiKey'
      x-oaiMeta:
        name: Create admin API key
        group: administration
        returns: The created [AdminApiKey](/docs/api-reference/admin-api-keys/object) object.
        examples:
          response: |
            {
              "object": "organization.admin_api_key",
              "id": "key_xyz",
              "name": "New Admin Key",
              "redacted_value": "sk-admin...xyz",
              "created_at": 1711471533,
              "last_used_at": 1711471534,
              "owner": {
                "type": "user",
                "object": "organization.user",
                "id": "user_123",
                "name": "John Doe",
                "created_at": 1711471533,
                "role": "owner"
              },
              "value": "sk-admin-1234abcd"
            }
          request:
            curl: |
              curl -X POST https://api.openai.com/v1/organization/admin_api_keys \
                -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
                -H "Content-Type: application/json" \
                -d '{
                    "name": "New Admin Key"
                }'
  /organization/admin_api_keys/{key_id}:
    get:
      summary: Retrieve a single organization API key
      operationId: admin-api-keys-get
      description: Get details for a specific organization API key by its ID.
      parameters:
        - in: path
          name: key_id
          required: true
          schema:
            type: string
            description: The ID of the API key.
      responses:
        '200':
          description: Details of the requested API key.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/AdminApiKey'
      x-oaiMeta:
        name: Retrieve admin API key
        group: administration
        returns: The requested [AdminApiKey](/docs/api-reference/admin-api-keys/object) object.
        examples:
          response: |
            {
              "object": "organization.admin_api_key",
              "id": "key_abc",
              "name": "Main Admin Key",
              "redacted_value": "sk-admin...xyz",
              "created_at": 1711471533,
              "last_used_at": 1711471534,
              "owner": {
                "type": "user",
                "object": "organization.user",
                "id": "user_123",
                "name": "John Doe",
                "created_at": 1711471533,
                "role": "owner"
              }
            }
          request:
            curl: |
              curl https://api.openai.com/v1/organization/admin_api_keys/key_abc \
                -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
                -H "Content-Type: application/json"
    delete:
      summary: Delete an organization admin API key
      operationId: admin-api-keys-delete
      description: Delete the specified admin API key.
      parameters:
        - in: path
          name: key_id
          required: true
          schema:
            type: string
            description: The ID of the API key to be deleted.
      responses:
        '200':
          description: Confirmation that the API key was deleted.
          content:
            application/json:
              schema:
                type: object
                properties:
                  id:
                    type: string
                    example: key_abc
                  object:
                    type: string
                    example: organization.admin_api_key.deleted
                  deleted:
                    type: boolean
                    example: true
      x-oaiMeta:
        name: Delete admin API key
        group: administration
        returns: A confirmation object indicating the key was deleted.
        examples:
          response: |
            {
              "id": "key_abc",
              "object": "organization.admin_api_key.deleted",
              "deleted": true
            }
          request:
            curl: |
              curl -X DELETE https://api.openai.com/v1/organization/admin_api_keys/key_abc \
                -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
                -H "Content-Type: application/json"
  /organization/audit_logs:
    get:
      summary: List user actions and configuration changes within this organization.
      operationId: list-audit-logs
      tags:
        - Audit Logs
      parameters:
        - name: effective_at
          in: query
          description: Return only events whose `effective_at` (Unix seconds) is in this range.
          required: false
          schema:
            type: object
            properties:
              gt:
                type: integer
                description: Return only events whose `effective_at` (Unix seconds) is greater than this value.
              gte:
                type: integer
                description: >-
                  Return only events whose `effective_at` (Unix seconds) is greater than or equal to this
                  value.
              lt:
                type: integer
                description: Return only events whose `effective_at` (Unix seconds) is less than this value.
              lte:
                type: integer
                description: Return only events whose `effective_at` (Unix seconds) is less than or equal to this value.
        - name: project_ids[]
          in: query
          description: Return only events for these projects.
          required: false
          schema:
            type: array
            items:
              type: string
        - name: event_types[]
          in: query
          description: >-
            Return only events with a `type` in one of these values. For example, `project.created`. For all
            options, see the documentation for the [audit log object](/docs/api-reference/audit-logs/object).
          required: false
          schema:
            type: array
            items:
              $ref: '#/components/schemas/AuditLogEventType'
        - name: actor_ids[]
          in: query
          description: >-
            Return only events performed by these actors. Can be a user ID, a service account ID, or an api
            key tracking ID.
          required: false
          schema:
            type: array
            items:
              type: string
        - name: actor_emails[]
          in: query
          description: Return only events performed by users with these emails.
          required: false
          schema:
            type: array
            items:
              type: string
        - name: resource_ids[]
          in: query
          description: Return only events performed on these targets. For example, a project ID updated.
          required: false
          schema:
            type: array
            items:
              type: string
        - name: limit
          in: query
          description: >
            A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
            default is 20.
          required: false
          schema:
            type: integer
            default: 20
        - name: after
          in: query
          description: >
            A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
            instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
            call can include after=obj_foo in order to fetch the next page of the list.
          schema:
            type: string
        - name: before
          in: query
          description: >
            A cursor for use in pagination. `before` is an object ID that defines your place in the list. For
            instance, if you make a list request and receive 100 objects, starting with obj_foo, your
            subsequent call can include before=obj_foo in order to fetch the previous page of the list.
          schema:
            type: string
      responses:
        '200':
          description: Audit logs listed successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ListAuditLogsResponse'
      x-oaiMeta:
        name: List audit logs
        group: audit-logs
        returns: A list of paginated [Audit Log](/docs/api-reference/audit-logs/object) objects.
        examples:
          response: |
            {
                "object": "list",
                "data": [
                    {
                        "id": "audit_log-xxx_yyyymmdd",
                        "type": "project.archived",
                        "effective_at": 1722461446,
                        "actor": {
                            "type": "api_key",
                            "api_key": {
                                "type": "user",
                                "user": {
                                    "id": "user-xxx",
                                    "email": "user@example.com"
                                }
                            }
                        },
                        "project.archived": {
                            "id": "proj_abc"
                        },
                    },
                    {
                        "id": "audit_log-yyy__20240101",
                        "type": "api_key.updated",
                        "effective_at": 1720804190,
                        "actor": {
                            "type": "session",
                            "session": {
                                "user": {
                                    "id": "user-xxx",
                                    "email": "user@example.com"
                                },
                                "ip_address": "127.0.0.1",
                                "user_agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36",
                                "ja3": "a497151ce4338a12c4418c44d375173e",
                                "ja4": "q13d0313h3_55b375c5d22e_c7319ce65786",
                                "ip_address_details": {
                                  "country": "US",
                                  "city": "San Francisco",
                                  "region": "California",
                                  "region_code": "CA",
                                  "asn": "1234",
                                  "latitude": "37.77490",
                                  "longitude": "-122.41940"
                                }
                            }
                        },
                        "api_key.updated": {
                            "id": "key_xxxx",
                            "data": {
                                "scopes": ["resource_2.operation_2"]
                            }
                        },
                    }
                ],
                "first_id": "audit_log-xxx__20240101",
                "last_id": "audit_log_yyy__20240101",
                "has_more": true
            }
          request:
            curl: |
              curl https://api.openai.com/v1/organization/audit_logs \
              -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
              -H "Content-Type: application/json"
  /organization/certificates:
    get:
      summary: List uploaded certificates for this organization.
      operationId: listOrganizationCertificates
      tags:
        - Certificates
      parameters:
        - name: limit
          in: query
          description: >
            A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
            default is 20.
          required: false
          schema:
            type: integer
            default: 20
        - name: after
          in: query
          description: >
            A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
            instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
            call can include after=obj_foo in order to fetch the next page of the list.
          required: false
          schema:
            type: string
        - name: order
          in: query
          description: >
            Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for
            descending order.
          schema:
            type: string
            default: desc
            enum:
              - asc
              - desc
      responses:
        '200':
          description: Certificates listed successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ListCertificatesResponse'
      x-oaiMeta:
        name: List organization certificates
        group: administration
        returns: A list of [Certificate](/docs/api-reference/certificates/object) objects.
        examples:
          request:
            curl: |
              curl https://api.openai.com/v1/organization/certificates \
              -H "Authorization: Bearer $OPENAI_ADMIN_KEY"
          response: |
            {
              "object": "list",
              "data": [
                {
                  "object": "organization.certificate",
                  "id": "cert_abc",
                  "name": "My Example Certificate",
                  "active": true,
                  "created_at": 1234567,
                  "certificate_details": {
                    "valid_at": 12345667,
                    "expires_at": 12345678
                  }
                },
              ],
              "first_id": "cert_abc",
              "last_id": "cert_abc",
              "has_more": false
            }
    post:
      summary: |
        Upload a certificate to the organization. This does **not** automatically activate the certificate.

        Organizations can upload up to 50 certificates.
      operationId: uploadCertificate
      tags:
        - Certificates
      requestBody:
        description: The certificate upload payload.
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/UploadCertificateRequest'
      responses:
        '200':
          description: Certificate uploaded successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Certificate'
      x-oaiMeta:
        name: Upload certificate
        group: administration
        returns: A single [Certificate](/docs/api-reference/certificates/object) object.
        examples:
          request:
            curl: |
              curl -X POST https://api.openai.com/v1/organization/certificates \
              -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
              -H "Content-Type: application/json" \
              -d '{
                "name": "My Example Certificate",
                "certificate": "-----BEGIN CERTIFICATE-----\\nMIIDeT...\\n-----END CERTIFICATE-----"
              }'
          response: |
            {
              "object": "certificate",
              "id": "cert_abc",
              "name": "My Example Certificate",
              "created_at": 1234567,
              "certificate_details": {
                "valid_at": 12345667,
                "expires_at": 12345678
              }
            }
  /organization/certificates/activate:
    post:
      summary: |
        Activate certificates at the organization level.

        You can atomically and idempotently activate up to 10 certificates at a time.
      operationId: activateOrganizationCertificates
      tags:
        - Certificates
      requestBody:
        description: The certificate activation payload.
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/ToggleCertificatesRequest'
      responses:
        '200':
          description: Certificates activated successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ListCertificatesResponse'
      x-oaiMeta:
        name: Activate certificates for organization
        group: administration
        returns: A list of [Certificate](/docs/api-reference/certificates/object) objects that were activated.
        examples:
          request:
            curl: |
              curl https://api.openai.com/v1/organization/certificates/activate \
              -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
              -H "Content-Type: application/json" \
              -d '{
                "data": ["cert_abc", "cert_def"]
              }'
          response: |
            {
              "object": "organization.certificate.activation",
              "data": [
                {
                  "object": "organization.certificate",
                  "id": "cert_abc",
                  "name": "My Example Certificate",
                  "active": true,
                  "created_at": 1234567,
                  "certificate_details": {
                    "valid_at": 12345667,
                    "expires_at": 12345678
                  }
                },
                {
                  "object": "organization.certificate",
                  "id": "cert_def",
                  "name": "My Example Certificate 2",
                  "active": true,
                  "created_at": 1234567,
                  "certificate_details": {
                    "valid_at": 12345667,
                    "expires_at": 12345678
                  }
                },
              ],
            }
  /organization/certificates/deactivate:
    post:
      summary: |
        Deactivate certificates at the organization level.

        You can atomically and idempotently deactivate up to 10 certificates at a time.
      operationId: deactivateOrganizationCertificates
      tags:
        - Certificates
      requestBody:
        description: The certificate deactivation payload.
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/ToggleCertificatesRequest'
      responses:
        '200':
          description: Certificates deactivated successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ListCertificatesResponse'
      x-oaiMeta:
        name: Deactivate certificates for organization
        group: administration
        returns: A list of [Certificate](/docs/api-reference/certificates/object) objects that were deactivated.
        examples:
          request:
            curl: |
              curl https://api.openai.com/v1/organization/certificates/deactivate \
              -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
              -H "Content-Type: application/json" \
              -d '{
                "data": ["cert_abc", "cert_def"]
              }'
          response: |
            {
              "object": "organization.certificate.deactivation",
              "data": [
                {
                  "object": "organization.certificate",
                  "id": "cert_abc",
                  "name": "My Example Certificate",
                  "active": false,
                  "created_at": 1234567,
                  "certificate_details": {
                    "valid_at": 12345667,
                    "expires_at": 12345678
                  }
                },
                {
                  "object": "organization.certificate",
                  "id": "cert_def",
                  "name": "My Example Certificate 2",
                  "active": false,
                  "created_at": 1234567,
                  "certificate_details": {
                    "valid_at": 12345667,
                    "expires_at": 12345678
                  }
                },
              ],
            }
  /organization/certificates/{certificate_id}:
    get:
      summary: |
        Get a certificate that has been uploaded to the organization.

        You can get a certificate regardless of whether it is active or not.
      operationId: getCertificate
      tags:
        - Certificates
      parameters:
        - name: certificate_id
          in: path
          description: Unique ID of the certificate to retrieve.
          required: true
          schema:
            type: string
        - name: include
          in: query
          description: >-
            A list of additional fields to include in the response. Currently the only supported value is
            `content` to fetch the PEM content of the certificate.
          required: false
          schema:
            type: array
            items:
              type: string
              enum:
                - content
      responses:
        '200':
          description: Certificate retrieved successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Certificate'
      x-oaiMeta:
        name: Get certificate
        group: administration
        returns: A single [Certificate](/docs/api-reference/certificates/object) object.
        examples:
          request:
            curl: |
              curl "https://api.openai.com/v1/organization/certificates/cert_abc?include[]=content" \
              -H "Authorization: Bearer $OPENAI_ADMIN_KEY"
          response: |
            {
              "object": "certificate",
              "id": "cert_abc",
              "name": "My Example Certificate",
              "created_at": 1234567,
              "certificate_details": {
                "valid_at": 1234567,
                "expires_at": 12345678,
                "content": "-----BEGIN CERTIFICATE-----MIIDeT...-----END CERTIFICATE-----"
              }
            }
    post:
      summary: |
        Modify a certificate. Note that only the name can be modified.
      operationId: modifyCertificate
      tags:
        - Certificates
      requestBody:
        description: The certificate modification payload.
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/ModifyCertificateRequest'
      responses:
        '200':
          description: Certificate modified successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Certificate'
      x-oaiMeta:
        name: Modify certificate
        group: administration
        returns: The updated [Certificate](/docs/api-reference/certificates/object) object.
        examples:
          request:
            curl: |
              curl -X POST https://api.openai.com/v1/organization/certificates/cert_abc \
              -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
              -H "Content-Type: application/json" \
              -d '{
                "name": "Renamed Certificate"
              }'
          response: |
            {
              "object": "certificate",
              "id": "cert_abc",
              "name": "Renamed Certificate",
              "created_at": 1234567,
              "certificate_details": {
                "valid_at": 12345667,
                "expires_at": 12345678
              }
            }
    delete:
      summary: |
        Delete a certificate from the organization.

        The certificate must be inactive for the organization and all projects.
      operationId: deleteCertificate
      tags:
        - Certificates
      responses:
        '200':
          description: Certificate deleted successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/DeleteCertificateResponse'
      x-oaiMeta:
        name: Delete certificate
        group: administration
        returns: A confirmation object indicating the certificate was deleted.
        examples:
          request:
            curl: |
              curl -X DELETE https://api.openai.com/v1/organization/certificates/cert_abc \
              -H "Authorization: Bearer $OPENAI_ADMIN_KEY"
          response: |
            {
              "object": "certificate.deleted",
              "id": "cert_abc"
            }
  /organization/costs:
    get:
      summary: Get costs details for the organization.
      operationId: usage-costs
      tags:
        - Usage
      parameters:
        - name: start_time
          in: query
          description: Start time (Unix seconds) of the query time range, inclusive.
          required: true
          schema:
            type: integer
        - name: end_time
          in: query
          description: End time (Unix seconds) of the query time range, exclusive.
          required: false
          schema:
            type: integer
        - name: bucket_width
          in: query
          description: Width of each time bucket in response. Currently only `1d` is supported, default to `1d`.
          required: false
          schema:
            type: string
            enum:
              - 1d
            default: 1d
        - name: project_ids
          in: query
          description: Return only costs for these projects.
          required: false
          schema:
            type: array
            items:
              type: string
        - name: group_by
          in: query
          description: >-
            Group the costs by the specified fields. Support fields include `project_id`, `line_item` and any
            combination of them.
          required: false
          schema:
            type: array
            items:
              type: string
              enum:
                - project_id
                - line_item
        - name: limit
          in: query
          description: >
            A limit on the number of buckets to be returned. Limit can range between 1 and 180, and the
            default is 7.
          required: false
          schema:
            type: integer
            default: 7
        - name: page
          in: query
          description: A cursor for use in pagination. Corresponding to the `next_page` field from the previous response.
          schema:
            type: string
      responses:
        '200':
          description: Costs data retrieved successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/UsageResponse'
      x-oaiMeta:
        name: Costs
        group: usage-costs
        returns: A list of paginated, time bucketed [Costs](/docs/api-reference/usage/costs_object) objects.
        examples:
          response: |
            {
                "object": "page",
                "data": [
                    {
                        "object": "bucket",
                        "start_time": 1730419200,
                        "end_time": 1730505600,
                        "results": [
                            {
                                "object": "organization.costs.result",
                                "amount": {
                                    "value": 0.06,
                                    "currency": "usd"
                                },
                                "line_item": null,
                                "project_id": null
                            }
                        ]
                    }
                ],
                "has_more": false,
                "next_page": null
            }
          request:
            curl: |
              curl "https://api.openai.com/v1/organization/costs?start_time=1730419200&limit=1" \
              -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
              -H "Content-Type: application/json"
  /organization/invites:
    get:
      summary: Returns a list of invites in the organization.
      operationId: list-invites
      tags:
        - Invites
      parameters:
        - name: limit
          in: query
          description: >
            A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
            default is 20.
          required: false
          schema:
            type: integer
            default: 20
        - name: after
          in: query
          description: >
            A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
            instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
            call can include after=obj_foo in order to fetch the next page of the list.
          required: false
          schema:
            type: string
      responses:
        '200':
          description: Invites listed successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/InviteListResponse'
      x-oaiMeta:
        name: List invites
        group: administration
        returns: A list of [Invite](/docs/api-reference/invite/object) objects.
        examples:
          response: |
            {
              "object": "list",
              "data": [
                {
                  "object": "organization.invite",
                  "id": "invite-abc",
                  "email": "user@example.com",
                  "role": "owner",
                  "status": "accepted",
                  "invited_at": 1711471533,
                  "expires_at": 1711471533,
                  "accepted_at": 1711471533
                }
              ],
              "first_id": "invite-abc",
              "last_id": "invite-abc",
              "has_more": false
            }
          request:
            curl: |
              curl https://api.openai.com/v1/organization/invites?after=invite-abc&limit=20 \
                -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
                -H "Content-Type: application/json"
    post:
      summary: >-
        Create an invite for a user to the organization. The invite must be accepted by the user before they
        have access to the organization.
      operationId: inviteUser
      tags:
        - Invites
      requestBody:
        description: The invite request payload.
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/InviteRequest'
      responses:
        '200':
          description: User invited successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Invite'
      x-oaiMeta:
        name: Create invite
        group: administration
        returns: The created [Invite](/docs/api-reference/invite/object) object.
        examples:
          response: |
            {
              "object": "organization.invite",
              "id": "invite-def",
              "email": "anotheruser@example.com",
              "role": "reader",
              "status": "pending",
              "invited_at": 1711471533,
              "expires_at": 1711471533,
              "accepted_at": null,
              "projects": [
                {
                  "id": "project-xyz",
                  "role": "member"
                },
                {
                  "id": "project-abc",
                  "role": "owner"
                }
              ]
            }
          request:
            curl: |
              curl -X POST https://api.openai.com/v1/organization/invites \
                -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
                -H "Content-Type: application/json" \
                -d '{
                    "email": "anotheruser@example.com",
                    "role": "reader",
                    "projects": [
                      {
                        "id": "project-xyz",
                        "role": "member"
                      },
                      {
                        "id": "project-abc",
                        "role": "owner"
                      }
                    ]
                }'
  /organization/invites/{invite_id}:
    get:
      summary: Retrieves an invite.
      operationId: retrieve-invite
      tags:
        - Invites
      parameters:
        - in: path
          name: invite_id
          required: true
          schema:
            type: string
          description: The ID of the invite to retrieve.
      responses:
        '200':
          description: Invite retrieved successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Invite'
      x-oaiMeta:
        name: Retrieve invite
        group: administration
        returns: The [Invite](/docs/api-reference/invite/object) object matching the specified ID.
        examples:
          response: |
            {
                "object": "organization.invite",
                "id": "invite-abc",
                "email": "user@example.com",
                "role": "owner",
                "status": "accepted",
                "invited_at": 1711471533,
                "expires_at": 1711471533,
                "accepted_at": 1711471533
            }
          request:
            curl: |
              curl https://api.openai.com/v1/organization/invites/invite-abc \
                -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
                -H "Content-Type: application/json"
    delete:
      summary: Delete an invite. If the invite has already been accepted, it cannot be deleted.
      operationId: delete-invite
      tags:
        - Invites
      parameters:
        - in: path
          name: invite_id
          required: true
          schema:
            type: string
          description: The ID of the invite to delete.
      responses:
        '200':
          description: Invite deleted successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/InviteDeleteResponse'
      x-oaiMeta:
        name: Delete invite
        group: administration
        returns: Confirmation that the invite has been deleted
        examples:
          response: |
            {
                "object": "organization.invite.deleted",
                "id": "invite-abc",
                "deleted": true
            }
          request:
            curl: |
              curl -X DELETE https://api.openai.com/v1/organization/invites/invite-abc \
                -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
                -H "Content-Type: application/json"
  /organization/projects:
    get:
      summary: Returns a list of projects.
      operationId: list-projects
      tags:
        - Projects
      parameters:
        - name: limit
          in: query
          description: >
            A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
            default is 20.
          required: false
          schema:
            type: integer
            default: 20
        - name: after
          in: query
          description: >
            A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
            instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
            call can include after=obj_foo in order to fetch the next page of the list.
          required: false
          schema:
            type: string
        - name: include_archived
          in: query
          schema:
            type: boolean
            default: false
          description: >-
            If `true` returns all projects including those that have been `archived`. Archived projects are
            not included by default.
      responses:
        '200':
          description: Projects listed successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ProjectListResponse'
      x-oaiMeta:
        name: List projects
        group: administration
        returns: A list of [Project](/docs/api-reference/projects/object) objects.
        examples:
          response: |
            {
                "object": "list",
                "data": [
                    {
                        "id": "proj_abc",
                        "object": "organization.project",
                        "name": "Project example",
                        "created_at": 1711471533,
                        "archived_at": null,
                        "status": "active"
                    }
                ],
                "first_id": "proj-abc",
                "last_id": "proj-xyz",
                "has_more": false
            }
          request:
            curl: >
              curl
              https://api.openai.com/v1/organization/projects?after=proj_abc&limit=20&include_archived=false \
                -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
                -H "Content-Type: application/json"
    post:
      summary: Create a new project in the organization. Projects can be created and archived, but cannot be deleted.
      operationId: create-project
      tags:
        - Projects
      requestBody:
        description: The project create request payload.
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/ProjectCreateRequest'
      responses:
        '200':
          description: Project created successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Project'
      x-oaiMeta:
        name: Create project
        group: administration
        returns: The created [Project](/docs/api-reference/projects/object) object.
        examples:
          response: |
            {
                "id": "proj_abc",
                "object": "organization.project",
                "name": "Project ABC",
                "created_at": 1711471533,
                "archived_at": null,
                "status": "active"
            }
          request:
            curl: |
              curl -X POST https://api.openai.com/v1/organization/projects \
                -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
                -H "Content-Type: application/json" \
                -d '{
                    "name": "Project ABC"
                }'
  /organization/projects/{project_id}:
    get:
      summary: Retrieves a project.
      operationId: retrieve-project
      tags:
        - Projects
      parameters:
        - name: project_id
          in: path
          description: The ID of the project.
          required: true
          schema:
            type: string
      responses:
        '200':
          description: Project retrieved successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Project'
      x-oaiMeta:
        name: Retrieve project
        group: administration
        description: Retrieve a project.
        returns: The [Project](/docs/api-reference/projects/object) object matching the specified ID.
        examples:
          response: |
            {
                "id": "proj_abc",
                "object": "organization.project",
                "name": "Project example",
                "created_at": 1711471533,
                "archived_at": null,
                "status": "active"
            }
          request:
            curl: |
              curl https://api.openai.com/v1/organization/projects/proj_abc \
                -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
                -H "Content-Type: application/json"
    post:
      summary: Modifies a project in the organization.
      operationId: modify-project
      tags:
        - Projects
      parameters:
        - name: project_id
          in: path
          description: The ID of the project.
          required: true
          schema:
            type: string
      requestBody:
        description: The project update request payload.
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/ProjectUpdateRequest'
      responses:
        '200':
          description: Project updated successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Project'
        '400':
          description: Error response when updating the default project.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ErrorResponse'
      x-oaiMeta:
        name: Modify project
        group: administration
        returns: The updated [Project](/docs/api-reference/projects/object) object.
        examples:
          response: ''
          request:
            curl: |
              curl -X POST https://api.openai.com/v1/organization/projects/proj_abc \
                -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
                -H "Content-Type: application/json" \
                -d '{
                    "name": "Project DEF"
                }'
  /organization/projects/{project_id}/api_keys:
    get:
      summary: Returns a list of API keys in the project.
      operationId: list-project-api-keys
      tags:
        - Projects
      parameters:
        - name: project_id
          in: path
          description: The ID of the project.
          required: true
          schema:
            type: string
        - name: limit
          in: query
          description: >
            A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
            default is 20.
          required: false
          schema:
            type: integer
            default: 20
        - name: after
          in: query
          description: >
            A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
            instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
            call can include after=obj_foo in order to fetch the next page of the list.
          required: false
          schema:
            type: string
      responses:
        '200':
          description: Project API keys listed successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ProjectApiKeyListResponse'
      x-oaiMeta:
        name: List project API keys
        group: administration
        returns: A list of [ProjectApiKey](/docs/api-reference/project-api-keys/object) objects.
        examples:
          response: |
            {
                "object": "list",
                "data": [
                    {
                        "object": "organization.project.api_key",
                        "redacted_value": "sk-abc...def",
                        "name": "My API Key",
                        "created_at": 1711471533,
                        "last_used_at": 1711471534,
                        "id": "key_abc",
                        "owner": {
                            "type": "user",
                            "user": {
                                "object": "organization.project.user",
                                "id": "user_abc",
                                "name": "First Last",
                                "email": "user@example.com",
                                "role": "owner",
                                "added_at": 1711471533
                            }
                        }
                    }
                ],
                "first_id": "key_abc",
                "last_id": "key_xyz",
                "has_more": false
            }
          request:
            curl: |
              curl https://api.openai.com/v1/organization/projects/proj_abc/api_keys?after=key_abc&limit=20 \
                -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
                -H "Content-Type: application/json"
  /organization/projects/{project_id}/api_keys/{key_id}:
    get:
      summary: Retrieves an API key in the project.
      operationId: retrieve-project-api-key
      tags:
        - Projects
      parameters:
        - name: project_id
          in: path
          description: The ID of the project.
          required: true
          schema:
            type: string
        - name: key_id
          in: path
          description: The ID of the API key.
          required: true
          schema:
            type: string
      responses:
        '200':
          description: Project API key retrieved successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ProjectApiKey'
      x-oaiMeta:
        name: Retrieve project API key
        group: administration
        returns: The [ProjectApiKey](/docs/api-reference/project-api-keys/object) object matching the specified ID.
        examples:
          response: |
            {
                "object": "organization.project.api_key",
                "redacted_value": "sk-abc...def",
                "name": "My API Key",
                "created_at": 1711471533,
                "last_used_at": 1711471534,
                "id": "key_abc",
                "owner": {
                    "type": "user",
                    "user": {
                        "object": "organization.project.user",
                        "id": "user_abc",
                        "name": "First Last",
                        "email": "user@example.com",
                        "role": "owner",
                        "added_at": 1711471533
                    }
                }
            }
          request:
            curl: |
              curl https://api.openai.com/v1/organization/projects/proj_abc/api_keys/key_abc \
                -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
                -H "Content-Type: application/json"
    delete:
      summary: Deletes an API key from the project.
      operationId: delete-project-api-key
      tags:
        - Projects
      parameters:
        - name: project_id
          in: path
          description: The ID of the project.
          required: true
          schema:
            type: string
        - name: key_id
          in: path
          description: The ID of the API key.
          required: true
          schema:
            type: string
      responses:
        '200':
          description: Project API key deleted successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ProjectApiKeyDeleteResponse'
        '400':
          description: Error response for various conditions.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ErrorResponse'
      x-oaiMeta:
        name: Delete project API key
        group: administration
        returns: Confirmation of the key's deletion or an error if the key belonged to a service account
        examples:
          response: |
            {
                "object": "organization.project.api_key.deleted",
                "id": "key_abc",
                "deleted": true
            }
          request:
            curl: |
              curl -X DELETE https://api.openai.com/v1/organization/projects/proj_abc/api_keys/key_abc \
                -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
                -H "Content-Type: application/json"
  /organization/projects/{project_id}/archive:
    post:
      summary: Archives a project in the organization. Archived projects cannot be used or updated.
      operationId: archive-project
      tags:
        - Projects
      parameters:
        - name: project_id
          in: path
          description: The ID of the project.
          required: true
          schema:
            type: string
      responses:
        '200':
          description: Project archived successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Project'
      x-oaiMeta:
        name: Archive project
        group: administration
        returns: The archived [Project](/docs/api-reference/projects/object) object.
        examples:
          response: |
            {
                "id": "proj_abc",
                "object": "organization.project",
                "name": "Project DEF",
                "created_at": 1711471533,
                "archived_at": 1711471533,
                "status": "archived"
            }
          request:
            curl: |
              curl -X POST https://api.openai.com/v1/organization/projects/proj_abc/archive \
                -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
                -H "Content-Type: application/json"
  /organization/projects/{project_id}/certificates:
    get:
      summary: List certificates for this project.
      operationId: listProjectCertificates
      tags:
        - Certificates
      parameters:
        - name: project_id
          in: path
          description: The ID of the project.
          required: true
          schema:
            type: string
        - name: limit
          in: query
          description: >
            A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
            default is 20.
          required: false
          schema:
            type: integer
            default: 20
        - name: after
          in: query
          description: >
            A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
            instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
            call can include after=obj_foo in order to fetch the next page of the list.
          required: false
          schema:
            type: string
        - name: order
          in: query
          description: >
            Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for
            descending order.
          schema:
            type: string
            default: desc
            enum:
              - asc
              - desc
      responses:
        '200':
          description: Certificates listed successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ListCertificatesResponse'
      x-oaiMeta:
        name: List project certificates
        group: administration
        returns: A list of [Certificate](/docs/api-reference/certificates/object) objects.
        examples:
          request:
            curl: |
              curl https://api.openai.com/v1/organization/projects/proj_abc/certificates \
              -H "Authorization: Bearer $OPENAI_ADMIN_KEY"
          response: |
            {
              "object": "list",
              "data": [
                {
                  "object": "organization.project.certificate",
                  "id": "cert_abc",
                  "name": "My Example Certificate",
                  "active": true,
                  "created_at": 1234567,
                  "certificate_details": {
                    "valid_at": 12345667,
                    "expires_at": 12345678
                  }
                },
              ],
              "first_id": "cert_abc",
              "last_id": "cert_abc",
              "has_more": false
            }
  /organization/projects/{project_id}/certificates/activate:
    post:
      summary: |
        Activate certificates at the project level.

        You can atomically and idempotently activate up to 10 certificates at a time.
      operationId: activateProjectCertificates
      tags:
        - Certificates
      parameters:
        - name: project_id
          in: path
          description: The ID of the project.
          required: true
          schema:
            type: string
      requestBody:
        description: The certificate activation payload.
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/ToggleCertificatesRequest'
      responses:
        '200':
          description: Certificates activated successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ListCertificatesResponse'
      x-oaiMeta:
        name: Activate certificates for project
        group: administration
        returns: A list of [Certificate](/docs/api-reference/certificates/object) objects that were activated.
        examples:
          request:
            curl: |
              curl https://api.openai.com/v1/organization/projects/proj_abc/certificates/activate \
              -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
              -H "Content-Type: application/json" \
              -d '{
                "data": ["cert_abc", "cert_def"]
              }'
          response: |
            {
              "object": "organization.project.certificate.activation",
              "data": [
                {
                  "object": "organization.project.certificate",
                  "id": "cert_abc",
                  "name": "My Example Certificate",
                  "active": true,
                  "created_at": 1234567,
                  "certificate_details": {
                    "valid_at": 12345667,
                    "expires_at": 12345678
                  }
                },
                {
                  "object": "organization.project.certificate",
                  "id": "cert_def",
                  "name": "My Example Certificate 2",
                  "active": true,
                  "created_at": 1234567,
                  "certificate_details": {
                    "valid_at": 12345667,
                    "expires_at": 12345678
                  }
                },
              ],
            }
  /organization/projects/{project_id}/certificates/deactivate:
    post:
      summary: |
        Deactivate certificates at the project level. You can atomically and 
        idempotently deactivate up to 10 certificates at a time.
      operationId: deactivateProjectCertificates
      tags:
        - Certificates
      parameters:
        - name: project_id
          in: path
          description: The ID of the project.
          required: true
          schema:
            type: string
      requestBody:
        description: The certificate deactivation payload.
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/ToggleCertificatesRequest'
      responses:
        '200':
          description: Certificates deactivated successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ListCertificatesResponse'
      x-oaiMeta:
        name: Deactivate certificates for project
        group: administration
        returns: A list of [Certificate](/docs/api-reference/certificates/object) objects that were deactivated.
        examples:
          request:
            curl: |
              curl https://api.openai.com/v1/organization/projects/proj_abc/certificates/deactivate \
              -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
              -H "Content-Type: application/json" \
              -d '{
                "data": ["cert_abc", "cert_def"]
              }'
          response: |
            {
              "object": "organization.project.certificate.deactivation",
              "data": [
                {
                  "object": "organization.project.certificate",
                  "id": "cert_abc",
                  "name": "My Example Certificate",
                  "active": false,
                  "created_at": 1234567,
                  "certificate_details": {
                    "valid_at": 12345667,
                    "expires_at": 12345678
                  }
                },
                {
                  "object": "organization.project.certificate",
                  "id": "cert_def",
                  "name": "My Example Certificate 2",
                  "active": false,
                  "created_at": 1234567,
                  "certificate_details": {
                    "valid_at": 12345667,
                    "expires_at": 12345678
                  }
                },
              ],
            }
  /organization/projects/{project_id}/rate_limits:
    get:
      summary: Returns the rate limits per model for a project.
      operationId: list-project-rate-limits
      tags:
        - Projects
      parameters:
        - name: project_id
          in: path
          description: The ID of the project.
          required: true
          schema:
            type: string
        - name: limit
          in: query
          description: |
            A limit on the number of objects to be returned. The default is 100.
          required: false
          schema:
            type: integer
            default: 100
        - name: after
          in: query
          description: >
            A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
            instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
            call can include after=obj_foo in order to fetch the next page of the list.
          required: false
          schema:
            type: string
        - name: before
          in: query
          description: >
            A cursor for use in pagination. `before` is an object ID that defines your place in the list. For
            instance, if you make a list request and receive 100 objects, beginning with obj_foo, your
            subsequent call can include before=obj_foo in order to fetch the previous page of the list.
          required: false
          schema:
            type: string
      responses:
        '200':
          description: Project rate limits listed successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ProjectRateLimitListResponse'
      x-oaiMeta:
        name: List project rate limits
        group: administration
        returns: A list of [ProjectRateLimit](/docs/api-reference/project-rate-limits/object) objects.
        examples:
          response: |
            {
                "object": "list",
                "data": [
                    {
                      "object": "project.rate_limit",
                      "id": "rl-ada",
                      "model": "ada",
                      "max_requests_per_1_minute": 600,
                      "max_tokens_per_1_minute": 150000,
                      "max_images_per_1_minute": 10
                    }
                ],
                "first_id": "rl-ada",
                "last_id": "rl-ada",
                "has_more": false
            }
          request:
            curl: >
              curl https://api.openai.com/v1/organization/projects/proj_abc/rate_limits?after=rl_xxx&limit=20
              \
                -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
                -H "Content-Type: application/json"
          error_response: |
            {
                "code": 404,
                "message": "The project {project_id} was not found"
            }
  /organization/projects/{project_id}/rate_limits/{rate_limit_id}:
    post:
      summary: Updates a project rate limit.
      operationId: update-project-rate-limits
      tags:
        - Projects
      parameters:
        - name: project_id
          in: path
          description: The ID of the project.
          required: true
          schema:
            type: string
        - name: rate_limit_id
          in: path
          description: The ID of the rate limit.
          required: true
          schema:
            type: string
      requestBody:
        description: The project rate limit update request payload.
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/ProjectRateLimitUpdateRequest'
      responses:
        '200':
          description: Project rate limit updated successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ProjectRateLimit'
        '400':
          description: Error response for various conditions.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ErrorResponse'
      x-oaiMeta:
        name: Modify project rate limit
        group: administration
        returns: The updated [ProjectRateLimit](/docs/api-reference/project-rate-limits/object) object.
        examples:
          response: |
            {
                "object": "project.rate_limit",
                "id": "rl-ada",
                "model": "ada",
                "max_requests_per_1_minute": 600,
                "max_tokens_per_1_minute": 150000,
                "max_images_per_1_minute": 10
              }
          request:
            curl: |
              curl -X POST https://api.openai.com/v1/organization/projects/proj_abc/rate_limits/rl_xxx \
                -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
                -H "Content-Type: application/json" \
                -d '{
                    "max_requests_per_1_minute": 500
                }'
          error_response: |
            {
                "code": 404,
                "message": "The project {project_id} was not found"
            }
  /organization/projects/{project_id}/service_accounts:
    get:
      summary: Returns a list of service accounts in the project.
      operationId: list-project-service-accounts
      tags:
        - Projects
      parameters:
        - name: project_id
          in: path
          description: The ID of the project.
          required: true
          schema:
            type: string
        - name: limit
          in: query
          description: >
            A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
            default is 20.
          required: false
          schema:
            type: integer
            default: 20
        - name: after
          in: query
          description: >
            A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
            instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
            call can include after=obj_foo in order to fetch the next page of the list.
          required: false
          schema:
            type: string
      responses:
        '200':
          description: Project service accounts listed successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ProjectServiceAccountListResponse'
        '400':
          description: Error response when project is archived.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ErrorResponse'
      x-oaiMeta:
        name: List project service accounts
        group: administration
        returns: A list of [ProjectServiceAccount](/docs/api-reference/project-service-accounts/object) objects.
        examples:
          response: |
            {
                "object": "list",
                "data": [
                    {
                        "object": "organization.project.service_account",
                        "id": "svc_acct_abc",
                        "name": "Service Account",
                        "role": "owner",
                        "created_at": 1711471533
                    }
                ],
                "first_id": "svc_acct_abc",
                "last_id": "svc_acct_xyz",
                "has_more": false
            }
          request:
            curl: >
              curl
              https://api.openai.com/v1/organization/projects/proj_abc/service_accounts?after=custom_id&limit=20
              \
                -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
                -H "Content-Type: application/json"
    post:
      summary: >-
        Creates a new service account in the project. This also returns an unredacted API key for the service
        account.
      operationId: create-project-service-account
      tags:
        - Projects
      parameters:
        - name: project_id
          in: path
          description: The ID of the project.
          required: true
          schema:
            type: string
      requestBody:
        description: The project service account create request payload.
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/ProjectServiceAccountCreateRequest'
      responses:
        '200':
          description: Project service account created successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ProjectServiceAccountCreateResponse'
        '400':
          description: Error response when project is archived.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ErrorResponse'
      x-oaiMeta:
        name: Create project service account
        group: administration
        returns: The created [ProjectServiceAccount](/docs/api-reference/project-service-accounts/object) object.
        examples:
          response: |
            {
                "object": "organization.project.service_account",
                "id": "svc_acct_abc",
                "name": "Production App",
                "role": "member",
                "created_at": 1711471533,
                "api_key": {
                    "object": "organization.project.service_account.api_key",
                    "value": "sk-abcdefghijklmnop123",
                    "name": "Secret Key",
                    "created_at": 1711471533,
                    "id": "key_abc"
                }
            }
          request:
            curl: |
              curl -X POST https://api.openai.com/v1/organization/projects/proj_abc/service_accounts \
                -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
                -H "Content-Type: application/json" \
                -d '{
                    "name": "Production App"
                }'
  /organization/projects/{project_id}/service_accounts/{service_account_id}:
    get:
      summary: Retrieves a service account in the project.
      operationId: retrieve-project-service-account
      tags:
        - Projects
      parameters:
        - name: project_id
          in: path
          description: The ID of the project.
          required: true
          schema:
            type: string
        - name: service_account_id
          in: path
          description: The ID of the service account.
          required: true
          schema:
            type: string
      responses:
        '200':
          description: Project service account retrieved successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ProjectServiceAccount'
      x-oaiMeta:
        name: Retrieve project service account
        group: administration
        returns: >-
          The [ProjectServiceAccount](/docs/api-reference/project-service-accounts/object) object matching the
          specified ID.
        examples:
          response: |
            {
                "object": "organization.project.service_account",
                "id": "svc_acct_abc",
                "name": "Service Account",
                "role": "owner",
                "created_at": 1711471533
            }
          request:
            curl: |
              curl https://api.openai.com/v1/organization/projects/proj_abc/service_accounts/svc_acct_abc \
                -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
                -H "Content-Type: application/json"
    delete:
      summary: Deletes a service account from the project.
      operationId: delete-project-service-account
      tags:
        - Projects
      parameters:
        - name: project_id
          in: path
          description: The ID of the project.
          required: true
          schema:
            type: string
        - name: service_account_id
          in: path
          description: The ID of the service account.
          required: true
          schema:
            type: string
      responses:
        '200':
          description: Project service account deleted successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ProjectServiceAccountDeleteResponse'
      x-oaiMeta:
        name: Delete project service account
        group: administration
        returns: >-
          Confirmation of service account being deleted, or an error in case of an archived project, which has
          no service accounts
        examples:
          response: |
            {
                "object": "organization.project.service_account.deleted",
                "id": "svc_acct_abc",
                "deleted": true
            }
          request:
            curl: >
              curl -X DELETE
              https://api.openai.com/v1/organization/projects/proj_abc/service_accounts/svc_acct_abc \
                -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
                -H "Content-Type: application/json"
  /organization/projects/{project_id}/users:
    get:
      summary: Returns a list of users in the project.
      operationId: list-project-users
      tags:
        - Projects
      parameters:
        - name: project_id
          in: path
          description: The ID of the project.
          required: true
          schema:
            type: string
        - name: limit
          in: query
          description: >
            A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
            default is 20.
          required: false
          schema:
            type: integer
            default: 20
        - name: after
          in: query
          description: >
            A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
            instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
            call can include after=obj_foo in order to fetch the next page of the list.
          required: false
          schema:
            type: string
      responses:
        '200':
          description: Project users listed successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ProjectUserListResponse'
        '400':
          description: Error response when project is archived.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ErrorResponse'
      x-oaiMeta:
        name: List project users
        group: administration
        returns: A list of [ProjectUser](/docs/api-reference/project-users/object) objects.
        examples:
          response: |
            {
                "object": "list",
                "data": [
                    {
                        "object": "organization.project.user",
                        "id": "user_abc",
                        "name": "First Last",
                        "email": "user@example.com",
                        "role": "owner",
                        "added_at": 1711471533
                    }
                ],
                "first_id": "user-abc",
                "last_id": "user-xyz",
                "has_more": false
            }
          request:
            curl: |
              curl https://api.openai.com/v1/organization/projects/proj_abc/users?after=user_abc&limit=20 \
                -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
                -H "Content-Type: application/json"
    post:
      summary: >-
        Adds a user to the project. Users must already be members of the organization to be added to a
        project.
      operationId: create-project-user
      parameters:
        - name: project_id
          in: path
          description: The ID of the project.
          required: true
          schema:
            type: string
      tags:
        - Projects
      requestBody:
        description: The project user create request payload.
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/ProjectUserCreateRequest'
      responses:
        '200':
          description: User added to project successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ProjectUser'
        '400':
          description: Error response for various conditions.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ErrorResponse'
      x-oaiMeta:
        name: Create project user
        group: administration
        returns: The created [ProjectUser](/docs/api-reference/project-users/object) object.
        examples:
          response: |
            {
                "object": "organization.project.user",
                "id": "user_abc",
                "email": "user@example.com",
                "role": "owner",
                "added_at": 1711471533
            }
          request:
            curl: |
              curl -X POST https://api.openai.com/v1/organization/projects/proj_abc/users \
                -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
                -H "Content-Type: application/json" \
                -d '{
                    "user_id": "user_abc",
                    "role": "member"
                }'
  /organization/projects/{project_id}/users/{user_id}:
    get:
      summary: Retrieves a user in the project.
      operationId: retrieve-project-user
      tags:
        - Projects
      parameters:
        - name: project_id
          in: path
          description: The ID of the project.
          required: true
          schema:
            type: string
        - name: user_id
          in: path
          description: The ID of the user.
          required: true
          schema:
            type: string
      responses:
        '200':
          description: Project user retrieved successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ProjectUser'
      x-oaiMeta:
        name: Retrieve project user
        group: administration
        returns: The [ProjectUser](/docs/api-reference/project-users/object) object matching the specified ID.
        examples:
          response: |
            {
                "object": "organization.project.user",
                "id": "user_abc",
                "name": "First Last",
                "email": "user@example.com",
                "role": "owner",
                "added_at": 1711471533
            }
          request:
            curl: |
              curl https://api.openai.com/v1/organization/projects/proj_abc/users/user_abc \
                -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
                -H "Content-Type: application/json"
    post:
      summary: Modifies a user's role in the project.
      operationId: modify-project-user
      tags:
        - Projects
      parameters:
        - name: project_id
          in: path
          description: The ID of the project.
          required: true
          schema:
            type: string
        - name: user_id
          in: path
          description: The ID of the user.
          required: true
          schema:
            type: string
      requestBody:
        description: The project user update request payload.
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/ProjectUserUpdateRequest'
      responses:
        '200':
          description: Project user's role updated successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ProjectUser'
        '400':
          description: Error response for various conditions.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ErrorResponse'
      x-oaiMeta:
        name: Modify project user
        group: administration
        returns: The updated [ProjectUser](/docs/api-reference/project-users/object) object.
        examples:
          response: |
            {
                "object": "organization.project.user",
                "id": "user_abc",
                "name": "First Last",
                "email": "user@example.com",
                "role": "owner",
                "added_at": 1711471533
            }
          request:
            curl: |
              curl -X POST https://api.openai.com/v1/organization/projects/proj_abc/users/user_abc \
                -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
                -H "Content-Type: application/json" \
                -d '{
                    "role": "owner"
                }'
    delete:
      summary: Deletes a user from the project.
      operationId: delete-project-user
      tags:
        - Projects
      parameters:
        - name: project_id
          in: path
          description: The ID of the project.
          required: true
          schema:
            type: string
        - name: user_id
          in: path
          description: The ID of the user.
          required: true
          schema:
            type: string
      responses:
        '200':
          description: Project user deleted successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ProjectUserDeleteResponse'
        '400':
          description: Error response for various conditions.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ErrorResponse'
      x-oaiMeta:
        name: Delete project user
        group: administration
        returns: >-
          Confirmation that project has been deleted or an error in case of an archived project, which has no
          users
        examples:
          response: |
            {
                "object": "organization.project.user.deleted",
                "id": "user_abc",
                "deleted": true
            }
          request:
            curl: |
              curl -X DELETE https://api.openai.com/v1/organization/projects/proj_abc/users/user_abc \
                -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
                -H "Content-Type: application/json"
  /organization/usage/audio_speeches:
    get:
      summary: Get audio speeches usage details for the organization.
      operationId: usage-audio-speeches
      tags:
        - Usage
      parameters:
        - name: start_time
          in: query
          description: Start time (Unix seconds) of the query time range, inclusive.
          required: true
          schema:
            type: integer
        - name: end_time
          in: query
          description: End time (Unix seconds) of the query time range, exclusive.
          required: false
          schema:
            type: integer
        - name: bucket_width
          in: query
          description: >-
            Width of each time bucket in response. Currently `1m`, `1h` and `1d` are supported, default to
            `1d`.
          required: false
          schema:
            type: string
            enum:
              - 1m
              - 1h
              - 1d
            default: 1d
        - name: project_ids
          in: query
          description: Return only usage for these projects.
          required: false
          schema:
            type: array
            items:
              type: string
        - name: user_ids
          in: query
          description: Return only usage for these users.
          required: false
          schema:
            type: array
            items:
              type: string
        - name: api_key_ids
          in: query
          description: Return only usage for these API keys.
          required: false
          schema:
            type: array
            items:
              type: string
        - name: models
          in: query
          description: Return only usage for these models.
          required: false
          schema:
            type: array
            items:
              type: string
        - name: group_by
          in: query
          description: >-
            Group the usage data by the specified fields. Support fields include `project_id`, `user_id`,
            `api_key_id`, `model` or any combination of them.
          required: false
          schema:
            type: array
            items:
              type: string
              enum:
                - project_id
                - user_id
                - api_key_id
                - model
        - name: limit
          in: query
          description: |
            Specifies the number of buckets to return.
            - `bucket_width=1d`: default: 7, max: 31
            - `bucket_width=1h`: default: 24, max: 168
            - `bucket_width=1m`: default: 60, max: 1440
          required: false
          schema:
            type: integer
        - name: page
          in: query
          description: A cursor for use in pagination. Corresponding to the `next_page` field from the previous response.
          schema:
            type: string
      responses:
        '200':
          description: Usage data retrieved successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/UsageResponse'
      x-oaiMeta:
        name: Audio speeches
        group: usage-audio-speeches
        returns: >-
          A list of paginated, time bucketed [Audio speeches
          usage](/docs/api-reference/usage/audio_speeches_object) objects.
        examples:
          response: |
            {
                "object": "page",
                "data": [
                    {
                        "object": "bucket",
                        "start_time": 1730419200,
                        "end_time": 1730505600,
                        "results": [
                            {
                                "object": "organization.usage.audio_speeches.result",
                                "characters": 45,
                                "num_model_requests": 1,
                                "project_id": null,
                                "user_id": null,
                                "api_key_id": null,
                                "model": null
                            }
                        ]
                    }
                ],
                "has_more": false,
                "next_page": null
            }
          request:
            curl: >
              curl "https://api.openai.com/v1/organization/usage/audio_speeches?start_time=1730419200&limit=1"
              \

              -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \

              -H "Content-Type: application/json"
  /organization/usage/audio_transcriptions:
    get:
      summary: Get audio transcriptions usage details for the organization.
      operationId: usage-audio-transcriptions
      tags:
        - Usage
      parameters:
        - name: start_time
          in: query
          description: Start time (Unix seconds) of the query time range, inclusive.
          required: true
          schema:
            type: integer
        - name: end_time
          in: query
          description: End time (Unix seconds) of the query time range, exclusive.
          required: false
          schema:
            type: integer
        - name: bucket_width
          in: query
          description: >-
            Width of each time bucket in response. Currently `1m`, `1h` and `1d` are supported, default to
            `1d`.
          required: false
          schema:
            type: string
            enum:
              - 1m
              - 1h
              - 1d
            default: 1d
        - name: project_ids
          in: query
          description: Return only usage for these projects.
          required: false
          schema:
            type: array
            items:
              type: string
        - name: user_ids
          in: query
          description: Return only usage for these users.
          required: false
          schema:
            type: array
            items:
              type: string
        - name: api_key_ids
          in: query
          description: Return only usage for these API keys.
          required: false
          schema:
            type: array
            items:
              type: string
        - name: models
          in: query
          description: Return only usage for these models.
          required: false
          schema:
            type: array
            items:
              type: string
        - name: group_by
          in: query
          description: >-
            Group the usage data by the specified fields. Support fields include `project_id`, `user_id`,
            `api_key_id`, `model` or any combination of them.
          required: false
          schema:
            type: array
            items:
              type: string
              enum:
                - project_id
                - user_id
                - api_key_id
                - model
        - name: limit
          in: query
          description: |
            Specifies the number of buckets to return.
            - `bucket_width=1d`: default: 7, max: 31
            - `bucket_width=1h`: default: 24, max: 168
            - `bucket_width=1m`: default: 60, max: 1440
          required: false
          schema:
            type: integer
        - name: page
          in: query
          description: A cursor for use in pagination. Corresponding to the `next_page` field from the previous response.
          schema:
            type: string
      responses:
        '200':
          description: Usage data retrieved successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/UsageResponse'
      x-oaiMeta:
        name: Audio transcriptions
        group: usage-audio-transcriptions
        returns: >-
          A list of paginated, time bucketed [Audio transcriptions
          usage](/docs/api-reference/usage/audio_transcriptions_object) objects.
        examples:
          response: |
            {
                "object": "page",
                "data": [
                    {
                        "object": "bucket",
                        "start_time": 1730419200,
                        "end_time": 1730505600,
                        "results": [
                            {
                                "object": "organization.usage.audio_transcriptions.result",
                                "seconds": 20,
                                "num_model_requests": 1,
                                "project_id": null,
                                "user_id": null,
                                "api_key_id": null,
                                "model": null
                            }
                        ]
                    }
                ],
                "has_more": false,
                "next_page": null
            }
          request:
            curl: >
              curl
              "https://api.openai.com/v1/organization/usage/audio_transcriptions?start_time=1730419200&limit=1"
              \

              -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \

              -H "Content-Type: application/json"
  /organization/usage/code_interpreter_sessions:
    get:
      summary: Get code interpreter sessions usage details for the organization.
      operationId: usage-code-interpreter-sessions
      tags:
        - Usage
      parameters:
        - name: start_time
          in: query
          description: Start time (Unix seconds) of the query time range, inclusive.
          required: true
          schema:
            type: integer
        - name: end_time
          in: query
          description: End time (Unix seconds) of the query time range, exclusive.
          required: false
          schema:
            type: integer
        - name: bucket_width
          in: query
          description: >-
            Width of each time bucket in response. Currently `1m`, `1h` and `1d` are supported, default to
            `1d`.
          required: false
          schema:
            type: string
            enum:
              - 1m
              - 1h
              - 1d
            default: 1d
        - name: project_ids
          in: query
          description: Return only usage for these projects.
          required: false
          schema:
            type: array
            items:
              type: string
        - name: group_by
          in: query
          description: Group the usage data by the specified fields. Support fields include `project_id`.
          required: false
          schema:
            type: array
            items:
              type: string
              enum:
                - project_id
        - name: limit
          in: query
          description: |
            Specifies the number of buckets to return.
            - `bucket_width=1d`: default: 7, max: 31
            - `bucket_width=1h`: default: 24, max: 168
            - `bucket_width=1m`: default: 60, max: 1440
          required: false
          schema:
            type: integer
        - name: page
          in: query
          description: A cursor for use in pagination. Corresponding to the `next_page` field from the previous response.
          schema:
            type: string
      responses:
        '200':
          description: Usage data retrieved successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/UsageResponse'
      x-oaiMeta:
        name: Code interpreter sessions
        group: usage-code-interpreter-sessions
        returns: >-
          A list of paginated, time bucketed [Code interpreter sessions
          usage](/docs/api-reference/usage/code_interpreter_sessions_object) objects.
        examples:
          response: |
            {
                "object": "page",
                "data": [
                    {
                        "object": "bucket",
                        "start_time": 1730419200,
                        "end_time": 1730505600,
                        "results": [
                            {
                                "object": "organization.usage.code_interpreter_sessions.result",
                                "num_sessions": 1,
                                "project_id": null
                            }
                        ]
                    }
                ],
                "has_more": false,
                "next_page": null
            }
          request:
            curl: >
              curl
              "https://api.openai.com/v1/organization/usage/code_interpreter_sessions?start_time=1730419200&limit=1"
              \

              -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \

              -H "Content-Type: application/json"
  /organization/usage/completions:
    get:
      summary: Get completions usage details for the organization.
      operationId: usage-completions
      tags:
        - Usage
      parameters:
        - name: start_time
          in: query
          description: Start time (Unix seconds) of the query time range, inclusive.
          required: true
          schema:
            type: integer
        - name: end_time
          in: query
          description: End time (Unix seconds) of the query time range, exclusive.
          required: false
          schema:
            type: integer
        - name: bucket_width
          in: query
          description: >-
            Width of each time bucket in response. Currently `1m`, `1h` and `1d` are supported, default to
            `1d`.
          required: false
          schema:
            type: string
            enum:
              - 1m
              - 1h
              - 1d
            default: 1d
        - name: project_ids
          in: query
          description: Return only usage for these projects.
          required: false
          schema:
            type: array
            items:
              type: string
        - name: user_ids
          in: query
          description: Return only usage for these users.
          required: false
          schema:
            type: array
            items:
              type: string
        - name: api_key_ids
          in: query
          description: Return only usage for these API keys.
          required: false
          schema:
            type: array
            items:
              type: string
        - name: models
          in: query
          description: Return only usage for these models.
          required: false
          schema:
            type: array
            items:
              type: string
        - name: batch
          in: query
          description: >
            If `true`, return batch jobs only. If `false`, return non-batch jobs only. By default, return
            both.
          required: false
          schema:
            type: boolean
        - name: group_by
          in: query
          description: >-
            Group the usage data by the specified fields. Support fields include `project_id`, `user_id`,
            `api_key_id`, `model`, `batch` or any combination of them.
          required: false
          schema:
            type: array
            items:
              type: string
              enum:
                - project_id
                - user_id
                - api_key_id
                - model
                - batch
        - name: limit
          in: query
          description: |
            Specifies the number of buckets to return.
            - `bucket_width=1d`: default: 7, max: 31
            - `bucket_width=1h`: default: 24, max: 168
            - `bucket_width=1m`: default: 60, max: 1440
          required: false
          schema:
            type: integer
        - name: page
          in: query
          description: A cursor for use in pagination. Corresponding to the `next_page` field from the previous response.
          schema:
            type: string
      responses:
        '200':
          description: Usage data retrieved successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/UsageResponse'
      x-oaiMeta:
        name: Completions
        group: usage-completions
        returns: >-
          A list of paginated, time bucketed [Completions usage](/docs/api-reference/usage/completions_object)
          objects.
        examples:
          response: |
            {
                "object": "page",
                "data": [
                    {
                        "object": "bucket",
                        "start_time": 1730419200,
                        "end_time": 1730505600,
                        "results": [
                            {
                                "object": "organization.usage.completions.result",
                                "input_tokens": 1000,
                                "output_tokens": 500,
                                "input_cached_tokens": 800,
                                "input_audio_tokens": 0,
                                "output_audio_tokens": 0,
                                "num_model_requests": 5,
                                "project_id": null,
                                "user_id": null,
                                "api_key_id": null,
                                "model": null,
                                "batch": null
                            }
                        ]
                    }
                ],
                "has_more": true,
                "next_page": "page_AAAAAGdGxdEiJdKOAAAAAGcqsYA="
            }
          request:
            curl: |
              curl "https://api.openai.com/v1/organization/usage/completions?start_time=1730419200&limit=1" \
              -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
              -H "Content-Type: application/json"
  /organization/usage/embeddings:
    get:
      summary: Get embeddings usage details for the organization.
      operationId: usage-embeddings
      tags:
        - Usage
      parameters:
        - name: start_time
          in: query
          description: Start time (Unix seconds) of the query time range, inclusive.
          required: true
          schema:
            type: integer
        - name: end_time
          in: query
          description: End time (Unix seconds) of the query time range, exclusive.
          required: false
          schema:
            type: integer
        - name: bucket_width
          in: query
          description: >-
            Width of each time bucket in response. Currently `1m`, `1h` and `1d` are supported, default to
            `1d`.
          required: false
          schema:
            type: string
            enum:
              - 1m
              - 1h
              - 1d
            default: 1d
        - name: project_ids
          in: query
          description: Return only usage for these projects.
          required: false
          schema:
            type: array
            items:
              type: string
        - name: user_ids
          in: query
          description: Return only usage for these users.
          required: false
          schema:
            type: array
            items:
              type: string
        - name: api_key_ids
          in: query
          description: Return only usage for these API keys.
          required: false
          schema:
            type: array
            items:
              type: string
        - name: models
          in: query
          description: Return only usage for these models.
          required: false
          schema:
            type: array
            items:
              type: string
        - name: group_by
          in: query
          description: >-
            Group the usage data by the specified fields. Support fields include `project_id`, `user_id`,
            `api_key_id`, `model` or any combination of them.
          required: false
          schema:
            type: array
            items:
              type: string
              enum:
                - project_id
                - user_id
                - api_key_id
                - model
        - name: limit
          in: query
          description: |
            Specifies the number of buckets to return.
            - `bucket_width=1d`: default: 7, max: 31
            - `bucket_width=1h`: default: 24, max: 168
            - `bucket_width=1m`: default: 60, max: 1440
          required: false
          schema:
            type: integer
        - name: page
          in: query
          description: A cursor for use in pagination. Corresponding to the `next_page` field from the previous response.
          schema:
            type: string
      responses:
        '200':
          description: Usage data retrieved successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/UsageResponse'
      x-oaiMeta:
        name: Embeddings
        group: usage-embeddings
        returns: >-
          A list of paginated, time bucketed [Embeddings usage](/docs/api-reference/usage/embeddings_object)
          objects.
        examples:
          response: |
            {
                "object": "page",
                "data": [
                    {
                        "object": "bucket",
                        "start_time": 1730419200,
                        "end_time": 1730505600,
                        "results": [
                            {
                                "object": "organization.usage.embeddings.result",
                                "input_tokens": 16,
                                "num_model_requests": 2,
                                "project_id": null,
                                "user_id": null,
                                "api_key_id": null,
                                "model": null
                            }
                        ]
                    }
                ],
                "has_more": false,
                "next_page": null
            }
          request:
            curl: |
              curl "https://api.openai.com/v1/organization/usage/embeddings?start_time=1730419200&limit=1" \
              -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
              -H "Content-Type: application/json"
  /organization/usage/images:
    get:
      summary: Get images usage details for the organization.
      operationId: usage-images
      tags:
        - Usage
      parameters:
        - name: start_time
          in: query
          description: Start time (Unix seconds) of the query time range, inclusive.
          required: true
          schema:
            type: integer
        - name: end_time
          in: query
          description: End time (Unix seconds) of the query time range, exclusive.
          required: false
          schema:
            type: integer
        - name: bucket_width
          in: query
          description: >-
            Width of each time bucket in response. Currently `1m`, `1h` and `1d` are supported, default to
            `1d`.
          required: false
          schema:
            type: string
            enum:
              - 1m
              - 1h
              - 1d
            default: 1d
        - name: sources
          in: query
          description: >-
            Return only usages for these sources. Possible values are `image.generation`, `image.edit`,
            `image.variation` or any combination of them.
          required: false
          schema:
            type: array
            items:
              type: string
              enum:
                - image.generation
                - image.edit
                - image.variation
        - name: sizes
          in: query
          description: >-
            Return only usages for these image sizes. Possible values are `256x256`, `512x512`, `1024x1024`,
            `1792x1792`, `1024x1792` or any combination of them.
          required: false
          schema:
            type: array
            items:
              type: string
              enum:
                - 256x256
                - 512x512
                - 1024x1024
                - 1792x1792
                - 1024x1792
        - name: project_ids
          in: query
          description: Return only usage for these projects.
          required: false
          schema:
            type: array
            items:
              type: string
        - name: user_ids
          in: query
          description: Return only usage for these users.
          required: false
          schema:
            type: array
            items:
              type: string
        - name: api_key_ids
          in: query
          description: Return only usage for these API keys.
          required: false
          schema:
            type: array
            items:
              type: string
        - name: models
          in: query
          description: Return only usage for these models.
          required: false
          schema:
            type: array
            items:
              type: string
        - name: group_by
          in: query
          description: >-
            Group the usage data by the specified fields. Support fields include `project_id`, `user_id`,
            `api_key_id`, `model`, `size`, `source` or any combination of them.
          required: false
          schema:
            type: array
            items:
              type: string
              enum:
                - project_id
                - user_id
                - api_key_id
                - model
                - size
                - source
        - name: limit
          in: query
          description: |
            Specifies the number of buckets to return.
            - `bucket_width=1d`: default: 7, max: 31
            - `bucket_width=1h`: default: 24, max: 168
            - `bucket_width=1m`: default: 60, max: 1440
          required: false
          schema:
            type: integer
        - name: page
          in: query
          description: A cursor for use in pagination. Corresponding to the `next_page` field from the previous response.
          schema:
            type: string
      responses:
        '200':
          description: Usage data retrieved successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/UsageResponse'
      x-oaiMeta:
        name: Images
        group: usage-images
        returns: A list of paginated, time bucketed [Images usage](/docs/api-reference/usage/images_object) objects.
        examples:
          response: |
            {
                "object": "page",
                "data": [
                    {
                        "object": "bucket",
                        "start_time": 1730419200,
                        "end_time": 1730505600,
                        "results": [
                            {
                                "object": "organization.usage.images.result",
                                "images": 2,
                                "num_model_requests": 2,
                                "size": null,
                                "source": null,
                                "project_id": null,
                                "user_id": null,
                                "api_key_id": null,
                                "model": null
                            }
                        ]
                    }
                ],
                "has_more": false,
                "next_page": null
            }
          request:
            curl: |
              curl "https://api.openai.com/v1/organization/usage/images?start_time=1730419200&limit=1" \
              -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
              -H "Content-Type: application/json"
  /organization/usage/moderations:
    get:
      summary: Get moderations usage details for the organization.
      operationId: usage-moderations
      tags:
        - Usage
      parameters:
        - name: start_time
          in: query
          description: Start time (Unix seconds) of the query time range, inclusive.
          required: true
          schema:
            type: integer
        - name: end_time
          in: query
          description: End time (Unix seconds) of the query time range, exclusive.
          required: false
          schema:
            type: integer
        - name: bucket_width
          in: query
          description: >-
            Width of each time bucket in response. Currently `1m`, `1h` and `1d` are supported, default to
            `1d`.
          required: false
          schema:
            type: string
            enum:
              - 1m
              - 1h
              - 1d
            default: 1d
        - name: project_ids
          in: query
          description: Return only usage for these projects.
          required: false
          schema:
            type: array
            items:
              type: string
        - name: user_ids
          in: query
          description: Return only usage for these users.
          required: false
          schema:
            type: array
            items:
              type: string
        - name: api_key_ids
          in: query
          description: Return only usage for these API keys.
          required: false
          schema:
            type: array
            items:
              type: string
        - name: models
          in: query
          description: Return only usage for these models.
          required: false
          schema:
            type: array
            items:
              type: string
        - name: group_by
          in: query
          description: >-
            Group the usage data by the specified fields. Support fields include `project_id`, `user_id`,
            `api_key_id`, `model` or any combination of them.
          required: false
          schema:
            type: array
            items:
              type: string
              enum:
                - project_id
                - user_id
                - api_key_id
                - model
        - name: limit
          in: query
          description: |
            Specifies the number of buckets to return.
            - `bucket_width=1d`: default: 7, max: 31
            - `bucket_width=1h`: default: 24, max: 168
            - `bucket_width=1m`: default: 60, max: 1440
          required: false
          schema:
            type: integer
        - name: page
          in: query
          description: A cursor for use in pagination. Corresponding to the `next_page` field from the previous response.
          schema:
            type: string
      responses:
        '200':
          description: Usage data retrieved successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/UsageResponse'
      x-oaiMeta:
        name: Moderations
        group: usage-moderations
        returns: >-
          A list of paginated, time bucketed [Moderations usage](/docs/api-reference/usage/moderations_object)
          objects.
        examples:
          response: |
            {
                "object": "page",
                "data": [
                    {
                        "object": "bucket",
                        "start_time": 1730419200,
                        "end_time": 1730505600,
                        "results": [
                            {
                                "object": "organization.usage.moderations.result",
                                "input_tokens": 16,
                                "num_model_requests": 2,
                                "project_id": null,
                                "user_id": null,
                                "api_key_id": null,
                                "model": null
                            }
                        ]
                    }
                ],
                "has_more": false,
                "next_page": null
            }
          request:
            curl: |
              curl "https://api.openai.com/v1/organization/usage/moderations?start_time=1730419200&limit=1" \
              -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
              -H "Content-Type: application/json"
  /organization/usage/vector_stores:
    get:
      summary: Get vector stores usage details for the organization.
      operationId: usage-vector-stores
      tags:
        - Usage
      parameters:
        - name: start_time
          in: query
          description: Start time (Unix seconds) of the query time range, inclusive.
          required: true
          schema:
            type: integer
        - name: end_time
          in: query
          description: End time (Unix seconds) of the query time range, exclusive.
          required: false
          schema:
            type: integer
        - name: bucket_width
          in: query
          description: >-
            Width of each time bucket in response. Currently `1m`, `1h` and `1d` are supported, default to
            `1d`.
          required: false
          schema:
            type: string
            enum:
              - 1m
              - 1h
              - 1d
            default: 1d
        - name: project_ids
          in: query
          description: Return only usage for these projects.
          required: false
          schema:
            type: array
            items:
              type: string
        - name: group_by
          in: query
          description: Group the usage data by the specified fields. Support fields include `project_id`.
          required: false
          schema:
            type: array
            items:
              type: string
              enum:
                - project_id
        - name: limit
          in: query
          description: |
            Specifies the number of buckets to return.
            - `bucket_width=1d`: default: 7, max: 31
            - `bucket_width=1h`: default: 24, max: 168
            - `bucket_width=1m`: default: 60, max: 1440
          required: false
          schema:
            type: integer
        - name: page
          in: query
          description: A cursor for use in pagination. Corresponding to the `next_page` field from the previous response.
          schema:
            type: string
      responses:
        '200':
          description: Usage data retrieved successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/UsageResponse'
      x-oaiMeta:
        name: Vector stores
        group: usage-vector-stores
        returns: >-
          A list of paginated, time bucketed [Vector stores
          usage](/docs/api-reference/usage/vector_stores_object) objects.
        examples:
          response: |
            {
                "object": "page",
                "data": [
                    {
                        "object": "bucket",
                        "start_time": 1730419200,
                        "end_time": 1730505600,
                        "results": [
                            {
                                "object": "organization.usage.vector_stores.result",
                                "usage_bytes": 1024,
                                "project_id": null
                            }
                        ]
                    }
                ],
                "has_more": false,
                "next_page": null
            }
          request:
            curl: >
              curl "https://api.openai.com/v1/organization/usage/vector_stores?start_time=1730419200&limit=1"
              \

              -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \

              -H "Content-Type: application/json"
  /organization/users:
    get:
      summary: Lists all of the users in the organization.
      operationId: list-users
      tags:
        - Users
      parameters:
        - name: limit
          in: query
          description: >
            A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
            default is 20.
          required: false
          schema:
            type: integer
            default: 20
        - name: after
          in: query
          description: >
            A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
            instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
            call can include after=obj_foo in order to fetch the next page of the list.
          required: false
          schema:
            type: string
        - name: emails
          in: query
          description: Filter by the email address of users.
          required: false
          schema:
            type: array
            items:
              type: string
      responses:
        '200':
          description: Users listed successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/UserListResponse'
      x-oaiMeta:
        name: List users
        group: administration
        returns: A list of [User](/docs/api-reference/users/object) objects.
        examples:
          response: |
            {
                "object": "list",
                "data": [
                    {
                        "object": "organization.user",
                        "id": "user_abc",
                        "name": "First Last",
                        "email": "user@example.com",
                        "role": "owner",
                        "added_at": 1711471533
                    }
                ],
                "first_id": "user-abc",
                "last_id": "user-xyz",
                "has_more": false
            }
          request:
            curl: |
              curl https://api.openai.com/v1/organization/users?after=user_abc&limit=20 \
                -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
                -H "Content-Type: application/json"
  /organization/users/{user_id}:
    get:
      summary: Retrieves a user by their identifier.
      operationId: retrieve-user
      tags:
        - Users
      parameters:
        - name: user_id
          in: path
          description: The ID of the user.
          required: true
          schema:
            type: string
      responses:
        '200':
          description: User retrieved successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/User'
      x-oaiMeta:
        name: Retrieve user
        group: administration
        returns: The [User](/docs/api-reference/users/object) object matching the specified ID.
        examples:
          response: |
            {
                "object": "organization.user",
                "id": "user_abc",
                "name": "First Last",
                "email": "user@example.com",
                "role": "owner",
                "added_at": 1711471533
            }
          request:
            curl: |
              curl https://api.openai.com/v1/organization/users/user_abc \
                -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
                -H "Content-Type: application/json"
    post:
      summary: Modifies a user's role in the organization.
      operationId: modify-user
      tags:
        - Users
      parameters:
        - name: user_id
          in: path
          description: The ID of the user.
          required: true
          schema:
            type: string
      requestBody:
        description: The new user role to modify. This must be one of `owner` or `member`.
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/UserRoleUpdateRequest'
      responses:
        '200':
          description: User role updated successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/User'
      x-oaiMeta:
        name: Modify user
        group: administration
        returns: The updated [User](/docs/api-reference/users/object) object.
        examples:
          response: |
            {
                "object": "organization.user",
                "id": "user_abc",
                "name": "First Last",
                "email": "user@example.com",
                "role": "owner",
                "added_at": 1711471533
            }
          request:
            curl: |
              curl -X POST https://api.openai.com/v1/organization/users/user_abc \
                -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
                -H "Content-Type: application/json" \
                -d '{
                    "role": "owner"
                }'
    delete:
      summary: Deletes a user from the organization.
      operationId: delete-user
      tags:
        - Users
      parameters:
        - name: user_id
          in: path
          description: The ID of the user.
          required: true
          schema:
            type: string
      responses:
        '200':
          description: User deleted successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/UserDeleteResponse'
      x-oaiMeta:
        name: Delete user
        group: administration
        returns: Confirmation of the deleted user
        examples:
          response: |
            {
                "object": "organization.user.deleted",
                "id": "user_abc",
                "deleted": true
            }
          request:
            curl: |
              curl -X DELETE https://api.openai.com/v1/organization/users/user_abc \
                -H "Authorization: Bearer $OPENAI_ADMIN_KEY" \
                -H "Content-Type: application/json"
  /realtime/sessions:
    post:
      summary: |
        Create an ephemeral API token for use in client-side applications with the
        Realtime API. Can be configured with the same session parameters as the
        `session.update` client event.

        It responds with a session object, plus a `client_secret` key which contains
        a usable ephemeral API token that can be used to authenticate browser clients
        for the Realtime API.
      operationId: create-realtime-session
      tags:
        - Realtime
      requestBody:
        description: Create an ephemeral API key with the given session configuration.
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/RealtimeSessionCreateRequest'
      responses:
        '200':
          description: Session created successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/RealtimeSessionCreateResponse'
      x-oaiMeta:
        name: Create session
        group: realtime
        returns: The created Realtime session object, plus an ephemeral key
        examples:
          response: |
            {
              "id": "sess_001",
              "object": "realtime.session",
              "model": "gpt-4o-realtime-preview",
              "modalities": ["audio", "text"],
              "instructions": "You are a friendly assistant.",
              "voice": "alloy",
              "input_audio_format": "pcm16",
              "output_audio_format": "pcm16",
              "input_audio_transcription": {
                  "model": "whisper-1"
              },
              "turn_detection": null,
              "tools": [],
              "tool_choice": "none",
              "temperature": 0.7,
              "max_response_output_tokens": 200,
              "speed": 1.1,
              "tracing": "auto",
              "client_secret": {
                "value": "ek_abc123", 
                "expires_at": 1234567890
              }
            }
          request:
            curl: |
              curl -X POST https://api.openai.com/v1/realtime/sessions \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
                -d '{
                  "model": "gpt-4o-realtime-preview",
                  "modalities": ["audio", "text"],
                  "instructions": "You are a friendly assistant."
                }'
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const session = await client.beta.realtime.sessions.create();

              console.log(session.client_secret);
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              session = client.beta.realtime.sessions.create()
              print(session.client_secret)
  /realtime/transcription_sessions:
    post:
      summary: |
        Create an ephemeral API token for use in client-side applications with the
        Realtime API specifically for realtime transcriptions. 
        Can be configured with the same session parameters as the `transcription_session.update` client event.

        It responds with a session object, plus a `client_secret` key which contains
        a usable ephemeral API token that can be used to authenticate browser clients
        for the Realtime API.
      operationId: create-realtime-transcription-session
      tags:
        - Realtime
      requestBody:
        description: Create an ephemeral API key with the given session configuration.
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/RealtimeTranscriptionSessionCreateRequest'
      responses:
        '200':
          description: Session created successfully.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/RealtimeTranscriptionSessionCreateResponse'
      x-oaiMeta:
        name: Create transcription session
        group: realtime
        returns: >-
          The created [Realtime transcription session
          object](/docs/api-reference/realtime-sessions/transcription_session_object), plus an ephemeral key
        examples:
          response: |
            {
              "id": "sess_BBwZc7cFV3XizEyKGDCGL",
              "object": "realtime.transcription_session",
              "modalities": ["audio", "text"],
              "turn_detection": {
                "type": "server_vad",
                "threshold": 0.5,
                "prefix_padding_ms": 300,
                "silence_duration_ms": 200
              },
              "input_audio_format": "pcm16",
              "input_audio_transcription": {
                "model": "gpt-4o-transcribe",
                "language": null,
                "prompt": ""
              },
              "client_secret": null
            }
          request:
            curl: |
              curl -X POST https://api.openai.com/v1/realtime/transcription_sessions \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
                -d '{}'
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const transcriptionSession = await client.beta.realtime.transcriptionSessions.create();

              console.log(transcriptionSession.client_secret);
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              transcription_session = client.beta.realtime.transcription_sessions.create()
              print(transcription_session.client_secret)
  /responses:
    post:
      operationId: createResponse
      tags:
        - Responses
      summary: |
        Creates a model response. Provide [text](/docs/guides/text) or
        [image](/docs/guides/images) inputs to generate [text](/docs/guides/text)
        or [JSON](/docs/guides/structured-outputs) outputs. Have the model call
        your own [custom code](/docs/guides/function-calling) or use built-in
        [tools](/docs/guides/tools) like [web search](/docs/guides/tools-web-search)
        or [file search](/docs/guides/tools-file-search) to use your own data
        as input for the model's response.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateResponse'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Response'
            text/event-stream:
              schema:
                $ref: '#/components/schemas/ResponseStreamEvent'
      x-oaiMeta:
        name: Create a model response
        group: responses
        returns: |
          Returns a [Response](/docs/api-reference/responses/object) object.
        path: create
        examples:
          - title: Text input
            request:
              curl: |
                curl https://api.openai.com/v1/responses \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -d '{
                    "model": "gpt-4.1",
                    "input": "Tell me a three sentence bedtime story about a unicorn."
                  }'
              javascript: |
                import OpenAI from "openai";

                const openai = new OpenAI();

                const response = await openai.responses.create({
                    model: "gpt-4.1",
                    input: "Tell me a three sentence bedtime story about a unicorn."
                });

                console.log(response);
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                response = client.responses.create()
                print(response.id)
              csharp: >
                using System;

                using OpenAI.Responses;


                OpenAIResponseClient client = new(
                    model: "gpt-4.1",
                    apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
                );


                OpenAIResponse response = client.CreateResponse("Tell me a three sentence bedtime story about
                a unicorn.");


                Console.WriteLine(response.GetOutputText());
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const response = await client.responses.create();

                console.log(response.id);
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                  "github.com/openai/openai-go/responses"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  response, err := client.Responses.New(context.TODO(), responses.ResponseNewParams{

                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", response.ID)
                }
              java: |-
                package com.openai.example;

                import com.openai.client.OpenAIClient;
                import com.openai.client.okhttp.OpenAIOkHttpClient;
                import com.openai.models.responses.Response;
                import com.openai.models.responses.ResponseCreateParams;

                public final class Main {
                    private Main() {}

                    public static void main(String[] args) {
                        // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                        Response response = client.responses().create();
                    }
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.responses.Response
                import com.openai.models.responses.ResponseCreateParams

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val response: Response = client.responses().create()
                }
              ruby: |-
                require "openai"

                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )

                response = openai.responses.create

                puts(response)
            response: |
              {
                "id": "resp_67ccd2bed1ec8190b14f964abc0542670bb6a6b452d3795b",
                "object": "response",
                "created_at": 1741476542,
                "status": "completed",
                "error": null,
                "incomplete_details": null,
                "instructions": null,
                "max_output_tokens": null,
                "model": "gpt-4.1-2025-04-14",
                "output": [
                  {
                    "type": "message",
                    "id": "msg_67ccd2bf17f0819081ff3bb2cf6508e60bb6a6b452d3795b",
                    "status": "completed",
                    "role": "assistant",
                    "content": [
                      {
                        "type": "output_text",
                        "text": "In a peaceful grove beneath a silver moon, a unicorn named Lumina discovered a hidden pool that reflected the stars. As she dipped her horn into the water, the pool began to shimmer, revealing a pathway to a magical realm of endless night skies. Filled with wonder, Lumina whispered a wish for all who dream to find their own hidden magic, and as she glanced back, her hoofprints sparkled like stardust.",
                        "annotations": []
                      }
                    ]
                  }
                ],
                "parallel_tool_calls": true,
                "previous_response_id": null,
                "reasoning": {
                  "effort": null,
                  "summary": null
                },
                "store": true,
                "temperature": 1.0,
                "text": {
                  "format": {
                    "type": "text"
                  }
                },
                "tool_choice": "auto",
                "tools": [],
                "top_p": 1.0,
                "truncation": "disabled",
                "usage": {
                  "input_tokens": 36,
                  "input_tokens_details": {
                    "cached_tokens": 0
                  },
                  "output_tokens": 87,
                  "output_tokens_details": {
                    "reasoning_tokens": 0
                  },
                  "total_tokens": 123
                },
                "user": null,
                "metadata": {}
              }
          - title: Image input
            request:
              curl: |
                curl https://api.openai.com/v1/responses \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -d '{
                    "model": "gpt-4.1",
                    "input": [
                      {
                        "role": "user",
                        "content": [
                          {"type": "input_text", "text": "what is in this image?"},
                          {
                            "type": "input_image",
                            "image_url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
                          }
                        ]
                      }
                    ]
                  }'
              javascript: |
                import OpenAI from "openai";

                const openai = new OpenAI();

                const response = await openai.responses.create({
                    model: "gpt-4.1",
                    input: [
                        {
                            role: "user",
                            content: [
                                { type: "input_text", text: "what is in this image?" },
                                {
                                    type: "input_image",
                                    image_url:
                                        "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg",
                                },
                            ],
                        },
                    ],
                });

                console.log(response);
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                response = client.responses.create()
                print(response.id)
              csharp: |
                using System;
                using System.Collections.Generic;

                using OpenAI.Responses;

                OpenAIResponseClient client = new(
                    model: "gpt-4.1",
                    apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
                );

                List<ResponseItem> inputItems =
                [
                    ResponseItem.CreateUserMessageItem(
                        [
                            ResponseContentPart.CreateInputTextPart("What is in this image?"),
                            ResponseContentPart.CreateInputImagePart(new Uri("https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"))
                        ]
                    )
                ];

                OpenAIResponse response = client.CreateResponse(inputItems);

                Console.WriteLine(response.GetOutputText());
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const response = await client.responses.create();

                console.log(response.id);
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                  "github.com/openai/openai-go/responses"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  response, err := client.Responses.New(context.TODO(), responses.ResponseNewParams{

                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", response.ID)
                }
              java: |-
                package com.openai.example;

                import com.openai.client.OpenAIClient;
                import com.openai.client.okhttp.OpenAIOkHttpClient;
                import com.openai.models.responses.Response;
                import com.openai.models.responses.ResponseCreateParams;

                public final class Main {
                    private Main() {}

                    public static void main(String[] args) {
                        // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                        Response response = client.responses().create();
                    }
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.responses.Response
                import com.openai.models.responses.ResponseCreateParams

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val response: Response = client.responses().create()
                }
              ruby: |-
                require "openai"

                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )

                response = openai.responses.create

                puts(response)
            response: |
              {
                "id": "resp_67ccd3a9da748190baa7f1570fe91ac604becb25c45c1d41",
                "object": "response",
                "created_at": 1741476777,
                "status": "completed",
                "error": null,
                "incomplete_details": null,
                "instructions": null,
                "max_output_tokens": null,
                "model": "gpt-4.1-2025-04-14",
                "output": [
                  {
                    "type": "message",
                    "id": "msg_67ccd3acc8d48190a77525dc6de64b4104becb25c45c1d41",
                    "status": "completed",
                    "role": "assistant",
                    "content": [
                      {
                        "type": "output_text",
                        "text": "The image depicts a scenic landscape with a wooden boardwalk or pathway leading through lush, green grass under a blue sky with some clouds. The setting suggests a peaceful natural area, possibly a park or nature reserve. There are trees and shrubs in the background.",
                        "annotations": []
                      }
                    ]
                  }
                ],
                "parallel_tool_calls": true,
                "previous_response_id": null,
                "reasoning": {
                  "effort": null,
                  "summary": null
                },
                "store": true,
                "temperature": 1.0,
                "text": {
                  "format": {
                    "type": "text"
                  }
                },
                "tool_choice": "auto",
                "tools": [],
                "top_p": 1.0,
                "truncation": "disabled",
                "usage": {
                  "input_tokens": 328,
                  "input_tokens_details": {
                    "cached_tokens": 0
                  },
                  "output_tokens": 52,
                  "output_tokens_details": {
                    "reasoning_tokens": 0
                  },
                  "total_tokens": 380
                },
                "user": null,
                "metadata": {}
              }
          - title: Web search
            request:
              curl: |
                curl https://api.openai.com/v1/responses \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -d '{
                    "model": "gpt-4.1",
                    "tools": [{ "type": "web_search_preview" }],
                    "input": "What was a positive news story from today?"
                  }'
              javascript: |
                import OpenAI from "openai";

                const openai = new OpenAI();

                const response = await openai.responses.create({
                    model: "gpt-4.1",
                    tools: [{ type: "web_search_preview" }],
                    input: "What was a positive news story from today?",
                });

                console.log(response);
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                response = client.responses.create()
                print(response.id)
              csharp: |
                using System;

                using OpenAI.Responses;

                OpenAIResponseClient client = new(
                    model: "gpt-4.1",
                    apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
                );

                string userInputText = "What was a positive news story from today?";

                ResponseCreationOptions options = new()
                {
                    Tools =
                    {
                        ResponseTool.CreateWebSearchTool()
                    },
                };

                OpenAIResponse response = client.CreateResponse(userInputText, options);

                Console.WriteLine(response.GetOutputText());
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const response = await client.responses.create();

                console.log(response.id);
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                  "github.com/openai/openai-go/responses"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  response, err := client.Responses.New(context.TODO(), responses.ResponseNewParams{

                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", response.ID)
                }
              java: |-
                package com.openai.example;

                import com.openai.client.OpenAIClient;
                import com.openai.client.okhttp.OpenAIOkHttpClient;
                import com.openai.models.responses.Response;
                import com.openai.models.responses.ResponseCreateParams;

                public final class Main {
                    private Main() {}

                    public static void main(String[] args) {
                        // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                        Response response = client.responses().create();
                    }
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.responses.Response
                import com.openai.models.responses.ResponseCreateParams

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val response: Response = client.responses().create()
                }
              ruby: |-
                require "openai"

                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )

                response = openai.responses.create

                puts(response)
            response: |
              {
                "id": "resp_67ccf18ef5fc8190b16dbee19bc54e5f087bb177ab789d5c",
                "object": "response",
                "created_at": 1741484430,
                "status": "completed",
                "error": null,
                "incomplete_details": null,
                "instructions": null,
                "max_output_tokens": null,
                "model": "gpt-4.1-2025-04-14",
                "output": [
                  {
                    "type": "web_search_call",
                    "id": "ws_67ccf18f64008190a39b619f4c8455ef087bb177ab789d5c",
                    "status": "completed"
                  },
                  {
                    "type": "message",
                    "id": "msg_67ccf190ca3881909d433c50b1f6357e087bb177ab789d5c",
                    "status": "completed",
                    "role": "assistant",
                    "content": [
                      {
                        "type": "output_text",
                        "text": "As of today, March 9, 2025, one notable positive news story...",
                        "annotations": [
                          {
                            "type": "url_citation",
                            "start_index": 442,
                            "end_index": 557,
                            "url": "https://.../?utm_source=chatgpt.com",
                            "title": "..."
                          },
                          {
                            "type": "url_citation",
                            "start_index": 962,
                            "end_index": 1077,
                            "url": "https://.../?utm_source=chatgpt.com",
                            "title": "..."
                          },
                          {
                            "type": "url_citation",
                            "start_index": 1336,
                            "end_index": 1451,
                            "url": "https://.../?utm_source=chatgpt.com",
                            "title": "..."
                          }
                        ]
                      }
                    ]
                  }
                ],
                "parallel_tool_calls": true,
                "previous_response_id": null,
                "reasoning": {
                  "effort": null,
                  "summary": null
                },
                "store": true,
                "temperature": 1.0,
                "text": {
                  "format": {
                    "type": "text"
                  }
                },
                "tool_choice": "auto",
                "tools": [
                  {
                    "type": "web_search_preview",
                    "domains": [],
                    "search_context_size": "medium",
                    "user_location": {
                      "type": "approximate",
                      "city": null,
                      "country": "US",
                      "region": null,
                      "timezone": null
                    }
                  }
                ],
                "top_p": 1.0,
                "truncation": "disabled",
                "usage": {
                  "input_tokens": 328,
                  "input_tokens_details": {
                    "cached_tokens": 0
                  },
                  "output_tokens": 356,
                  "output_tokens_details": {
                    "reasoning_tokens": 0
                  },
                  "total_tokens": 684
                },
                "user": null,
                "metadata": {}
              }
          - title: File search
            request:
              curl: |
                curl https://api.openai.com/v1/responses \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -d '{
                    "model": "gpt-4.1",
                    "tools": [{
                      "type": "file_search",
                      "vector_store_ids": ["vs_1234567890"],
                      "max_num_results": 20
                    }],
                    "input": "What are the attributes of an ancient brown dragon?"
                  }'
              javascript: |
                import OpenAI from "openai";

                const openai = new OpenAI();

                const response = await openai.responses.create({
                    model: "gpt-4.1",
                    tools: [{
                      type: "file_search",
                      vector_store_ids: ["vs_1234567890"],
                      max_num_results: 20
                    }],
                    input: "What are the attributes of an ancient brown dragon?",
                });

                console.log(response);
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                response = client.responses.create()
                print(response.id)
              csharp: |
                using System;

                using OpenAI.Responses;

                OpenAIResponseClient client = new(
                    model: "gpt-4.1",
                    apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
                );

                string userInputText = "What are the attributes of an ancient brown dragon?";

                ResponseCreationOptions options = new()
                {
                    Tools =
                    {
                        ResponseTool.CreateFileSearchTool(
                            vectorStoreIds: ["vs_1234567890"],
                            maxResultCount: 20
                        )
                    },
                };

                OpenAIResponse response = client.CreateResponse(userInputText, options);

                Console.WriteLine(response.GetOutputText());
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const response = await client.responses.create();

                console.log(response.id);
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                  "github.com/openai/openai-go/responses"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  response, err := client.Responses.New(context.TODO(), responses.ResponseNewParams{

                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", response.ID)
                }
              java: |-
                package com.openai.example;

                import com.openai.client.OpenAIClient;
                import com.openai.client.okhttp.OpenAIOkHttpClient;
                import com.openai.models.responses.Response;
                import com.openai.models.responses.ResponseCreateParams;

                public final class Main {
                    private Main() {}

                    public static void main(String[] args) {
                        // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                        Response response = client.responses().create();
                    }
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.responses.Response
                import com.openai.models.responses.ResponseCreateParams

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val response: Response = client.responses().create()
                }
              ruby: |-
                require "openai"

                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )

                response = openai.responses.create

                puts(response)
            response: |
              {
                "id": "resp_67ccf4c55fc48190b71bd0463ad3306d09504fb6872380d7",
                "object": "response",
                "created_at": 1741485253,
                "status": "completed",
                "error": null,
                "incomplete_details": null,
                "instructions": null,
                "max_output_tokens": null,
                "model": "gpt-4.1-2025-04-14",
                "output": [
                  {
                    "type": "file_search_call",
                    "id": "fs_67ccf4c63cd08190887ef6464ba5681609504fb6872380d7",
                    "status": "completed",
                    "queries": [
                      "attributes of an ancient brown dragon"
                    ],
                    "results": null
                  },
                  {
                    "type": "message",
                    "id": "msg_67ccf4c93e5c81909d595b369351a9d309504fb6872380d7",
                    "status": "completed",
                    "role": "assistant",
                    "content": [
                      {
                        "type": "output_text",
                        "text": "The attributes of an ancient brown dragon include...",
                        "annotations": [
                          {
                            "type": "file_citation",
                            "index": 320,
                            "file_id": "file-4wDz5b167pAf72nx1h9eiN",
                            "filename": "dragons.pdf"
                          },
                          {
                            "type": "file_citation",
                            "index": 576,
                            "file_id": "file-4wDz5b167pAf72nx1h9eiN",
                            "filename": "dragons.pdf"
                          },
                          {
                            "type": "file_citation",
                            "index": 815,
                            "file_id": "file-4wDz5b167pAf72nx1h9eiN",
                            "filename": "dragons.pdf"
                          },
                          {
                            "type": "file_citation",
                            "index": 815,
                            "file_id": "file-4wDz5b167pAf72nx1h9eiN",
                            "filename": "dragons.pdf"
                          },
                          {
                            "type": "file_citation",
                            "index": 1030,
                            "file_id": "file-4wDz5b167pAf72nx1h9eiN",
                            "filename": "dragons.pdf"
                          },
                          {
                            "type": "file_citation",
                            "index": 1030,
                            "file_id": "file-4wDz5b167pAf72nx1h9eiN",
                            "filename": "dragons.pdf"
                          },
                          {
                            "type": "file_citation",
                            "index": 1156,
                            "file_id": "file-4wDz5b167pAf72nx1h9eiN",
                            "filename": "dragons.pdf"
                          },
                          {
                            "type": "file_citation",
                            "index": 1225,
                            "file_id": "file-4wDz5b167pAf72nx1h9eiN",
                            "filename": "dragons.pdf"
                          }
                        ]
                      }
                    ]
                  }
                ],
                "parallel_tool_calls": true,
                "previous_response_id": null,
                "reasoning": {
                  "effort": null,
                  "summary": null
                },
                "store": true,
                "temperature": 1.0,
                "text": {
                  "format": {
                    "type": "text"
                  }
                },
                "tool_choice": "auto",
                "tools": [
                  {
                    "type": "file_search",
                    "filters": null,
                    "max_num_results": 20,
                    "ranking_options": {
                      "ranker": "auto",
                      "score_threshold": 0.0
                    },
                    "vector_store_ids": [
                      "vs_1234567890"
                    ]
                  }
                ],
                "top_p": 1.0,
                "truncation": "disabled",
                "usage": {
                  "input_tokens": 18307,
                  "input_tokens_details": {
                    "cached_tokens": 0
                  },
                  "output_tokens": 348,
                  "output_tokens_details": {
                    "reasoning_tokens": 0
                  },
                  "total_tokens": 18655
                },
                "user": null,
                "metadata": {}
              }      
          - title: Streaming
            request:
              curl: |
                curl https://api.openai.com/v1/responses \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -d '{
                    "model": "gpt-4.1",
                    "instructions": "You are a helpful assistant.",
                    "input": "Hello!",
                    "stream": true
                  }'
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                response = client.responses.create()
                print(response.id)
              javascript: |
                import OpenAI from "openai";

                const openai = new OpenAI();

                const response = await openai.responses.create({
                    model: "gpt-4.1",
                    instructions: "You are a helpful assistant.",
                    input: "Hello!",
                    stream: true,
                });

                for await (const event of response) {
                    console.log(event);
                }
              csharp: >
                using System;

                using System.ClientModel;

                using System.Threading.Tasks;


                using OpenAI.Responses;


                OpenAIResponseClient client = new(
                    model: "gpt-4.1",
                    apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
                );


                string userInputText = "Hello!";


                ResponseCreationOptions options = new()

                {
                    Instructions = "You are a helpful assistant.",
                };


                AsyncCollectionResult<StreamingResponseUpdate> responseUpdates =
                client.CreateResponseStreamingAsync(userInputText, options);


                await foreach (StreamingResponseUpdate responseUpdate in responseUpdates)

                {
                    if (responseUpdate is StreamingResponseOutputTextDeltaUpdate outputTextDeltaUpdate)
                    {
                        Console.Write(outputTextDeltaUpdate.Delta);
                    }
                }
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const response = await client.responses.create();

                console.log(response.id);
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                  "github.com/openai/openai-go/responses"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  response, err := client.Responses.New(context.TODO(), responses.ResponseNewParams{

                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", response.ID)
                }
              java: |-
                package com.openai.example;

                import com.openai.client.OpenAIClient;
                import com.openai.client.okhttp.OpenAIOkHttpClient;
                import com.openai.models.responses.Response;
                import com.openai.models.responses.ResponseCreateParams;

                public final class Main {
                    private Main() {}

                    public static void main(String[] args) {
                        // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                        Response response = client.responses().create();
                    }
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.responses.Response
                import com.openai.models.responses.ResponseCreateParams

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val response: Response = client.responses().create()
                }
              ruby: |-
                require "openai"

                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )

                response = openai.responses.create

                puts(response)
            response: >
              event: response.created

              data:
              {"type":"response.created","response":{"id":"resp_67c9fdcecf488190bdd9a0409de3a1ec07b8b0ad4e5eb654","object":"response","created_at":1741290958,"status":"in_progress","error":null,"incomplete_details":null,"instructions":"You
              are a helpful
              assistant.","max_output_tokens":null,"model":"gpt-4.1-2025-04-14","output":[],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"summary":null},"store":true,"temperature":1.0,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"truncation":"disabled","usage":null,"user":null,"metadata":{}}}


              event: response.in_progress

              data:
              {"type":"response.in_progress","response":{"id":"resp_67c9fdcecf488190bdd9a0409de3a1ec07b8b0ad4e5eb654","object":"response","created_at":1741290958,"status":"in_progress","error":null,"incomplete_details":null,"instructions":"You
              are a helpful
              assistant.","max_output_tokens":null,"model":"gpt-4.1-2025-04-14","output":[],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"summary":null},"store":true,"temperature":1.0,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"truncation":"disabled","usage":null,"user":null,"metadata":{}}}


              event: response.output_item.added

              data:
              {"type":"response.output_item.added","output_index":0,"item":{"id":"msg_67c9fdcf37fc8190ba82116e33fb28c507b8b0ad4e5eb654","type":"message","status":"in_progress","role":"assistant","content":[]}}


              event: response.content_part.added

              data:
              {"type":"response.content_part.added","item_id":"msg_67c9fdcf37fc8190ba82116e33fb28c507b8b0ad4e5eb654","output_index":0,"content_index":0,"part":{"type":"output_text","text":"","annotations":[]}}


              event: response.output_text.delta

              data:
              {"type":"response.output_text.delta","item_id":"msg_67c9fdcf37fc8190ba82116e33fb28c507b8b0ad4e5eb654","output_index":0,"content_index":0,"delta":"Hi"}


              ...


              event: response.output_text.done

              data:
              {"type":"response.output_text.done","item_id":"msg_67c9fdcf37fc8190ba82116e33fb28c507b8b0ad4e5eb654","output_index":0,"content_index":0,"text":"Hi
              there! How can I assist you today?"}


              event: response.content_part.done

              data:
              {"type":"response.content_part.done","item_id":"msg_67c9fdcf37fc8190ba82116e33fb28c507b8b0ad4e5eb654","output_index":0,"content_index":0,"part":{"type":"output_text","text":"Hi
              there! How can I assist you today?","annotations":[]}}


              event: response.output_item.done

              data:
              {"type":"response.output_item.done","output_index":0,"item":{"id":"msg_67c9fdcf37fc8190ba82116e33fb28c507b8b0ad4e5eb654","type":"message","status":"completed","role":"assistant","content":[{"type":"output_text","text":"Hi
              there! How can I assist you today?","annotations":[]}]}}


              event: response.completed

              data:
              {"type":"response.completed","response":{"id":"resp_67c9fdcecf488190bdd9a0409de3a1ec07b8b0ad4e5eb654","object":"response","created_at":1741290958,"status":"completed","error":null,"incomplete_details":null,"instructions":"You
              are a helpful
              assistant.","max_output_tokens":null,"model":"gpt-4.1-2025-04-14","output":[{"id":"msg_67c9fdcf37fc8190ba82116e33fb28c507b8b0ad4e5eb654","type":"message","status":"completed","role":"assistant","content":[{"type":"output_text","text":"Hi
              there! How can I assist you
              today?","annotations":[]}]}],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"summary":null},"store":true,"temperature":1.0,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"truncation":"disabled","usage":{"input_tokens":37,"output_tokens":11,"output_tokens_details":{"reasoning_tokens":0},"total_tokens":48},"user":null,"metadata":{}}}
          - title: Functions
            request:
              curl: |
                curl https://api.openai.com/v1/responses \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -d '{
                    "model": "gpt-4.1",
                    "input": "What is the weather like in Boston today?",
                    "tools": [
                      {
                        "type": "function",
                        "name": "get_current_weather",
                        "description": "Get the current weather in a given location",
                        "parameters": {
                          "type": "object",
                          "properties": {
                            "location": {
                              "type": "string",
                              "description": "The city and state, e.g. San Francisco, CA"
                            },
                            "unit": {
                              "type": "string",
                              "enum": ["celsius", "fahrenheit"]
                            }
                          },
                          "required": ["location", "unit"]
                        }
                      }
                    ],
                    "tool_choice": "auto"
                  }'
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                response = client.responses.create()
                print(response.id)
              javascript: |
                import OpenAI from "openai";

                const openai = new OpenAI();

                const tools = [
                    {
                        type: "function",
                        name: "get_current_weather",
                        description: "Get the current weather in a given location",
                        parameters: {
                            type: "object",
                            properties: {
                                location: {
                                    type: "string",
                                    description: "The city and state, e.g. San Francisco, CA",
                                },
                                unit: { type: "string", enum: ["celsius", "fahrenheit"] },
                            },
                            required: ["location", "unit"],
                        },
                    },
                ];

                const response = await openai.responses.create({
                    model: "gpt-4.1",
                    tools: tools,
                    input: "What is the weather like in Boston today?",
                    tool_choice: "auto",
                });

                console.log(response);
              csharp: |
                using System;
                using OpenAI.Responses;

                OpenAIResponseClient client = new(
                    model: "gpt-4.1",
                    apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
                );

                ResponseTool getCurrentWeatherFunctionTool = ResponseTool.CreateFunctionTool(
                    functionName: "get_current_weather",
                    functionDescription: "Get the current weather in a given location",
                    functionParameters: BinaryData.FromString("""
                        {
                            "type": "object",
                            "properties": {
                                "location": {
                                    "type": "string",
                                    "description": "The city and state, e.g. San Francisco, CA"
                                },
                                "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]}
                            },
                            "required": ["location", "unit"]
                        }
                        """
                    )
                );

                string userInputText = "What is the weather like in Boston today?";

                ResponseCreationOptions options = new()
                {
                    Tools =
                    {
                        getCurrentWeatherFunctionTool
                    },
                    ToolChoice = ResponseToolChoice.CreateAutoChoice(),
                };

                OpenAIResponse response = client.CreateResponse(userInputText, options);
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const response = await client.responses.create();

                console.log(response.id);
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                  "github.com/openai/openai-go/responses"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  response, err := client.Responses.New(context.TODO(), responses.ResponseNewParams{

                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", response.ID)
                }
              java: |-
                package com.openai.example;

                import com.openai.client.OpenAIClient;
                import com.openai.client.okhttp.OpenAIOkHttpClient;
                import com.openai.models.responses.Response;
                import com.openai.models.responses.ResponseCreateParams;

                public final class Main {
                    private Main() {}

                    public static void main(String[] args) {
                        // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                        Response response = client.responses().create();
                    }
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.responses.Response
                import com.openai.models.responses.ResponseCreateParams

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val response: Response = client.responses().create()
                }
              ruby: |-
                require "openai"

                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )

                response = openai.responses.create

                puts(response)
            response: |
              {
                "id": "resp_67ca09c5efe0819096d0511c92b8c890096610f474011cc0",
                "object": "response",
                "created_at": 1741294021,
                "status": "completed",
                "error": null,
                "incomplete_details": null,
                "instructions": null,
                "max_output_tokens": null,
                "model": "gpt-4.1-2025-04-14",
                "output": [
                  {
                    "type": "function_call",
                    "id": "fc_67ca09c6bedc8190a7abfec07b1a1332096610f474011cc0",
                    "call_id": "call_unLAR8MvFNptuiZK6K6HCy5k",
                    "name": "get_current_weather",
                    "arguments": "{\"location\":\"Boston, MA\",\"unit\":\"celsius\"}",
                    "status": "completed"
                  }
                ],
                "parallel_tool_calls": true,
                "previous_response_id": null,
                "reasoning": {
                  "effort": null,
                  "summary": null
                },
                "store": true,
                "temperature": 1.0,
                "text": {
                  "format": {
                    "type": "text"
                  }
                },
                "tool_choice": "auto",
                "tools": [
                  {
                    "type": "function",
                    "description": "Get the current weather in a given location",
                    "name": "get_current_weather",
                    "parameters": {
                      "type": "object",
                      "properties": {
                        "location": {
                          "type": "string",
                          "description": "The city and state, e.g. San Francisco, CA"
                        },
                        "unit": {
                          "type": "string",
                          "enum": [
                            "celsius",
                            "fahrenheit"
                          ]
                        }
                      },
                      "required": [
                        "location",
                        "unit"
                      ]
                    },
                    "strict": true
                  }
                ],
                "top_p": 1.0,
                "truncation": "disabled",
                "usage": {
                  "input_tokens": 291,
                  "output_tokens": 23,
                  "output_tokens_details": {
                    "reasoning_tokens": 0
                  },
                  "total_tokens": 314
                },
                "user": null,
                "metadata": {}
              }
          - title: Reasoning
            request:
              curl: |
                curl https://api.openai.com/v1/responses \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -d '{
                    "model": "o3-mini",
                    "input": "How much wood would a woodchuck chuck?",
                    "reasoning": {
                      "effort": "high"
                    }
                  }'
              javascript: |
                import OpenAI from "openai";
                const openai = new OpenAI();

                const response = await openai.responses.create({
                    model: "o3-mini",
                    input: "How much wood would a woodchuck chuck?",
                    reasoning: {
                      effort: "high"
                    }
                });

                console.log(response);
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                response = client.responses.create()
                print(response.id)
              csharp: |
                using System;
                using OpenAI.Responses;

                OpenAIResponseClient client = new(
                    model: "o3-mini",
                    apiKey: Environment.GetEnvironmentVariable("OPENAI_API_KEY")
                );

                string userInputText = "How much wood would a woodchuck chuck?";

                ResponseCreationOptions options = new()
                {
                    ReasoningOptions = new()
                    {
                        ReasoningEffortLevel = ResponseReasoningEffortLevel.High,
                    },
                };

                OpenAIResponse response = client.CreateResponse(userInputText, options);

                Console.WriteLine(response.GetOutputText());
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const response = await client.responses.create();

                console.log(response.id);
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                  "github.com/openai/openai-go/responses"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  response, err := client.Responses.New(context.TODO(), responses.ResponseNewParams{

                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", response.ID)
                }
              java: |-
                package com.openai.example;

                import com.openai.client.OpenAIClient;
                import com.openai.client.okhttp.OpenAIOkHttpClient;
                import com.openai.models.responses.Response;
                import com.openai.models.responses.ResponseCreateParams;

                public final class Main {
                    private Main() {}

                    public static void main(String[] args) {
                        // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                        Response response = client.responses().create();
                    }
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.responses.Response
                import com.openai.models.responses.ResponseCreateParams

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val response: Response = client.responses().create()
                }
              ruby: |-
                require "openai"

                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )

                response = openai.responses.create

                puts(response)
            response: |
              {
                "id": "resp_67ccd7eca01881908ff0b5146584e408072912b2993db808",
                "object": "response",
                "created_at": 1741477868,
                "status": "completed",
                "error": null,
                "incomplete_details": null,
                "instructions": null,
                "max_output_tokens": null,
                "model": "o1-2024-12-17",
                "output": [
                  {
                    "type": "message",
                    "id": "msg_67ccd7f7b5848190a6f3e95d809f6b44072912b2993db808",
                    "status": "completed",
                    "role": "assistant",
                    "content": [
                      {
                        "type": "output_text",
                        "text": "The classic tongue twister...",
                        "annotations": []
                      }
                    ]
                  }
                ],
                "parallel_tool_calls": true,
                "previous_response_id": null,
                "reasoning": {
                  "effort": "high",
                  "summary": null
                },
                "store": true,
                "temperature": 1.0,
                "text": {
                  "format": {
                    "type": "text"
                  }
                },
                "tool_choice": "auto",
                "tools": [],
                "top_p": 1.0,
                "truncation": "disabled",
                "usage": {
                  "input_tokens": 81,
                  "input_tokens_details": {
                    "cached_tokens": 0
                  },
                  "output_tokens": 1035,
                  "output_tokens_details": {
                    "reasoning_tokens": 832
                  },
                  "total_tokens": 1116
                },
                "user": null,
                "metadata": {}
              }
  /responses/{response_id}:
    get:
      operationId: getResponse
      tags:
        - Responses
      summary: |
        Retrieves a model response with the given ID.
      parameters:
        - in: path
          name: response_id
          required: true
          schema:
            type: string
            example: resp_677efb5139a88190b512bc3fef8e535d
          description: The ID of the response to retrieve.
        - in: query
          name: include
          schema:
            type: array
            items:
              $ref: '#/components/schemas/Includable'
          description: |
            Additional fields to include in the response. See the `include`
            parameter for Response creation above for more information.
        - in: query
          name: stream
          schema:
            type: boolean
          description: >
            If set to true, the model response data will be streamed to the client

            as it is generated using [server-sent
            events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format).

            See the [Streaming section below](/docs/api-reference/responses-streaming)

            for more information.
        - in: query
          name: starting_after
          schema:
            type: integer
          description: |
            The sequence number of the event after which to start streaming.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Response'
      x-oaiMeta:
        name: Get a model response
        group: responses
        returns: |
          The [Response](/docs/api-reference/responses/object) object matching the
          specified ID.
        examples:
          response: |
            {
              "id": "resp_67cb71b351908190a308f3859487620d06981a8637e6bc44",
              "object": "response",
              "created_at": 1741386163,
              "status": "completed",
              "error": null,
              "incomplete_details": null,
              "instructions": null,
              "max_output_tokens": null,
              "model": "gpt-4o-2024-08-06",
              "output": [
                {
                  "type": "message",
                  "id": "msg_67cb71b3c2b0819084d481baaaf148f206981a8637e6bc44",
                  "status": "completed",
                  "role": "assistant",
                  "content": [
                    {
                      "type": "output_text",
                      "text": "Silent circuits hum,  \nThoughts emerge in data streams—  \nDigital dawn breaks.",
                      "annotations": []
                    }
                  ]
                }
              ],
              "parallel_tool_calls": true,
              "previous_response_id": null,
              "reasoning": {
                "effort": null,
                "summary": null
              },
              "store": true,
              "temperature": 1.0,
              "text": {
                "format": {
                  "type": "text"
                }
              },
              "tool_choice": "auto",
              "tools": [],
              "top_p": 1.0,
              "truncation": "disabled",
              "usage": {
                "input_tokens": 32,
                "input_tokens_details": {
                  "cached_tokens": 0
                },
                "output_tokens": 18,
                "output_tokens_details": {
                  "reasoning_tokens": 0
                },
                "total_tokens": 50
              },
              "user": null,
              "metadata": {}
            }
          request:
            curl: |
              curl https://api.openai.com/v1/responses/resp_123 \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY"
            javascript: |
              import OpenAI from "openai";
              const client = new OpenAI();

              const response = await client.responses.retrieve("resp_123");
              console.log(response);
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              response = client.responses.retrieve(
                  response_id="resp_677efb5139a88190b512bc3fef8e535d",
              )
              print(response.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const response = await client.responses.retrieve('resp_677efb5139a88190b512bc3fef8e535d');

              console.log(response.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
                "github.com/openai/openai-go/responses"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                response, err := client.Responses.Get(
                  context.TODO(),
                  "resp_677efb5139a88190b512bc3fef8e535d",
                  responses.ResponseGetParams{

                  },
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", response.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.responses.Response;
              import com.openai.models.responses.ResponseRetrieveParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      Response response = client.responses().retrieve("resp_677efb5139a88190b512bc3fef8e535d");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.responses.Response
              import com.openai.models.responses.ResponseRetrieveParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val response: Response = client.responses().retrieve("resp_677efb5139a88190b512bc3fef8e535d")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              response = openai.responses.retrieve("resp_677efb5139a88190b512bc3fef8e535d")

              puts(response)
    delete:
      operationId: deleteResponse
      tags:
        - Responses
      summary: |
        Deletes a model response with the given ID.
      parameters:
        - in: path
          name: response_id
          required: true
          schema:
            type: string
            example: resp_677efb5139a88190b512bc3fef8e535d
          description: The ID of the response to delete.
      responses:
        '200':
          description: OK
        '404':
          description: Not Found
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Error'
      x-oaiMeta:
        name: Delete a model response
        group: responses
        returns: |
          A success message.
        examples:
          response: |
            {
              "id": "resp_6786a1bec27481909a17d673315b29f6",
              "object": "response",
              "deleted": true
            }
          request:
            curl: |
              curl -X DELETE https://api.openai.com/v1/responses/resp_123 \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY"
            javascript: |
              import OpenAI from "openai";
              const client = new OpenAI();

              const response = await client.responses.del("resp_123");
              console.log(response);
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              client.responses.delete(
                  "resp_677efb5139a88190b512bc3fef8e535d",
              )
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              await client.responses.delete('resp_677efb5139a88190b512bc3fef8e535d');
            go: |
              package main

              import (
                "context"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                err := client.Responses.Delete(context.TODO(), "resp_677efb5139a88190b512bc3fef8e535d")
                if err != nil {
                  panic(err.Error())
                }
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.responses.ResponseDeleteParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      client.responses().delete("resp_677efb5139a88190b512bc3fef8e535d");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.responses.ResponseDeleteParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  client.responses().delete("resp_677efb5139a88190b512bc3fef8e535d")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              result = openai.responses.delete("resp_677efb5139a88190b512bc3fef8e535d")

              puts(result)
  /responses/{response_id}/cancel:
    post:
      operationId: cancelResponse
      tags:
        - Responses
      summary: |
        Cancels a model response with the given ID. Only responses created with
        the `background` parameter set to `true` can be cancelled. 
        [Learn more](/docs/guides/background).
      parameters:
        - in: path
          name: response_id
          required: true
          schema:
            type: string
            example: resp_677efb5139a88190b512bc3fef8e535d
          description: The ID of the response to cancel.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Response'
        '404':
          description: Not Found
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Error'
      x-oaiMeta:
        name: Cancel a response
        group: responses
        returns: |
          A [Response](/docs/api-reference/responses/object) object.
        examples:
          response: |
            {
              "id": "resp_67cb71b351908190a308f3859487620d06981a8637e6bc44",
              "object": "response",
              "created_at": 1741386163,
              "status": "completed",
              "error": null,
              "incomplete_details": null,
              "instructions": null,
              "max_output_tokens": null,
              "model": "gpt-4o-2024-08-06",
              "output": [
                {
                  "type": "message",
                  "id": "msg_67cb71b3c2b0819084d481baaaf148f206981a8637e6bc44",
                  "status": "completed",
                  "role": "assistant",
                  "content": [
                    {
                      "type": "output_text",
                      "text": "Silent circuits hum,  \nThoughts emerge in data streams—  \nDigital dawn breaks.",
                      "annotations": []
                    }
                  ]
                }
              ],
              "parallel_tool_calls": true,
              "previous_response_id": null,
              "reasoning": {
                "effort": null,
                "summary": null
              },
              "store": true,
              "temperature": 1.0,
              "text": {
                "format": {
                  "type": "text"
                }
              },
              "tool_choice": "auto",
              "tools": [],
              "top_p": 1.0,
              "truncation": "disabled",
              "usage": {
                "input_tokens": 32,
                "input_tokens_details": {
                  "cached_tokens": 0
                },
                "output_tokens": 18,
                "output_tokens_details": {
                  "reasoning_tokens": 0
                },
                "total_tokens": 50
              },
              "user": null,
              "metadata": {}
            }
          request:
            curl: |
              curl -X POST https://api.openai.com/v1/responses/resp_123/cancel \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY"
            javascript: |
              import OpenAI from "openai";
              const client = new OpenAI();

              const response = await client.responses.cancel("resp_123");
              console.log(response);  
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              response = client.responses.cancel(
                  "resp_677efb5139a88190b512bc3fef8e535d",
              )
              print(response.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const response = await client.responses.cancel('resp_677efb5139a88190b512bc3fef8e535d');

              console.log(response.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                response, err := client.Responses.Cancel(context.TODO(), "resp_677efb5139a88190b512bc3fef8e535d")
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", response.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.responses.Response;
              import com.openai.models.responses.ResponseCancelParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      Response response = client.responses().cancel("resp_677efb5139a88190b512bc3fef8e535d");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.responses.Response
              import com.openai.models.responses.ResponseCancelParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val response: Response = client.responses().cancel("resp_677efb5139a88190b512bc3fef8e535d")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              response = openai.responses.cancel("resp_677efb5139a88190b512bc3fef8e535d")

              puts(response)
  /responses/{response_id}/input_items:
    get:
      operationId: listInputItems
      tags:
        - Responses
      summary: Returns a list of input items for a given response.
      parameters:
        - in: path
          name: response_id
          required: true
          schema:
            type: string
          description: The ID of the response to retrieve input items for.
        - name: limit
          in: query
          description: |
            A limit on the number of objects to be returned. Limit can range between
            1 and 100, and the default is 20.
          required: false
          schema:
            type: integer
            default: 20
        - in: query
          name: order
          schema:
            type: string
            enum:
              - asc
              - desc
          description: |
            The order to return the input items in. Default is `desc`.
            - `asc`: Return the input items in ascending order.
            - `desc`: Return the input items in descending order.
        - in: query
          name: after
          schema:
            type: string
          description: |
            An item ID to list items after, used in pagination.
        - in: query
          name: before
          schema:
            type: string
          description: |
            An item ID to list items before, used in pagination.
        - in: query
          name: include
          schema:
            type: array
            items:
              $ref: '#/components/schemas/Includable'
          description: |
            Additional fields to include in the response. See the `include`
            parameter for Response creation above for more information.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ResponseItemList'
      x-oaiMeta:
        name: List input items
        group: responses
        returns: A list of input item objects.
        examples:
          response: |
            {
              "object": "list",
              "data": [
                {
                  "id": "msg_abc123",
                  "type": "message",
                  "role": "user",
                  "content": [
                    {
                      "type": "input_text",
                      "text": "Tell me a three sentence bedtime story about a unicorn."
                    }
                  ]
                }
              ],
              "first_id": "msg_abc123",
              "last_id": "msg_abc123",
              "has_more": false
            }
          request:
            curl: |
              curl https://api.openai.com/v1/responses/resp_abc123/input_items \
                -H "Content-Type: application/json" \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            javascript: |
              import OpenAI from "openai";
              const client = new OpenAI();

              const response = await client.responses.inputItems.list("resp_123");
              console.log(response.data);  
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              page = client.responses.input_items.list(
                  response_id="response_id",
              )
              page = page.data[0]
              print(page)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              // Automatically fetches more pages as needed.
              for await (const responseItem of client.responses.inputItems.list('response_id')) {
                console.log(responseItem);
              }
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
                "github.com/openai/openai-go/responses"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                page, err := client.Responses.InputItems.List(
                  context.TODO(),
                  "response_id",
                  responses.InputItemListParams{

                  },
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", page)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.responses.inputitems.InputItemListPage;
              import com.openai.models.responses.inputitems.InputItemListParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      InputItemListPage page = client.responses().inputItems().list("response_id");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.responses.inputitems.InputItemListPage
              import com.openai.models.responses.inputitems.InputItemListParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val page: InputItemListPage = client.responses().inputItems().list("response_id")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              page = openai.responses.input_items.list("response_id")

              puts(page)
  /threads:
    post:
      operationId: createThread
      tags:
        - Assistants
      summary: Create a thread.
      requestBody:
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateThreadRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ThreadObject'
      x-oaiMeta:
        name: Create thread
        group: threads
        beta: true
        returns: A [thread](/docs/api-reference/threads) object.
        examples:
          - title: Empty
            request:
              curl: |
                curl https://api.openai.com/v1/threads \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -H "OpenAI-Beta: assistants=v2" \
                  -d ''
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                thread = client.beta.threads.create()
                print(thread.id)
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const thread = await client.beta.threads.create();

                console.log(thread.id);
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  thread, err := client.Beta.Threads.New(context.TODO(), openai.BetaThreadNewParams{

                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", thread.ID)
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.beta.threads.Thread
                import com.openai.models.beta.threads.ThreadCreateParams

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val thread: Thread = client.beta().threads().create()
                }
              ruby: |-
                require "openai"

                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )

                thread = openai.beta.threads.create

                puts(thread)
            response: |
              {
                "id": "thread_abc123",
                "object": "thread",
                "created_at": 1699012949,
                "metadata": {},
                "tool_resources": {}
              }
          - title: Messages
            request:
              curl: |
                curl https://api.openai.com/v1/threads \
                -H "Content-Type: application/json" \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "OpenAI-Beta: assistants=v2" \
                -d '{
                    "messages": [{
                      "role": "user",
                      "content": "Hello, what is AI?"
                    }, {
                      "role": "user",
                      "content": "How does AI work? Explain it in simple terms."
                    }]
                  }'
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                thread = client.beta.threads.create()
                print(thread.id)
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const thread = await client.beta.threads.create();

                console.log(thread.id);
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  thread, err := client.Beta.Threads.New(context.TODO(), openai.BetaThreadNewParams{

                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", thread.ID)
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.beta.threads.Thread
                import com.openai.models.beta.threads.ThreadCreateParams

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val thread: Thread = client.beta().threads().create()
                }
              ruby: |-
                require "openai"

                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )

                thread = openai.beta.threads.create

                puts(thread)
            response: |
              {
                "id": "thread_abc123",
                "object": "thread",
                "created_at": 1699014083,
                "metadata": {},
                "tool_resources": {}
              }
  /threads/runs:
    post:
      operationId: createThreadAndRun
      tags:
        - Assistants
      summary: Create a thread and run it in one request.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateThreadAndRunRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/RunObject'
      x-oaiMeta:
        name: Create thread and run
        group: threads
        beta: true
        returns: A [run](/docs/api-reference/runs/object) object.
        examples:
          - title: Default
            request:
              curl: |
                curl https://api.openai.com/v1/threads/runs \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -H "Content-Type: application/json" \
                  -H "OpenAI-Beta: assistants=v2" \
                  -d '{
                      "assistant_id": "asst_abc123",
                      "thread": {
                        "messages": [
                          {"role": "user", "content": "Explain deep learning to a 5 year old."}
                        ]
                      }
                    }'
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                run = client.beta.threads.create_and_run(
                    assistant_id="assistant_id",
                )
                print(run.id)
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const run = await client.beta.threads.createAndRun({ assistant_id: 'assistant_id' });

                console.log(run.id);
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  run, err := client.Beta.Threads.NewAndRun(context.TODO(), openai.BetaThreadNewAndRunParams{
                    AssistantID: "assistant_id",
                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", run.ID)
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.beta.threads.ThreadCreateAndRunParams
                import com.openai.models.beta.threads.runs.Run

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val params: ThreadCreateAndRunParams = ThreadCreateAndRunParams.builder()
                        .assistantId("assistant_id")
                        .build()
                    val run: Run = client.beta().threads().createAndRun(params)
                }
              ruby: |-
                require "openai"

                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )

                run = openai.beta.threads.create_and_run(assistant_id: "assistant_id")

                puts(run)
            response: |
              {
                "id": "run_abc123",
                "object": "thread.run",
                "created_at": 1699076792,
                "assistant_id": "asst_abc123",
                "thread_id": "thread_abc123",
                "status": "queued",
                "started_at": null,
                "expires_at": 1699077392,
                "cancelled_at": null,
                "failed_at": null,
                "completed_at": null,
                "required_action": null,
                "last_error": null,
                "model": "gpt-4o",
                "instructions": "You are a helpful assistant.",
                "tools": [],
                "tool_resources": {},
                "metadata": {},
                "temperature": 1.0,
                "top_p": 1.0,
                "max_completion_tokens": null,
                "max_prompt_tokens": null,
                "truncation_strategy": {
                  "type": "auto",
                  "last_messages": null
                },
                "incomplete_details": null,
                "usage": null,
                "response_format": "auto",
                "tool_choice": "auto",
                "parallel_tool_calls": true
              }
          - title: Streaming
            request:
              curl: |
                curl https://api.openai.com/v1/threads/runs \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -H "Content-Type: application/json" \
                  -H "OpenAI-Beta: assistants=v2" \
                  -d '{
                    "assistant_id": "asst_123",
                    "thread": {
                      "messages": [
                        {"role": "user", "content": "Hello"}
                      ]
                    },
                    "stream": true
                  }'
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                run = client.beta.threads.create_and_run(
                    assistant_id="assistant_id",
                )
                print(run.id)
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const run = await client.beta.threads.createAndRun({ assistant_id: 'assistant_id' });

                console.log(run.id);
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  run, err := client.Beta.Threads.NewAndRun(context.TODO(), openai.BetaThreadNewAndRunParams{
                    AssistantID: "assistant_id",
                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", run.ID)
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.beta.threads.ThreadCreateAndRunParams
                import com.openai.models.beta.threads.runs.Run

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val params: ThreadCreateAndRunParams = ThreadCreateAndRunParams.builder()
                        .assistantId("assistant_id")
                        .build()
                    val run: Run = client.beta().threads().createAndRun(params)
                }
              ruby: |-
                require "openai"

                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )

                run = openai.beta.threads.create_and_run(assistant_id: "assistant_id")

                puts(run)
            response: >
              event: thread.created

              data: {"id":"thread_123","object":"thread","created_at":1710348075,"metadata":{}}


              event: thread.run.created

              data:
              {"id":"run_123","object":"thread.run","created_at":1710348075,"assistant_id":"asst_123","thread_id":"thread_123","status":"queued","started_at":null,"expires_at":1710348675,"cancelled_at":null,"failed_at":null,"completed_at":null,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[],"tool_resources":{},"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":null,"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}


              event: thread.run.queued

              data:
              {"id":"run_123","object":"thread.run","created_at":1710348075,"assistant_id":"asst_123","thread_id":"thread_123","status":"queued","started_at":null,"expires_at":1710348675,"cancelled_at":null,"failed_at":null,"completed_at":null,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[],"tool_resources":{},"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":null,"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}


              event: thread.run.in_progress

              data:
              {"id":"run_123","object":"thread.run","created_at":1710348075,"assistant_id":"asst_123","thread_id":"thread_123","status":"in_progress","started_at":null,"expires_at":1710348675,"cancelled_at":null,"failed_at":null,"completed_at":null,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[],"tool_resources":{},"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":null,"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}


              event: thread.run.step.created

              data:
              {"id":"step_001","object":"thread.run.step","created_at":1710348076,"run_id":"run_123","assistant_id":"asst_123","thread_id":"thread_123","type":"message_creation","status":"in_progress","cancelled_at":null,"completed_at":null,"expires_at":1710348675,"failed_at":null,"last_error":null,"step_details":{"type":"message_creation","message_creation":{"message_id":"msg_001"}},"usage":null}


              event: thread.run.step.in_progress

              data:
              {"id":"step_001","object":"thread.run.step","created_at":1710348076,"run_id":"run_123","assistant_id":"asst_123","thread_id":"thread_123","type":"message_creation","status":"in_progress","cancelled_at":null,"completed_at":null,"expires_at":1710348675,"failed_at":null,"last_error":null,"step_details":{"type":"message_creation","message_creation":{"message_id":"msg_001"}},"usage":null}


              event: thread.message.created

              data:
              {"id":"msg_001","object":"thread.message","created_at":1710348076,"assistant_id":"asst_123","thread_id":"thread_123","run_id":"run_123","status":"in_progress","incomplete_details":null,"incomplete_at":null,"completed_at":null,"role":"assistant","content":[],
              "metadata":{}}


              event: thread.message.in_progress

              data:
              {"id":"msg_001","object":"thread.message","created_at":1710348076,"assistant_id":"asst_123","thread_id":"thread_123","run_id":"run_123","status":"in_progress","incomplete_details":null,"incomplete_at":null,"completed_at":null,"role":"assistant","content":[],
              "metadata":{}}


              event: thread.message.delta

              data:
              {"id":"msg_001","object":"thread.message.delta","delta":{"content":[{"index":0,"type":"text","text":{"value":"Hello","annotations":[]}}]}}


              ...


              event: thread.message.delta

              data:
              {"id":"msg_001","object":"thread.message.delta","delta":{"content":[{"index":0,"type":"text","text":{"value":"
              today"}}]}}


              event: thread.message.delta

              data:
              {"id":"msg_001","object":"thread.message.delta","delta":{"content":[{"index":0,"type":"text","text":{"value":"?"}}]}}


              event: thread.message.completed

              data:
              {"id":"msg_001","object":"thread.message","created_at":1710348076,"assistant_id":"asst_123","thread_id":"thread_123","run_id":"run_123","status":"completed","incomplete_details":null,"incomplete_at":null,"completed_at":1710348077,"role":"assistant","content":[{"type":"text","text":{"value":"Hello!
              How can I assist you today?","annotations":[]}}], "metadata":{}}


              event: thread.run.step.completed

              data:
              {"id":"step_001","object":"thread.run.step","created_at":1710348076,"run_id":"run_123","assistant_id":"asst_123","thread_id":"thread_123","type":"message_creation","status":"completed","cancelled_at":null,"completed_at":1710348077,"expires_at":1710348675,"failed_at":null,"last_error":null,"step_details":{"type":"message_creation","message_creation":{"message_id":"msg_001"}},"usage":{"prompt_tokens":20,"completion_tokens":11,"total_tokens":31}}


              event: thread.run.completed

              {"id":"run_123","object":"thread.run","created_at":1710348076,"assistant_id":"asst_123","thread_id":"thread_123","status":"completed","started_at":1713226836,"expires_at":null,"cancelled_at":null,"failed_at":null,"completed_at":1713226837,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":{"prompt_tokens":345,"completion_tokens":11,"total_tokens":356},"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}


              event: done

              data: [DONE]
          - title: Streaming with Functions
            request:
              curl: |
                curl https://api.openai.com/v1/threads/runs \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -H "Content-Type: application/json" \
                  -H "OpenAI-Beta: assistants=v2" \
                  -d '{
                    "assistant_id": "asst_abc123",
                    "thread": {
                      "messages": [
                        {"role": "user", "content": "What is the weather like in San Francisco?"}
                      ]
                    },
                    "tools": [
                      {
                        "type": "function",
                        "function": {
                          "name": "get_current_weather",
                          "description": "Get the current weather in a given location",
                          "parameters": {
                            "type": "object",
                            "properties": {
                              "location": {
                                "type": "string",
                                "description": "The city and state, e.g. San Francisco, CA"
                              },
                              "unit": {
                                "type": "string",
                                "enum": ["celsius", "fahrenheit"]
                              }
                            },
                            "required": ["location"]
                          }
                        }
                      }
                    ],
                    "stream": true
                  }'
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                run = client.beta.threads.create_and_run(
                    assistant_id="assistant_id",
                )
                print(run.id)
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const run = await client.beta.threads.createAndRun({ assistant_id: 'assistant_id' });

                console.log(run.id);
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  run, err := client.Beta.Threads.NewAndRun(context.TODO(), openai.BetaThreadNewAndRunParams{
                    AssistantID: "assistant_id",
                  })
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", run.ID)
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.beta.threads.ThreadCreateAndRunParams
                import com.openai.models.beta.threads.runs.Run

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val params: ThreadCreateAndRunParams = ThreadCreateAndRunParams.builder()
                        .assistantId("assistant_id")
                        .build()
                    val run: Run = client.beta().threads().createAndRun(params)
                }
              ruby: |-
                require "openai"

                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )

                run = openai.beta.threads.create_and_run(assistant_id: "assistant_id")

                puts(run)
            response: >
              event: thread.created

              data: {"id":"thread_123","object":"thread","created_at":1710351818,"metadata":{}}


              event: thread.run.created

              data:
              {"id":"run_123","object":"thread.run","created_at":1710351818,"assistant_id":"asst_123","thread_id":"thread_123","status":"queued","started_at":null,"expires_at":1710352418,"cancelled_at":null,"failed_at":null,"completed_at":null,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[{"type":"function","function":{"name":"get_current_weather","description":"Get
              the current weather in a given
              location","parameters":{"type":"object","properties":{"location":{"type":"string","description":"The
              city and state, e.g. San Francisco,
              CA"},"unit":{"type":"string","enum":["celsius","fahrenheit"]}},"required":["location"]}}}],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":null,"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}}


              event: thread.run.queued

              data:
              {"id":"run_123","object":"thread.run","created_at":1710351818,"assistant_id":"asst_123","thread_id":"thread_123","status":"queued","started_at":null,"expires_at":1710352418,"cancelled_at":null,"failed_at":null,"completed_at":null,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[{"type":"function","function":{"name":"get_current_weather","description":"Get
              the current weather in a given
              location","parameters":{"type":"object","properties":{"location":{"type":"string","description":"The
              city and state, e.g. San Francisco,
              CA"},"unit":{"type":"string","enum":["celsius","fahrenheit"]}},"required":["location"]}}}],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":null,"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}}


              event: thread.run.in_progress

              data:
              {"id":"run_123","object":"thread.run","created_at":1710351818,"assistant_id":"asst_123","thread_id":"thread_123","status":"in_progress","started_at":1710351818,"expires_at":1710352418,"cancelled_at":null,"failed_at":null,"completed_at":null,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[{"type":"function","function":{"name":"get_current_weather","description":"Get
              the current weather in a given
              location","parameters":{"type":"object","properties":{"location":{"type":"string","description":"The
              city and state, e.g. San Francisco,
              CA"},"unit":{"type":"string","enum":["celsius","fahrenheit"]}},"required":["location"]}}}],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":null,"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}}


              event: thread.run.step.created

              data:
              {"id":"step_001","object":"thread.run.step","created_at":1710351819,"run_id":"run_123","assistant_id":"asst_123","thread_id":"thread_123","type":"tool_calls","status":"in_progress","cancelled_at":null,"completed_at":null,"expires_at":1710352418,"failed_at":null,"last_error":null,"step_details":{"type":"tool_calls","tool_calls":[]},"usage":null}


              event: thread.run.step.in_progress

              data:
              {"id":"step_001","object":"thread.run.step","created_at":1710351819,"run_id":"run_123","assistant_id":"asst_123","thread_id":"thread_123","type":"tool_calls","status":"in_progress","cancelled_at":null,"completed_at":null,"expires_at":1710352418,"failed_at":null,"last_error":null,"step_details":{"type":"tool_calls","tool_calls":[]},"usage":null}


              event: thread.run.step.delta

              data:
              {"id":"step_001","object":"thread.run.step.delta","delta":{"step_details":{"type":"tool_calls","tool_calls":[{"index":0,"id":"call_XXNp8YGaFrjrSjgqxtC8JJ1B","type":"function","function":{"name":"get_current_weather","arguments":"","output":null}}]}}}


              event: thread.run.step.delta

              data:
              {"id":"step_001","object":"thread.run.step.delta","delta":{"step_details":{"type":"tool_calls","tool_calls":[{"index":0,"type":"function","function":{"arguments":"{\""}}]}}}


              event: thread.run.step.delta

              data:
              {"id":"step_001","object":"thread.run.step.delta","delta":{"step_details":{"type":"tool_calls","tool_calls":[{"index":0,"type":"function","function":{"arguments":"location"}}]}}}


              ...


              event: thread.run.step.delta

              data:
              {"id":"step_001","object":"thread.run.step.delta","delta":{"step_details":{"type":"tool_calls","tool_calls":[{"index":0,"type":"function","function":{"arguments":"ahrenheit"}}]}}}


              event: thread.run.step.delta

              data:
              {"id":"step_001","object":"thread.run.step.delta","delta":{"step_details":{"type":"tool_calls","tool_calls":[{"index":0,"type":"function","function":{"arguments":"\"}"}}]}}}


              event: thread.run.requires_action

              data:
              {"id":"run_123","object":"thread.run","created_at":1710351818,"assistant_id":"asst_123","thread_id":"thread_123","status":"requires_action","started_at":1710351818,"expires_at":1710352418,"cancelled_at":null,"failed_at":null,"completed_at":null,"required_action":{"type":"submit_tool_outputs","submit_tool_outputs":{"tool_calls":[{"id":"call_XXNp8YGaFrjrSjgqxtC8JJ1B","type":"function","function":{"name":"get_current_weather","arguments":"{\"location\":\"San
              Francisco,
              CA\",\"unit\":\"fahrenheit\"}"}}]}},"last_error":null,"model":"gpt-4o","instructions":null,"tools":[{"type":"function","function":{"name":"get_current_weather","description":"Get
              the current weather in a given
              location","parameters":{"type":"object","properties":{"location":{"type":"string","description":"The
              city and state, e.g. San Francisco,
              CA"},"unit":{"type":"string","enum":["celsius","fahrenheit"]}},"required":["location"]}}}],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":{"prompt_tokens":345,"completion_tokens":11,"total_tokens":356},"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}}


              event: done

              data: [DONE]
  /threads/{thread_id}:
    get:
      operationId: getThread
      tags:
        - Assistants
      summary: Retrieves a thread.
      parameters:
        - in: path
          name: thread_id
          required: true
          schema:
            type: string
          description: The ID of the thread to retrieve.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ThreadObject'
      x-oaiMeta:
        name: Retrieve thread
        group: threads
        beta: true
        returns: The [thread](/docs/api-reference/threads/object) object matching the specified ID.
        examples:
          response: |
            {
              "id": "thread_abc123",
              "object": "thread",
              "created_at": 1699014083,
              "metadata": {},
              "tool_resources": {
                "code_interpreter": {
                  "file_ids": []
                }
              }
            }
          request:
            curl: |
              curl https://api.openai.com/v1/threads/thread_abc123 \
                -H "Content-Type: application/json" \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "OpenAI-Beta: assistants=v2"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              thread = client.beta.threads.retrieve(
                  "thread_id",
              )
              print(thread.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const thread = await client.beta.threads.retrieve('thread_id');

              console.log(thread.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                thread, err := client.Beta.Threads.Get(context.TODO(), "thread_id")
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", thread.ID)
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.beta.threads.Thread
              import com.openai.models.beta.threads.ThreadRetrieveParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val thread: Thread = client.beta().threads().retrieve("thread_id")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              thread = openai.beta.threads.retrieve("thread_id")

              puts(thread)
    post:
      operationId: modifyThread
      tags:
        - Assistants
      summary: Modifies a thread.
      parameters:
        - in: path
          name: thread_id
          required: true
          schema:
            type: string
          description: The ID of the thread to modify. Only the `metadata` can be modified.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/ModifyThreadRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ThreadObject'
      x-oaiMeta:
        name: Modify thread
        group: threads
        beta: true
        returns: The modified [thread](/docs/api-reference/threads/object) object matching the specified ID.
        examples:
          response: |
            {
              "id": "thread_abc123",
              "object": "thread",
              "created_at": 1699014083,
              "metadata": {
                "modified": "true",
                "user": "abc123"
              },
              "tool_resources": {}
            }
          request:
            curl: |
              curl https://api.openai.com/v1/threads/thread_abc123 \
                -H "Content-Type: application/json" \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "OpenAI-Beta: assistants=v2" \
                -d '{
                    "metadata": {
                      "modified": "true",
                      "user": "abc123"
                    }
                  }'
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              thread = client.beta.threads.update(
                  thread_id="thread_id",
              )
              print(thread.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const thread = await client.beta.threads.update('thread_id');

              console.log(thread.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                thread, err := client.Beta.Threads.Update(
                  context.TODO(),
                  "thread_id",
                  openai.BetaThreadUpdateParams{

                  },
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", thread.ID)
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.beta.threads.Thread
              import com.openai.models.beta.threads.ThreadUpdateParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val thread: Thread = client.beta().threads().update("thread_id")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              thread = openai.beta.threads.update("thread_id")

              puts(thread)
    delete:
      operationId: deleteThread
      tags:
        - Assistants
      summary: Delete a thread.
      parameters:
        - in: path
          name: thread_id
          required: true
          schema:
            type: string
          description: The ID of the thread to delete.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/DeleteThreadResponse'
      x-oaiMeta:
        name: Delete thread
        group: threads
        beta: true
        returns: Deletion status
        examples:
          response: |
            {
              "id": "thread_abc123",
              "object": "thread.deleted",
              "deleted": true
            }
          request:
            curl: |
              curl https://api.openai.com/v1/threads/thread_abc123 \
                -H "Content-Type: application/json" \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "OpenAI-Beta: assistants=v2" \
                -X DELETE
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              thread_deleted = client.beta.threads.delete(
                  "thread_id",
              )
              print(thread_deleted.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const threadDeleted = await client.beta.threads.delete('thread_id');

              console.log(threadDeleted.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                threadDeleted, err := client.Beta.Threads.Delete(context.TODO(), "thread_id")
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", threadDeleted.ID)
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.beta.threads.ThreadDeleteParams
              import com.openai.models.beta.threads.ThreadDeleted

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val threadDeleted: ThreadDeleted = client.beta().threads().delete("thread_id")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              thread_deleted = openai.beta.threads.delete("thread_id")

              puts(thread_deleted)
  /threads/{thread_id}/messages:
    get:
      operationId: listMessages
      tags:
        - Assistants
      summary: Returns a list of messages for a given thread.
      parameters:
        - in: path
          name: thread_id
          required: true
          schema:
            type: string
          description: The ID of the [thread](/docs/api-reference/threads) the messages belong to.
        - name: limit
          in: query
          description: >
            A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
            default is 20.
          required: false
          schema:
            type: integer
            default: 20
        - name: order
          in: query
          description: >
            Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for
            descending order.
          schema:
            type: string
            default: desc
            enum:
              - asc
              - desc
        - name: after
          in: query
          description: >
            A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
            instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
            call can include after=obj_foo in order to fetch the next page of the list.
          schema:
            type: string
        - name: before
          in: query
          description: >
            A cursor for use in pagination. `before` is an object ID that defines your place in the list. For
            instance, if you make a list request and receive 100 objects, starting with obj_foo, your
            subsequent call can include before=obj_foo in order to fetch the previous page of the list.
          schema:
            type: string
        - name: run_id
          in: query
          description: |
            Filter messages by the run ID that generated them.
          schema:
            type: string
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ListMessagesResponse'
      x-oaiMeta:
        name: List messages
        group: threads
        beta: true
        returns: A list of [message](/docs/api-reference/messages) objects.
        examples:
          response: |
            {
              "object": "list",
              "data": [
                {
                  "id": "msg_abc123",
                  "object": "thread.message",
                  "created_at": 1699016383,
                  "assistant_id": null,
                  "thread_id": "thread_abc123",
                  "run_id": null,
                  "role": "user",
                  "content": [
                    {
                      "type": "text",
                      "text": {
                        "value": "How does AI work? Explain it in simple terms.",
                        "annotations": []
                      }
                    }
                  ],
                  "attachments": [],
                  "metadata": {}
                },
                {
                  "id": "msg_abc456",
                  "object": "thread.message",
                  "created_at": 1699016383,
                  "assistant_id": null,
                  "thread_id": "thread_abc123",
                  "run_id": null,
                  "role": "user",
                  "content": [
                    {
                      "type": "text",
                      "text": {
                        "value": "Hello, what is AI?",
                        "annotations": []
                      }
                    }
                  ],
                  "attachments": [],
                  "metadata": {}
                }
              ],
              "first_id": "msg_abc123",
              "last_id": "msg_abc456",
              "has_more": false
            }
          request:
            curl: |
              curl https://api.openai.com/v1/threads/thread_abc123/messages \
                -H "Content-Type: application/json" \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "OpenAI-Beta: assistants=v2"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              page = client.beta.threads.messages.list(
                  thread_id="thread_id",
              )
              page = page.data[0]
              print(page.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              // Automatically fetches more pages as needed.
              for await (const message of client.beta.threads.messages.list('thread_id')) {
                console.log(message.id);
              }
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                page, err := client.Beta.Threads.Messages.List(
                  context.TODO(),
                  "thread_id",
                  openai.BetaThreadMessageListParams{

                  },
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", page)
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.beta.threads.messages.MessageListPage
              import com.openai.models.beta.threads.messages.MessageListParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val page: MessageListPage = client.beta().threads().messages().list("thread_id")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              page = openai.beta.threads.messages.list("thread_id")

              puts(page)
    post:
      operationId: createMessage
      tags:
        - Assistants
      summary: Create a message.
      parameters:
        - in: path
          name: thread_id
          required: true
          schema:
            type: string
          description: The ID of the [thread](/docs/api-reference/threads) to create a message for.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateMessageRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/MessageObject'
      x-oaiMeta:
        name: Create message
        group: threads
        beta: true
        returns: A [message](/docs/api-reference/messages/object) object.
        examples:
          response: |
            {
              "id": "msg_abc123",
              "object": "thread.message",
              "created_at": 1713226573,
              "assistant_id": null,
              "thread_id": "thread_abc123",
              "run_id": null,
              "role": "user",
              "content": [
                {
                  "type": "text",
                  "text": {
                    "value": "How does AI work? Explain it in simple terms.",
                    "annotations": []
                  }
                }
              ],
              "attachments": [],
              "metadata": {}
            }
          request:
            curl: |
              curl https://api.openai.com/v1/threads/thread_abc123/messages \
                -H "Content-Type: application/json" \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "OpenAI-Beta: assistants=v2" \
                -d '{
                    "role": "user",
                    "content": "How does AI work? Explain it in simple terms."
                  }'
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              message = client.beta.threads.messages.create(
                  thread_id="thread_id",
                  content="string",
                  role="user",
              )
              print(message.id)
            node.js: >-
              import OpenAI from 'openai';


              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });


              const message = await client.beta.threads.messages.create('thread_id', { content: 'string',
              role: 'user' });


              console.log(message.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                message, err := client.Beta.Threads.Messages.New(
                  context.TODO(),
                  "thread_id",
                  openai.BetaThreadMessageNewParams{
                    Content: openai.BetaThreadMessageNewParamsContentUnion{
                      OfString: openai.String("string"),
                    },
                    Role: openai.BetaThreadMessageNewParamsRoleUser,
                  },
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", message.ID)
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.beta.threads.messages.Message
              import com.openai.models.beta.threads.messages.MessageCreateParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: MessageCreateParams = MessageCreateParams.builder()
                      .threadId("thread_id")
                      .content("string")
                      .role(MessageCreateParams.Role.USER)
                      .build()
                  val message: Message = client.beta().threads().messages().create(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              message = openai.beta.threads.messages.create("thread_id", content: "string", role: :user)

              puts(message)
  /threads/{thread_id}/messages/{message_id}:
    get:
      operationId: getMessage
      tags:
        - Assistants
      summary: Retrieve a message.
      parameters:
        - in: path
          name: thread_id
          required: true
          schema:
            type: string
          description: The ID of the [thread](/docs/api-reference/threads) to which this message belongs.
        - in: path
          name: message_id
          required: true
          schema:
            type: string
          description: The ID of the message to retrieve.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/MessageObject'
      x-oaiMeta:
        name: Retrieve message
        group: threads
        beta: true
        returns: The [message](/docs/api-reference/messages/object) object matching the specified ID.
        examples:
          response: |
            {
              "id": "msg_abc123",
              "object": "thread.message",
              "created_at": 1699017614,
              "assistant_id": null,
              "thread_id": "thread_abc123",
              "run_id": null,
              "role": "user",
              "content": [
                {
                  "type": "text",
                  "text": {
                    "value": "How does AI work? Explain it in simple terms.",
                    "annotations": []
                  }
                }
              ],
              "attachments": [],
              "metadata": {}
            }
          request:
            curl: |
              curl https://api.openai.com/v1/threads/thread_abc123/messages/msg_abc123 \
                -H "Content-Type: application/json" \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "OpenAI-Beta: assistants=v2"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              message = client.beta.threads.messages.retrieve(
                  message_id="message_id",
                  thread_id="thread_id",
              )
              print(message.id)
            node.js: >-
              import OpenAI from 'openai';


              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });


              const message = await client.beta.threads.messages.retrieve('message_id', { thread_id:
              'thread_id' });


              console.log(message.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                message, err := client.Beta.Threads.Messages.Get(
                  context.TODO(),
                  "thread_id",
                  "message_id",
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", message.ID)
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.beta.threads.messages.Message
              import com.openai.models.beta.threads.messages.MessageRetrieveParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: MessageRetrieveParams = MessageRetrieveParams.builder()
                      .threadId("thread_id")
                      .messageId("message_id")
                      .build()
                  val message: Message = client.beta().threads().messages().retrieve(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              message = openai.beta.threads.messages.retrieve("message_id", thread_id: "thread_id")

              puts(message)
    post:
      operationId: modifyMessage
      tags:
        - Assistants
      summary: Modifies a message.
      parameters:
        - in: path
          name: thread_id
          required: true
          schema:
            type: string
          description: The ID of the thread to which this message belongs.
        - in: path
          name: message_id
          required: true
          schema:
            type: string
          description: The ID of the message to modify.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/ModifyMessageRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/MessageObject'
      x-oaiMeta:
        name: Modify message
        group: threads
        beta: true
        returns: The modified [message](/docs/api-reference/messages/object) object.
        examples:
          response: |
            {
              "id": "msg_abc123",
              "object": "thread.message",
              "created_at": 1699017614,
              "assistant_id": null,
              "thread_id": "thread_abc123",
              "run_id": null,
              "role": "user",
              "content": [
                {
                  "type": "text",
                  "text": {
                    "value": "How does AI work? Explain it in simple terms.",
                    "annotations": []
                  }
                }
              ],
              "file_ids": [],
              "metadata": {
                "modified": "true",
                "user": "abc123"
              }
            }
          request:
            curl: |
              curl https://api.openai.com/v1/threads/thread_abc123/messages/msg_abc123 \
                -H "Content-Type: application/json" \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "OpenAI-Beta: assistants=v2" \
                -d '{
                    "metadata": {
                      "modified": "true",
                      "user": "abc123"
                    }
                  }'
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              message = client.beta.threads.messages.update(
                  message_id="message_id",
                  thread_id="thread_id",
              )
              print(message.id)
            node.js: >-
              import OpenAI from 'openai';


              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });


              const message = await client.beta.threads.messages.update('message_id', { thread_id: 'thread_id'
              });


              console.log(message.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                message, err := client.Beta.Threads.Messages.Update(
                  context.TODO(),
                  "thread_id",
                  "message_id",
                  openai.BetaThreadMessageUpdateParams{

                  },
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", message.ID)
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.beta.threads.messages.Message
              import com.openai.models.beta.threads.messages.MessageUpdateParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: MessageUpdateParams = MessageUpdateParams.builder()
                      .threadId("thread_id")
                      .messageId("message_id")
                      .build()
                  val message: Message = client.beta().threads().messages().update(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              message = openai.beta.threads.messages.update("message_id", thread_id: "thread_id")

              puts(message)
    delete:
      operationId: deleteMessage
      tags:
        - Assistants
      summary: Deletes a message.
      parameters:
        - in: path
          name: thread_id
          required: true
          schema:
            type: string
          description: The ID of the thread to which this message belongs.
        - in: path
          name: message_id
          required: true
          schema:
            type: string
          description: The ID of the message to delete.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/DeleteMessageResponse'
      x-oaiMeta:
        name: Delete message
        group: threads
        beta: true
        returns: Deletion status
        examples:
          response: |
            {
              "id": "msg_abc123",
              "object": "thread.message.deleted",
              "deleted": true
            }
          request:
            curl: |
              curl -X DELETE https://api.openai.com/v1/threads/thread_abc123/messages/msg_abc123 \
                -H "Content-Type: application/json" \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "OpenAI-Beta: assistants=v2"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              message_deleted = client.beta.threads.messages.delete(
                  message_id="message_id",
                  thread_id="thread_id",
              )
              print(message_deleted.id)
            node.js: >-
              import OpenAI from 'openai';


              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });


              const messageDeleted = await client.beta.threads.messages.delete('message_id', { thread_id:
              'thread_id' });


              console.log(messageDeleted.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                messageDeleted, err := client.Beta.Threads.Messages.Delete(
                  context.TODO(),
                  "thread_id",
                  "message_id",
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", messageDeleted.ID)
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.beta.threads.messages.MessageDeleteParams
              import com.openai.models.beta.threads.messages.MessageDeleted

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: MessageDeleteParams = MessageDeleteParams.builder()
                      .threadId("thread_id")
                      .messageId("message_id")
                      .build()
                  val messageDeleted: MessageDeleted = client.beta().threads().messages().delete(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              message_deleted = openai.beta.threads.messages.delete("message_id", thread_id: "thread_id")

              puts(message_deleted)
  /threads/{thread_id}/runs:
    get:
      operationId: listRuns
      tags:
        - Assistants
      summary: Returns a list of runs belonging to a thread.
      parameters:
        - name: thread_id
          in: path
          required: true
          schema:
            type: string
          description: The ID of the thread the run belongs to.
        - name: limit
          in: query
          description: >
            A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
            default is 20.
          required: false
          schema:
            type: integer
            default: 20
        - name: order
          in: query
          description: >
            Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for
            descending order.
          schema:
            type: string
            default: desc
            enum:
              - asc
              - desc
        - name: after
          in: query
          description: >
            A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
            instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
            call can include after=obj_foo in order to fetch the next page of the list.
          schema:
            type: string
        - name: before
          in: query
          description: >
            A cursor for use in pagination. `before` is an object ID that defines your place in the list. For
            instance, if you make a list request and receive 100 objects, starting with obj_foo, your
            subsequent call can include before=obj_foo in order to fetch the previous page of the list.
          schema:
            type: string
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ListRunsResponse'
      x-oaiMeta:
        name: List runs
        group: threads
        beta: true
        returns: A list of [run](/docs/api-reference/runs/object) objects.
        examples:
          response: |
            {
              "object": "list",
              "data": [
                {
                  "id": "run_abc123",
                  "object": "thread.run",
                  "created_at": 1699075072,
                  "assistant_id": "asst_abc123",
                  "thread_id": "thread_abc123",
                  "status": "completed",
                  "started_at": 1699075072,
                  "expires_at": null,
                  "cancelled_at": null,
                  "failed_at": null,
                  "completed_at": 1699075073,
                  "last_error": null,
                  "model": "gpt-4o",
                  "instructions": null,
                  "incomplete_details": null,
                  "tools": [
                    {
                      "type": "code_interpreter"
                    }
                  ],
                  "tool_resources": {
                    "code_interpreter": {
                      "file_ids": [
                        "file-abc123",
                        "file-abc456"
                      ]
                    }
                  },
                  "metadata": {},
                  "usage": {
                    "prompt_tokens": 123,
                    "completion_tokens": 456,
                    "total_tokens": 579
                  },
                  "temperature": 1.0,
                  "top_p": 1.0,
                  "max_prompt_tokens": 1000,
                  "max_completion_tokens": 1000,
                  "truncation_strategy": {
                    "type": "auto",
                    "last_messages": null
                  },
                  "response_format": "auto",
                  "tool_choice": "auto",
                  "parallel_tool_calls": true
                },
                {
                  "id": "run_abc456",
                  "object": "thread.run",
                  "created_at": 1699063290,
                  "assistant_id": "asst_abc123",
                  "thread_id": "thread_abc123",
                  "status": "completed",
                  "started_at": 1699063290,
                  "expires_at": null,
                  "cancelled_at": null,
                  "failed_at": null,
                  "completed_at": 1699063291,
                  "last_error": null,
                  "model": "gpt-4o",
                  "instructions": null,
                  "incomplete_details": null,
                  "tools": [
                    {
                      "type": "code_interpreter"
                    }
                  ],
                  "tool_resources": {
                    "code_interpreter": {
                      "file_ids": [
                        "file-abc123",
                        "file-abc456"
                      ]
                    }
                  },
                  "metadata": {},
                  "usage": {
                    "prompt_tokens": 123,
                    "completion_tokens": 456,
                    "total_tokens": 579
                  },
                  "temperature": 1.0,
                  "top_p": 1.0,
                  "max_prompt_tokens": 1000,
                  "max_completion_tokens": 1000,
                  "truncation_strategy": {
                    "type": "auto",
                    "last_messages": null
                  },
                  "response_format": "auto",
                  "tool_choice": "auto",
                  "parallel_tool_calls": true
                }
              ],
              "first_id": "run_abc123",
              "last_id": "run_abc456",
              "has_more": false
            }
          request:
            curl: |
              curl https://api.openai.com/v1/threads/thread_abc123/runs \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
                -H "OpenAI-Beta: assistants=v2"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              page = client.beta.threads.runs.list(
                  thread_id="thread_id",
              )
              page = page.data[0]
              print(page.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              // Automatically fetches more pages as needed.
              for await (const run of client.beta.threads.runs.list('thread_id')) {
                console.log(run.id);
              }
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                page, err := client.Beta.Threads.Runs.List(
                  context.TODO(),
                  "thread_id",
                  openai.BetaThreadRunListParams{

                  },
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", page)
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.beta.threads.runs.RunListPage
              import com.openai.models.beta.threads.runs.RunListParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val page: RunListPage = client.beta().threads().runs().list("thread_id")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              page = openai.beta.threads.runs.list("thread_id")

              puts(page)
    post:
      operationId: createRun
      tags:
        - Assistants
      summary: Create a run.
      parameters:
        - in: path
          name: thread_id
          required: true
          schema:
            type: string
          description: The ID of the thread to run.
        - name: include[]
          in: query
          description: >
            A list of additional fields to include in the response. Currently the only supported value is
            `step_details.tool_calls[*].file_search.results[*].content` to fetch the file search result
            content.


            See the [file search tool
            documentation](/docs/assistants/tools/file-search#customizing-file-search-settings) for more
            information.
          schema:
            type: array
            items:
              type: string
              enum:
                - step_details.tool_calls[*].file_search.results[*].content
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateRunRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/RunObject'
      x-oaiMeta:
        name: Create run
        group: threads
        beta: true
        returns: A [run](/docs/api-reference/runs/object) object.
        examples:
          - title: Default
            request:
              curl: |
                curl https://api.openai.com/v1/threads/thread_abc123/runs \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -H "Content-Type: application/json" \
                  -H "OpenAI-Beta: assistants=v2" \
                  -d '{
                    "assistant_id": "asst_abc123"
                  }'
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                run = client.beta.threads.runs.create(
                    thread_id="thread_id",
                    assistant_id="assistant_id",
                )
                print(run.id)
              node.js: >-
                import OpenAI from 'openai';


                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });


                const run = await client.beta.threads.runs.create('thread_id', { assistant_id: 'assistant_id'
                });


                console.log(run.id);
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  run, err := client.Beta.Threads.Runs.New(
                    context.TODO(),
                    "thread_id",
                    openai.BetaThreadRunNewParams{
                      AssistantID: "assistant_id",
                    },
                  )
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", run.ID)
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.beta.threads.runs.Run
                import com.openai.models.beta.threads.runs.RunCreateParams

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val params: RunCreateParams = RunCreateParams.builder()
                        .threadId("thread_id")
                        .assistantId("assistant_id")
                        .build()
                    val run: Run = client.beta().threads().runs().create(params)
                }
              ruby: |-
                require "openai"

                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )

                run = openai.beta.threads.runs.create("thread_id", assistant_id: "assistant_id")

                puts(run)
            response: |
              {
                "id": "run_abc123",
                "object": "thread.run",
                "created_at": 1699063290,
                "assistant_id": "asst_abc123",
                "thread_id": "thread_abc123",
                "status": "queued",
                "started_at": 1699063290,
                "expires_at": null,
                "cancelled_at": null,
                "failed_at": null,
                "completed_at": 1699063291,
                "last_error": null,
                "model": "gpt-4o",
                "instructions": null,
                "incomplete_details": null,
                "tools": [
                  {
                    "type": "code_interpreter"
                  }
                ],
                "metadata": {},
                "usage": null,
                "temperature": 1.0,
                "top_p": 1.0,
                "max_prompt_tokens": 1000,
                "max_completion_tokens": 1000,
                "truncation_strategy": {
                  "type": "auto",
                  "last_messages": null
                },
                "response_format": "auto",
                "tool_choice": "auto",
                "parallel_tool_calls": true
              }
          - title: Streaming
            request:
              curl: |
                curl https://api.openai.com/v1/threads/thread_123/runs \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -H "Content-Type: application/json" \
                  -H "OpenAI-Beta: assistants=v2" \
                  -d '{
                    "assistant_id": "asst_123",
                    "stream": true
                  }'
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                run = client.beta.threads.runs.create(
                    thread_id="thread_id",
                    assistant_id="assistant_id",
                )
                print(run.id)
              node.js: >-
                import OpenAI from 'openai';


                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });


                const run = await client.beta.threads.runs.create('thread_id', { assistant_id: 'assistant_id'
                });


                console.log(run.id);
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  run, err := client.Beta.Threads.Runs.New(
                    context.TODO(),
                    "thread_id",
                    openai.BetaThreadRunNewParams{
                      AssistantID: "assistant_id",
                    },
                  )
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", run.ID)
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.beta.threads.runs.Run
                import com.openai.models.beta.threads.runs.RunCreateParams

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val params: RunCreateParams = RunCreateParams.builder()
                        .threadId("thread_id")
                        .assistantId("assistant_id")
                        .build()
                    val run: Run = client.beta().threads().runs().create(params)
                }
              ruby: |-
                require "openai"

                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )

                run = openai.beta.threads.runs.create("thread_id", assistant_id: "assistant_id")

                puts(run)
            response: >
              event: thread.run.created

              data:
              {"id":"run_123","object":"thread.run","created_at":1710330640,"assistant_id":"asst_123","thread_id":"thread_123","status":"queued","started_at":null,"expires_at":1710331240,"cancelled_at":null,"failed_at":null,"completed_at":null,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":null,"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}}


              event: thread.run.queued

              data:
              {"id":"run_123","object":"thread.run","created_at":1710330640,"assistant_id":"asst_123","thread_id":"thread_123","status":"queued","started_at":null,"expires_at":1710331240,"cancelled_at":null,"failed_at":null,"completed_at":null,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":null,"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}}


              event: thread.run.in_progress

              data:
              {"id":"run_123","object":"thread.run","created_at":1710330640,"assistant_id":"asst_123","thread_id":"thread_123","status":"in_progress","started_at":1710330641,"expires_at":1710331240,"cancelled_at":null,"failed_at":null,"completed_at":null,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":null,"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}}


              event: thread.run.step.created

              data:
              {"id":"step_001","object":"thread.run.step","created_at":1710330641,"run_id":"run_123","assistant_id":"asst_123","thread_id":"thread_123","type":"message_creation","status":"in_progress","cancelled_at":null,"completed_at":null,"expires_at":1710331240,"failed_at":null,"last_error":null,"step_details":{"type":"message_creation","message_creation":{"message_id":"msg_001"}},"usage":null}


              event: thread.run.step.in_progress

              data:
              {"id":"step_001","object":"thread.run.step","created_at":1710330641,"run_id":"run_123","assistant_id":"asst_123","thread_id":"thread_123","type":"message_creation","status":"in_progress","cancelled_at":null,"completed_at":null,"expires_at":1710331240,"failed_at":null,"last_error":null,"step_details":{"type":"message_creation","message_creation":{"message_id":"msg_001"}},"usage":null}


              event: thread.message.created

              data:
              {"id":"msg_001","object":"thread.message","created_at":1710330641,"assistant_id":"asst_123","thread_id":"thread_123","run_id":"run_123","status":"in_progress","incomplete_details":null,"incomplete_at":null,"completed_at":null,"role":"assistant","content":[],"metadata":{}}


              event: thread.message.in_progress

              data:
              {"id":"msg_001","object":"thread.message","created_at":1710330641,"assistant_id":"asst_123","thread_id":"thread_123","run_id":"run_123","status":"in_progress","incomplete_details":null,"incomplete_at":null,"completed_at":null,"role":"assistant","content":[],"metadata":{}}


              event: thread.message.delta

              data:
              {"id":"msg_001","object":"thread.message.delta","delta":{"content":[{"index":0,"type":"text","text":{"value":"Hello","annotations":[]}}]}}


              ...


              event: thread.message.delta

              data:
              {"id":"msg_001","object":"thread.message.delta","delta":{"content":[{"index":0,"type":"text","text":{"value":"
              today"}}]}}


              event: thread.message.delta

              data:
              {"id":"msg_001","object":"thread.message.delta","delta":{"content":[{"index":0,"type":"text","text":{"value":"?"}}]}}


              event: thread.message.completed

              data:
              {"id":"msg_001","object":"thread.message","created_at":1710330641,"assistant_id":"asst_123","thread_id":"thread_123","run_id":"run_123","status":"completed","incomplete_details":null,"incomplete_at":null,"completed_at":1710330642,"role":"assistant","content":[{"type":"text","text":{"value":"Hello!
              How can I assist you today?","annotations":[]}}],"metadata":{}}


              event: thread.run.step.completed

              data:
              {"id":"step_001","object":"thread.run.step","created_at":1710330641,"run_id":"run_123","assistant_id":"asst_123","thread_id":"thread_123","type":"message_creation","status":"completed","cancelled_at":null,"completed_at":1710330642,"expires_at":1710331240,"failed_at":null,"last_error":null,"step_details":{"type":"message_creation","message_creation":{"message_id":"msg_001"}},"usage":{"prompt_tokens":20,"completion_tokens":11,"total_tokens":31}}


              event: thread.run.completed

              data:
              {"id":"run_123","object":"thread.run","created_at":1710330640,"assistant_id":"asst_123","thread_id":"thread_123","status":"completed","started_at":1710330641,"expires_at":null,"cancelled_at":null,"failed_at":null,"completed_at":1710330642,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":{"prompt_tokens":20,"completion_tokens":11,"total_tokens":31},"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}}


              event: done

              data: [DONE]
          - title: Streaming with Functions
            request:
              curl: |
                curl https://api.openai.com/v1/threads/thread_abc123/runs \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -H "Content-Type: application/json" \
                  -H "OpenAI-Beta: assistants=v2" \
                  -d '{
                    "assistant_id": "asst_abc123",
                    "tools": [
                      {
                        "type": "function",
                        "function": {
                          "name": "get_current_weather",
                          "description": "Get the current weather in a given location",
                          "parameters": {
                            "type": "object",
                            "properties": {
                              "location": {
                                "type": "string",
                                "description": "The city and state, e.g. San Francisco, CA"
                              },
                              "unit": {
                                "type": "string",
                                "enum": ["celsius", "fahrenheit"]
                              }
                            },
                            "required": ["location"]
                          }
                        }
                      }
                    ],
                    "stream": true
                  }'
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                run = client.beta.threads.runs.create(
                    thread_id="thread_id",
                    assistant_id="assistant_id",
                )
                print(run.id)
              node.js: >-
                import OpenAI from 'openai';


                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });


                const run = await client.beta.threads.runs.create('thread_id', { assistant_id: 'assistant_id'
                });


                console.log(run.id);
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  run, err := client.Beta.Threads.Runs.New(
                    context.TODO(),
                    "thread_id",
                    openai.BetaThreadRunNewParams{
                      AssistantID: "assistant_id",
                    },
                  )
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", run.ID)
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.beta.threads.runs.Run
                import com.openai.models.beta.threads.runs.RunCreateParams

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val params: RunCreateParams = RunCreateParams.builder()
                        .threadId("thread_id")
                        .assistantId("assistant_id")
                        .build()
                    val run: Run = client.beta().threads().runs().create(params)
                }
              ruby: |-
                require "openai"

                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )

                run = openai.beta.threads.runs.create("thread_id", assistant_id: "assistant_id")

                puts(run)
            response: >
              event: thread.run.created

              data:
              {"id":"run_123","object":"thread.run","created_at":1710348075,"assistant_id":"asst_123","thread_id":"thread_123","status":"queued","started_at":null,"expires_at":1710348675,"cancelled_at":null,"failed_at":null,"completed_at":null,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":null,"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}}


              event: thread.run.queued

              data:
              {"id":"run_123","object":"thread.run","created_at":1710348075,"assistant_id":"asst_123","thread_id":"thread_123","status":"queued","started_at":null,"expires_at":1710348675,"cancelled_at":null,"failed_at":null,"completed_at":null,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":null,"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}}


              event: thread.run.in_progress

              data:
              {"id":"run_123","object":"thread.run","created_at":1710348075,"assistant_id":"asst_123","thread_id":"thread_123","status":"in_progress","started_at":1710348075,"expires_at":1710348675,"cancelled_at":null,"failed_at":null,"completed_at":null,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":null,"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}}


              event: thread.run.step.created

              data:
              {"id":"step_001","object":"thread.run.step","created_at":1710348076,"run_id":"run_123","assistant_id":"asst_123","thread_id":"thread_123","type":"message_creation","status":"in_progress","cancelled_at":null,"completed_at":null,"expires_at":1710348675,"failed_at":null,"last_error":null,"step_details":{"type":"message_creation","message_creation":{"message_id":"msg_001"}},"usage":null}


              event: thread.run.step.in_progress

              data:
              {"id":"step_001","object":"thread.run.step","created_at":1710348076,"run_id":"run_123","assistant_id":"asst_123","thread_id":"thread_123","type":"message_creation","status":"in_progress","cancelled_at":null,"completed_at":null,"expires_at":1710348675,"failed_at":null,"last_error":null,"step_details":{"type":"message_creation","message_creation":{"message_id":"msg_001"}},"usage":null}


              event: thread.message.created

              data:
              {"id":"msg_001","object":"thread.message","created_at":1710348076,"assistant_id":"asst_123","thread_id":"thread_123","run_id":"run_123","status":"in_progress","incomplete_details":null,"incomplete_at":null,"completed_at":null,"role":"assistant","content":[],"metadata":{}}


              event: thread.message.in_progress

              data:
              {"id":"msg_001","object":"thread.message","created_at":1710348076,"assistant_id":"asst_123","thread_id":"thread_123","run_id":"run_123","status":"in_progress","incomplete_details":null,"incomplete_at":null,"completed_at":null,"role":"assistant","content":[],"metadata":{}}


              event: thread.message.delta

              data:
              {"id":"msg_001","object":"thread.message.delta","delta":{"content":[{"index":0,"type":"text","text":{"value":"Hello","annotations":[]}}]}}


              ...


              event: thread.message.delta

              data:
              {"id":"msg_001","object":"thread.message.delta","delta":{"content":[{"index":0,"type":"text","text":{"value":"
              today"}}]}}


              event: thread.message.delta

              data:
              {"id":"msg_001","object":"thread.message.delta","delta":{"content":[{"index":0,"type":"text","text":{"value":"?"}}]}}


              event: thread.message.completed

              data:
              {"id":"msg_001","object":"thread.message","created_at":1710348076,"assistant_id":"asst_123","thread_id":"thread_123","run_id":"run_123","status":"completed","incomplete_details":null,"incomplete_at":null,"completed_at":1710348077,"role":"assistant","content":[{"type":"text","text":{"value":"Hello!
              How can I assist you today?","annotations":[]}}],"metadata":{}}


              event: thread.run.step.completed

              data:
              {"id":"step_001","object":"thread.run.step","created_at":1710348076,"run_id":"run_123","assistant_id":"asst_123","thread_id":"thread_123","type":"message_creation","status":"completed","cancelled_at":null,"completed_at":1710348077,"expires_at":1710348675,"failed_at":null,"last_error":null,"step_details":{"type":"message_creation","message_creation":{"message_id":"msg_001"}},"usage":{"prompt_tokens":20,"completion_tokens":11,"total_tokens":31}}


              event: thread.run.completed

              data:
              {"id":"run_123","object":"thread.run","created_at":1710348075,"assistant_id":"asst_123","thread_id":"thread_123","status":"completed","started_at":1710348075,"expires_at":null,"cancelled_at":null,"failed_at":null,"completed_at":1710348077,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":{"prompt_tokens":20,"completion_tokens":11,"total_tokens":31},"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}}


              event: done

              data: [DONE]
  /threads/{thread_id}/runs/{run_id}:
    get:
      operationId: getRun
      tags:
        - Assistants
      summary: Retrieves a run.
      parameters:
        - in: path
          name: thread_id
          required: true
          schema:
            type: string
          description: The ID of the [thread](/docs/api-reference/threads) that was run.
        - in: path
          name: run_id
          required: true
          schema:
            type: string
          description: The ID of the run to retrieve.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/RunObject'
      x-oaiMeta:
        name: Retrieve run
        group: threads
        beta: true
        returns: The [run](/docs/api-reference/runs/object) object matching the specified ID.
        examples:
          response: |
            {
              "id": "run_abc123",
              "object": "thread.run",
              "created_at": 1699075072,
              "assistant_id": "asst_abc123",
              "thread_id": "thread_abc123",
              "status": "completed",
              "started_at": 1699075072,
              "expires_at": null,
              "cancelled_at": null,
              "failed_at": null,
              "completed_at": 1699075073,
              "last_error": null,
              "model": "gpt-4o",
              "instructions": null,
              "incomplete_details": null,
              "tools": [
                {
                  "type": "code_interpreter"
                }
              ],
              "metadata": {},
              "usage": {
                "prompt_tokens": 123,
                "completion_tokens": 456,
                "total_tokens": 579
              },
              "temperature": 1.0,
              "top_p": 1.0,
              "max_prompt_tokens": 1000,
              "max_completion_tokens": 1000,
              "truncation_strategy": {
                "type": "auto",
                "last_messages": null
              },
              "response_format": "auto",
              "tool_choice": "auto",
              "parallel_tool_calls": true
            }
          request:
            curl: |
              curl https://api.openai.com/v1/threads/thread_abc123/runs/run_abc123 \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "OpenAI-Beta: assistants=v2"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              run = client.beta.threads.runs.retrieve(
                  run_id="run_id",
                  thread_id="thread_id",
              )
              print(run.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const run = await client.beta.threads.runs.retrieve('run_id', { thread_id: 'thread_id' });

              console.log(run.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                run, err := client.Beta.Threads.Runs.Get(
                  context.TODO(),
                  "thread_id",
                  "run_id",
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", run.ID)
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.beta.threads.runs.Run
              import com.openai.models.beta.threads.runs.RunRetrieveParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: RunRetrieveParams = RunRetrieveParams.builder()
                      .threadId("thread_id")
                      .runId("run_id")
                      .build()
                  val run: Run = client.beta().threads().runs().retrieve(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              run = openai.beta.threads.runs.retrieve("run_id", thread_id: "thread_id")

              puts(run)
    post:
      operationId: modifyRun
      tags:
        - Assistants
      summary: Modifies a run.
      parameters:
        - in: path
          name: thread_id
          required: true
          schema:
            type: string
          description: The ID of the [thread](/docs/api-reference/threads) that was run.
        - in: path
          name: run_id
          required: true
          schema:
            type: string
          description: The ID of the run to modify.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/ModifyRunRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/RunObject'
      x-oaiMeta:
        name: Modify run
        group: threads
        beta: true
        returns: The modified [run](/docs/api-reference/runs/object) object matching the specified ID.
        examples:
          response: |
            {
              "id": "run_abc123",
              "object": "thread.run",
              "created_at": 1699075072,
              "assistant_id": "asst_abc123",
              "thread_id": "thread_abc123",
              "status": "completed",
              "started_at": 1699075072,
              "expires_at": null,
              "cancelled_at": null,
              "failed_at": null,
              "completed_at": 1699075073,
              "last_error": null,
              "model": "gpt-4o",
              "instructions": null,
              "incomplete_details": null,
              "tools": [
                {
                  "type": "code_interpreter"
                }
              ],
              "tool_resources": {
                "code_interpreter": {
                  "file_ids": [
                    "file-abc123",
                    "file-abc456"
                  ]
                }
              },
              "metadata": {
                "user_id": "user_abc123"
              },
              "usage": {
                "prompt_tokens": 123,
                "completion_tokens": 456,
                "total_tokens": 579
              },
              "temperature": 1.0,
              "top_p": 1.0,
              "max_prompt_tokens": 1000,
              "max_completion_tokens": 1000,
              "truncation_strategy": {
                "type": "auto",
                "last_messages": null
              },
              "response_format": "auto",
              "tool_choice": "auto",
              "parallel_tool_calls": true
            }
          request:
            curl: |
              curl https://api.openai.com/v1/threads/thread_abc123/runs/run_abc123 \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
                -H "OpenAI-Beta: assistants=v2" \
                -d '{
                  "metadata": {
                    "user_id": "user_abc123"
                  }
                }'
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              run = client.beta.threads.runs.update(
                  run_id="run_id",
                  thread_id="thread_id",
              )
              print(run.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const run = await client.beta.threads.runs.update('run_id', { thread_id: 'thread_id' });

              console.log(run.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                run, err := client.Beta.Threads.Runs.Update(
                  context.TODO(),
                  "thread_id",
                  "run_id",
                  openai.BetaThreadRunUpdateParams{

                  },
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", run.ID)
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.beta.threads.runs.Run
              import com.openai.models.beta.threads.runs.RunUpdateParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: RunUpdateParams = RunUpdateParams.builder()
                      .threadId("thread_id")
                      .runId("run_id")
                      .build()
                  val run: Run = client.beta().threads().runs().update(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              run = openai.beta.threads.runs.update("run_id", thread_id: "thread_id")

              puts(run)
  /threads/{thread_id}/runs/{run_id}/cancel:
    post:
      operationId: cancelRun
      tags:
        - Assistants
      summary: Cancels a run that is `in_progress`.
      parameters:
        - in: path
          name: thread_id
          required: true
          schema:
            type: string
          description: The ID of the thread to which this run belongs.
        - in: path
          name: run_id
          required: true
          schema:
            type: string
          description: The ID of the run to cancel.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/RunObject'
      x-oaiMeta:
        name: Cancel a run
        group: threads
        beta: true
        returns: The modified [run](/docs/api-reference/runs/object) object matching the specified ID.
        examples:
          response: |
            {
              "id": "run_abc123",
              "object": "thread.run",
              "created_at": 1699076126,
              "assistant_id": "asst_abc123",
              "thread_id": "thread_abc123",
              "status": "cancelling",
              "started_at": 1699076126,
              "expires_at": 1699076726,
              "cancelled_at": null,
              "failed_at": null,
              "completed_at": null,
              "last_error": null,
              "model": "gpt-4o",
              "instructions": "You summarize books.",
              "tools": [
                {
                  "type": "file_search"
                }
              ],
              "tool_resources": {
                "file_search": {
                  "vector_store_ids": ["vs_123"]
                }
              },
              "metadata": {},
              "usage": null,
              "temperature": 1.0,
              "top_p": 1.0,
              "response_format": "auto",
              "tool_choice": "auto",
              "parallel_tool_calls": true
            }
          request:
            curl: |
              curl https://api.openai.com/v1/threads/thread_abc123/runs/run_abc123/cancel \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "OpenAI-Beta: assistants=v2" \
                -X POST
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              run = client.beta.threads.runs.cancel(
                  run_id="run_id",
                  thread_id="thread_id",
              )
              print(run.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const run = await client.beta.threads.runs.cancel('run_id', { thread_id: 'thread_id' });

              console.log(run.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                run, err := client.Beta.Threads.Runs.Cancel(
                  context.TODO(),
                  "thread_id",
                  "run_id",
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", run.ID)
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.beta.threads.runs.Run
              import com.openai.models.beta.threads.runs.RunCancelParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: RunCancelParams = RunCancelParams.builder()
                      .threadId("thread_id")
                      .runId("run_id")
                      .build()
                  val run: Run = client.beta().threads().runs().cancel(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              run = openai.beta.threads.runs.cancel("run_id", thread_id: "thread_id")

              puts(run)
  /threads/{thread_id}/runs/{run_id}/steps:
    get:
      operationId: listRunSteps
      tags:
        - Assistants
      summary: Returns a list of run steps belonging to a run.
      parameters:
        - name: thread_id
          in: path
          required: true
          schema:
            type: string
          description: The ID of the thread the run and run steps belong to.
        - name: run_id
          in: path
          required: true
          schema:
            type: string
          description: The ID of the run the run steps belong to.
        - name: limit
          in: query
          description: >
            A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
            default is 20.
          required: false
          schema:
            type: integer
            default: 20
        - name: order
          in: query
          description: >
            Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for
            descending order.
          schema:
            type: string
            default: desc
            enum:
              - asc
              - desc
        - name: after
          in: query
          description: >
            A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
            instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
            call can include after=obj_foo in order to fetch the next page of the list.
          schema:
            type: string
        - name: before
          in: query
          description: >
            A cursor for use in pagination. `before` is an object ID that defines your place in the list. For
            instance, if you make a list request and receive 100 objects, starting with obj_foo, your
            subsequent call can include before=obj_foo in order to fetch the previous page of the list.
          schema:
            type: string
        - name: include[]
          in: query
          description: >
            A list of additional fields to include in the response. Currently the only supported value is
            `step_details.tool_calls[*].file_search.results[*].content` to fetch the file search result
            content.


            See the [file search tool
            documentation](/docs/assistants/tools/file-search#customizing-file-search-settings) for more
            information.
          schema:
            type: array
            items:
              type: string
              enum:
                - step_details.tool_calls[*].file_search.results[*].content
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ListRunStepsResponse'
      x-oaiMeta:
        name: List run steps
        group: threads
        beta: true
        returns: A list of [run step](/docs/api-reference/run-steps/step-object) objects.
        examples:
          response: |
            {
              "object": "list",
              "data": [
                {
                  "id": "step_abc123",
                  "object": "thread.run.step",
                  "created_at": 1699063291,
                  "run_id": "run_abc123",
                  "assistant_id": "asst_abc123",
                  "thread_id": "thread_abc123",
                  "type": "message_creation",
                  "status": "completed",
                  "cancelled_at": null,
                  "completed_at": 1699063291,
                  "expired_at": null,
                  "failed_at": null,
                  "last_error": null,
                  "step_details": {
                    "type": "message_creation",
                    "message_creation": {
                      "message_id": "msg_abc123"
                    }
                  },
                  "usage": {
                    "prompt_tokens": 123,
                    "completion_tokens": 456,
                    "total_tokens": 579
                  }
                }
              ],
              "first_id": "step_abc123",
              "last_id": "step_abc456",
              "has_more": false
            }
          request:
            curl: |
              curl https://api.openai.com/v1/threads/thread_abc123/runs/run_abc123/steps \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
                -H "OpenAI-Beta: assistants=v2"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              page = client.beta.threads.runs.steps.list(
                  run_id="run_id",
                  thread_id="thread_id",
              )
              page = page.data[0]
              print(page.id)
            node.js: >-
              import OpenAI from 'openai';


              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });


              // Automatically fetches more pages as needed.

              for await (const runStep of client.beta.threads.runs.steps.list('run_id', { thread_id:
              'thread_id' })) {
                console.log(runStep.id);
              }
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                page, err := client.Beta.Threads.Runs.Steps.List(
                  context.TODO(),
                  "thread_id",
                  "run_id",
                  openai.BetaThreadRunStepListParams{

                  },
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", page)
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.beta.threads.runs.steps.StepListPage
              import com.openai.models.beta.threads.runs.steps.StepListParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: StepListParams = StepListParams.builder()
                      .threadId("thread_id")
                      .runId("run_id")
                      .build()
                  val page: StepListPage = client.beta().threads().runs().steps().list(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              page = openai.beta.threads.runs.steps.list("run_id", thread_id: "thread_id")

              puts(page)
  /threads/{thread_id}/runs/{run_id}/steps/{step_id}:
    get:
      operationId: getRunStep
      tags:
        - Assistants
      summary: Retrieves a run step.
      parameters:
        - in: path
          name: thread_id
          required: true
          schema:
            type: string
          description: The ID of the thread to which the run and run step belongs.
        - in: path
          name: run_id
          required: true
          schema:
            type: string
          description: The ID of the run to which the run step belongs.
        - in: path
          name: step_id
          required: true
          schema:
            type: string
          description: The ID of the run step to retrieve.
        - name: include[]
          in: query
          description: >
            A list of additional fields to include in the response. Currently the only supported value is
            `step_details.tool_calls[*].file_search.results[*].content` to fetch the file search result
            content.


            See the [file search tool
            documentation](/docs/assistants/tools/file-search#customizing-file-search-settings) for more
            information.
          schema:
            type: array
            items:
              type: string
              enum:
                - step_details.tool_calls[*].file_search.results[*].content
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/RunStepObject'
      x-oaiMeta:
        name: Retrieve run step
        group: threads
        beta: true
        returns: The [run step](/docs/api-reference/run-steps/step-object) object matching the specified ID.
        examples:
          response: |
            {
              "id": "step_abc123",
              "object": "thread.run.step",
              "created_at": 1699063291,
              "run_id": "run_abc123",
              "assistant_id": "asst_abc123",
              "thread_id": "thread_abc123",
              "type": "message_creation",
              "status": "completed",
              "cancelled_at": null,
              "completed_at": 1699063291,
              "expired_at": null,
              "failed_at": null,
              "last_error": null,
              "step_details": {
                "type": "message_creation",
                "message_creation": {
                  "message_id": "msg_abc123"
                }
              },
              "usage": {
                "prompt_tokens": 123,
                "completion_tokens": 456,
                "total_tokens": 579
              }
            }
          request:
            curl: |
              curl https://api.openai.com/v1/threads/thread_abc123/runs/run_abc123/steps/step_abc123 \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
                -H "OpenAI-Beta: assistants=v2"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              run_step = client.beta.threads.runs.steps.retrieve(
                  step_id="step_id",
                  thread_id="thread_id",
                  run_id="run_id",
              )
              print(run_step.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const runStep = await client.beta.threads.runs.steps.retrieve('step_id', {
                thread_id: 'thread_id',
                run_id: 'run_id',
              });

              console.log(runStep.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                runStep, err := client.Beta.Threads.Runs.Steps.Get(
                  context.TODO(),
                  "thread_id",
                  "run_id",
                  "step_id",
                  openai.BetaThreadRunStepGetParams{

                  },
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", runStep.ID)
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.beta.threads.runs.steps.RunStep
              import com.openai.models.beta.threads.runs.steps.StepRetrieveParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: StepRetrieveParams = StepRetrieveParams.builder()
                      .threadId("thread_id")
                      .runId("run_id")
                      .stepId("step_id")
                      .build()
                  val runStep: RunStep = client.beta().threads().runs().steps().retrieve(params)
              }
            ruby: >-
              require "openai"


              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )


              run_step = openai.beta.threads.runs.steps.retrieve("step_id", thread_id: "thread_id", run_id:
              "run_id")


              puts(run_step)
  /threads/{thread_id}/runs/{run_id}/submit_tool_outputs:
    post:
      operationId: submitToolOuputsToRun
      tags:
        - Assistants
      summary: >
        When a run has the `status: "requires_action"` and `required_action.type` is `submit_tool_outputs`,
        this endpoint can be used to submit the outputs from the tool calls once they're all completed. All
        outputs must be submitted in a single request.
      parameters:
        - in: path
          name: thread_id
          required: true
          schema:
            type: string
          description: The ID of the [thread](/docs/api-reference/threads) to which this run belongs.
        - in: path
          name: run_id
          required: true
          schema:
            type: string
          description: The ID of the run that requires the tool output submission.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/SubmitToolOutputsRunRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/RunObject'
      x-oaiMeta:
        name: Submit tool outputs to run
        group: threads
        beta: true
        returns: The modified [run](/docs/api-reference/runs/object) object matching the specified ID.
        examples:
          - title: Default
            request:
              curl: |
                curl https://api.openai.com/v1/threads/thread_123/runs/run_123/submit_tool_outputs \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -H "Content-Type: application/json" \
                  -H "OpenAI-Beta: assistants=v2" \
                  -d '{
                    "tool_outputs": [
                      {
                        "tool_call_id": "call_001",
                        "output": "70 degrees and sunny."
                      }
                    ]
                  }'
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                run = client.beta.threads.runs.submit_tool_outputs(
                    run_id="run_id",
                    thread_id="thread_id",
                    tool_outputs=[{}],
                )
                print(run.id)
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const run = await client.beta.threads.runs.submitToolOutputs('run_id', {
                  thread_id: 'thread_id',
                  tool_outputs: [{}],
                });

                console.log(run.id);
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  run, err := client.Beta.Threads.Runs.SubmitToolOutputs(
                    context.TODO(),
                    "thread_id",
                    "run_id",
                    openai.BetaThreadRunSubmitToolOutputsParams{
                      ToolOutputs: []openai.BetaThreadRunSubmitToolOutputsParamsToolOutput{openai.BetaThreadRunSubmitToolOutputsParamsToolOutput{

                      }},
                    },
                  )
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", run.ID)
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.beta.threads.runs.Run
                import com.openai.models.beta.threads.runs.RunSubmitToolOutputsParams

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val params: RunSubmitToolOutputsParams = RunSubmitToolOutputsParams.builder()
                        .threadId("thread_id")
                        .runId("run_id")
                        .addToolOutput(RunSubmitToolOutputsParams.ToolOutput.builder().build())
                        .build()
                    val run: Run = client.beta().threads().runs().submitToolOutputs(params)
                }
              ruby: >-
                require "openai"


                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )


                run = openai.beta.threads.runs.submit_tool_outputs("run_id", thread_id: "thread_id",
                tool_outputs: [{}])


                puts(run)
            response: |
              {
                "id": "run_123",
                "object": "thread.run",
                "created_at": 1699075592,
                "assistant_id": "asst_123",
                "thread_id": "thread_123",
                "status": "queued",
                "started_at": 1699075592,
                "expires_at": 1699076192,
                "cancelled_at": null,
                "failed_at": null,
                "completed_at": null,
                "last_error": null,
                "model": "gpt-4o",
                "instructions": null,
                "tools": [
                  {
                    "type": "function",
                    "function": {
                      "name": "get_current_weather",
                      "description": "Get the current weather in a given location",
                      "parameters": {
                        "type": "object",
                        "properties": {
                          "location": {
                            "type": "string",
                            "description": "The city and state, e.g. San Francisco, CA"
                          },
                          "unit": {
                            "type": "string",
                            "enum": ["celsius", "fahrenheit"]
                          }
                        },
                        "required": ["location"]
                      }
                    }
                  }
                ],
                "metadata": {},
                "usage": null,
                "temperature": 1.0,
                "top_p": 1.0,
                "max_prompt_tokens": 1000,
                "max_completion_tokens": 1000,
                "truncation_strategy": {
                  "type": "auto",
                  "last_messages": null
                },
                "response_format": "auto",
                "tool_choice": "auto",
                "parallel_tool_calls": true
              }
          - title: Streaming
            request:
              curl: |
                curl https://api.openai.com/v1/threads/thread_123/runs/run_123/submit_tool_outputs \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -H "Content-Type: application/json" \
                  -H "OpenAI-Beta: assistants=v2" \
                  -d '{
                    "tool_outputs": [
                      {
                        "tool_call_id": "call_001",
                        "output": "70 degrees and sunny."
                      }
                    ],
                    "stream": true
                  }'
              python: |-
                import os
                from openai import OpenAI

                client = OpenAI(
                    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
                )
                run = client.beta.threads.runs.submit_tool_outputs(
                    run_id="run_id",
                    thread_id="thread_id",
                    tool_outputs=[{}],
                )
                print(run.id)
              node.js: |-
                import OpenAI from 'openai';

                const client = new OpenAI({
                  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
                });

                const run = await client.beta.threads.runs.submitToolOutputs('run_id', {
                  thread_id: 'thread_id',
                  tool_outputs: [{}],
                });

                console.log(run.id);
              go: |
                package main

                import (
                  "context"
                  "fmt"

                  "github.com/openai/openai-go"
                  "github.com/openai/openai-go/option"
                )

                func main() {
                  client := openai.NewClient(
                    option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                  )
                  run, err := client.Beta.Threads.Runs.SubmitToolOutputs(
                    context.TODO(),
                    "thread_id",
                    "run_id",
                    openai.BetaThreadRunSubmitToolOutputsParams{
                      ToolOutputs: []openai.BetaThreadRunSubmitToolOutputsParamsToolOutput{openai.BetaThreadRunSubmitToolOutputsParamsToolOutput{

                      }},
                    },
                  )
                  if err != nil {
                    panic(err.Error())
                  }
                  fmt.Printf("%+v\n", run.ID)
                }
              kotlin: |-
                package com.openai.example

                import com.openai.client.OpenAIClient
                import com.openai.client.okhttp.OpenAIOkHttpClient
                import com.openai.models.beta.threads.runs.Run
                import com.openai.models.beta.threads.runs.RunSubmitToolOutputsParams

                fun main() {
                    // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                    val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                    val params: RunSubmitToolOutputsParams = RunSubmitToolOutputsParams.builder()
                        .threadId("thread_id")
                        .runId("run_id")
                        .addToolOutput(RunSubmitToolOutputsParams.ToolOutput.builder().build())
                        .build()
                    val run: Run = client.beta().threads().runs().submitToolOutputs(params)
                }
              ruby: >-
                require "openai"


                openai = OpenAI::Client.new(
                  api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
                )


                run = openai.beta.threads.runs.submit_tool_outputs("run_id", thread_id: "thread_id",
                tool_outputs: [{}])


                puts(run)
            response: >
              event: thread.run.step.completed

              data:
              {"id":"step_001","object":"thread.run.step","created_at":1710352449,"run_id":"run_123","assistant_id":"asst_123","thread_id":"thread_123","type":"tool_calls","status":"completed","cancelled_at":null,"completed_at":1710352475,"expires_at":1710353047,"failed_at":null,"last_error":null,"step_details":{"type":"tool_calls","tool_calls":[{"id":"call_iWr0kQ2EaYMaxNdl0v3KYkx7","type":"function","function":{"name":"get_current_weather","arguments":"{\"location\":\"San
              Francisco, CA\",\"unit\":\"fahrenheit\"}","output":"70 degrees and
              sunny."}}]},"usage":{"prompt_tokens":291,"completion_tokens":24,"total_tokens":315}}


              event: thread.run.queued

              data:
              {"id":"run_123","object":"thread.run","created_at":1710352447,"assistant_id":"asst_123","thread_id":"thread_123","status":"queued","started_at":1710352448,"expires_at":1710353047,"cancelled_at":null,"failed_at":null,"completed_at":null,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[{"type":"function","function":{"name":"get_current_weather","description":"Get
              the current weather in a given
              location","parameters":{"type":"object","properties":{"location":{"type":"string","description":"The
              city and state, e.g. San Francisco,
              CA"},"unit":{"type":"string","enum":["celsius","fahrenheit"]}},"required":["location"]}}}],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":null,"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}}


              event: thread.run.in_progress

              data:
              {"id":"run_123","object":"thread.run","created_at":1710352447,"assistant_id":"asst_123","thread_id":"thread_123","status":"in_progress","started_at":1710352475,"expires_at":1710353047,"cancelled_at":null,"failed_at":null,"completed_at":null,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[{"type":"function","function":{"name":"get_current_weather","description":"Get
              the current weather in a given
              location","parameters":{"type":"object","properties":{"location":{"type":"string","description":"The
              city and state, e.g. San Francisco,
              CA"},"unit":{"type":"string","enum":["celsius","fahrenheit"]}},"required":["location"]}}}],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":null,"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}}


              event: thread.run.step.created

              data:
              {"id":"step_002","object":"thread.run.step","created_at":1710352476,"run_id":"run_123","assistant_id":"asst_123","thread_id":"thread_123","type":"message_creation","status":"in_progress","cancelled_at":null,"completed_at":null,"expires_at":1710353047,"failed_at":null,"last_error":null,"step_details":{"type":"message_creation","message_creation":{"message_id":"msg_002"}},"usage":null}


              event: thread.run.step.in_progress

              data:
              {"id":"step_002","object":"thread.run.step","created_at":1710352476,"run_id":"run_123","assistant_id":"asst_123","thread_id":"thread_123","type":"message_creation","status":"in_progress","cancelled_at":null,"completed_at":null,"expires_at":1710353047,"failed_at":null,"last_error":null,"step_details":{"type":"message_creation","message_creation":{"message_id":"msg_002"}},"usage":null}


              event: thread.message.created

              data:
              {"id":"msg_002","object":"thread.message","created_at":1710352476,"assistant_id":"asst_123","thread_id":"thread_123","run_id":"run_123","status":"in_progress","incomplete_details":null,"incomplete_at":null,"completed_at":null,"role":"assistant","content":[],"metadata":{}}


              event: thread.message.in_progress

              data:
              {"id":"msg_002","object":"thread.message","created_at":1710352476,"assistant_id":"asst_123","thread_id":"thread_123","run_id":"run_123","status":"in_progress","incomplete_details":null,"incomplete_at":null,"completed_at":null,"role":"assistant","content":[],"metadata":{}}


              event: thread.message.delta

              data:
              {"id":"msg_002","object":"thread.message.delta","delta":{"content":[{"index":0,"type":"text","text":{"value":"The","annotations":[]}}]}}


              event: thread.message.delta

              data:
              {"id":"msg_002","object":"thread.message.delta","delta":{"content":[{"index":0,"type":"text","text":{"value":"
              current"}}]}}


              event: thread.message.delta

              data:
              {"id":"msg_002","object":"thread.message.delta","delta":{"content":[{"index":0,"type":"text","text":{"value":"
              weather"}}]}}


              ...


              event: thread.message.delta

              data:
              {"id":"msg_002","object":"thread.message.delta","delta":{"content":[{"index":0,"type":"text","text":{"value":"
              sunny"}}]}}


              event: thread.message.delta

              data:
              {"id":"msg_002","object":"thread.message.delta","delta":{"content":[{"index":0,"type":"text","text":{"value":"."}}]}}


              event: thread.message.completed

              data:
              {"id":"msg_002","object":"thread.message","created_at":1710352476,"assistant_id":"asst_123","thread_id":"thread_123","run_id":"run_123","status":"completed","incomplete_details":null,"incomplete_at":null,"completed_at":1710352477,"role":"assistant","content":[{"type":"text","text":{"value":"The
              current weather in San Francisco, CA is 70 degrees Fahrenheit and
              sunny.","annotations":[]}}],"metadata":{}}


              event: thread.run.step.completed

              data:
              {"id":"step_002","object":"thread.run.step","created_at":1710352476,"run_id":"run_123","assistant_id":"asst_123","thread_id":"thread_123","type":"message_creation","status":"completed","cancelled_at":null,"completed_at":1710352477,"expires_at":1710353047,"failed_at":null,"last_error":null,"step_details":{"type":"message_creation","message_creation":{"message_id":"msg_002"}},"usage":{"prompt_tokens":329,"completion_tokens":18,"total_tokens":347}}


              event: thread.run.completed

              data:
              {"id":"run_123","object":"thread.run","created_at":1710352447,"assistant_id":"asst_123","thread_id":"thread_123","status":"completed","started_at":1710352475,"expires_at":null,"cancelled_at":null,"failed_at":null,"completed_at":1710352477,"required_action":null,"last_error":null,"model":"gpt-4o","instructions":null,"tools":[{"type":"function","function":{"name":"get_current_weather","description":"Get
              the current weather in a given
              location","parameters":{"type":"object","properties":{"location":{"type":"string","description":"The
              city and state, e.g. San Francisco,
              CA"},"unit":{"type":"string","enum":["celsius","fahrenheit"]}},"required":["location"]}}}],"metadata":{},"temperature":1.0,"top_p":1.0,"max_completion_tokens":null,"max_prompt_tokens":null,"truncation_strategy":{"type":"auto","last_messages":null},"incomplete_details":null,"usage":{"prompt_tokens":20,"completion_tokens":11,"total_tokens":31},"response_format":"auto","tool_choice":"auto","parallel_tool_calls":true}}


              event: done

              data: [DONE]
  /uploads:
    post:
      operationId: createUpload
      tags:
        - Uploads
      summary: |
        Creates an intermediate [Upload](/docs/api-reference/uploads/object) object
        that you can add [Parts](/docs/api-reference/uploads/part-object) to.
        Currently, an Upload can accept at most 8 GB in total and expires after an
        hour after you create it.

        Once you complete the Upload, we will create a
        [File](/docs/api-reference/files/object) object that contains all the parts
        you uploaded. This File is usable in the rest of our platform as a regular
        File object.

        For certain `purpose` values, the correct `mime_type` must be specified. 
        Please refer to documentation for the 
        [supported MIME types for your use case](/docs/assistants/tools/file-search#supported-files).

        For guidance on the proper filename extensions for each purpose, please
        follow the documentation on [creating a
        File](/docs/api-reference/files/create).
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateUploadRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Upload'
      x-oaiMeta:
        name: Create upload
        group: uploads
        returns: The [Upload](/docs/api-reference/uploads/object) object with status `pending`.
        examples:
          response: |
            {
              "id": "upload_abc123",
              "object": "upload",
              "bytes": 2147483648,
              "created_at": 1719184911,
              "filename": "training_examples.jsonl",
              "purpose": "fine-tune",
              "status": "pending",
              "expires_at": 1719127296
            }
          request:
            curl: |
              curl https://api.openai.com/v1/uploads \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -d '{
                  "purpose": "fine-tune",
                  "filename": "training_examples.jsonl",
                  "bytes": 2147483648,
                  "mime_type": "text/jsonl"
                }'
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const upload = await client.uploads.create({
                bytes: 0,
                filename: 'filename',
                mime_type: 'mime_type',
                purpose: 'assistants',
              });

              console.log(upload.id);
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              upload = client.uploads.create(
                  bytes=0,
                  filename="filename",
                  mime_type="mime_type",
                  purpose="assistants",
              )
              print(upload.id)
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                upload, err := client.Uploads.New(context.TODO(), openai.UploadNewParams{
                  Bytes: 0,
                  Filename: "filename",
                  MimeType: "mime_type",
                  Purpose: openai.FilePurposeAssistants,
                })
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", upload.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.files.FilePurpose;
              import com.openai.models.uploads.Upload;
              import com.openai.models.uploads.UploadCreateParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      UploadCreateParams params = UploadCreateParams.builder()
                          .bytes(0L)
                          .filename("filename")
                          .mimeType("mime_type")
                          .purpose(FilePurpose.ASSISTANTS)
                          .build();
                      Upload upload = client.uploads().create(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.files.FilePurpose
              import com.openai.models.uploads.Upload
              import com.openai.models.uploads.UploadCreateParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: UploadCreateParams = UploadCreateParams.builder()
                      .bytes(0L)
                      .filename("filename")
                      .mimeType("mime_type")
                      .purpose(FilePurpose.ASSISTANTS)
                      .build()
                  val upload: Upload = client.uploads().create(params)
              }
            ruby: >-
              require "openai"


              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )


              upload = openai.uploads.create(bytes: 0, filename: "filename", mime_type: "mime_type", purpose:
              :assistants)


              puts(upload)
  /uploads/{upload_id}/cancel:
    post:
      operationId: cancelUpload
      tags:
        - Uploads
      summary: |
        Cancels the Upload. No Parts may be added after an Upload is cancelled.
      parameters:
        - in: path
          name: upload_id
          required: true
          schema:
            type: string
            example: upload_abc123
          description: |
            The ID of the Upload.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Upload'
      x-oaiMeta:
        name: Cancel upload
        group: uploads
        returns: The [Upload](/docs/api-reference/uploads/object) object with status `cancelled`.
        examples:
          response: |
            {
              "id": "upload_abc123",
              "object": "upload",
              "bytes": 2147483648,
              "created_at": 1719184911,
              "filename": "training_examples.jsonl",
              "purpose": "fine-tune",
              "status": "cancelled",
              "expires_at": 1719127296
            }
          request:
            curl: |
              curl https://api.openai.com/v1/uploads/upload_abc123/cancel
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const upload = await client.uploads.cancel('upload_abc123');

              console.log(upload.id);
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              upload = client.uploads.cancel(
                  "upload_abc123",
              )
              print(upload.id)
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                upload, err := client.Uploads.Cancel(context.TODO(), "upload_abc123")
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", upload.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.uploads.Upload;
              import com.openai.models.uploads.UploadCancelParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      Upload upload = client.uploads().cancel("upload_abc123");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.uploads.Upload
              import com.openai.models.uploads.UploadCancelParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val upload: Upload = client.uploads().cancel("upload_abc123")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              upload = openai.uploads.cancel("upload_abc123")

              puts(upload)
  /uploads/{upload_id}/complete:
    post:
      operationId: completeUpload
      tags:
        - Uploads
      summary: >
        Completes the [Upload](/docs/api-reference/uploads/object). 


        Within the returned Upload object, there is a nested [File](/docs/api-reference/files/object) object
        that is ready to use in the rest of the platform.


        You can specify the order of the Parts by passing in an ordered list of the Part IDs.


        The number of bytes uploaded upon completion must match the number of bytes initially specified when
        creating the Upload object. No Parts may be added after an Upload is completed.
      parameters:
        - in: path
          name: upload_id
          required: true
          schema:
            type: string
            example: upload_abc123
          description: |
            The ID of the Upload.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CompleteUploadRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Upload'
      x-oaiMeta:
        name: Complete upload
        group: uploads
        returns: >-
          The [Upload](/docs/api-reference/uploads/object) object with status `completed` with an additional
          `file` property containing the created usable File object.
        examples:
          response: |
            {
              "id": "upload_abc123",
              "object": "upload",
              "bytes": 2147483648,
              "created_at": 1719184911,
              "filename": "training_examples.jsonl",
              "purpose": "fine-tune",
              "status": "completed",
              "expires_at": 1719127296,
              "file": {
                "id": "file-xyz321",
                "object": "file",
                "bytes": 2147483648,
                "created_at": 1719186911,
                "filename": "training_examples.jsonl",
                "purpose": "fine-tune",
              }
            }
          request:
            curl: |
              curl https://api.openai.com/v1/uploads/upload_abc123/complete
                -d '{
                  "part_ids": ["part_def456", "part_ghi789"]
                }'
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const upload = await client.uploads.complete('upload_abc123', { part_ids: ['string'] });

              console.log(upload.id);
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              upload = client.uploads.complete(
                  upload_id="upload_abc123",
                  part_ids=["string"],
              )
              print(upload.id)
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                upload, err := client.Uploads.Complete(
                  context.TODO(),
                  "upload_abc123",
                  openai.UploadCompleteParams{
                    PartIDs: []string{"string"},
                  },
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", upload.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.uploads.Upload;
              import com.openai.models.uploads.UploadCompleteParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      UploadCompleteParams params = UploadCompleteParams.builder()
                          .uploadId("upload_abc123")
                          .addPartId("string")
                          .build();
                      Upload upload = client.uploads().complete(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.uploads.Upload
              import com.openai.models.uploads.UploadCompleteParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: UploadCompleteParams = UploadCompleteParams.builder()
                      .uploadId("upload_abc123")
                      .addPartId("string")
                      .build()
                  val upload: Upload = client.uploads().complete(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              upload = openai.uploads.complete("upload_abc123", part_ids: ["string"])

              puts(upload)
  /uploads/{upload_id}/parts:
    post:
      operationId: addUploadPart
      tags:
        - Uploads
      summary: >
        Adds a [Part](/docs/api-reference/uploads/part-object) to an
        [Upload](/docs/api-reference/uploads/object) object. A Part represents a chunk of bytes from the file
        you are trying to upload. 


        Each Part can be at most 64 MB, and you can add Parts until you hit the Upload maximum of 8 GB.


        It is possible to add multiple Parts in parallel. You can decide the intended order of the Parts when
        you [complete the Upload](/docs/api-reference/uploads/complete).
      parameters:
        - in: path
          name: upload_id
          required: true
          schema:
            type: string
            example: upload_abc123
          description: |
            The ID of the Upload.
      requestBody:
        required: true
        content:
          multipart/form-data:
            schema:
              $ref: '#/components/schemas/AddUploadPartRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/UploadPart'
      x-oaiMeta:
        name: Add upload part
        group: uploads
        returns: The upload [Part](/docs/api-reference/uploads/part-object) object.
        examples:
          response: |
            {
              "id": "part_def456",
              "object": "upload.part",
              "created_at": 1719185911,
              "upload_id": "upload_abc123"
            }
          request:
            curl: |
              curl https://api.openai.com/v1/uploads/upload_abc123/parts
                -F data="aHR0cHM6Ly9hcGkub3BlbmFpLmNvbS92MS91cGxvYWRz..."
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const uploadPart = await client.uploads.parts.create('upload_abc123', {
                data: fs.createReadStream('path/to/file'),
              });

              console.log(uploadPart.id);
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              upload_part = client.uploads.parts.create(
                  upload_id="upload_abc123",
                  data=b"raw file contents",
              )
              print(upload_part.id)
            go: |
              package main

              import (
                "bytes"
                "context"
                "fmt"
                "io"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                uploadPart, err := client.Uploads.Parts.New(
                  context.TODO(),
                  "upload_abc123",
                  openai.UploadPartNewParams{
                    Data: io.Reader(bytes.NewBuffer([]byte("some file contents"))),
                  },
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", uploadPart.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.uploads.parts.PartCreateParams;
              import com.openai.models.uploads.parts.UploadPart;
              import java.io.ByteArrayInputStream;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      PartCreateParams params = PartCreateParams.builder()
                          .uploadId("upload_abc123")
                          .data(ByteArrayInputStream("some content".getBytes()))
                          .build();
                      UploadPart uploadPart = client.uploads().parts().create(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.uploads.parts.PartCreateParams
              import com.openai.models.uploads.parts.UploadPart
              import java.io.ByteArrayInputStream

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: PartCreateParams = PartCreateParams.builder()
                      .uploadId("upload_abc123")
                      .data("some content".byteInputStream())
                      .build()
                  val uploadPart: UploadPart = client.uploads().parts().create(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              upload_part = openai.uploads.parts.create("upload_abc123", data: Pathname(__FILE__))

              puts(upload_part)
  /vector_stores:
    get:
      operationId: listVectorStores
      tags:
        - Vector stores
      summary: Returns a list of vector stores.
      parameters:
        - name: limit
          in: query
          description: >
            A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
            default is 20.
          required: false
          schema:
            type: integer
            default: 20
        - name: order
          in: query
          description: >
            Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for
            descending order.
          schema:
            type: string
            default: desc
            enum:
              - asc
              - desc
        - name: after
          in: query
          description: >
            A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
            instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
            call can include after=obj_foo in order to fetch the next page of the list.
          schema:
            type: string
        - name: before
          in: query
          description: >
            A cursor for use in pagination. `before` is an object ID that defines your place in the list. For
            instance, if you make a list request and receive 100 objects, starting with obj_foo, your
            subsequent call can include before=obj_foo in order to fetch the previous page of the list.
          schema:
            type: string
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ListVectorStoresResponse'
      x-oaiMeta:
        name: List vector stores
        group: vector_stores
        returns: A list of [vector store](/docs/api-reference/vector-stores/object) objects.
        examples:
          response: |
            {
              "object": "list",
              "data": [
                {
                  "id": "vs_abc123",
                  "object": "vector_store",
                  "created_at": 1699061776,
                  "name": "Support FAQ",
                  "bytes": 139920,
                  "file_counts": {
                    "in_progress": 0,
                    "completed": 3,
                    "failed": 0,
                    "cancelled": 0,
                    "total": 3
                  }
                },
                {
                  "id": "vs_abc456",
                  "object": "vector_store",
                  "created_at": 1699061776,
                  "name": "Support FAQ v2",
                  "bytes": 139920,
                  "file_counts": {
                    "in_progress": 0,
                    "completed": 3,
                    "failed": 0,
                    "cancelled": 0,
                    "total": 3
                  }
                }
              ],
              "first_id": "vs_abc123",
              "last_id": "vs_abc456",
              "has_more": false
            }
          request:
            curl: |
              curl https://api.openai.com/v1/vector_stores \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
                -H "OpenAI-Beta: assistants=v2"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              page = client.vector_stores.list()
              page = page.data[0]
              print(page.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              // Automatically fetches more pages as needed.
              for await (const vectorStore of client.vectorStores.list()) {
                console.log(vectorStore.id);
              }
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                page, err := client.VectorStores.List(context.TODO(), openai.VectorStoreListParams{

                })
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", page)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.vectorstores.VectorStoreListPage;
              import com.openai.models.vectorstores.VectorStoreListParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      VectorStoreListPage page = client.vectorStores().list();
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.vectorstores.VectorStoreListPage
              import com.openai.models.vectorstores.VectorStoreListParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val page: VectorStoreListPage = client.vectorStores().list()
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              page = openai.vector_stores.list

              puts(page)
    post:
      operationId: createVectorStore
      tags:
        - Vector stores
      summary: Create a vector store.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateVectorStoreRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorStoreObject'
      x-oaiMeta:
        name: Create vector store
        group: vector_stores
        returns: A [vector store](/docs/api-reference/vector-stores/object) object.
        examples:
          response: |
            {
              "id": "vs_abc123",
              "object": "vector_store",
              "created_at": 1699061776,
              "name": "Support FAQ",
              "bytes": 139920,
              "file_counts": {
                "in_progress": 0,
                "completed": 3,
                "failed": 0,
                "cancelled": 0,
                "total": 3
              }
            }
          request:
            curl: |
              curl https://api.openai.com/v1/vector_stores \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
                -H "OpenAI-Beta: assistants=v2" \
                -d '{
                  "name": "Support FAQ"
                }'
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              vector_store = client.vector_stores.create()
              print(vector_store.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const vectorStore = await client.vectorStores.create();

              console.log(vectorStore.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                vectorStore, err := client.VectorStores.New(context.TODO(), openai.VectorStoreNewParams{

                })
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", vectorStore.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.vectorstores.VectorStore;
              import com.openai.models.vectorstores.VectorStoreCreateParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      VectorStore vectorStore = client.vectorStores().create();
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.vectorstores.VectorStore
              import com.openai.models.vectorstores.VectorStoreCreateParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val vectorStore: VectorStore = client.vectorStores().create()
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              vector_store = openai.vector_stores.create

              puts(vector_store)
  /vector_stores/{vector_store_id}:
    get:
      operationId: getVectorStore
      tags:
        - Vector stores
      summary: Retrieves a vector store.
      parameters:
        - in: path
          name: vector_store_id
          required: true
          schema:
            type: string
          description: The ID of the vector store to retrieve.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorStoreObject'
      x-oaiMeta:
        name: Retrieve vector store
        group: vector_stores
        returns: The [vector store](/docs/api-reference/vector-stores/object) object matching the specified ID.
        examples:
          response: |
            {
              "id": "vs_abc123",
              "object": "vector_store",
              "created_at": 1699061776
            }
          request:
            curl: |
              curl https://api.openai.com/v1/vector_stores/vs_abc123 \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
                -H "OpenAI-Beta: assistants=v2"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              vector_store = client.vector_stores.retrieve(
                  "vector_store_id",
              )
              print(vector_store.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const vectorStore = await client.vectorStores.retrieve('vector_store_id');

              console.log(vectorStore.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                vectorStore, err := client.VectorStores.Get(context.TODO(), "vector_store_id")
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", vectorStore.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.vectorstores.VectorStore;
              import com.openai.models.vectorstores.VectorStoreRetrieveParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      VectorStore vectorStore = client.vectorStores().retrieve("vector_store_id");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.vectorstores.VectorStore
              import com.openai.models.vectorstores.VectorStoreRetrieveParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val vectorStore: VectorStore = client.vectorStores().retrieve("vector_store_id")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              vector_store = openai.vector_stores.retrieve("vector_store_id")

              puts(vector_store)
    post:
      operationId: modifyVectorStore
      tags:
        - Vector stores
      summary: Modifies a vector store.
      parameters:
        - in: path
          name: vector_store_id
          required: true
          schema:
            type: string
          description: The ID of the vector store to modify.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/UpdateVectorStoreRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorStoreObject'
      x-oaiMeta:
        name: Modify vector store
        group: vector_stores
        returns: The modified [vector store](/docs/api-reference/vector-stores/object) object.
        examples:
          response: |
            {
              "id": "vs_abc123",
              "object": "vector_store",
              "created_at": 1699061776,
              "name": "Support FAQ",
              "bytes": 139920,
              "file_counts": {
                "in_progress": 0,
                "completed": 3,
                "failed": 0,
                "cancelled": 0,
                "total": 3
              }
            }
          request:
            curl: |
              curl https://api.openai.com/v1/vector_stores/vs_abc123 \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
                -H "OpenAI-Beta: assistants=v2"
                -d '{
                  "name": "Support FAQ"
                }'
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              vector_store = client.vector_stores.update(
                  vector_store_id="vector_store_id",
              )
              print(vector_store.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const vectorStore = await client.vectorStores.update('vector_store_id');

              console.log(vectorStore.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                vectorStore, err := client.VectorStores.Update(
                  context.TODO(),
                  "vector_store_id",
                  openai.VectorStoreUpdateParams{

                  },
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", vectorStore.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.vectorstores.VectorStore;
              import com.openai.models.vectorstores.VectorStoreUpdateParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      VectorStore vectorStore = client.vectorStores().update("vector_store_id");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.vectorstores.VectorStore
              import com.openai.models.vectorstores.VectorStoreUpdateParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val vectorStore: VectorStore = client.vectorStores().update("vector_store_id")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              vector_store = openai.vector_stores.update("vector_store_id")

              puts(vector_store)
    delete:
      operationId: deleteVectorStore
      tags:
        - Vector stores
      summary: Delete a vector store.
      parameters:
        - in: path
          name: vector_store_id
          required: true
          schema:
            type: string
          description: The ID of the vector store to delete.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/DeleteVectorStoreResponse'
      x-oaiMeta:
        name: Delete vector store
        group: vector_stores
        returns: Deletion status
        examples:
          response: |
            {
              id: "vs_abc123",
              object: "vector_store.deleted",
              deleted: true
            }
          request:
            curl: |
              curl https://api.openai.com/v1/vector_stores/vs_abc123 \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
                -H "OpenAI-Beta: assistants=v2" \
                -X DELETE
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              vector_store_deleted = client.vector_stores.delete(
                  "vector_store_id",
              )
              print(vector_store_deleted.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const vectorStoreDeleted = await client.vectorStores.delete('vector_store_id');

              console.log(vectorStoreDeleted.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                vectorStoreDeleted, err := client.VectorStores.Delete(context.TODO(), "vector_store_id")
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", vectorStoreDeleted.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.vectorstores.VectorStoreDeleteParams;
              import com.openai.models.vectorstores.VectorStoreDeleted;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      VectorStoreDeleted vectorStoreDeleted = client.vectorStores().delete("vector_store_id");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.vectorstores.VectorStoreDeleteParams
              import com.openai.models.vectorstores.VectorStoreDeleted

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val vectorStoreDeleted: VectorStoreDeleted = client.vectorStores().delete("vector_store_id")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              vector_store_deleted = openai.vector_stores.delete("vector_store_id")

              puts(vector_store_deleted)
  /vector_stores/{vector_store_id}/file_batches:
    post:
      operationId: createVectorStoreFileBatch
      tags:
        - Vector stores
      summary: Create a vector store file batch.
      parameters:
        - in: path
          name: vector_store_id
          required: true
          schema:
            type: string
            example: vs_abc123
          description: |
            The ID of the vector store for which to create a File Batch.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateVectorStoreFileBatchRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorStoreFileBatchObject'
      x-oaiMeta:
        name: Create vector store file batch
        group: vector_stores
        returns: A [vector store file batch](/docs/api-reference/vector-stores-file-batches/batch-object) object.
        examples:
          response: |
            {
              "id": "vsfb_abc123",
              "object": "vector_store.file_batch",
              "created_at": 1699061776,
              "vector_store_id": "vs_abc123",
              "status": "in_progress",
              "file_counts": {
                "in_progress": 1,
                "completed": 1,
                "failed": 0,
                "cancelled": 0,
                "total": 0,
              }
            }
          request:
            curl: |
              curl https://api.openai.com/v1/vector_stores/vs_abc123/file_batches \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -H "Content-Type: application/json \
                  -H "OpenAI-Beta: assistants=v2" \
                  -d '{
                    "file_ids": ["file-abc123", "file-abc456"]
                  }'
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              vector_store_file_batch = client.vector_stores.file_batches.create(
                  vector_store_id="vs_abc123",
                  file_ids=["string"],
              )
              print(vector_store_file_batch.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const vectorStoreFileBatch = await client.vectorStores.fileBatches.create('vs_abc123', {
                file_ids: ['string'],
              });

              console.log(vectorStoreFileBatch.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                vectorStoreFileBatch, err := client.VectorStores.FileBatches.New(
                  context.TODO(),
                  "vs_abc123",
                  openai.VectorStoreFileBatchNewParams{
                    FileIDs: []string{"string"},
                  },
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", vectorStoreFileBatch.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.vectorstores.filebatches.FileBatchCreateParams;
              import com.openai.models.vectorstores.filebatches.VectorStoreFileBatch;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      FileBatchCreateParams params = FileBatchCreateParams.builder()
                          .vectorStoreId("vs_abc123")
                          .addFileId("string")
                          .build();
                      VectorStoreFileBatch vectorStoreFileBatch = client.vectorStores().fileBatches().create(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.vectorstores.filebatches.FileBatchCreateParams
              import com.openai.models.vectorstores.filebatches.VectorStoreFileBatch

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: FileBatchCreateParams = FileBatchCreateParams.builder()
                      .vectorStoreId("vs_abc123")
                      .addFileId("string")
                      .build()
                  val vectorStoreFileBatch: VectorStoreFileBatch = client.vectorStores().fileBatches().create(params)
              }
            ruby: >-
              require "openai"


              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )


              vector_store_file_batch = openai.vector_stores.file_batches.create("vs_abc123", file_ids:
              ["string"])


              puts(vector_store_file_batch)
  /vector_stores/{vector_store_id}/file_batches/{batch_id}:
    get:
      operationId: getVectorStoreFileBatch
      tags:
        - Vector stores
      summary: Retrieves a vector store file batch.
      parameters:
        - in: path
          name: vector_store_id
          required: true
          schema:
            type: string
            example: vs_abc123
          description: The ID of the vector store that the file batch belongs to.
        - in: path
          name: batch_id
          required: true
          schema:
            type: string
            example: vsfb_abc123
          description: The ID of the file batch being retrieved.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorStoreFileBatchObject'
      x-oaiMeta:
        name: Retrieve vector store file batch
        group: vector_stores
        returns: The [vector store file batch](/docs/api-reference/vector-stores-file-batches/batch-object) object.
        examples:
          response: |
            {
              "id": "vsfb_abc123",
              "object": "vector_store.file_batch",
              "created_at": 1699061776,
              "vector_store_id": "vs_abc123",
              "status": "in_progress",
              "file_counts": {
                "in_progress": 1,
                "completed": 1,
                "failed": 0,
                "cancelled": 0,
                "total": 0,
              }
            }
          request:
            curl: |
              curl https://api.openai.com/v1/vector_stores/vs_abc123/files_batches/vsfb_abc123 \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
                -H "OpenAI-Beta: assistants=v2"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              vector_store_file_batch = client.vector_stores.file_batches.retrieve(
                  batch_id="vsfb_abc123",
                  vector_store_id="vs_abc123",
              )
              print(vector_store_file_batch.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const vectorStoreFileBatch = await client.vectorStores.fileBatches.retrieve('vsfb_abc123', {
                vector_store_id: 'vs_abc123',
              });

              console.log(vectorStoreFileBatch.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                vectorStoreFileBatch, err := client.VectorStores.FileBatches.Get(
                  context.TODO(),
                  "vs_abc123",
                  "vsfb_abc123",
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", vectorStoreFileBatch.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.vectorstores.filebatches.FileBatchRetrieveParams;
              import com.openai.models.vectorstores.filebatches.VectorStoreFileBatch;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      FileBatchRetrieveParams params = FileBatchRetrieveParams.builder()
                          .vectorStoreId("vs_abc123")
                          .batchId("vsfb_abc123")
                          .build();
                      VectorStoreFileBatch vectorStoreFileBatch = client.vectorStores().fileBatches().retrieve(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.vectorstores.filebatches.FileBatchRetrieveParams
              import com.openai.models.vectorstores.filebatches.VectorStoreFileBatch

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: FileBatchRetrieveParams = FileBatchRetrieveParams.builder()
                      .vectorStoreId("vs_abc123")
                      .batchId("vsfb_abc123")
                      .build()
                  val vectorStoreFileBatch: VectorStoreFileBatch = client.vectorStores().fileBatches().retrieve(params)
              }
            ruby: >-
              require "openai"


              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )


              vector_store_file_batch = openai.vector_stores.file_batches.retrieve("vsfb_abc123",
              vector_store_id: "vs_abc123")


              puts(vector_store_file_batch)
  /vector_stores/{vector_store_id}/file_batches/{batch_id}/cancel:
    post:
      operationId: cancelVectorStoreFileBatch
      tags:
        - Vector stores
      summary: >-
        Cancel a vector store file batch. This attempts to cancel the processing of files in this batch as
        soon as possible.
      parameters:
        - in: path
          name: vector_store_id
          required: true
          schema:
            type: string
          description: The ID of the vector store that the file batch belongs to.
        - in: path
          name: batch_id
          required: true
          schema:
            type: string
          description: The ID of the file batch to cancel.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorStoreFileBatchObject'
      x-oaiMeta:
        name: Cancel vector store file batch
        group: vector_stores
        returns: The modified vector store file batch object.
        examples:
          response: |
            {
              "id": "vsfb_abc123",
              "object": "vector_store.file_batch",
              "created_at": 1699061776,
              "vector_store_id": "vs_abc123",
              "status": "in_progress",
              "file_counts": {
                "in_progress": 12,
                "completed": 3,
                "failed": 0,
                "cancelled": 0,
                "total": 15,
              }
            }
          request:
            curl: |
              curl https://api.openai.com/v1/vector_stores/vs_abc123/files_batches/vsfb_abc123/cancel \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
                -H "OpenAI-Beta: assistants=v2" \
                -X POST
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              vector_store_file_batch = client.vector_stores.file_batches.cancel(
                  batch_id="batch_id",
                  vector_store_id="vector_store_id",
              )
              print(vector_store_file_batch.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const vectorStoreFileBatch = await client.vectorStores.fileBatches.cancel('batch_id', {
                vector_store_id: 'vector_store_id',
              });

              console.log(vectorStoreFileBatch.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                vectorStoreFileBatch, err := client.VectorStores.FileBatches.Cancel(
                  context.TODO(),
                  "vector_store_id",
                  "batch_id",
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", vectorStoreFileBatch.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.vectorstores.filebatches.FileBatchCancelParams;
              import com.openai.models.vectorstores.filebatches.VectorStoreFileBatch;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      FileBatchCancelParams params = FileBatchCancelParams.builder()
                          .vectorStoreId("vector_store_id")
                          .batchId("batch_id")
                          .build();
                      VectorStoreFileBatch vectorStoreFileBatch = client.vectorStores().fileBatches().cancel(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.vectorstores.filebatches.FileBatchCancelParams
              import com.openai.models.vectorstores.filebatches.VectorStoreFileBatch

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: FileBatchCancelParams = FileBatchCancelParams.builder()
                      .vectorStoreId("vector_store_id")
                      .batchId("batch_id")
                      .build()
                  val vectorStoreFileBatch: VectorStoreFileBatch = client.vectorStores().fileBatches().cancel(params)
              }
            ruby: >-
              require "openai"


              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )


              vector_store_file_batch = openai.vector_stores.file_batches.cancel("batch_id", vector_store_id:
              "vector_store_id")


              puts(vector_store_file_batch)
  /vector_stores/{vector_store_id}/file_batches/{batch_id}/files:
    get:
      operationId: listFilesInVectorStoreBatch
      tags:
        - Vector stores
      summary: Returns a list of vector store files in a batch.
      parameters:
        - name: vector_store_id
          in: path
          description: The ID of the vector store that the files belong to.
          required: true
          schema:
            type: string
        - name: batch_id
          in: path
          description: The ID of the file batch that the files belong to.
          required: true
          schema:
            type: string
        - name: limit
          in: query
          description: >
            A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
            default is 20.
          required: false
          schema:
            type: integer
            default: 20
        - name: order
          in: query
          description: >
            Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for
            descending order.
          schema:
            type: string
            default: desc
            enum:
              - asc
              - desc
        - name: after
          in: query
          description: >
            A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
            instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
            call can include after=obj_foo in order to fetch the next page of the list.
          schema:
            type: string
        - name: before
          in: query
          description: >
            A cursor for use in pagination. `before` is an object ID that defines your place in the list. For
            instance, if you make a list request and receive 100 objects, starting with obj_foo, your
            subsequent call can include before=obj_foo in order to fetch the previous page of the list.
          schema:
            type: string
        - name: filter
          in: query
          description: Filter by file status. One of `in_progress`, `completed`, `failed`, `cancelled`.
          schema:
            type: string
            enum:
              - in_progress
              - completed
              - failed
              - cancelled
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ListVectorStoreFilesResponse'
      x-oaiMeta:
        name: List vector store files in a batch
        group: vector_stores
        returns: A list of [vector store file](/docs/api-reference/vector-stores-files/file-object) objects.
        examples:
          response: |
            {
              "object": "list",
              "data": [
                {
                  "id": "file-abc123",
                  "object": "vector_store.file",
                  "created_at": 1699061776,
                  "vector_store_id": "vs_abc123"
                },
                {
                  "id": "file-abc456",
                  "object": "vector_store.file",
                  "created_at": 1699061776,
                  "vector_store_id": "vs_abc123"
                }
              ],
              "first_id": "file-abc123",
              "last_id": "file-abc456",
              "has_more": false
            }
          request:
            curl: |
              curl https://api.openai.com/v1/vector_stores/vs_abc123/files_batches/vsfb_abc123/files \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
                -H "OpenAI-Beta: assistants=v2"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              page = client.vector_stores.file_batches.list_files(
                  batch_id="batch_id",
                  vector_store_id="vector_store_id",
              )
              page = page.data[0]
              print(page.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              // Automatically fetches more pages as needed.
              for await (const vectorStoreFile of client.vectorStores.fileBatches.listFiles('batch_id', {
                vector_store_id: 'vector_store_id',
              })) {
                console.log(vectorStoreFile.id);
              }
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                page, err := client.VectorStores.FileBatches.ListFiles(
                  context.TODO(),
                  "vector_store_id",
                  "batch_id",
                  openai.VectorStoreFileBatchListFilesParams{

                  },
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", page)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.vectorstores.filebatches.FileBatchListFilesPage;
              import com.openai.models.vectorstores.filebatches.FileBatchListFilesParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      FileBatchListFilesParams params = FileBatchListFilesParams.builder()
                          .vectorStoreId("vector_store_id")
                          .batchId("batch_id")
                          .build();
                      FileBatchListFilesPage page = client.vectorStores().fileBatches().listFiles(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.vectorstores.filebatches.FileBatchListFilesPage
              import com.openai.models.vectorstores.filebatches.FileBatchListFilesParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: FileBatchListFilesParams = FileBatchListFilesParams.builder()
                      .vectorStoreId("vector_store_id")
                      .batchId("batch_id")
                      .build()
                  val page: FileBatchListFilesPage = client.vectorStores().fileBatches().listFiles(params)
              }
            ruby: >-
              require "openai"


              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )


              page = openai.vector_stores.file_batches.list_files("batch_id", vector_store_id:
              "vector_store_id")


              puts(page)
  /vector_stores/{vector_store_id}/files:
    get:
      operationId: listVectorStoreFiles
      tags:
        - Vector stores
      summary: Returns a list of vector store files.
      parameters:
        - name: vector_store_id
          in: path
          description: The ID of the vector store that the files belong to.
          required: true
          schema:
            type: string
        - name: limit
          in: query
          description: >
            A limit on the number of objects to be returned. Limit can range between 1 and 100, and the
            default is 20.
          required: false
          schema:
            type: integer
            default: 20
        - name: order
          in: query
          description: >
            Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for
            descending order.
          schema:
            type: string
            default: desc
            enum:
              - asc
              - desc
        - name: after
          in: query
          description: >
            A cursor for use in pagination. `after` is an object ID that defines your place in the list. For
            instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent
            call can include after=obj_foo in order to fetch the next page of the list.
          schema:
            type: string
        - name: before
          in: query
          description: >
            A cursor for use in pagination. `before` is an object ID that defines your place in the list. For
            instance, if you make a list request and receive 100 objects, starting with obj_foo, your
            subsequent call can include before=obj_foo in order to fetch the previous page of the list.
          schema:
            type: string
        - name: filter
          in: query
          description: Filter by file status. One of `in_progress`, `completed`, `failed`, `cancelled`.
          schema:
            type: string
            enum:
              - in_progress
              - completed
              - failed
              - cancelled
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ListVectorStoreFilesResponse'
      x-oaiMeta:
        name: List vector store files
        group: vector_stores
        returns: A list of [vector store file](/docs/api-reference/vector-stores-files/file-object) objects.
        examples:
          response: |
            {
              "object": "list",
              "data": [
                {
                  "id": "file-abc123",
                  "object": "vector_store.file",
                  "created_at": 1699061776,
                  "vector_store_id": "vs_abc123"
                },
                {
                  "id": "file-abc456",
                  "object": "vector_store.file",
                  "created_at": 1699061776,
                  "vector_store_id": "vs_abc123"
                }
              ],
              "first_id": "file-abc123",
              "last_id": "file-abc456",
              "has_more": false
            }
          request:
            curl: |
              curl https://api.openai.com/v1/vector_stores/vs_abc123/files \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
                -H "OpenAI-Beta: assistants=v2"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              page = client.vector_stores.files.list(
                  vector_store_id="vector_store_id",
              )
              page = page.data[0]
              print(page.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              // Automatically fetches more pages as needed.
              for await (const vectorStoreFile of client.vectorStores.files.list('vector_store_id')) {
                console.log(vectorStoreFile.id);
              }
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                page, err := client.VectorStores.Files.List(
                  context.TODO(),
                  "vector_store_id",
                  openai.VectorStoreFileListParams{

                  },
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", page)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.vectorstores.files.FileListPage;
              import com.openai.models.vectorstores.files.FileListParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      FileListPage page = client.vectorStores().files().list("vector_store_id");
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.vectorstores.files.FileListPage
              import com.openai.models.vectorstores.files.FileListParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val page: FileListPage = client.vectorStores().files().list("vector_store_id")
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              page = openai.vector_stores.files.list("vector_store_id")

              puts(page)
    post:
      operationId: createVectorStoreFile
      tags:
        - Vector stores
      summary: >-
        Create a vector store file by attaching a [File](/docs/api-reference/files) to a [vector
        store](/docs/api-reference/vector-stores/object).
      parameters:
        - in: path
          name: vector_store_id
          required: true
          schema:
            type: string
            example: vs_abc123
          description: |
            The ID of the vector store for which to create a File.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateVectorStoreFileRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorStoreFileObject'
      x-oaiMeta:
        name: Create vector store file
        group: vector_stores
        returns: A [vector store file](/docs/api-reference/vector-stores-files/file-object) object.
        examples:
          response: |
            {
              "id": "file-abc123",
              "object": "vector_store.file",
              "created_at": 1699061776,
              "usage_bytes": 1234,
              "vector_store_id": "vs_abcd",
              "status": "completed",
              "last_error": null
            }
          request:
            curl: |
              curl https://api.openai.com/v1/vector_stores/vs_abc123/files \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -H "Content-Type: application/json" \
                  -H "OpenAI-Beta: assistants=v2" \
                  -d '{
                    "file_id": "file-abc123"
                  }'
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              vector_store_file = client.vector_stores.files.create(
                  vector_store_id="vs_abc123",
                  file_id="file_id",
              )
              print(vector_store_file.id)
            node.js: >-
              import OpenAI from 'openai';


              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });


              const vectorStoreFile = await client.vectorStores.files.create('vs_abc123', { file_id: 'file_id'
              });


              console.log(vectorStoreFile.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                vectorStoreFile, err := client.VectorStores.Files.New(
                  context.TODO(),
                  "vs_abc123",
                  openai.VectorStoreFileNewParams{
                    FileID: "file_id",
                  },
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", vectorStoreFile.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.vectorstores.files.FileCreateParams;
              import com.openai.models.vectorstores.files.VectorStoreFile;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      FileCreateParams params = FileCreateParams.builder()
                          .vectorStoreId("vs_abc123")
                          .fileId("file_id")
                          .build();
                      VectorStoreFile vectorStoreFile = client.vectorStores().files().create(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.vectorstores.files.FileCreateParams
              import com.openai.models.vectorstores.files.VectorStoreFile

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: FileCreateParams = FileCreateParams.builder()
                      .vectorStoreId("vs_abc123")
                      .fileId("file_id")
                      .build()
                  val vectorStoreFile: VectorStoreFile = client.vectorStores().files().create(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              vector_store_file = openai.vector_stores.files.create("vs_abc123", file_id: "file_id")

              puts(vector_store_file)
  /vector_stores/{vector_store_id}/files/{file_id}:
    get:
      operationId: getVectorStoreFile
      tags:
        - Vector stores
      summary: Retrieves a vector store file.
      parameters:
        - in: path
          name: vector_store_id
          required: true
          schema:
            type: string
            example: vs_abc123
          description: The ID of the vector store that the file belongs to.
        - in: path
          name: file_id
          required: true
          schema:
            type: string
            example: file-abc123
          description: The ID of the file being retrieved.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorStoreFileObject'
      x-oaiMeta:
        name: Retrieve vector store file
        group: vector_stores
        returns: The [vector store file](/docs/api-reference/vector-stores-files/file-object) object.
        examples:
          response: |
            {
              "id": "file-abc123",
              "object": "vector_store.file",
              "created_at": 1699061776,
              "vector_store_id": "vs_abcd",
              "status": "completed",
              "last_error": null
            }
          request:
            curl: |
              curl https://api.openai.com/v1/vector_stores/vs_abc123/files/file-abc123 \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
                -H "OpenAI-Beta: assistants=v2"
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              vector_store_file = client.vector_stores.files.retrieve(
                  file_id="file-abc123",
                  vector_store_id="vs_abc123",
              )
              print(vector_store_file.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const vectorStoreFile = await client.vectorStores.files.retrieve('file-abc123', {
                vector_store_id: 'vs_abc123',
              });

              console.log(vectorStoreFile.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                vectorStoreFile, err := client.VectorStores.Files.Get(
                  context.TODO(),
                  "vs_abc123",
                  "file-abc123",
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", vectorStoreFile.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.vectorstores.files.FileRetrieveParams;
              import com.openai.models.vectorstores.files.VectorStoreFile;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      FileRetrieveParams params = FileRetrieveParams.builder()
                          .vectorStoreId("vs_abc123")
                          .fileId("file-abc123")
                          .build();
                      VectorStoreFile vectorStoreFile = client.vectorStores().files().retrieve(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.vectorstores.files.FileRetrieveParams
              import com.openai.models.vectorstores.files.VectorStoreFile

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: FileRetrieveParams = FileRetrieveParams.builder()
                      .vectorStoreId("vs_abc123")
                      .fileId("file-abc123")
                      .build()
                  val vectorStoreFile: VectorStoreFile = client.vectorStores().files().retrieve(params)
              }
            ruby: >-
              require "openai"


              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )


              vector_store_file = openai.vector_stores.files.retrieve("file-abc123", vector_store_id:
              "vs_abc123")


              puts(vector_store_file)
    delete:
      operationId: deleteVectorStoreFile
      tags:
        - Vector stores
      summary: >-
        Delete a vector store file. This will remove the file from the vector store but the file itself will
        not be deleted. To delete the file, use the [delete file](/docs/api-reference/files/delete) endpoint.
      parameters:
        - in: path
          name: vector_store_id
          required: true
          schema:
            type: string
          description: The ID of the vector store that the file belongs to.
        - in: path
          name: file_id
          required: true
          schema:
            type: string
          description: The ID of the file to delete.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/DeleteVectorStoreFileResponse'
      x-oaiMeta:
        name: Delete vector store file
        group: vector_stores
        returns: Deletion status
        examples:
          response: |
            {
              id: "file-abc123",
              object: "vector_store.file.deleted",
              deleted: true
            }
          request:
            curl: |
              curl https://api.openai.com/v1/vector_stores/vs_abc123/files/file-abc123 \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
                -H "OpenAI-Beta: assistants=v2" \
                -X DELETE
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              vector_store_file_deleted = client.vector_stores.files.delete(
                  file_id="file_id",
                  vector_store_id="vector_store_id",
              )
              print(vector_store_file_deleted.id)
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const vectorStoreFileDeleted = await client.vectorStores.files.delete('file_id', {
                vector_store_id: 'vector_store_id',
              });

              console.log(vectorStoreFileDeleted.id);
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                vectorStoreFileDeleted, err := client.VectorStores.Files.Delete(
                  context.TODO(),
                  "vector_store_id",
                  "file_id",
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", vectorStoreFileDeleted.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.vectorstores.files.FileDeleteParams;
              import com.openai.models.vectorstores.files.VectorStoreFileDeleted;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      FileDeleteParams params = FileDeleteParams.builder()
                          .vectorStoreId("vector_store_id")
                          .fileId("file_id")
                          .build();
                      VectorStoreFileDeleted vectorStoreFileDeleted = client.vectorStores().files().delete(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.vectorstores.files.FileDeleteParams
              import com.openai.models.vectorstores.files.VectorStoreFileDeleted

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: FileDeleteParams = FileDeleteParams.builder()
                      .vectorStoreId("vector_store_id")
                      .fileId("file_id")
                      .build()
                  val vectorStoreFileDeleted: VectorStoreFileDeleted = client.vectorStores().files().delete(params)
              }
            ruby: >-
              require "openai"


              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )


              vector_store_file_deleted = openai.vector_stores.files.delete("file_id", vector_store_id:
              "vector_store_id")


              puts(vector_store_file_deleted)
    post:
      operationId: updateVectorStoreFileAttributes
      tags:
        - Vector stores
      summary: Update attributes on a vector store file.
      parameters:
        - in: path
          name: vector_store_id
          required: true
          schema:
            type: string
            example: vs_abc123
          description: The ID of the vector store the file belongs to.
        - in: path
          name: file_id
          required: true
          schema:
            type: string
            example: file-abc123
          description: The ID of the file to update attributes.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/UpdateVectorStoreFileAttributesRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorStoreFileObject'
      x-oaiMeta:
        name: Update vector store file attributes
        group: vector_stores
        returns: The updated [vector store file](/docs/api-reference/vector-stores-files/file-object) object.
        examples:
          response: |
            {
              "id": "file-abc123",
              "object": "vector_store.file",
              "usage_bytes": 1234,
              "created_at": 1699061776,
              "vector_store_id": "vs_abcd",
              "status": "completed",
              "last_error": null,
              "chunking_strategy": {...},
              "attributes": {"key1": "value1", "key2": 2}
            }
          request:
            curl: |
              curl https://api.openai.com/v1/vector_stores/{vector_store_id}/files/{file_id} \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
                -d '{"attributes": {"key1": "value1", "key2": 2}}'
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              const vectorStoreFile = await client.vectorStores.files.update('file-abc123', {
                vector_store_id: 'vs_abc123',
                attributes: { foo: 'string' },
              });

              console.log(vectorStoreFile.id);
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              vector_store_file = client.vector_stores.files.update(
                  file_id="file-abc123",
                  vector_store_id="vs_abc123",
                  attributes={
                      "foo": "string"
                  },
              )
              print(vector_store_file.id)
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                vectorStoreFile, err := client.VectorStores.Files.Update(
                  context.TODO(),
                  "vs_abc123",
                  "file-abc123",
                  openai.VectorStoreFileUpdateParams{
                    Attributes: map[string]openai.VectorStoreFileUpdateParamsAttributeUnion{
                    "foo": openai.VectorStoreFileUpdateParamsAttributeUnion{
                      OfString: openai.String("string"),
                    },
                    },
                  },
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", vectorStoreFile.ID)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.core.JsonValue;
              import com.openai.models.vectorstores.files.FileUpdateParams;
              import com.openai.models.vectorstores.files.VectorStoreFile;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      FileUpdateParams params = FileUpdateParams.builder()
                          .vectorStoreId("vs_abc123")
                          .fileId("file-abc123")
                          .attributes(FileUpdateParams.Attributes.builder()
                              .putAdditionalProperty("foo", JsonValue.from("string"))
                              .build())
                          .build();
                      VectorStoreFile vectorStoreFile = client.vectorStores().files().update(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.core.JsonValue
              import com.openai.models.vectorstores.files.FileUpdateParams
              import com.openai.models.vectorstores.files.VectorStoreFile

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: FileUpdateParams = FileUpdateParams.builder()
                      .vectorStoreId("vs_abc123")
                      .fileId("file-abc123")
                      .attributes(FileUpdateParams.Attributes.builder()
                          .putAdditionalProperty("foo", JsonValue.from("string"))
                          .build())
                      .build()
                  val vectorStoreFile: VectorStoreFile = client.vectorStores().files().update(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              vector_store_file = openai.vector_stores.files.update(
                "file-abc123",
                vector_store_id: "vs_abc123",
                attributes: {foo: "string"}
              )

              puts(vector_store_file)
  /vector_stores/{vector_store_id}/files/{file_id}/content:
    get:
      operationId: retrieveVectorStoreFileContent
      tags:
        - Vector stores
      summary: Retrieve the parsed contents of a vector store file.
      parameters:
        - in: path
          name: vector_store_id
          required: true
          schema:
            type: string
            example: vs_abc123
          description: The ID of the vector store.
        - in: path
          name: file_id
          required: true
          schema:
            type: string
            example: file-abc123
          description: The ID of the file within the vector store.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorStoreFileContentResponse'
      x-oaiMeta:
        name: Retrieve vector store file content
        group: vector_stores
        returns: The parsed contents of the specified vector store file.
        examples:
          response: |
            {
              "file_id": "file-abc123",
              "filename": "example.txt",
              "attributes": {"key": "value"},
              "content": [
                {"type": "text", "text": "..."},
                ...
              ]
            }
          request:
            curl: |
              curl \
              https://api.openai.com/v1/vector_stores/vs_abc123/files/file-abc123/content \
              -H "Authorization: Bearer $OPENAI_API_KEY"
            node.js: |-
              import OpenAI from 'openai';

              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });

              // Automatically fetches more pages as needed.
              for await (const fileContentResponse of client.vectorStores.files.content('file-abc123', {
                vector_store_id: 'vs_abc123',
              })) {
                console.log(fileContentResponse.text);
              }
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              page = client.vector_stores.files.content(
                  file_id="file-abc123",
                  vector_store_id="vs_abc123",
              )
              page = page.data[0]
              print(page.text)
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                page, err := client.VectorStores.Files.Content(
                  context.TODO(),
                  "vs_abc123",
                  "file-abc123",
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", page)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.vectorstores.files.FileContentPage;
              import com.openai.models.vectorstores.files.FileContentParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      FileContentParams params = FileContentParams.builder()
                          .vectorStoreId("vs_abc123")
                          .fileId("file-abc123")
                          .build();
                      FileContentPage page = client.vectorStores().files().content(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.vectorstores.files.FileContentPage
              import com.openai.models.vectorstores.files.FileContentParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: FileContentParams = FileContentParams.builder()
                      .vectorStoreId("vs_abc123")
                      .fileId("file-abc123")
                      .build()
                  val page: FileContentPage = client.vectorStores().files().content(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              page = openai.vector_stores.files.content("file-abc123", vector_store_id: "vs_abc123")

              puts(page)
  /vector_stores/{vector_store_id}/search:
    post:
      operationId: searchVectorStore
      tags:
        - Vector stores
      summary: Search a vector store for relevant chunks based on a query and file attributes filter.
      parameters:
        - in: path
          name: vector_store_id
          required: true
          schema:
            type: string
            example: vs_abc123
          description: The ID of the vector store to search.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/VectorStoreSearchRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorStoreSearchResultsPage'
      x-oaiMeta:
        name: Search vector store
        group: vector_stores
        returns: A page of search results from the vector store.
        examples:
          response: |
            {
              "object": "vector_store.search_results.page",
              "search_query": "What is the return policy?",
              "data": [
                {
                  "file_id": "file_123",
                  "filename": "document.pdf",
                  "score": 0.95,
                  "attributes": {
                    "author": "John Doe",
                    "date": "2023-01-01"
                  },
                  "content": [
                    {
                      "type": "text",
                      "text": "Relevant chunk"
                    }
                  ]
                },
                {
                  "file_id": "file_456",
                  "filename": "notes.txt",
                  "score": 0.89,
                  "attributes": {
                    "author": "Jane Smith",
                    "date": "2023-01-02"
                  },
                  "content": [
                    {
                      "type": "text",
                      "text": "Sample text content from the vector store."
                    }
                  ]
                }
              ],
              "has_more": false,
              "next_page": null
            }
          request:
            curl: |
              curl -X POST \
              https://api.openai.com/v1/vector_stores/vs_abc123/search \
              -H "Authorization: Bearer $OPENAI_API_KEY" \
              -H "Content-Type: application/json" \
              -d '{"query": "What is the return policy?", "filters": {...}}'
            node.js: >-
              import OpenAI from 'openai';


              const client = new OpenAI({
                apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted
              });


              // Automatically fetches more pages as needed.

              for await (const vectorStoreSearchResponse of client.vectorStores.search('vs_abc123', { query:
              'string' })) {
                console.log(vectorStoreSearchResponse.file_id);
              }
            python: |-
              import os
              from openai import OpenAI

              client = OpenAI(
                  api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
              )
              page = client.vector_stores.search(
                  vector_store_id="vs_abc123",
                  query="string",
              )
              page = page.data[0]
              print(page.file_id)
            go: |
              package main

              import (
                "context"
                "fmt"

                "github.com/openai/openai-go"
                "github.com/openai/openai-go/option"
              )

              func main() {
                client := openai.NewClient(
                  option.WithAPIKey("My API Key"), // defaults to os.LookupEnv("OPENAI_API_KEY")
                )
                page, err := client.VectorStores.Search(
                  context.TODO(),
                  "vs_abc123",
                  openai.VectorStoreSearchParams{
                    Query: openai.VectorStoreSearchParamsQueryUnion{
                      OfString: openai.String("string"),
                    },
                  },
                )
                if err != nil {
                  panic(err.Error())
                }
                fmt.Printf("%+v\n", page)
              }
            java: |-
              package com.openai.example;

              import com.openai.client.OpenAIClient;
              import com.openai.client.okhttp.OpenAIOkHttpClient;
              import com.openai.models.vectorstores.VectorStoreSearchPage;
              import com.openai.models.vectorstores.VectorStoreSearchParams;

              public final class Main {
                  private Main() {}

                  public static void main(String[] args) {
                      // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                      OpenAIClient client = OpenAIOkHttpClient.fromEnv();

                      VectorStoreSearchParams params = VectorStoreSearchParams.builder()
                          .vectorStoreId("vs_abc123")
                          .query("string")
                          .build();
                      VectorStoreSearchPage page = client.vectorStores().search(params);
                  }
              }
            kotlin: |-
              package com.openai.example

              import com.openai.client.OpenAIClient
              import com.openai.client.okhttp.OpenAIOkHttpClient
              import com.openai.models.vectorstores.VectorStoreSearchPage
              import com.openai.models.vectorstores.VectorStoreSearchParams

              fun main() {
                  // Configures using the `OPENAI_API_KEY`, `OPENAI_ORG_ID`, `OPENAI_PROJECT_ID` and `OPENAI_BASE_URL` environment variables
                  val client: OpenAIClient = OpenAIOkHttpClient.fromEnv()

                  val params: VectorStoreSearchParams = VectorStoreSearchParams.builder()
                      .vectorStoreId("vs_abc123")
                      .query("string")
                      .build()
                  val page: VectorStoreSearchPage = client.vectorStores().search(params)
              }
            ruby: |-
              require "openai"

              openai = OpenAI::Client.new(
                api_key: ENV["OPENAI_API_KEY"] # This is the default and can be omitted
              )

              page = openai.vector_stores.search("vs_abc123", query: "string")

              puts(page)
components:
  schemas:
    AddUploadPartRequest:
      type: object
      additionalProperties: false
      properties:
        data:
          description: |
            The chunk of bytes for this Part.
          type: string
          format: binary
      required:
        - data
    AdminApiKey:
      type: object
      description: Represents an individual Admin API key in an org.
      properties:
        object:
          type: string
          example: organization.admin_api_key
          description: The object type, which is always `organization.admin_api_key`
          x-stainless-const: true
        id:
          type: string
          example: key_abc
          description: The identifier, which can be referenced in API endpoints
        name:
          type: string
          example: Administration Key
          description: The name of the API key
        redacted_value:
          type: string
          example: sk-admin...def
          description: The redacted value of the API key
        value:
          type: string
          example: sk-admin-1234abcd
          description: The value of the API key. Only shown on create.
        created_at:
          type: integer
          format: int64
          example: 1711471533
          description: The Unix timestamp (in seconds) of when the API key was created
        last_used_at:
          type: integer
          format: int64
          nullable: true
          example: 1711471534
          description: The Unix timestamp (in seconds) of when the API key was last used
        owner:
          type: object
          properties:
            type:
              type: string
              example: user
              description: Always `user`
            object:
              type: string
              example: organization.user
              description: The object type, which is always organization.user
            id:
              type: string
              example: sa_456
              description: The identifier, which can be referenced in API endpoints
            name:
              type: string
              example: My Service Account
              description: The name of the user
            created_at:
              type: integer
              format: int64
              example: 1711471533
              description: The Unix timestamp (in seconds) of when the user was created
            role:
              type: string
              example: owner
              description: Always `owner`
      required:
        - object
        - redacted_value
        - name
        - created_at
        - last_used_at
        - id
        - owner
      x-oaiMeta:
        name: The admin API key object
        example: |
          {
            "object": "organization.admin_api_key",
            "id": "key_abc",
            "name": "Main Admin Key",
            "redacted_value": "sk-admin...xyz",
            "created_at": 1711471533,
            "last_used_at": 1711471534,
            "owner": {
              "type": "user",
              "object": "organization.user",
              "id": "user_123",
              "name": "John Doe",
              "created_at": 1711471533,
              "role": "owner"
            }
          }
    ApiKeyList:
      type: object
      properties:
        object:
          type: string
          example: list
        data:
          type: array
          items:
            $ref: '#/components/schemas/AdminApiKey'
        has_more:
          type: boolean
          example: false
        first_id:
          type: string
          example: key_abc
        last_id:
          type: string
          example: key_xyz
    AssistantObject:
      type: object
      title: Assistant
      description: Represents an `assistant` that can call the model and use tools.
      properties:
        id:
          description: The identifier, which can be referenced in API endpoints.
          type: string
        object:
          description: The object type, which is always `assistant`.
          type: string
          enum:
            - assistant
          x-stainless-const: true
        created_at:
          description: The Unix timestamp (in seconds) for when the assistant was created.
          type: integer
        name:
          description: |
            The name of the assistant. The maximum length is 256 characters.
          type: string
          maxLength: 256
          nullable: true
        description:
          description: |
            The description of the assistant. The maximum length is 512 characters.
          type: string
          maxLength: 512
          nullable: true
        model:
          description: >
            ID of the model to use. You can use the [List models](/docs/api-reference/models/list) API to see
            all of your available models, or see our [Model overview](/docs/models) for descriptions of them.
          type: string
        instructions:
          description: |
            The system instructions that the assistant uses. The maximum length is 256,000 characters.
          type: string
          maxLength: 256000
          nullable: true
        tools:
          description: >
            A list of tool enabled on the assistant. There can be a maximum of 128 tools per assistant. Tools
            can be of types `code_interpreter`, `file_search`, or `function`.
          default: []
          type: array
          maxItems: 128
          items:
            oneOf:
              - $ref: '#/components/schemas/AssistantToolsCode'
              - $ref: '#/components/schemas/AssistantToolsFileSearch'
              - $ref: '#/components/schemas/AssistantToolsFunction'
        tool_resources:
          type: object
          description: >
            A set of resources that are used by the assistant's tools. The resources are specific to the type
            of tool. For example, the `code_interpreter` tool requires a list of file IDs, while the
            `file_search` tool requires a list of vector store IDs.
          properties:
            code_interpreter:
              type: object
              properties:
                file_ids:
                  type: array
                  description: >
                    A list of [file](/docs/api-reference/files) IDs made available to the `code_interpreter``
                    tool. There can be a maximum of 20 files associated with the tool.
                  default: []
                  maxItems: 20
                  items:
                    type: string
            file_search:
              type: object
              properties:
                vector_store_ids:
                  type: array
                  description: >
                    The ID of the [vector store](/docs/api-reference/vector-stores/object) attached to this
                    assistant. There can be a maximum of 1 vector store attached to the assistant.
                  maxItems: 1
                  items:
                    type: string
          nullable: true
        metadata:
          $ref: '#/components/schemas/Metadata'
        temperature:
          description: >
            What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output
            more random, while lower values like 0.2 will make it more focused and deterministic.
          type: number
          minimum: 0
          maximum: 2
          default: 1
          example: 1
          nullable: true
        top_p:
          type: number
          minimum: 0
          maximum: 1
          default: 1
          example: 1
          nullable: true
          description: >
            An alternative to sampling with temperature, called nucleus sampling, where the model considers
            the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the
            top 10% probability mass are considered.


            We generally recommend altering this or temperature but not both.
        response_format:
          $ref: '#/components/schemas/AssistantsApiResponseFormatOption'
          nullable: true
      required:
        - id
        - object
        - created_at
        - name
        - description
        - model
        - instructions
        - tools
        - metadata
      x-oaiMeta:
        name: The assistant object
        beta: true
        example: |
          {
            "id": "asst_abc123",
            "object": "assistant",
            "created_at": 1698984975,
            "name": "Math Tutor",
            "description": null,
            "model": "gpt-4o",
            "instructions": "You are a personal math tutor. When asked a question, write and run Python code to answer the question.",
            "tools": [
              {
                "type": "code_interpreter"
              }
            ],
            "metadata": {},
            "top_p": 1.0,
            "temperature": 1.0,
            "response_format": "auto"
          }
    AssistantStreamEvent:
      description: |
        Represents an event emitted when streaming a Run.

        Each event in a server-sent events stream has an `event` and `data` property:

        ```
        event: thread.created
        data: {"id": "thread_123", "object": "thread", ...}
        ```

        We emit events whenever a new object is created, transitions to a new state, or is being
        streamed in parts (deltas). For example, we emit `thread.run.created` when a new run
        is created, `thread.run.completed` when a run completes, and so on. When an Assistant chooses
        to create a message during a run, we emit a `thread.message.created event`, a
        `thread.message.in_progress` event, many `thread.message.delta` events, and finally a
        `thread.message.completed` event.

        We may add additional events over time, so we recommend handling unknown events gracefully
        in your code. See the [Assistants API quickstart](/docs/assistants/overview) to learn how to
        integrate the Assistants API with streaming.
      oneOf:
        - $ref: '#/components/schemas/ThreadStreamEvent'
        - $ref: '#/components/schemas/RunStreamEvent'
        - $ref: '#/components/schemas/RunStepStreamEvent'
        - $ref: '#/components/schemas/MessageStreamEvent'
        - $ref: '#/components/schemas/ErrorEvent'
        - $ref: '#/components/schemas/DoneEvent'
      x-oaiMeta:
        name: Assistant stream events
        beta: true
    AssistantSupportedModels:
      type: string
      enum:
        - gpt-4.1
        - gpt-4.1-mini
        - gpt-4.1-nano
        - gpt-4.1-2025-04-14
        - gpt-4.1-mini-2025-04-14
        - gpt-4.1-nano-2025-04-14
        - o3-mini
        - o3-mini-2025-01-31
        - o1
        - o1-2024-12-17
        - gpt-4o
        - gpt-4o-2024-11-20
        - gpt-4o-2024-08-06
        - gpt-4o-2024-05-13
        - gpt-4o-mini
        - gpt-4o-mini-2024-07-18
        - gpt-4.5-preview
        - gpt-4.5-preview-2025-02-27
        - gpt-4-turbo
        - gpt-4-turbo-2024-04-09
        - gpt-4-0125-preview
        - gpt-4-turbo-preview
        - gpt-4-1106-preview
        - gpt-4-vision-preview
        - gpt-4
        - gpt-4-0314
        - gpt-4-0613
        - gpt-4-32k
        - gpt-4-32k-0314
        - gpt-4-32k-0613
        - gpt-3.5-turbo
        - gpt-3.5-turbo-16k
        - gpt-3.5-turbo-0613
        - gpt-3.5-turbo-1106
        - gpt-3.5-turbo-0125
        - gpt-3.5-turbo-16k-0613
    AssistantToolsCode:
      type: object
      title: Code interpreter tool
      properties:
        type:
          type: string
          description: 'The type of tool being defined: `code_interpreter`'
          enum:
            - code_interpreter
          x-stainless-const: true
      required:
        - type
    AssistantToolsFileSearch:
      type: object
      title: FileSearch tool
      properties:
        type:
          type: string
          description: 'The type of tool being defined: `file_search`'
          enum:
            - file_search
          x-stainless-const: true
        file_search:
          type: object
          description: Overrides for the file search tool.
          properties:
            max_num_results:
              type: integer
              minimum: 1
              maximum: 50
              description: >
                The maximum number of results the file search tool should output. The default is 20 for
                `gpt-4*` models and 5 for `gpt-3.5-turbo`. This number should be between 1 and 50 inclusive.


                Note that the file search tool may output fewer than `max_num_results` results. See the [file
                search tool
                documentation](/docs/assistants/tools/file-search#customizing-file-search-settings) for more
                information.
            ranking_options:
              $ref: '#/components/schemas/FileSearchRankingOptions'
      required:
        - type
    AssistantToolsFileSearchTypeOnly:
      type: object
      title: FileSearch tool
      properties:
        type:
          type: string
          description: 'The type of tool being defined: `file_search`'
          enum:
            - file_search
          x-stainless-const: true
      required:
        - type
    AssistantToolsFunction:
      type: object
      title: Function tool
      properties:
        type:
          type: string
          description: 'The type of tool being defined: `function`'
          enum:
            - function
          x-stainless-const: true
        function:
          $ref: '#/components/schemas/FunctionObject'
      required:
        - type
        - function
    AssistantsApiResponseFormatOption:
      description: >
        Specifies the format that the model must output. Compatible with [GPT-4o](/docs/models#gpt-4o), [GPT-4
        Turbo](/docs/models#gpt-4-turbo-and-gpt-4), and all GPT-3.5 Turbo models since `gpt-3.5-turbo-1106`.


        Setting to `{ "type": "json_schema", "json_schema": {...} }` enables Structured Outputs which ensures
        the model will match your supplied JSON schema. Learn more in the [Structured Outputs
        guide](/docs/guides/structured-outputs).


        Setting to `{ "type": "json_object" }` enables JSON mode, which ensures the message the model
        generates is valid JSON.


        **Important:** when using JSON mode, you **must** also instruct the model to produce JSON yourself via
        a system or user message. Without this, the model may generate an unending stream of whitespace until
        the generation reaches the token limit, resulting in a long-running and seemingly "stuck" request.
        Also note that the message content may be partially cut off if `finish_reason="length"`, which
        indicates the generation exceeded `max_tokens` or the conversation exceeded the max context length.
      oneOf:
        - type: string
          description: |
            `auto` is the default value
          enum:
            - auto
          x-stainless-const: true
        - $ref: '#/components/schemas/ResponseFormatText'
        - $ref: '#/components/schemas/ResponseFormatJsonObject'
        - $ref: '#/components/schemas/ResponseFormatJsonSchema'
    AssistantsApiToolChoiceOption:
      description: >
        Controls which (if any) tool is called by the model.

        `none` means the model will not call any tools and instead generates a message.

        `auto` is the default value and means the model can pick between generating a message or calling one
        or more tools.

        `required` means the model must call one or more tools before responding to the user.

        Specifying a particular tool like `{"type": "file_search"}` or `{"type": "function", "function":
        {"name": "my_function"}}` forces the model to call that tool.
      oneOf:
        - type: string
          description: >
            `none` means the model will not call any tools and instead generates a message. `auto` means the
            model can pick between generating a message or calling one or more tools. `required` means the
            model must call one or more tools before responding to the user.
          enum:
            - none
            - auto
            - required
        - $ref: '#/components/schemas/AssistantsNamedToolChoice'
    AssistantsNamedToolChoice:
      type: object
      description: Specifies a tool the model should use. Use to force the model to call a specific tool.
      properties:
        type:
          type: string
          enum:
            - function
            - code_interpreter
            - file_search
          description: The type of the tool. If type is `function`, the function name must be set
        function:
          type: object
          properties:
            name:
              type: string
              description: The name of the function to call.
          required:
            - name
      required:
        - type
    AudioResponseFormat:
      description: >
        The format of the output, in one of these options: `json`, `text`, `srt`, `verbose_json`, or `vtt`.
        For `gpt-4o-transcribe` and `gpt-4o-mini-transcribe`, the only supported format is `json`.
      type: string
      enum:
        - json
        - text
        - srt
        - verbose_json
        - vtt
      default: json
    AuditLog:
      type: object
      description: A log of a user action or configuration change within this organization.
      properties:
        id:
          type: string
          description: The ID of this log.
        type:
          $ref: '#/components/schemas/AuditLogEventType'
        effective_at:
          type: integer
          description: The Unix timestamp (in seconds) of the event.
        project:
          type: object
          description: The project that the action was scoped to. Absent for actions not scoped to projects.
          properties:
            id:
              type: string
              description: The project ID.
            name:
              type: string
              description: The project title.
        actor:
          $ref: '#/components/schemas/AuditLogActor'
        api_key.created:
          type: object
          description: The details for events with this `type`.
          properties:
            id:
              type: string
              description: The tracking ID of the API key.
            data:
              type: object
              description: The payload used to create the API key.
              properties:
                scopes:
                  type: array
                  items:
                    type: string
                  description: A list of scopes allowed for the API key, e.g. `["api.model.request"]`
        api_key.updated:
          type: object
          description: The details for events with this `type`.
          properties:
            id:
              type: string
              description: The tracking ID of the API key.
            changes_requested:
              type: object
              description: The payload used to update the API key.
              properties:
                scopes:
                  type: array
                  items:
                    type: string
                  description: A list of scopes allowed for the API key, e.g. `["api.model.request"]`
        api_key.deleted:
          type: object
          description: The details for events with this `type`.
          properties:
            id:
              type: string
              description: The tracking ID of the API key.
        checkpoint_permission.created:
          type: object
          description: The project and fine-tuned model checkpoint that the checkpoint permission was created for.
          properties:
            id:
              type: string
              description: The ID of the checkpoint permission.
            data:
              type: object
              description: The payload used to create the checkpoint permission.
              properties:
                project_id:
                  type: string
                  description: The ID of the project that the checkpoint permission was created for.
                fine_tuned_model_checkpoint:
                  type: string
                  description: The ID of the fine-tuned model checkpoint.
        checkpoint_permission.deleted:
          type: object
          description: The details for events with this `type`.
          properties:
            id:
              type: string
              description: The ID of the checkpoint permission.
        invite.sent:
          type: object
          description: The details for events with this `type`.
          properties:
            id:
              type: string
              description: The ID of the invite.
            data:
              type: object
              description: The payload used to create the invite.
              properties:
                email:
                  type: string
                  description: The email invited to the organization.
                role:
                  type: string
                  description: The role the email was invited to be. Is either `owner` or `member`.
        invite.accepted:
          type: object
          description: The details for events with this `type`.
          properties:
            id:
              type: string
              description: The ID of the invite.
        invite.deleted:
          type: object
          description: The details for events with this `type`.
          properties:
            id:
              type: string
              description: The ID of the invite.
        login.failed:
          type: object
          description: The details for events with this `type`.
          properties:
            error_code:
              type: string
              description: The error code of the failure.
            error_message:
              type: string
              description: The error message of the failure.
        logout.failed:
          type: object
          description: The details for events with this `type`.
          properties:
            error_code:
              type: string
              description: The error code of the failure.
            error_message:
              type: string
              description: The error message of the failure.
        organization.updated:
          type: object
          description: The details for events with this `type`.
          properties:
            id:
              type: string
              description: The organization ID.
            changes_requested:
              type: object
              description: The payload used to update the organization settings.
              properties:
                title:
                  type: string
                  description: The organization title.
                description:
                  type: string
                  description: The organization description.
                name:
                  type: string
                  description: The organization name.
                threads_ui_visibility:
                  type: string
                  description: >-
                    Visibility of the threads page which shows messages created with the Assistants API and
                    Playground. One of `ANY_ROLE`, `OWNERS`, or `NONE`.
                usage_dashboard_visibility:
                  type: string
                  description: >-
                    Visibility of the usage dashboard which shows activity and costs for your organization.
                    One of `ANY_ROLE` or `OWNERS`.
                api_call_logging:
                  type: string
                  description: >-
                    How your organization logs data from supported API calls. One of `disabled`,
                    `enabled_per_call`, `enabled_for_all_projects`, or `enabled_for_selected_projects`
                api_call_logging_project_ids:
                  type: string
                  description: The list of project ids if api_call_logging is set to `enabled_for_selected_projects`
        project.created:
          type: object
          description: The details for events with this `type`.
          properties:
            id:
              type: string
              description: The project ID.
            data:
              type: object
              description: The payload used to create the project.
              properties:
                name:
                  type: string
                  description: The project name.
                title:
                  type: string
                  description: The title of the project as seen on the dashboard.
        project.updated:
          type: object
          description: The details for events with this `type`.
          properties:
            id:
              type: string
              description: The project ID.
            changes_requested:
              type: object
              description: The payload used to update the project.
              properties:
                title:
                  type: string
                  description: The title of the project as seen on the dashboard.
        project.archived:
          type: object
          description: The details for events with this `type`.
          properties:
            id:
              type: string
              description: The project ID.
        rate_limit.updated:
          type: object
          description: The details for events with this `type`.
          properties:
            id:
              type: string
              description: The rate limit ID
            changes_requested:
              type: object
              description: The payload used to update the rate limits.
              properties:
                max_requests_per_1_minute:
                  type: integer
                  description: The maximum requests per minute.
                max_tokens_per_1_minute:
                  type: integer
                  description: The maximum tokens per minute.
                max_images_per_1_minute:
                  type: integer
                  description: The maximum images per minute. Only relevant for certain models.
                max_audio_megabytes_per_1_minute:
                  type: integer
                  description: The maximum audio megabytes per minute. Only relevant for certain models.
                max_requests_per_1_day:
                  type: integer
                  description: The maximum requests per day. Only relevant for certain models.
                batch_1_day_max_input_tokens:
                  type: integer
                  description: The maximum batch input tokens per day. Only relevant for certain models.
        rate_limit.deleted:
          type: object
          description: The details for events with this `type`.
          properties:
            id:
              type: string
              description: The rate limit ID
        service_account.created:
          type: object
          description: The details for events with this `type`.
          properties:
            id:
              type: string
              description: The service account ID.
            data:
              type: object
              description: The payload used to create the service account.
              properties:
                role:
                  type: string
                  description: The role of the service account. Is either `owner` or `member`.
        service_account.updated:
          type: object
          description: The details for events with this `type`.
          properties:
            id:
              type: string
              description: The service account ID.
            changes_requested:
              type: object
              description: The payload used to updated the service account.
              properties:
                role:
                  type: string
                  description: The role of the service account. Is either `owner` or `member`.
        service_account.deleted:
          type: object
          description: The details for events with this `type`.
          properties:
            id:
              type: string
              description: The service account ID.
        user.added:
          type: object
          description: The details for events with this `type`.
          properties:
            id:
              type: string
              description: The user ID.
            data:
              type: object
              description: The payload used to add the user to the project.
              properties:
                role:
                  type: string
                  description: The role of the user. Is either `owner` or `member`.
        user.updated:
          type: object
          description: The details for events with this `type`.
          properties:
            id:
              type: string
              description: The project ID.
            changes_requested:
              type: object
              description: The payload used to update the user.
              properties:
                role:
                  type: string
                  description: The role of the user. Is either `owner` or `member`.
        user.deleted:
          type: object
          description: The details for events with this `type`.
          properties:
            id:
              type: string
              description: The user ID.
        certificate.created:
          type: object
          description: The details for events with this `type`.
          properties:
            id:
              type: string
              description: The certificate ID.
            name:
              type: string
              description: The name of the certificate.
        certificate.updated:
          type: object
          description: The details for events with this `type`.
          properties:
            id:
              type: string
              description: The certificate ID.
            name:
              type: string
              description: The name of the certificate.
        certificate.deleted:
          type: object
          description: The details for events with this `type`.
          properties:
            id:
              type: string
              description: The certificate ID.
            name:
              type: string
              description: The name of the certificate.
            certificate:
              type: string
              description: The certificate content in PEM format.
        certificates.activated:
          type: object
          description: The details for events with this `type`.
          properties:
            certificates:
              type: array
              items:
                type: object
                properties:
                  id:
                    type: string
                    description: The certificate ID.
                  name:
                    type: string
                    description: The name of the certificate.
        certificates.deactivated:
          type: object
          description: The details for events with this `type`.
          properties:
            certificates:
              type: array
              items:
                type: object
                properties:
                  id:
                    type: string
                    description: The certificate ID.
                  name:
                    type: string
                    description: The name of the certificate.
      required:
        - id
        - type
        - effective_at
        - actor
      x-oaiMeta:
        name: The audit log object
        example: |
          {
              "id": "req_xxx_20240101",
              "type": "api_key.created",
              "effective_at": 1720804090,
              "actor": {
                  "type": "session",
                  "session": {
                      "user": {
                          "id": "user-xxx",
                          "email": "user@example.com"
                      },
                      "ip_address": "127.0.0.1",
                      "user_agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36"
                  }
              },
              "api_key.created": {
                  "id": "key_xxxx",
                  "data": {
                      "scopes": ["resource.operation"]
                  }
              }
          }
    AuditLogActor:
      type: object
      description: The actor who performed the audit logged action.
      properties:
        type:
          type: string
          description: The type of actor. Is either `session` or `api_key`.
          enum:
            - session
            - api_key
        session:
          $ref: '#/components/schemas/AuditLogActorSession'
        api_key:
          $ref: '#/components/schemas/AuditLogActorApiKey'
    AuditLogActorApiKey:
      type: object
      description: The API Key used to perform the audit logged action.
      properties:
        id:
          type: string
          description: The tracking id of the API key.
        type:
          type: string
          description: The type of API key. Can be either `user` or `service_account`.
          enum:
            - user
            - service_account
        user:
          $ref: '#/components/schemas/AuditLogActorUser'
        service_account:
          $ref: '#/components/schemas/AuditLogActorServiceAccount'
    AuditLogActorServiceAccount:
      type: object
      description: The service account that performed the audit logged action.
      properties:
        id:
          type: string
          description: The service account id.
    AuditLogActorSession:
      type: object
      description: The session in which the audit logged action was performed.
      properties:
        user:
          $ref: '#/components/schemas/AuditLogActorUser'
        ip_address:
          type: string
          description: The IP address from which the action was performed.
    AuditLogActorUser:
      type: object
      description: The user who performed the audit logged action.
      properties:
        id:
          type: string
          description: The user id.
        email:
          type: string
          description: The user email.
    AuditLogEventType:
      type: string
      description: The event type.
      enum:
        - api_key.created
        - api_key.updated
        - api_key.deleted
        - checkpoint_permission.created
        - checkpoint_permission.deleted
        - invite.sent
        - invite.accepted
        - invite.deleted
        - login.succeeded
        - login.failed
        - logout.succeeded
        - logout.failed
        - organization.updated
        - project.created
        - project.updated
        - project.archived
        - service_account.created
        - service_account.updated
        - service_account.deleted
        - rate_limit.updated
        - rate_limit.deleted
        - user.added
        - user.updated
        - user.deleted
    AutoChunkingStrategyRequestParam:
      type: object
      title: Auto Chunking Strategy
      description: >-
        The default strategy. This strategy currently uses a `max_chunk_size_tokens` of `800` and
        `chunk_overlap_tokens` of `400`.
      additionalProperties: false
      properties:
        type:
          type: string
          description: Always `auto`.
          enum:
            - auto
          x-stainless-const: true
      required:
        - type
    Batch:
      type: object
      properties:
        id:
          type: string
        object:
          type: string
          enum:
            - batch
          description: The object type, which is always `batch`.
          x-stainless-const: true
        endpoint:
          type: string
          description: The OpenAI API endpoint used by the batch.
        errors:
          type: object
          properties:
            object:
              type: string
              description: The object type, which is always `list`.
            data:
              type: array
              items:
                type: object
                properties:
                  code:
                    type: string
                    description: An error code identifying the error type.
                  message:
                    type: string
                    description: A human-readable message providing more details about the error.
                  param:
                    type: string
                    description: The name of the parameter that caused the error, if applicable.
                    nullable: true
                  line:
                    type: integer
                    description: The line number of the input file where the error occurred, if applicable.
                    nullable: true
        input_file_id:
          type: string
          description: The ID of the input file for the batch.
        completion_window:
          type: string
          description: The time frame within which the batch should be processed.
        status:
          type: string
          description: The current status of the batch.
          enum:
            - validating
            - failed
            - in_progress
            - finalizing
            - completed
            - expired
            - cancelling
            - cancelled
        output_file_id:
          type: string
          description: The ID of the file containing the outputs of successfully executed requests.
        error_file_id:
          type: string
          description: The ID of the file containing the outputs of requests with errors.
        created_at:
          type: integer
          description: The Unix timestamp (in seconds) for when the batch was created.
        in_progress_at:
          type: integer
          description: The Unix timestamp (in seconds) for when the batch started processing.
        expires_at:
          type: integer
          description: The Unix timestamp (in seconds) for when the batch will expire.
        finalizing_at:
          type: integer
          description: The Unix timestamp (in seconds) for when the batch started finalizing.
        completed_at:
          type: integer
          description: The Unix timestamp (in seconds) for when the batch was completed.
        failed_at:
          type: integer
          description: The Unix timestamp (in seconds) for when the batch failed.
        expired_at:
          type: integer
          description: The Unix timestamp (in seconds) for when the batch expired.
        cancelling_at:
          type: integer
          description: The Unix timestamp (in seconds) for when the batch started cancelling.
        cancelled_at:
          type: integer
          description: The Unix timestamp (in seconds) for when the batch was cancelled.
        request_counts:
          type: object
          properties:
            total:
              type: integer
              description: Total number of requests in the batch.
            completed:
              type: integer
              description: Number of requests that have been completed successfully.
            failed:
              type: integer
              description: Number of requests that have failed.
          required:
            - total
            - completed
            - failed
          description: The request counts for different statuses within the batch.
        metadata:
          $ref: '#/components/schemas/Metadata'
      required:
        - id
        - object
        - endpoint
        - input_file_id
        - completion_window
        - status
        - created_at
      x-oaiMeta:
        name: The batch object
        example: |
          {
            "id": "batch_abc123",
            "object": "batch",
            "endpoint": "/v1/completions",
            "errors": null,
            "input_file_id": "file-abc123",
            "completion_window": "24h",
            "status": "completed",
            "output_file_id": "file-cvaTdG",
            "error_file_id": "file-HOWS94",
            "created_at": 1711471533,
            "in_progress_at": 1711471538,
            "expires_at": 1711557933,
            "finalizing_at": 1711493133,
            "completed_at": 1711493163,
            "failed_at": null,
            "expired_at": null,
            "cancelling_at": null,
            "cancelled_at": null,
            "request_counts": {
              "total": 100,
              "completed": 95,
              "failed": 5
            },
            "metadata": {
              "customer_id": "user_123456789",
              "batch_description": "Nightly eval job",
            }
          }
    BatchRequestInput:
      type: object
      description: The per-line object of the batch input file
      properties:
        custom_id:
          type: string
          description: >-
            A developer-provided per-request id that will be used to match outputs to inputs. Must be unique
            for each request in a batch.
        method:
          type: string
          enum:
            - POST
          description: The HTTP method to be used for the request. Currently only `POST` is supported.
          x-stainless-const: true
        url:
          type: string
          description: >-
            The OpenAI API relative URL to be used for the request. Currently `/v1/chat/completions`,
            `/v1/embeddings`, and `/v1/completions` are supported.
      x-oaiMeta:
        name: The request input object
        example: >
          {"custom_id": "request-1", "method": "POST", "url": "/v1/chat/completions", "body": {"model":
          "gpt-4o-mini", "messages": [{"role": "system", "content": "You are a helpful assistant."}, {"role":
          "user", "content": "What is 2+2?"}]}}
    BatchRequestOutput:
      type: object
      description: The per-line object of the batch output and error files
      properties:
        id:
          type: string
        custom_id:
          type: string
          description: A developer-provided per-request id that will be used to match outputs to inputs.
        response:
          type: object
          nullable: true
          properties:
            status_code:
              type: integer
              description: The HTTP status code of the response
            request_id:
              type: string
              description: >-
                An unique identifier for the OpenAI API request. Please include this request ID when
                contacting support.
            body:
              type: object
              x-oaiTypeLabel: map
              description: The JSON body of the response
        error:
          type: object
          nullable: true
          description: >-
            For requests that failed with a non-HTTP error, this will contain more information on the cause of
            the failure.
          properties:
            code:
              type: string
              description: A machine-readable error code.
            message:
              type: string
              description: A human-readable error message.
      x-oaiMeta:
        name: The request output object
        example: >
          {"id": "batch_req_wnaDys", "custom_id": "request-2", "response": {"status_code": 200, "request_id":
          "req_c187b3", "body": {"id": "chatcmpl-9758Iw", "object": "chat.completion", "created": 1711475054,
          "model": "gpt-4o-mini", "choices": [{"index": 0, "message": {"role": "assistant", "content": "2 + 2
          equals 4."}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 24, "completion_tokens": 15,
          "total_tokens": 39}, "system_fingerprint": null}}, "error": null}
    Certificate:
      type: object
      description: Represents an individual `certificate` uploaded to the organization.
      properties:
        object:
          type: string
          enum:
            - certificate
            - organization.certificate
            - organization.project.certificate
          description: >
            The object type.


            - If creating, updating, or getting a specific certificate, the object type is `certificate`.

            - If listing, activating, or deactivating certificates for the organization, the object type is
            `organization.certificate`.

            - If listing, activating, or deactivating certificates for a project, the object type is
            `organization.project.certificate`.
          x-stainless-const: true
        id:
          type: string
          description: The identifier, which can be referenced in API endpoints
        name:
          type: string
          description: The name of the certificate.
        created_at:
          type: integer
          description: The Unix timestamp (in seconds) of when the certificate was uploaded.
        certificate_details:
          type: object
          properties:
            valid_at:
              type: integer
              description: The Unix timestamp (in seconds) of when the certificate becomes valid.
            expires_at:
              type: integer
              description: The Unix timestamp (in seconds) of when the certificate expires.
            content:
              type: string
              description: The content of the certificate in PEM format.
        active:
          type: boolean
          description: >-
            Whether the certificate is currently active at the specified scope. Not returned when getting
            details for a specific certificate.
      required:
        - object
        - id
        - name
        - created_at
        - certificate_details
      x-oaiMeta:
        name: The certificate object
        example: |
          {
            "object": "certificate",
            "id": "cert_abc",
            "name": "My Certificate",
            "created_at": 1234567,
            "certificate_details": {
              "valid_at": 1234567,
              "expires_at": 12345678,
              "content": "-----BEGIN CERTIFICATE----- MIIGAjCCA...6znFlOW+ -----END CERTIFICATE-----"
            }
          }
    ChatCompletionDeleted:
      type: object
      properties:
        object:
          type: string
          description: The type of object being deleted.
          enum:
            - chat.completion.deleted
          x-stainless-const: true
        id:
          type: string
          description: The ID of the chat completion that was deleted.
        deleted:
          type: boolean
          description: Whether the chat completion was deleted.
      required:
        - object
        - id
        - deleted
    ChatCompletionFunctionCallOption:
      type: object
      description: |
        Specifying a particular function via `{"name": "my_function"}` forces the model to call that function.
      properties:
        name:
          type: string
          description: The name of the function to call.
      required:
        - name
    ChatCompletionFunctions:
      type: object
      deprecated: true
      properties:
        description:
          type: string
          description: >-
            A description of what the function does, used by the model to choose when and how to call the
            function.
        name:
          type: string
          description: >-
            The name of the function to be called. Must be a-z, A-Z, 0-9, or contain underscores and dashes,
            with a maximum length of 64.
        parameters:
          $ref: '#/components/schemas/FunctionParameters'
      required:
        - name
    ChatCompletionList:
      type: object
      title: ChatCompletionList
      description: |
        An object representing a list of Chat Completions.
      properties:
        object:
          type: string
          enum:
            - list
          default: list
          description: |
            The type of this object. It is always set to "list".
          x-stainless-const: true
        data:
          type: array
          description: |
            An array of chat completion objects.
          items:
            $ref: '#/components/schemas/CreateChatCompletionResponse'
        first_id:
          type: string
          description: The identifier of the first chat completion in the data array.
        last_id:
          type: string
          description: The identifier of the last chat completion in the data array.
        has_more:
          type: boolean
          description: Indicates whether there are more Chat Completions available.
      required:
        - object
        - data
        - first_id
        - last_id
        - has_more
      x-oaiMeta:
        name: The chat completion list object
        group: chat
        example: |
          {
            "object": "list",
            "data": [
              {
                "object": "chat.completion",
                "id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2",
                "model": "gpt-4o-2024-08-06",
                "created": 1738960610,
                "request_id": "req_ded8ab984ec4bf840f37566c1011c417",
                "tool_choice": null,
                "usage": {
                  "total_tokens": 31,
                  "completion_tokens": 18,
                  "prompt_tokens": 13
                },
                "seed": 4944116822809979520,
                "top_p": 1.0,
                "temperature": 1.0,
                "presence_penalty": 0.0,
                "frequency_penalty": 0.0,
                "system_fingerprint": "fp_50cad350e4",
                "input_user": null,
                "service_tier": "default",
                "tools": null,
                "metadata": {},
                "choices": [
                  {
                    "index": 0,
                    "message": {
                      "content": "Mind of circuits hum,  \nLearning patterns in silence—  \nFuture's quiet spark.",
                      "role": "assistant",
                      "tool_calls": null,
                      "function_call": null
                    },
                    "finish_reason": "stop",
                    "logprobs": null
                  }
                ],
                "response_format": null
              }
            ],
            "first_id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2",
            "last_id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2",
            "has_more": false
          }
    ChatCompletionMessageList:
      type: object
      title: ChatCompletionMessageList
      description: |
        An object representing a list of chat completion messages.
      properties:
        object:
          type: string
          enum:
            - list
          default: list
          description: |
            The type of this object. It is always set to "list".
          x-stainless-const: true
        data:
          type: array
          description: |
            An array of chat completion message objects.
          items:
            allOf:
              - $ref: '#/components/schemas/ChatCompletionResponseMessage'
              - type: object
                required:
                  - id
                properties:
                  id:
                    type: string
                    description: The identifier of the chat message.
        first_id:
          type: string
          description: The identifier of the first chat message in the data array.
        last_id:
          type: string
          description: The identifier of the last chat message in the data array.
        has_more:
          type: boolean
          description: Indicates whether there are more chat messages available.
      required:
        - object
        - data
        - first_id
        - last_id
        - has_more
      x-oaiMeta:
        name: The chat completion message list object
        group: chat
        example: |
          {
            "object": "list",
            "data": [
              {
                "id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2-0",
                "role": "user",
                "content": "write a haiku about ai",
                "name": null,
                "content_parts": null
              }
            ],
            "first_id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2-0",
            "last_id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2-0",
            "has_more": false
          }
    ChatCompletionMessageToolCall:
      type: object
      properties:
        id:
          type: string
          description: The ID of the tool call.
        type:
          type: string
          enum:
            - function
          description: The type of the tool. Currently, only `function` is supported.
          x-stainless-const: true
        function:
          type: object
          description: The function that the model called.
          properties:
            name:
              type: string
              description: The name of the function to call.
            arguments:
              type: string
              description: >-
                The arguments to call the function with, as generated by the model in JSON format. Note that
                the model does not always generate valid JSON, and may hallucinate parameters not defined by
                your function schema. Validate the arguments in your code before calling your function.
          required:
            - name
            - arguments
      required:
        - id
        - type
        - function
    ChatCompletionMessageToolCallChunk:
      type: object
      properties:
        index:
          type: integer
        id:
          type: string
          description: The ID of the tool call.
        type:
          type: string
          enum:
            - function
          description: The type of the tool. Currently, only `function` is supported.
          x-stainless-const: true
        function:
          type: object
          properties:
            name:
              type: string
              description: The name of the function to call.
            arguments:
              type: string
              description: >-
                The arguments to call the function with, as generated by the model in JSON format. Note that
                the model does not always generate valid JSON, and may hallucinate parameters not defined by
                your function schema. Validate the arguments in your code before calling your function.
      required:
        - index
    ChatCompletionMessageToolCalls:
      type: array
      description: The tool calls generated by the model, such as function calls.
      items:
        $ref: '#/components/schemas/ChatCompletionMessageToolCall'
    ChatCompletionModalities:
      type: array
      nullable: true
      description: |
        Output types that you would like the model to generate for this request.
        Most models are capable of generating text, which is the default:

        `["text"]`

        The `gpt-4o-audio-preview` model can also be used to [generate audio](/docs/guides/audio). To
        request that this model generate both text and audio responses, you can
        use:

        `["text", "audio"]`
      items:
        type: string
        enum:
          - text
          - audio
    ChatCompletionNamedToolChoice:
      type: object
      description: Specifies a tool the model should use. Use to force the model to call a specific function.
      properties:
        type:
          type: string
          enum:
            - function
          description: The type of the tool. Currently, only `function` is supported.
          x-stainless-const: true
        function:
          type: object
          properties:
            name:
              type: string
              description: The name of the function to call.
          required:
            - name
      required:
        - type
        - function
    ChatCompletionRequestAssistantMessage:
      type: object
      title: Assistant message
      description: |
        Messages sent by the model in response to user messages.
      properties:
        content:
          nullable: true
          oneOf:
            - type: string
              description: The contents of the assistant message.
              title: Text content
            - type: array
              description: >-
                An array of content parts with a defined type. Can be one or more of type `text`, or exactly
                one of type `refusal`.
              title: Array of content parts
              items:
                $ref: '#/components/schemas/ChatCompletionRequestAssistantMessageContentPart'
              minItems: 1
          description: >
            The contents of the assistant message. Required unless `tool_calls` or `function_call` is
            specified.
        refusal:
          nullable: true
          type: string
          description: The refusal message by the assistant.
        role:
          type: string
          enum:
            - assistant
          description: The role of the messages author, in this case `assistant`.
          x-stainless-const: true
        name:
          type: string
          description: >-
            An optional name for the participant. Provides the model information to differentiate between
            participants of the same role.
        audio:
          type: object
          nullable: true
          description: |
            Data about a previous audio response from the model. 
            [Learn more](/docs/guides/audio).
          required:
            - id
          properties:
            id:
              type: string
              description: |
                Unique identifier for a previous audio response from the model.
        tool_calls:
          $ref: '#/components/schemas/ChatCompletionMessageToolCalls'
        function_call:
          type: object
          deprecated: true
          description: >-
            Deprecated and replaced by `tool_calls`. The name and arguments of a function that should be
            called, as generated by the model.
          nullable: true
          properties:
            arguments:
              type: string
              description: >-
                The arguments to call the function with, as generated by the model in JSON format. Note that
                the model does not always generate valid JSON, and may hallucinate parameters not defined by
                your function schema. Validate the arguments in your code before calling your function.
            name:
              type: string
              description: The name of the function to call.
          required:
            - arguments
            - name
      required:
        - role
    ChatCompletionRequestAssistantMessageContentPart:
      oneOf:
        - $ref: '#/components/schemas/ChatCompletionRequestMessageContentPartText'
        - $ref: '#/components/schemas/ChatCompletionRequestMessageContentPartRefusal'
    ChatCompletionRequestDeveloperMessage:
      type: object
      title: Developer message
      description: |
        Developer-provided instructions that the model should follow, regardless of
        messages sent by the user. With o1 models and newer, `developer` messages
        replace the previous `system` messages.
      properties:
        content:
          description: The contents of the developer message.
          oneOf:
            - type: string
              description: The contents of the developer message.
              title: Text content
            - type: array
              description: >-
                An array of content parts with a defined type. For developer messages, only type `text` is
                supported.
              title: Array of content parts
              items:
                $ref: '#/components/schemas/ChatCompletionRequestMessageContentPartText'
              minItems: 1
        role:
          type: string
          enum:
            - developer
          description: The role of the messages author, in this case `developer`.
          x-stainless-const: true
        name:
          type: string
          description: >-
            An optional name for the participant. Provides the model information to differentiate between
            participants of the same role.
      required:
        - content
        - role
    ChatCompletionRequestFunctionMessage:
      type: object
      title: Function message
      deprecated: true
      properties:
        role:
          type: string
          enum:
            - function
          description: The role of the messages author, in this case `function`.
          x-stainless-const: true
        content:
          nullable: true
          type: string
          description: The contents of the function message.
        name:
          type: string
          description: The name of the function to call.
      required:
        - role
        - content
        - name
    ChatCompletionRequestMessage:
      oneOf:
        - $ref: '#/components/schemas/ChatCompletionRequestDeveloperMessage'
        - $ref: '#/components/schemas/ChatCompletionRequestSystemMessage'
        - $ref: '#/components/schemas/ChatCompletionRequestUserMessage'
        - $ref: '#/components/schemas/ChatCompletionRequestAssistantMessage'
        - $ref: '#/components/schemas/ChatCompletionRequestToolMessage'
        - $ref: '#/components/schemas/ChatCompletionRequestFunctionMessage'
    ChatCompletionRequestMessageContentPartAudio:
      type: object
      title: Audio content part
      description: |
        Learn about [audio inputs](/docs/guides/audio).
      properties:
        type:
          type: string
          enum:
            - input_audio
          description: The type of the content part. Always `input_audio`.
          x-stainless-const: true
        input_audio:
          type: object
          properties:
            data:
              type: string
              description: Base64 encoded audio data.
            format:
              type: string
              enum:
                - wav
                - mp3
              description: |
                The format of the encoded audio data. Currently supports "wav" and "mp3".
          required:
            - data
            - format
      required:
        - type
        - input_audio
    ChatCompletionRequestMessageContentPartFile:
      type: object
      title: File content part
      description: |
        Learn about [file inputs](/docs/guides/text) for text generation.
      properties:
        type:
          type: string
          enum:
            - file
          description: The type of the content part. Always `file`.
          x-stainless-const: true
        file:
          type: object
          properties:
            filename:
              type: string
              description: |
                The name of the file, used when passing the file to the model as a 
                string.
            file_data:
              type: string
              description: |
                The base64 encoded file data, used when passing the file to the model 
                as a string.
            file_id:
              type: string
              description: |
                The ID of an uploaded file to use as input.
      required:
        - type
        - file
    ChatCompletionRequestMessageContentPartImage:
      type: object
      title: Image content part
      description: |
        Learn about [image inputs](/docs/guides/vision).
      properties:
        type:
          type: string
          enum:
            - image_url
          description: The type of the content part.
          x-stainless-const: true
        image_url:
          type: object
          properties:
            url:
              type: string
              description: Either a URL of the image or the base64 encoded image data.
              format: uri
            detail:
              type: string
              description: >-
                Specifies the detail level of the image. Learn more in the [Vision
                guide](/docs/guides/vision#low-or-high-fidelity-image-understanding).
              enum:
                - auto
                - low
                - high
              default: auto
          required:
            - url
      required:
        - type
        - image_url
    ChatCompletionRequestMessageContentPartRefusal:
      type: object
      title: Refusal content part
      properties:
        type:
          type: string
          enum:
            - refusal
          description: The type of the content part.
          x-stainless-const: true
        refusal:
          type: string
          description: The refusal message generated by the model.
      required:
        - type
        - refusal
    ChatCompletionRequestMessageContentPartText:
      type: object
      title: Text content part
      description: |
        Learn about [text inputs](/docs/guides/text-generation).
      properties:
        type:
          type: string
          enum:
            - text
          description: The type of the content part.
          x-stainless-const: true
        text:
          type: string
          description: The text content.
      required:
        - type
        - text
    ChatCompletionRequestSystemMessage:
      type: object
      title: System message
      description: |
        Developer-provided instructions that the model should follow, regardless of
        messages sent by the user. With o1 models and newer, use `developer` messages
        for this purpose instead.
      properties:
        content:
          description: The contents of the system message.
          oneOf:
            - type: string
              description: The contents of the system message.
              title: Text content
            - type: array
              description: >-
                An array of content parts with a defined type. For system messages, only type `text` is
                supported.
              title: Array of content parts
              items:
                $ref: '#/components/schemas/ChatCompletionRequestSystemMessageContentPart'
              minItems: 1
        role:
          type: string
          enum:
            - system
          description: The role of the messages author, in this case `system`.
          x-stainless-const: true
        name:
          type: string
          description: >-
            An optional name for the participant. Provides the model information to differentiate between
            participants of the same role.
      required:
        - content
        - role
    ChatCompletionRequestSystemMessageContentPart:
      oneOf:
        - $ref: '#/components/schemas/ChatCompletionRequestMessageContentPartText'
    ChatCompletionRequestToolMessage:
      type: object
      title: Tool message
      properties:
        role:
          type: string
          enum:
            - tool
          description: The role of the messages author, in this case `tool`.
          x-stainless-const: true
        content:
          oneOf:
            - type: string
              description: The contents of the tool message.
              title: Text content
            - type: array
              description: >-
                An array of content parts with a defined type. For tool messages, only type `text` is
                supported.
              title: Array of content parts
              items:
                $ref: '#/components/schemas/ChatCompletionRequestToolMessageContentPart'
              minItems: 1
          description: The contents of the tool message.
        tool_call_id:
          type: string
          description: Tool call that this message is responding to.
      required:
        - role
        - content
        - tool_call_id
    ChatCompletionRequestToolMessageContentPart:
      oneOf:
        - $ref: '#/components/schemas/ChatCompletionRequestMessageContentPartText'
    ChatCompletionRequestUserMessage:
      type: object
      title: User message
      description: |
        Messages sent by an end user, containing prompts or additional context
        information.
      properties:
        content:
          description: |
            The contents of the user message.
          oneOf:
            - type: string
              description: The text contents of the message.
              title: Text content
            - type: array
              description: >-
                An array of content parts with a defined type. Supported options differ based on the
                [model](/docs/models) being used to generate the response. Can contain text, image, or audio
                inputs.
              title: Array of content parts
              items:
                $ref: '#/components/schemas/ChatCompletionRequestUserMessageContentPart'
              minItems: 1
        role:
          type: string
          enum:
            - user
          description: The role of the messages author, in this case `user`.
          x-stainless-const: true
        name:
          type: string
          description: >-
            An optional name for the participant. Provides the model information to differentiate between
            participants of the same role.
      required:
        - content
        - role
    ChatCompletionRequestUserMessageContentPart:
      oneOf:
        - $ref: '#/components/schemas/ChatCompletionRequestMessageContentPartText'
        - $ref: '#/components/schemas/ChatCompletionRequestMessageContentPartImage'
        - $ref: '#/components/schemas/ChatCompletionRequestMessageContentPartAudio'
        - $ref: '#/components/schemas/ChatCompletionRequestMessageContentPartFile'
    ChatCompletionResponseMessage:
      type: object
      description: A chat completion message generated by the model.
      properties:
        content:
          type: string
          description: The contents of the message.
          nullable: true
        refusal:
          type: string
          description: The refusal message generated by the model.
          nullable: true
        tool_calls:
          $ref: '#/components/schemas/ChatCompletionMessageToolCalls'
        annotations:
          type: array
          description: |
            Annotations for the message, when applicable, as when using the
            [web search tool](/docs/guides/tools-web-search?api-mode=chat).
          items:
            type: object
            description: |
              A URL citation when using web search.
            required:
              - type
              - url_citation
            properties:
              type:
                type: string
                description: The type of the URL citation. Always `url_citation`.
                enum:
                  - url_citation
                x-stainless-const: true
              url_citation:
                type: object
                description: A URL citation when using web search.
                required:
                  - end_index
                  - start_index
                  - url
                  - title
                properties:
                  end_index:
                    type: integer
                    description: The index of the last character of the URL citation in the message.
                  start_index:
                    type: integer
                    description: The index of the first character of the URL citation in the message.
                  url:
                    type: string
                    description: The URL of the web resource.
                  title:
                    type: string
                    description: The title of the web resource.
        role:
          type: string
          enum:
            - assistant
          description: The role of the author of this message.
          x-stainless-const: true
        function_call:
          type: object
          deprecated: true
          description: >-
            Deprecated and replaced by `tool_calls`. The name and arguments of a function that should be
            called, as generated by the model.
          properties:
            arguments:
              type: string
              description: >-
                The arguments to call the function with, as generated by the model in JSON format. Note that
                the model does not always generate valid JSON, and may hallucinate parameters not defined by
                your function schema. Validate the arguments in your code before calling your function.
            name:
              type: string
              description: The name of the function to call.
          required:
            - name
            - arguments
        audio:
          type: object
          nullable: true
          description: |
            If the audio output modality is requested, this object contains data
            about the audio response from the model. [Learn more](/docs/guides/audio).
          required:
            - id
            - expires_at
            - data
            - transcript
          properties:
            id:
              type: string
              description: Unique identifier for this audio response.
            expires_at:
              type: integer
              description: |
                The Unix timestamp (in seconds) for when this audio response will
                no longer be accessible on the server for use in multi-turn
                conversations.
            data:
              type: string
              description: |
                Base64 encoded audio bytes generated by the model, in the format
                specified in the request.
            transcript:
              type: string
              description: Transcript of the audio generated by the model.
      required:
        - role
        - content
        - refusal
    ChatCompletionRole:
      type: string
      description: The role of the author of a message
      enum:
        - developer
        - system
        - user
        - assistant
        - tool
        - function
    ChatCompletionStreamOptions:
      description: |
        Options for streaming response. Only set this when you set `stream: true`.
      type: object
      nullable: true
      default: null
      properties:
        include_usage:
          type: boolean
          description: |
            If set, an additional chunk will be streamed before the `data: [DONE]`
            message. The `usage` field on this chunk shows the token usage statistics
            for the entire request, and the `choices` field will always be an empty
            array. 

            All other chunks will also include a `usage` field, but with a null
            value. **NOTE:** If the stream is interrupted, you may not receive the
            final usage chunk which contains the total token usage for the request.
    ChatCompletionStreamResponseDelta:
      type: object
      description: A chat completion delta generated by streamed model responses.
      properties:
        content:
          type: string
          description: The contents of the chunk message.
          nullable: true
        function_call:
          deprecated: true
          type: object
          description: >-
            Deprecated and replaced by `tool_calls`. The name and arguments of a function that should be
            called, as generated by the model.
          properties:
            arguments:
              type: string
              description: >-
                The arguments to call the function with, as generated by the model in JSON format. Note that
                the model does not always generate valid JSON, and may hallucinate parameters not defined by
                your function schema. Validate the arguments in your code before calling your function.
            name:
              type: string
              description: The name of the function to call.
        tool_calls:
          type: array
          items:
            $ref: '#/components/schemas/ChatCompletionMessageToolCallChunk'
        role:
          type: string
          enum:
            - developer
            - system
            - user
            - assistant
            - tool
          description: The role of the author of this message.
        refusal:
          type: string
          description: The refusal message generated by the model.
          nullable: true
    ChatCompletionTokenLogprob:
      type: object
      properties:
        token:
          description: The token.
          type: string
        logprob:
          description: >-
            The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the
            value `-9999.0` is used to signify that the token is very unlikely.
          type: number
        bytes:
          description: >-
            A list of integers representing the UTF-8 bytes representation of the token. Useful in instances
            where characters are represented by multiple tokens and their byte representations must be
            combined to generate the correct text representation. Can be `null` if there is no bytes
            representation for the token.
          type: array
          items:
            type: integer
          nullable: true
        top_logprobs:
          description: >-
            List of the most likely tokens and their log probability, at this token position. In rare cases,
            there may be fewer than the number of requested `top_logprobs` returned.
          type: array
          items:
            type: object
            properties:
              token:
                description: The token.
                type: string
              logprob:
                description: >-
                  The log probability of this token, if it is within the top 20 most likely tokens. Otherwise,
                  the value `-9999.0` is used to signify that the token is very unlikely.
                type: number
              bytes:
                description: >-
                  A list of integers representing the UTF-8 bytes representation of the token. Useful in
                  instances where characters are represented by multiple tokens and their byte representations
                  must be combined to generate the correct text representation. Can be `null` if there is no
                  bytes representation for the token.
                type: array
                items:
                  type: integer
                nullable: true
            required:
              - token
              - logprob
              - bytes
      required:
        - token
        - logprob
        - bytes
        - top_logprobs
    ChatCompletionTool:
      type: object
      properties:
        type:
          type: string
          enum:
            - function
          description: The type of the tool. Currently, only `function` is supported.
          x-stainless-const: true
        function:
          $ref: '#/components/schemas/FunctionObject'
      required:
        - type
        - function
    ChatCompletionToolChoiceOption:
      description: >
        Controls which (if any) tool is called by the model.

        `none` means the model will not call any tool and instead generates a message.

        `auto` means the model can pick between generating a message or calling one or more tools.

        `required` means the model must call one or more tools.

        Specifying a particular tool via `{"type": "function", "function": {"name": "my_function"}}` forces
        the model to call that tool.


        `none` is the default when no tools are present. `auto` is the default if tools are present.
      oneOf:
        - type: string
          description: >
            `none` means the model will not call any tool and instead generates a message. `auto` means the
            model can pick between generating a message or calling one or more tools. `required` means the
            model must call one or more tools.
          enum:
            - none
            - auto
            - required
        - $ref: '#/components/schemas/ChatCompletionNamedToolChoice'
    ChunkingStrategyRequestParam:
      type: object
      description: The chunking strategy used to chunk the file(s). If not set, will use the `auto` strategy.
      oneOf:
        - $ref: '#/components/schemas/AutoChunkingStrategyRequestParam'
        - $ref: '#/components/schemas/StaticChunkingStrategyRequestParam'
    Click:
      type: object
      title: Click
      description: |
        A click action.
      properties:
        type:
          type: string
          enum:
            - click
          default: click
          description: |
            Specifies the event type. For a click action, this property is 
            always set to `click`.
          x-stainless-const: true
        button:
          type: string
          enum:
            - left
            - right
            - wheel
            - back
            - forward
          description: >
            Indicates which mouse button was pressed during the click. One of `left`, `right`, `wheel`,
            `back`, or `forward`.
        x:
          type: integer
          description: |
            The x-coordinate where the click occurred.
        'y':
          type: integer
          description: |
            The y-coordinate where the click occurred.
      required:
        - type
        - button
        - x
        - 'y'
    CodeInterpreterFileOutput:
      type: object
      title: Code interpreter file output
      description: |
        The output of a code interpreter tool call that is a file.
      properties:
        type:
          type: string
          enum:
            - files
          description: |
            The type of the code interpreter file output. Always `files`.
          x-stainless-const: true
        files:
          type: array
          items:
            type: object
            properties:
              mime_type:
                type: string
                description: |
                  The MIME type of the file.
              file_id:
                type: string
                description: |
                  The ID of the file.
            required:
              - mime_type
              - file_id
      required:
        - type
        - files
    CodeInterpreterTextOutput:
      type: object
      title: Code interpreter text output
      description: |
        The output of a code interpreter tool call that is text.
      properties:
        type:
          type: string
          enum:
            - logs
          description: |
            The type of the code interpreter text output. Always `logs`.
          x-stainless-const: true
        logs:
          type: string
          description: |
            The logs of the code interpreter tool call.
      required:
        - type
        - logs
    CodeInterpreterTool:
      type: object
      title: Code interpreter
      description: |
        A tool that runs Python code to help generate a response to a prompt.
      properties:
        type:
          type: string
          enum:
            - code_interpreter
          description: |
            The type of the code interpreter tool. Always `code_interpreter`.
          x-stainless-const: true
        container:
          description: |
            The code interpreter container. Can be a container ID or an object that
            specifies uploaded file IDs to make available to your code.
          discriminator:
            propertyName: type
          oneOf:
            - type: string
              description: The container ID.
            - $ref: '#/components/schemas/CodeInterpreterToolAuto'
      required:
        - type
        - container
    CodeInterpreterToolAuto:
      type: object
      title: CodeInterpreterContainerAuto
      description: |
        Configuration for a code interpreter container. Optionally specify the IDs
        of the files to run the code on.
      required:
        - type
      properties:
        type:
          type: string
          enum:
            - auto
          description: Always `auto`.
          x-stainless-const: true
        file_ids:
          type: array
          items:
            type: string
          description: |
            An optional list of uploaded files to make available to your code.
    CodeInterpreterToolCall:
      type: object
      title: Code interpreter tool call
      description: |
        A tool call to run code.
      properties:
        id:
          type: string
          description: |
            The unique ID of the code interpreter tool call.
        type:
          type: string
          enum:
            - code_interpreter_call
          description: |
            The type of the code interpreter tool call. Always `code_interpreter_call`.
          x-stainless-const: true
        container_id:
          type: string
          description: |
            The ID of the container used to run the code.
        code:
          type: string
          description: |
            The code to run.
        status:
          type: string
          enum:
            - in_progress
            - interpreting
            - completed
          description: |
            The status of the code interpreter tool call.
        results:
          type: array
          items:
            $ref: '#/components/schemas/CodeInterpreterToolOutput'
          description: |
            The results of the code interpreter tool call.
      required:
        - id
        - type
        - code
        - status
        - results
    CodeInterpreterToolOutput:
      title: Code interpreter tool output
      description: |
        The output of a code interpreter tool.
      discriminator:
        propertyName: type
      oneOf:
        - $ref: '#/components/schemas/CodeInterpreterTextOutput'
        - $ref: '#/components/schemas/CodeInterpreterFileOutput'
    ComparisonFilter:
      type: object
      additionalProperties: false
      title: Comparison Filter
      description: >
        A filter used to compare a specified attribute key to a given value using a defined comparison
        operation.
      properties:
        type:
          type: string
          default: eq
          enum:
            - eq
            - ne
            - gt
            - gte
            - lt
            - lte
          description: |
            Specifies the comparison operator: `eq`, `ne`, `gt`, `gte`, `lt`, `lte`.
            - `eq`: equals
            - `ne`: not equal
            - `gt`: greater than
            - `gte`: greater than or equal
            - `lt`: less than
            - `lte`: less than or equal
        key:
          type: string
          description: The key to compare against the value.
        value:
          oneOf:
            - type: string
            - type: number
            - type: boolean
          description: The value to compare against the attribute key; supports string, number, or boolean types.
      required:
        - type
        - key
        - value
      x-oaiMeta:
        name: ComparisonFilter
    CompleteUploadRequest:
      type: object
      additionalProperties: false
      properties:
        part_ids:
          type: array
          description: |
            The ordered list of Part IDs.
          items:
            type: string
        md5:
          description: >
            The optional md5 checksum for the file contents to verify if the bytes uploaded matches what you
            expect.
          type: string
      required:
        - part_ids
    CompletionUsage:
      type: object
      description: Usage statistics for the completion request.
      properties:
        completion_tokens:
          type: integer
          default: 0
          description: Number of tokens in the generated completion.
        prompt_tokens:
          type: integer
          default: 0
          description: Number of tokens in the prompt.
        total_tokens:
          type: integer
          default: 0
          description: Total number of tokens used in the request (prompt + completion).
        completion_tokens_details:
          type: object
          description: Breakdown of tokens used in a completion.
          properties:
            accepted_prediction_tokens:
              type: integer
              default: 0
              description: |
                When using Predicted Outputs, the number of tokens in the
                prediction that appeared in the completion.
            audio_tokens:
              type: integer
              default: 0
              description: Audio input tokens generated by the model.
            reasoning_tokens:
              type: integer
              default: 0
              description: Tokens generated by the model for reasoning.
            rejected_prediction_tokens:
              type: integer
              default: 0
              description: |
                When using Predicted Outputs, the number of tokens in the
                prediction that did not appear in the completion. However, like
                reasoning tokens, these tokens are still counted in the total
                completion tokens for purposes of billing, output, and context window
                limits.
        prompt_tokens_details:
          type: object
          description: Breakdown of tokens used in the prompt.
          properties:
            audio_tokens:
              type: integer
              default: 0
              description: Audio input tokens present in the prompt.
            cached_tokens:
              type: integer
              default: 0
              description: Cached tokens present in the prompt.
      required:
        - prompt_tokens
        - completion_tokens
        - total_tokens
    CompoundFilter:
      $recursiveAnchor: true
      type: object
      additionalProperties: false
      title: Compound Filter
      description: Combine multiple filters using `and` or `or`.
      properties:
        type:
          type: string
          description: 'Type of operation: `and` or `or`.'
          enum:
            - and
            - or
        filters:
          type: array
          description: Array of filters to combine. Items can be `ComparisonFilter` or `CompoundFilter`.
          items:
            oneOf:
              - $ref: '#/components/schemas/ComparisonFilter'
              - $recursiveRef: '#'
      required:
        - type
        - filters
      x-oaiMeta:
        name: CompoundFilter
    ComputerAction:
      oneOf:
        - $ref: '#/components/schemas/Click'
        - $ref: '#/components/schemas/DoubleClick'
        - $ref: '#/components/schemas/Drag'
        - $ref: '#/components/schemas/KeyPress'
        - $ref: '#/components/schemas/Move'
        - $ref: '#/components/schemas/Screenshot'
        - $ref: '#/components/schemas/Scroll'
        - $ref: '#/components/schemas/Type'
        - $ref: '#/components/schemas/Wait'
    ComputerScreenshotImage:
      type: object
      description: |
        A computer screenshot image used with the computer use tool.
      properties:
        type:
          type: string
          enum:
            - computer_screenshot
          default: computer_screenshot
          description: |
            Specifies the event type. For a computer screenshot, this property is 
            always set to `computer_screenshot`.
          x-stainless-const: true
        image_url:
          type: string
          description: The URL of the screenshot image.
        file_id:
          type: string
          description: The identifier of an uploaded file that contains the screenshot.
      required:
        - type
    ComputerToolCall:
      type: object
      title: Computer tool call
      description: |
        A tool call to a computer use tool. See the 
        [computer use guide](/docs/guides/tools-computer-use) for more information.
      properties:
        type:
          type: string
          description: The type of the computer call. Always `computer_call`.
          enum:
            - computer_call
          default: computer_call
        id:
          type: string
          description: The unique ID of the computer call.
        call_id:
          type: string
          description: |
            An identifier used when responding to the tool call with output.
        action:
          $ref: '#/components/schemas/ComputerAction'
        pending_safety_checks:
          type: array
          items:
            $ref: '#/components/schemas/ComputerToolCallSafetyCheck'
          description: |
            The pending safety checks for the computer call.
        status:
          type: string
          description: |
            The status of the item. One of `in_progress`, `completed`, or
            `incomplete`. Populated when items are returned via API.
          enum:
            - in_progress
            - completed
            - incomplete
      required:
        - type
        - id
        - action
        - call_id
        - pending_safety_checks
        - status
    ComputerToolCallOutput:
      type: object
      title: Computer tool call output
      description: |
        The output of a computer tool call.
      properties:
        type:
          type: string
          description: |
            The type of the computer tool call output. Always `computer_call_output`.
          enum:
            - computer_call_output
          default: computer_call_output
          x-stainless-const: true
        id:
          type: string
          description: |
            The ID of the computer tool call output.
        call_id:
          type: string
          description: |
            The ID of the computer tool call that produced the output.
        acknowledged_safety_checks:
          type: array
          description: |
            The safety checks reported by the API that have been acknowledged by the 
            developer.
          items:
            $ref: '#/components/schemas/ComputerToolCallSafetyCheck'
        output:
          $ref: '#/components/schemas/ComputerScreenshotImage'
        status:
          type: string
          description: |
            The status of the message input. One of `in_progress`, `completed`, or
            `incomplete`. Populated when input items are returned via API.
          enum:
            - in_progress
            - completed
            - incomplete
      required:
        - type
        - call_id
        - output
    ComputerToolCallOutputResource:
      allOf:
        - $ref: '#/components/schemas/ComputerToolCallOutput'
        - type: object
          properties:
            id:
              type: string
              description: |
                The unique ID of the computer call tool output.
          required:
            - id
    ComputerToolCallSafetyCheck:
      type: object
      description: |
        A pending safety check for the computer call.
      properties:
        id:
          type: string
          description: The ID of the pending safety check.
        code:
          type: string
          description: The type of the pending safety check.
        message:
          type: string
          description: Details about the pending safety check.
      required:
        - id
        - code
        - message
    ContainerFileListResource:
      type: object
      properties:
        object:
          type: string
          enum:
            - list
          description: The type of object returned, must be 'list'.
        data:
          type: array
          description: A list of container files.
          items:
            $ref: '#/components/schemas/ContainerFileResource'
        first_id:
          type: string
          description: The ID of the first file in the list.
        last_id:
          type: string
          description: The ID of the last file in the list.
        has_more:
          type: boolean
          description: Whether there are more files available.
      required:
        - object
        - data
        - first_id
        - last_id
        - has_more
    ContainerFileResource:
      type: object
      title: The container file object
      properties:
        id:
          type: string
          description: Unique identifier for the file.
        object:
          type: string
          description: The type of this object (`container.file`).
        container_id:
          type: string
          description: The container this file belongs to.
        created_at:
          type: integer
          description: Unix timestamp (in seconds) when the file was created.
        bytes:
          type: integer
          description: Size of the file in bytes.
        path:
          type: string
          description: Path of the file in the container.
        source:
          type: string
          description: Source of the file (e.g., `user`, `assistant`).
      required:
        - id
        - object
        - created_at
        - bytes
        - container_id
        - path
        - source
      x-oaiMeta:
        name: The container file object
        example: |
          {
              "id": "cfile_682e0e8a43c88191a7978f477a09bdf5",
              "object": "container.file",
              "created_at": 1747848842,
              "bytes": 880,
              "container_id": "cntr_682e0e7318108198aa783fd921ff305e08e78805b9fdbb04",
              "path": "/mnt/data/88e12fa445d32636f190a0b33daed6cb-tsconfig.json",
              "source": "user"
          }
    ContainerListResource:
      type: object
      properties:
        object:
          type: string
          enum:
            - list
          description: The type of object returned, must be 'list'.
        data:
          type: array
          description: A list of containers.
          items:
            $ref: '#/components/schemas/ContainerResource'
        first_id:
          type: string
          description: The ID of the first container in the list.
        last_id:
          type: string
          description: The ID of the last container in the list.
        has_more:
          type: boolean
          description: Whether there are more containers available.
      required:
        - object
        - data
        - first_id
        - last_id
        - has_more
    ContainerResource:
      type: object
      title: The container object
      properties:
        id:
          type: string
          description: Unique identifier for the container.
        object:
          type: string
          description: The type of this object.
        name:
          type: string
          description: Name of the container.
        created_at:
          type: integer
          description: Unix timestamp (in seconds) when the container was created.
        status:
          type: string
          description: Status of the container (e.g., active, deleted).
        expires_after:
          type: object
          description: |
            The container will expire after this time period.
            The anchor is the reference point for the expiration.
            The minutes is the number of minutes after the anchor before the container expires.
          properties:
            anchor:
              type: string
              description: The reference point for the expiration.
              enum:
                - last_active_at
            minutes:
              type: integer
              description: The number of minutes after the anchor before the container expires.
      required:
        - id
        - object
        - name
        - created_at
        - status
        - id
        - name
        - created_at
        - status
      x-oaiMeta:
        name: The container object
        example: |
          {
             "id": "cntr_682dfebaacac8198bbfe9c2474fb6f4a085685cbe3cb5863",
             "object": "container",
             "created_at": 1747844794,
             "status": "running",
             "expires_after": {
               "anchor": "last_active_at",
               "minutes": 20
             },
             "last_active_at": 1747844794,
             "name": "My Container"
          }
    Content:
      description: |
        Multi-modal input and output contents.
      oneOf:
        - title: Input content types
          $ref: '#/components/schemas/InputContent'
        - title: Output content types
          $ref: '#/components/schemas/OutputContent'
    Coordinate:
      type: object
      title: Coordinate
      description: |
        An x/y coordinate pair, e.g. `{ x: 100, y: 200 }`.
      properties:
        x:
          type: integer
          description: |
            The x-coordinate.
        'y':
          type: integer
          description: |
            The y-coordinate.
      required:
        - x
        - 'y'
    CostsResult:
      type: object
      description: The aggregated costs details of the specific time bucket.
      properties:
        object:
          type: string
          enum:
            - organization.costs.result
          x-stainless-const: true
        amount:
          type: object
          description: The monetary value in its associated currency.
          properties:
            value:
              type: number
              description: The numeric value of the cost.
            currency:
              type: string
              description: Lowercase ISO-4217 currency e.g. "usd"
        line_item:
          type: string
          nullable: true
          description: When `group_by=line_item`, this field provides the line item of the grouped costs result.
        project_id:
          type: string
          nullable: true
          description: When `group_by=project_id`, this field provides the project ID of the grouped costs result.
      required:
        - object
      x-oaiMeta:
        name: Costs object
        example: |
          {
              "object": "organization.costs.result",
              "amount": {
                "value": 0.06,
                "currency": "usd"
              },
              "line_item": "Image models",
              "project_id": "proj_abc"
          }
    CreateAssistantRequest:
      type: object
      additionalProperties: false
      properties:
        model:
          description: >
            ID of the model to use. You can use the [List models](/docs/api-reference/models/list) API to see
            all of your available models, or see our [Model overview](/docs/models) for descriptions of them.
          example: gpt-4o
          anyOf:
            - type: string
            - $ref: '#/components/schemas/AssistantSupportedModels'
          x-oaiTypeLabel: string
        name:
          description: |
            The name of the assistant. The maximum length is 256 characters.
          type: string
          nullable: true
          maxLength: 256
        description:
          description: |
            The description of the assistant. The maximum length is 512 characters.
          type: string
          nullable: true
          maxLength: 512
        instructions:
          description: |
            The system instructions that the assistant uses. The maximum length is 256,000 characters.
          type: string
          nullable: true
          maxLength: 256000
        reasoning_effort:
          $ref: '#/components/schemas/ReasoningEffort'
        tools:
          description: >
            A list of tool enabled on the assistant. There can be a maximum of 128 tools per assistant. Tools
            can be of types `code_interpreter`, `file_search`, or `function`.
          default: []
          type: array
          maxItems: 128
          items:
            oneOf:
              - $ref: '#/components/schemas/AssistantToolsCode'
              - $ref: '#/components/schemas/AssistantToolsFileSearch'
              - $ref: '#/components/schemas/AssistantToolsFunction'
        tool_resources:
          type: object
          description: >
            A set of resources that are used by the assistant's tools. The resources are specific to the type
            of tool. For example, the `code_interpreter` tool requires a list of file IDs, while the
            `file_search` tool requires a list of vector store IDs.
          properties:
            code_interpreter:
              type: object
              properties:
                file_ids:
                  type: array
                  description: >
                    A list of [file](/docs/api-reference/files) IDs made available to the `code_interpreter`
                    tool. There can be a maximum of 20 files associated with the tool.
                  default: []
                  maxItems: 20
                  items:
                    type: string
            file_search:
              type: object
              properties:
                vector_store_ids:
                  type: array
                  description: >
                    The [vector store](/docs/api-reference/vector-stores/object) attached to this assistant.
                    There can be a maximum of 1 vector store attached to the assistant.
                  maxItems: 1
                  items:
                    type: string
                vector_stores:
                  type: array
                  description: >
                    A helper to create a [vector store](/docs/api-reference/vector-stores/object) with
                    file_ids and attach it to this assistant. There can be a maximum of 1 vector store
                    attached to the assistant.
                  maxItems: 1
                  items:
                    type: object
                    properties:
                      file_ids:
                        type: array
                        description: >
                          A list of [file](/docs/api-reference/files) IDs to add to the vector store. There
                          can be a maximum of 10000 files in a vector store.
                        maxItems: 10000
                        items:
                          type: string
                      chunking_strategy:
                        type: object
                        description: >-
                          The chunking strategy used to chunk the file(s). If not set, will use the `auto`
                          strategy.
                        oneOf:
                          - type: object
                            title: Auto Chunking Strategy
                            description: >-
                              The default strategy. This strategy currently uses a `max_chunk_size_tokens` of
                              `800` and `chunk_overlap_tokens` of `400`.
                            additionalProperties: false
                            properties:
                              type:
                                type: string
                                description: Always `auto`.
                                enum:
                                  - auto
                                x-stainless-const: true
                            required:
                              - type
                          - type: object
                            title: Static Chunking Strategy
                            additionalProperties: false
                            properties:
                              type:
                                type: string
                                description: Always `static`.
                                enum:
                                  - static
                                x-stainless-const: true
                              static:
                                type: object
                                additionalProperties: false
                                properties:
                                  max_chunk_size_tokens:
                                    type: integer
                                    minimum: 100
                                    maximum: 4096
                                    description: >-
                                      The maximum number of tokens in each chunk. The default value is `800`.
                                      The minimum value is `100` and the maximum value is `4096`.
                                  chunk_overlap_tokens:
                                    type: integer
                                    description: >
                                      The number of tokens that overlap between chunks. The default value is
                                      `400`.


                                      Note that the overlap must not exceed half of `max_chunk_size_tokens`.
                                required:
                                  - max_chunk_size_tokens
                                  - chunk_overlap_tokens
                            required:
                              - type
                              - static
                      metadata:
                        $ref: '#/components/schemas/Metadata'
              oneOf:
                - required:
                    - vector_store_ids
                - required:
                    - vector_stores
          nullable: true
        metadata:
          $ref: '#/components/schemas/Metadata'
        temperature:
          description: >
            What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output
            more random, while lower values like 0.2 will make it more focused and deterministic.
          type: number
          minimum: 0
          maximum: 2
          default: 1
          example: 1
          nullable: true
        top_p:
          type: number
          minimum: 0
          maximum: 1
          default: 1
          example: 1
          nullable: true
          description: >
            An alternative to sampling with temperature, called nucleus sampling, where the model considers
            the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the
            top 10% probability mass are considered.


            We generally recommend altering this or temperature but not both.
        response_format:
          $ref: '#/components/schemas/AssistantsApiResponseFormatOption'
          nullable: true
      required:
        - model
    CreateChatCompletionRequest:
      allOf:
        - $ref: '#/components/schemas/CreateModelResponseProperties'
        - type: object
          properties:
            messages:
              description: |
                A list of messages comprising the conversation so far. Depending on the
                [model](/docs/models) you use, different message types (modalities) are
                supported, like [text](/docs/guides/text-generation),
                [images](/docs/guides/vision), and [audio](/docs/guides/audio).
              type: array
              minItems: 1
              items:
                $ref: '#/components/schemas/ChatCompletionRequestMessage'
            model:
              description: |
                Model ID used to generate the response, like `gpt-4o` or `o3`. OpenAI
                offers a wide range of models with different capabilities, performance
                characteristics, and price points. Refer to the [model guide](/docs/models)
                to browse and compare available models.
              $ref: '#/components/schemas/ModelIdsShared'
            modalities:
              $ref: '#/components/schemas/ResponseModalities'
            reasoning_effort:
              $ref: '#/components/schemas/ReasoningEffort'
            max_completion_tokens:
              description: >
                An upper bound for the number of tokens that can be generated for a completion, including
                visible output tokens and [reasoning tokens](/docs/guides/reasoning).
              type: integer
              nullable: true
            frequency_penalty:
              type: number
              default: 0
              minimum: -2
              maximum: 2
              nullable: true
              description: |
                Number between -2.0 and 2.0. Positive values penalize new tokens based on
                their existing frequency in the text so far, decreasing the model's
                likelihood to repeat the same line verbatim.
            presence_penalty:
              type: number
              default: 0
              minimum: -2
              maximum: 2
              nullable: true
              description: |
                Number between -2.0 and 2.0. Positive values penalize new tokens based on
                whether they appear in the text so far, increasing the model's likelihood
                to talk about new topics.
            web_search_options:
              type: object
              title: Web search
              description: |
                This tool searches the web for relevant results to use in a response.
                Learn more about the [web search tool](/docs/guides/tools-web-search?api-mode=chat).
              properties:
                user_location:
                  type: object
                  nullable: true
                  required:
                    - type
                    - approximate
                  description: |
                    Approximate location parameters for the search.
                  properties:
                    type:
                      type: string
                      description: |
                        The type of location approximation. Always `approximate`.
                      enum:
                        - approximate
                      x-stainless-const: true
                    approximate:
                      $ref: '#/components/schemas/WebSearchLocation'
                search_context_size:
                  $ref: '#/components/schemas/WebSearchContextSize'
            top_logprobs:
              description: |
                An integer between 0 and 20 specifying the number of most likely tokens to
                return at each token position, each with an associated log probability.
                `logprobs` must be set to `true` if this parameter is used.
              type: integer
              minimum: 0
              maximum: 20
              nullable: true
            response_format:
              description: |
                An object specifying the format that the model must output.

                Setting to `{ "type": "json_schema", "json_schema": {...} }` enables
                Structured Outputs which ensures the model will match your supplied JSON
                schema. Learn more in the [Structured Outputs
                guide](/docs/guides/structured-outputs).

                Setting to `{ "type": "json_object" }` enables the older JSON mode, which
                ensures the message the model generates is valid JSON. Using `json_schema`
                is preferred for models that support it.
              oneOf:
                - $ref: '#/components/schemas/ResponseFormatText'
                - $ref: '#/components/schemas/ResponseFormatJsonSchema'
                - $ref: '#/components/schemas/ResponseFormatJsonObject'
            audio:
              type: object
              nullable: true
              description: |
                Parameters for audio output. Required when audio output is requested with
                `modalities: ["audio"]`. [Learn more](/docs/guides/audio).
              required:
                - voice
                - format
              properties:
                voice:
                  $ref: '#/components/schemas/VoiceIdsShared'
                  description: |
                    The voice the model uses to respond. Supported voices are 
                    `alloy`, `ash`, `ballad`, `coral`, `echo`, `fable`, `nova`, `onyx`, `sage`, and `shimmer`.
                format:
                  type: string
                  enum:
                    - wav
                    - aac
                    - mp3
                    - flac
                    - opus
                    - pcm16
                  description: |
                    Specifies the output audio format. Must be one of `wav`, `mp3`, `flac`,
                    `opus`, or `pcm16`.
            store:
              type: boolean
              default: false
              nullable: true
              description: |
                Whether or not to store the output of this chat completion request for 
                use in our [model distillation](/docs/guides/distillation) or
                [evals](/docs/guides/evals) products.
            stream:
              description: >
                If set to true, the model response data will be streamed to the client

                as it is generated using [server-sent
                events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format).

                See the [Streaming section below](/docs/api-reference/chat/streaming)

                for more information, along with the [streaming responses](/docs/guides/streaming-responses)

                guide for more information on how to handle the streaming events.
              type: boolean
              nullable: true
              default: false
            stop:
              $ref: '#/components/schemas/StopConfiguration'
            logit_bias:
              type: object
              x-oaiTypeLabel: map
              default: null
              nullable: true
              additionalProperties:
                type: integer
              description: |
                Modify the likelihood of specified tokens appearing in the completion.

                Accepts a JSON object that maps tokens (specified by their token ID in the
                tokenizer) to an associated bias value from -100 to 100. Mathematically,
                the bias is added to the logits generated by the model prior to sampling.
                The exact effect will vary per model, but values between -1 and 1 should
                decrease or increase likelihood of selection; values like -100 or 100
                should result in a ban or exclusive selection of the relevant token.
            logprobs:
              description: |
                Whether to return log probabilities of the output tokens or not. If true,
                returns the log probabilities of each output token returned in the
                `content` of `message`.
              type: boolean
              default: false
              nullable: true
            max_tokens:
              description: |
                The maximum number of [tokens](/tokenizer) that can be generated in the
                chat completion. This value can be used to control
                [costs](https://openai.com/api/pricing/) for text generated via API.

                This value is now deprecated in favor of `max_completion_tokens`, and is
                not compatible with [o-series models](/docs/guides/reasoning).
              type: integer
              nullable: true
              deprecated: true
            'n':
              type: integer
              minimum: 1
              maximum: 128
              default: 1
              example: 1
              nullable: true
              description: >-
                How many chat completion choices to generate for each input message. Note that you will be
                charged based on the number of generated tokens across all of the choices. Keep `n` as `1` to
                minimize costs.
            prediction:
              nullable: true
              description: |
                Configuration for a [Predicted Output](/docs/guides/predicted-outputs),
                which can greatly improve response times when large parts of the model
                response are known ahead of time. This is most common when you are
                regenerating a file with only minor changes to most of the content.
              oneOf:
                - $ref: '#/components/schemas/PredictionContent'
            seed:
              type: integer
              minimum: -9223372036854776000
              maximum: 9223372036854776000
              nullable: true
              description: >
                This feature is in Beta.

                If specified, our system will make a best effort to sample deterministically, such that
                repeated requests with the same `seed` and parameters should return the same result.

                Determinism is not guaranteed, and you should refer to the `system_fingerprint` response
                parameter to monitor changes in the backend.
              x-oaiMeta:
                beta: true
            stream_options:
              $ref: '#/components/schemas/ChatCompletionStreamOptions'
            tools:
              type: array
              description: >
                A list of tools the model may call. Currently, only functions are supported as a tool. Use
                this to provide a list of functions the model may generate JSON inputs for. A max of 128
                functions are supported.
              items:
                $ref: '#/components/schemas/ChatCompletionTool'
            tool_choice:
              $ref: '#/components/schemas/ChatCompletionToolChoiceOption'
            parallel_tool_calls:
              $ref: '#/components/schemas/ParallelToolCalls'
            function_call:
              deprecated: true
              description: |
                Deprecated in favor of `tool_choice`.

                Controls which (if any) function is called by the model.

                `none` means the model will not call a function and instead generates a
                message.

                `auto` means the model can pick between generating a message or calling a
                function.

                Specifying a particular function via `{"name": "my_function"}` forces the
                model to call that function.

                `none` is the default when no functions are present. `auto` is the default
                if functions are present.
              oneOf:
                - type: string
                  description: >
                    `none` means the model will not call a function and instead generates a message. `auto`
                    means the model can pick between generating a message or calling a function.
                  enum:
                    - none
                    - auto
                - $ref: '#/components/schemas/ChatCompletionFunctionCallOption'
            functions:
              deprecated: true
              description: |
                Deprecated in favor of `tools`.

                A list of functions the model may generate JSON inputs for.
              type: array
              minItems: 1
              maxItems: 128
              items:
                $ref: '#/components/schemas/ChatCompletionFunctions'
          required:
            - model
            - messages
    CreateChatCompletionResponse:
      type: object
      description: Represents a chat completion response returned by model, based on the provided input.
      properties:
        id:
          type: string
          description: A unique identifier for the chat completion.
        choices:
          type: array
          description: A list of chat completion choices. Can be more than one if `n` is greater than 1.
          items:
            type: object
            required:
              - finish_reason
              - index
              - message
              - logprobs
            properties:
              finish_reason:
                type: string
                description: >
                  The reason the model stopped generating tokens. This will be `stop` if the model hit a
                  natural stop point or a provided stop sequence,

                  `length` if the maximum number of tokens specified in the request was reached,

                  `content_filter` if content was omitted due to a flag from our content filters,

                  `tool_calls` if the model called a tool, or `function_call` (deprecated) if the model called
                  a function.
                enum:
                  - stop
                  - length
                  - tool_calls
                  - content_filter
                  - function_call
              index:
                type: integer
                description: The index of the choice in the list of choices.
              message:
                $ref: '#/components/schemas/ChatCompletionResponseMessage'
              logprobs:
                description: Log probability information for the choice.
                type: object
                nullable: true
                properties:
                  content:
                    description: A list of message content tokens with log probability information.
                    type: array
                    items:
                      $ref: '#/components/schemas/ChatCompletionTokenLogprob'
                    nullable: true
                  refusal:
                    description: A list of message refusal tokens with log probability information.
                    type: array
                    items:
                      $ref: '#/components/schemas/ChatCompletionTokenLogprob'
                    nullable: true
                required:
                  - content
                  - refusal
        created:
          type: integer
          description: The Unix timestamp (in seconds) of when the chat completion was created.
        model:
          type: string
          description: The model used for the chat completion.
        service_tier:
          $ref: '#/components/schemas/ServiceTier'
        system_fingerprint:
          type: string
          description: >
            This fingerprint represents the backend configuration that the model runs with.


            Can be used in conjunction with the `seed` request parameter to understand when backend changes
            have been made that might impact determinism.
        object:
          type: string
          description: The object type, which is always `chat.completion`.
          enum:
            - chat.completion
          x-stainless-const: true
        usage:
          $ref: '#/components/schemas/CompletionUsage'
      required:
        - choices
        - created
        - id
        - model
        - object
      x-oaiMeta:
        name: The chat completion object
        group: chat
        example: |
          {
            "id": "chatcmpl-B9MHDbslfkBeAs8l4bebGdFOJ6PeG",
            "object": "chat.completion",
            "created": 1741570283,
            "model": "gpt-4o-2024-08-06",
            "choices": [
              {
                "index": 0,
                "message": {
                  "role": "assistant",
                  "content": "The image shows a wooden boardwalk path running through a lush green field or meadow. The sky is bright blue with some scattered clouds, giving the scene a serene and peaceful atmosphere. Trees and shrubs are visible in the background.",
                  "refusal": null,
                  "annotations": []
                },
                "logprobs": null,
                "finish_reason": "stop"
              }
            ],
            "usage": {
              "prompt_tokens": 1117,
              "completion_tokens": 46,
              "total_tokens": 1163,
              "prompt_tokens_details": {
                "cached_tokens": 0,
                "audio_tokens": 0
              },
              "completion_tokens_details": {
                "reasoning_tokens": 0,
                "audio_tokens": 0,
                "accepted_prediction_tokens": 0,
                "rejected_prediction_tokens": 0
              }
            },
            "service_tier": "default",
            "system_fingerprint": "fp_fc9f1d7035"
          }
    CreateChatCompletionStreamResponse:
      type: object
      description: |
        Represents a streamed chunk of a chat completion response returned
        by the model, based on the provided input. 
        [Learn more](/docs/guides/streaming-responses).
      properties:
        id:
          type: string
          description: A unique identifier for the chat completion. Each chunk has the same ID.
        choices:
          type: array
          description: >
            A list of chat completion choices. Can contain more than one elements if `n` is greater than 1.
            Can also be empty for the

            last chunk if you set `stream_options: {"include_usage": true}`.
          items:
            type: object
            required:
              - delta
              - finish_reason
              - index
            properties:
              delta:
                $ref: '#/components/schemas/ChatCompletionStreamResponseDelta'
              logprobs:
                description: Log probability information for the choice.
                type: object
                nullable: true
                properties:
                  content:
                    description: A list of message content tokens with log probability information.
                    type: array
                    items:
                      $ref: '#/components/schemas/ChatCompletionTokenLogprob'
                    nullable: true
                  refusal:
                    description: A list of message refusal tokens with log probability information.
                    type: array
                    items:
                      $ref: '#/components/schemas/ChatCompletionTokenLogprob'
                    nullable: true
                required:
                  - content
                  - refusal
              finish_reason:
                type: string
                description: >
                  The reason the model stopped generating tokens. This will be `stop` if the model hit a
                  natural stop point or a provided stop sequence,

                  `length` if the maximum number of tokens specified in the request was reached,

                  `content_filter` if content was omitted due to a flag from our content filters,

                  `tool_calls` if the model called a tool, or `function_call` (deprecated) if the model called
                  a function.
                enum:
                  - stop
                  - length
                  - tool_calls
                  - content_filter
                  - function_call
                nullable: true
              index:
                type: integer
                description: The index of the choice in the list of choices.
        created:
          type: integer
          description: >-
            The Unix timestamp (in seconds) of when the chat completion was created. Each chunk has the same
            timestamp.
        model:
          type: string
          description: The model to generate the completion.
        service_tier:
          $ref: '#/components/schemas/ServiceTier'
        system_fingerprint:
          type: string
          description: >
            This fingerprint represents the backend configuration that the model runs with.

            Can be used in conjunction with the `seed` request parameter to understand when backend changes
            have been made that might impact determinism.
        object:
          type: string
          description: The object type, which is always `chat.completion.chunk`.
          enum:
            - chat.completion.chunk
          x-stainless-const: true
        usage:
          $ref: '#/components/schemas/CompletionUsage'
          nullable: true
          description: |
            An optional field that will only be present when you set
            `stream_options: {"include_usage": true}` in your request. When present, it
            contains a null value **except for the last chunk** which contains the
            token usage statistics for the entire request.

            **NOTE:** If the stream is interrupted or cancelled, you may not
            receive the final usage chunk which contains the total token usage for
            the request.
      required:
        - choices
        - created
        - id
        - model
        - object
      x-oaiMeta:
        name: The chat completion chunk object
        group: chat
        example: >
          {"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"gpt-4o-mini",
          "system_fingerprint": "fp_44709d6fcb",
          "choices":[{"index":0,"delta":{"role":"assistant","content":""},"logprobs":null,"finish_reason":null}]}


          {"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"gpt-4o-mini",
          "system_fingerprint": "fp_44709d6fcb",
          "choices":[{"index":0,"delta":{"content":"Hello"},"logprobs":null,"finish_reason":null}]}


          ....


          {"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"gpt-4o-mini",
          "system_fingerprint": "fp_44709d6fcb",
          "choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}]}
    CreateCompletionRequest:
      type: object
      properties:
        model:
          description: >
            ID of the model to use. You can use the [List models](/docs/api-reference/models/list) API to see
            all of your available models, or see our [Model overview](/docs/models) for descriptions of them.
          anyOf:
            - type: string
            - type: string
              enum:
                - gpt-3.5-turbo-instruct
                - davinci-002
                - babbage-002
          x-oaiTypeLabel: string
        prompt:
          description: >
            The prompt(s) to generate completions for, encoded as a string, array of strings, array of tokens,
            or array of token arrays.


            Note that <|endoftext|> is the document separator that the model sees during training, so if a
            prompt is not specified the model will generate as if from the beginning of a new document.
          default: <|endoftext|>
          nullable: true
          oneOf:
            - type: string
              default: ''
              example: This is a test.
            - type: array
              items:
                type: string
                default: ''
                example: This is a test.
            - type: array
              minItems: 1
              items:
                type: integer
              example: '[1212, 318, 257, 1332, 13]'
            - type: array
              minItems: 1
              items:
                type: array
                minItems: 1
                items:
                  type: integer
              example: '[[1212, 318, 257, 1332, 13]]'
        best_of:
          type: integer
          default: 1
          minimum: 0
          maximum: 20
          nullable: true
          description: >
            Generates `best_of` completions server-side and returns the "best" (the one with the highest log
            probability per token). Results cannot be streamed.


            When used with `n`, `best_of` controls the number of candidate completions and `n` specifies how
            many to return – `best_of` must be greater than `n`.


            **Note:** Because this parameter generates many completions, it can quickly consume your token
            quota. Use carefully and ensure that you have reasonable settings for `max_tokens` and `stop`.
        echo:
          type: boolean
          default: false
          nullable: true
          description: |
            Echo back the prompt in addition to the completion
        frequency_penalty:
          type: number
          default: 0
          minimum: -2
          maximum: 2
          nullable: true
          description: >
            Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency
            in the text so far, decreasing the model's likelihood to repeat the same line verbatim.


            [See more information about frequency and presence penalties.](/docs/guides/text-generation)
        logit_bias:
          type: object
          x-oaiTypeLabel: map
          default: null
          nullable: true
          additionalProperties:
            type: integer
          description: >
            Modify the likelihood of specified tokens appearing in the completion.


            Accepts a JSON object that maps tokens (specified by their token ID in the GPT tokenizer) to an
            associated bias value from -100 to 100. You can use this [tokenizer tool](/tokenizer?view=bpe) to
            convert text to token IDs. Mathematically, the bias is added to the logits generated by the model
            prior to sampling. The exact effect will vary per model, but values between -1 and 1 should
            decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or
            exclusive selection of the relevant token.


            As an example, you can pass `{"50256": -100}` to prevent the <|endoftext|> token from being
            generated.
        logprobs:
          type: integer
          minimum: 0
          maximum: 5
          default: null
          nullable: true
          description: >
            Include the log probabilities on the `logprobs` most likely output tokens, as well the chosen
            tokens. For example, if `logprobs` is 5, the API will return a list of the 5 most likely tokens.
            The API will always return the `logprob` of the sampled token, so there may be up to `logprobs+1`
            elements in the response.


            The maximum value for `logprobs` is 5.
        max_tokens:
          type: integer
          minimum: 0
          default: 16
          example: 16
          nullable: true
          description: >
            The maximum number of [tokens](/tokenizer) that can be generated in the completion.


            The token count of your prompt plus `max_tokens` cannot exceed the model's context length.
            [Example Python code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken) for
            counting tokens.
        'n':
          type: integer
          minimum: 1
          maximum: 128
          default: 1
          example: 1
          nullable: true
          description: >
            How many completions to generate for each prompt.


            **Note:** Because this parameter generates many completions, it can quickly consume your token
            quota. Use carefully and ensure that you have reasonable settings for `max_tokens` and `stop`.
        presence_penalty:
          type: number
          default: 0
          minimum: -2
          maximum: 2
          nullable: true
          description: >
            Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in
            the text so far, increasing the model's likelihood to talk about new topics.


            [See more information about frequency and presence penalties.](/docs/guides/text-generation)
        seed:
          type: integer
          format: int64
          nullable: true
          description: >
            If specified, our system will make a best effort to sample deterministically, such that repeated
            requests with the same `seed` and parameters should return the same result.


            Determinism is not guaranteed, and you should refer to the `system_fingerprint` response parameter
            to monitor changes in the backend.
        stop:
          $ref: '#/components/schemas/StopConfiguration'
        stream:
          description: >
            Whether to stream back partial progress. If set, tokens will be sent as data-only [server-sent
            events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format)
            as they become available, with the stream terminated by a `data: [DONE]` message. [Example Python
            code](https://cookbook.openai.com/examples/how_to_stream_completions).
          type: boolean
          nullable: true
          default: false
        stream_options:
          $ref: '#/components/schemas/ChatCompletionStreamOptions'
        suffix:
          description: |
            The suffix that comes after a completion of inserted text.

            This parameter is only supported for `gpt-3.5-turbo-instruct`.
          default: null
          nullable: true
          type: string
          example: test.
        temperature:
          type: number
          minimum: 0
          maximum: 2
          default: 1
          example: 1
          nullable: true
          description: >
            What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output
            more random, while lower values like 0.2 will make it more focused and deterministic.


            We generally recommend altering this or `top_p` but not both.
        top_p:
          type: number
          minimum: 0
          maximum: 1
          default: 1
          example: 1
          nullable: true
          description: >
            An alternative to sampling with temperature, called nucleus sampling, where the model considers
            the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the
            top 10% probability mass are considered.


            We generally recommend altering this or `temperature` but not both.
        user:
          type: string
          example: user-1234
          description: >
            A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse.
            [Learn more](/docs/guides/safety-best-practices#end-user-ids).
      required:
        - model
        - prompt
    CreateCompletionResponse:
      type: object
      description: >
        Represents a completion response from the API. Note: both the streamed and non-streamed response
        objects share the same shape (unlike the chat endpoint).
      properties:
        id:
          type: string
          description: A unique identifier for the completion.
        choices:
          type: array
          description: The list of completion choices the model generated for the input prompt.
          items:
            type: object
            required:
              - finish_reason
              - index
              - logprobs
              - text
            properties:
              finish_reason:
                type: string
                description: >
                  The reason the model stopped generating tokens. This will be `stop` if the model hit a
                  natural stop point or a provided stop sequence,

                  `length` if the maximum number of tokens specified in the request was reached,

                  or `content_filter` if content was omitted due to a flag from our content filters.
                enum:
                  - stop
                  - length
                  - content_filter
              index:
                type: integer
              logprobs:
                type: object
                nullable: true
                properties:
                  text_offset:
                    type: array
                    items:
                      type: integer
                  token_logprobs:
                    type: array
                    items:
                      type: number
                  tokens:
                    type: array
                    items:
                      type: string
                  top_logprobs:
                    type: array
                    items:
                      type: object
                      additionalProperties:
                        type: number
              text:
                type: string
        created:
          type: integer
          description: The Unix timestamp (in seconds) of when the completion was created.
        model:
          type: string
          description: The model used for completion.
        system_fingerprint:
          type: string
          description: >
            This fingerprint represents the backend configuration that the model runs with.


            Can be used in conjunction with the `seed` request parameter to understand when backend changes
            have been made that might impact determinism.
        object:
          type: string
          description: The object type, which is always "text_completion"
          enum:
            - text_completion
          x-stainless-const: true
        usage:
          $ref: '#/components/schemas/CompletionUsage'
      required:
        - id
        - object
        - created
        - model
        - choices
      x-oaiMeta:
        name: The completion object
        legacy: true
        example: |
          {
            "id": "cmpl-uqkvlQyYK7bGYrRHQ0eXlWi7",
            "object": "text_completion",
            "created": 1589478378,
            "model": "gpt-4-turbo",
            "choices": [
              {
                "text": "\n\nThis is indeed a test",
                "index": 0,
                "logprobs": null,
                "finish_reason": "length"
              }
            ],
            "usage": {
              "prompt_tokens": 5,
              "completion_tokens": 7,
              "total_tokens": 12
            }
          }
    CreateContainerBody:
      type: object
      properties:
        name:
          type: string
          description: Name of the container to create.
        file_ids:
          type: array
          description: IDs of files to copy to the container.
          items:
            type: string
        expires_after:
          type: object
          description: Container expiration time in seconds relative to the 'anchor' time.
          properties:
            anchor:
              type: string
              enum:
                - last_active_at
              description: Time anchor for the expiration time. Currently only 'last_active_at' is supported.
            minutes:
              type: integer
          required:
            - anchor
            - minutes
      required:
        - name
    CreateContainerFileBody:
      type: object
      properties:
        file_id:
          type: string
          description: Name of the file to create.
        file:
          description: |
            The File object (not file name) to be uploaded.
          type: string
          format: binary
      required: []
    CreateEmbeddingRequest:
      type: object
      additionalProperties: false
      properties:
        input:
          description: >
            Input text to embed, encoded as a string or array of tokens. To embed multiple inputs in a single
            request, pass an array of strings or array of token arrays. The input must not exceed the max
            input tokens for the model (8192 tokens for all embedding models), cannot be an empty string, and
            any array must be 2048 dimensions or less. [Example Python
            code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken) for counting tokens.
            In addition to the per-input token limit, all embedding  models enforce a maximum of 300,000
            tokens summed across all inputs in a  single request.
          example: The quick brown fox jumped over the lazy dog
          oneOf:
            - type: string
              title: string
              description: The string that will be turned into an embedding.
              default: ''
              example: This is a test.
            - type: array
              title: array
              description: The array of strings that will be turned into an embedding.
              minItems: 1
              maxItems: 2048
              items:
                type: string
                default: ''
                example: '[''This is a test.'']'
            - type: array
              title: array
              description: The array of integers that will be turned into an embedding.
              minItems: 1
              maxItems: 2048
              items:
                type: integer
              example: '[1212, 318, 257, 1332, 13]'
            - type: array
              title: array
              description: The array of arrays containing integers that will be turned into an embedding.
              minItems: 1
              maxItems: 2048
              items:
                type: array
                minItems: 1
                items:
                  type: integer
              example: '[[1212, 318, 257, 1332, 13]]'
        model:
          description: >
            ID of the model to use. You can use the [List models](/docs/api-reference/models/list) API to see
            all of your available models, or see our [Model overview](/docs/models) for descriptions of them.
          example: text-embedding-3-small
          anyOf:
            - type: string
            - type: string
              enum:
                - text-embedding-ada-002
                - text-embedding-3-small
                - text-embedding-3-large
          x-oaiTypeLabel: string
        encoding_format:
          description: >-
            The format to return the embeddings in. Can be either `float` or
            [`base64`](https://pypi.org/project/pybase64/).
          example: float
          default: float
          type: string
          enum:
            - float
            - base64
        dimensions:
          description: >
            The number of dimensions the resulting output embeddings should have. Only supported in
            `text-embedding-3` and later models.
          type: integer
          minimum: 1
        user:
          type: string
          example: user-1234
          description: >
            A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse.
            [Learn more](/docs/guides/safety-best-practices#end-user-ids).
      required:
        - model
        - input
    CreateEmbeddingResponse:
      type: object
      properties:
        data:
          type: array
          description: The list of embeddings generated by the model.
          items:
            $ref: '#/components/schemas/Embedding'
        model:
          type: string
          description: The name of the model used to generate the embedding.
        object:
          type: string
          description: The object type, which is always "list".
          enum:
            - list
          x-stainless-const: true
        usage:
          type: object
          description: The usage information for the request.
          properties:
            prompt_tokens:
              type: integer
              description: The number of tokens used by the prompt.
            total_tokens:
              type: integer
              description: The total number of tokens used by the request.
          required:
            - prompt_tokens
            - total_tokens
      required:
        - object
        - model
        - data
        - usage
    CreateEvalCompletionsRunDataSource:
      type: object
      title: CompletionsRunDataSource
      description: |
        A CompletionsRunDataSource object describing a model sampling configuration.
      properties:
        type:
          type: string
          enum:
            - completions
          default: completions
          description: The type of run data source. Always `completions`.
        input_messages:
          description: >-
            Used when sampling from a model. Dictates the structure of the messages passed into the model. Can
            either be a reference to a prebuilt trajectory (ie, `item.input_trajectory`), or a template with
            variable references to the `item` namespace.
          oneOf:
            - type: object
              title: TemplateInputMessages
              properties:
                type:
                  type: string
                  enum:
                    - template
                  description: The type of input messages. Always `template`.
                template:
                  type: array
                  description: >-
                    A list of chat messages forming the prompt or context. May include variable references to
                    the `item` namespace, ie {{item.name}}.
                  items:
                    oneOf:
                      - $ref: '#/components/schemas/EasyInputMessage'
                      - $ref: '#/components/schemas/EvalItem'
              required:
                - type
                - template
            - type: object
              title: ItemReferenceInputMessages
              properties:
                type:
                  type: string
                  enum:
                    - item_reference
                  description: The type of input messages. Always `item_reference`.
                item_reference:
                  type: string
                  description: A reference to a variable in the `item` namespace. Ie, "item.input_trajectory"
              required:
                - type
                - item_reference
        sampling_params:
          type: object
          properties:
            temperature:
              type: number
              description: A higher temperature increases randomness in the outputs.
              default: 1
            max_completion_tokens:
              type: integer
              description: The maximum number of tokens in the generated output.
            top_p:
              type: number
              description: An alternative to temperature for nucleus sampling; 1.0 includes all tokens.
              default: 1
            seed:
              type: integer
              description: A seed value to initialize the randomness, during sampling.
              default: 42
            response_format:
              description: |
                An object specifying the format that the model must output.

                Setting to `{ "type": "json_schema", "json_schema": {...} }` enables
                Structured Outputs which ensures the model will match your supplied JSON
                schema. Learn more in the [Structured Outputs
                guide](/docs/guides/structured-outputs).

                Setting to `{ "type": "json_object" }` enables the older JSON mode, which
                ensures the message the model generates is valid JSON. Using `json_schema`
                is preferred for models that support it.
              oneOf:
                - $ref: '#/components/schemas/ResponseFormatText'
                - $ref: '#/components/schemas/ResponseFormatJsonSchema'
                - $ref: '#/components/schemas/ResponseFormatJsonObject'
            tools:
              type: array
              description: >
                A list of tools the model may call. Currently, only functions are supported as a tool. Use
                this to provide a list of functions the model may generate JSON inputs for. A max of 128
                functions are supported.
              items:
                $ref: '#/components/schemas/ChatCompletionTool'
        model:
          type: string
          description: The name of the model to use for generating completions (e.g. "o3-mini").
        source:
          description: Determines what populates the `item` namespace in this run's data source.
          oneOf:
            - $ref: '#/components/schemas/EvalJsonlFileContentSource'
            - $ref: '#/components/schemas/EvalJsonlFileIdSource'
            - $ref: '#/components/schemas/EvalStoredCompletionsSource'
      required:
        - type
        - source
      x-oaiMeta:
        name: The completions data source object used to configure an individual run
        group: eval runs
        example: |
          {
            "name": "gpt-4o-mini-2024-07-18",
            "data_source": {
              "type": "completions",
              "input_messages": {
                "type": "item_reference",
                "item_reference": "item.input"
              },
              "model": "gpt-4o-mini-2024-07-18",
              "source": {
                "type": "stored_completions",
                "model": "gpt-4o-mini-2024-07-18"
              }
            }
          }
    CreateEvalCustomDataSourceConfig:
      type: object
      title: CustomDataSourceConfig
      description: >
        A CustomDataSourceConfig object that defines the schema for the data source used for the evaluation
        runs.

        This schema is used to define the shape of the data that will be:

        - Used to define your testing criteria and

        - What data is required when creating a run
      properties:
        type:
          type: string
          enum:
            - custom
          default: custom
          description: The type of data source. Always `custom`.
          x-stainless-const: true
        item_schema:
          type: object
          description: The json schema for each row in the data source.
          additionalProperties: true
          example: |
            {
              "type": "object",
              "properties": {
                "name": {"type": "string"},
                "age": {"type": "integer"}
              },
              "required": ["name", "age"]
            }
        include_sample_schema:
          type: boolean
          default: false
          description: >-
            Whether the eval should expect you to populate the sample namespace (ie, by generating responses
            off of your data source)
      required:
        - item_schema
        - type
      x-oaiMeta:
        name: The eval file data source config object
        group: evals
        example: |
          {
            "type": "custom",
            "item_schema": {
              "type": "object",
              "properties": {
                "name": {"type": "string"},
                "age": {"type": "integer"}
              },
              "required": ["name", "age"]
            },
            "include_sample_schema": true
          }
    CreateEvalItem:
      title: CreateEvalItem
      description: >-
        A chat message that makes up the prompt or context. May include variable references to the `item`
        namespace, ie {{item.name}}.
      type: object
      oneOf:
        - type: object
          title: SimpleInputMessage
          properties:
            role:
              type: string
              description: The role of the message (e.g. "system", "assistant", "user").
            content:
              type: string
              description: The content of the message.
          required:
            - role
            - content
        - $ref: '#/components/schemas/EvalItem'
      x-oaiMeta:
        name: The chat message object used to configure an individual run
    CreateEvalJsonlRunDataSource:
      type: object
      title: JsonlRunDataSource
      description: |
        A JsonlRunDataSource object with that specifies a JSONL file that matches the eval 
      properties:
        type:
          type: string
          enum:
            - jsonl
          default: jsonl
          description: The type of data source. Always `jsonl`.
          x-stainless-const: true
        source:
          description: Determines what populates the `item` namespace in the data source.
          oneOf:
            - $ref: '#/components/schemas/EvalJsonlFileContentSource'
            - $ref: '#/components/schemas/EvalJsonlFileIdSource'
      required:
        - type
        - source
      x-oaiMeta:
        name: The file data source object for the eval run configuration
        group: evals
        example: |
          {
           "type": "jsonl",
           "source": {
             "type": "file_id",
             "id": "file-9GYS6xbkWgWhmE7VoLUWFg"
           }
          }
    CreateEvalLabelModelGrader:
      type: object
      title: LabelModelGrader
      description: |
        A LabelModelGrader object which uses a model to assign labels to each item
        in the evaluation.
      properties:
        type:
          description: The object type, which is always `label_model`.
          type: string
          enum:
            - label_model
          x-stainless-const: true
        name:
          type: string
          description: The name of the grader.
        model:
          type: string
          description: The model to use for the evaluation. Must support structured outputs.
        input:
          type: array
          description: >-
            A list of chat messages forming the prompt or context. May include variable references to the
            `item` namespace, ie {{item.name}}.
          items:
            $ref: '#/components/schemas/CreateEvalItem'
        labels:
          type: array
          items:
            type: string
          description: The labels to classify to each item in the evaluation.
        passing_labels:
          type: array
          items:
            type: string
          description: The labels that indicate a passing result. Must be a subset of labels.
      required:
        - type
        - model
        - input
        - passing_labels
        - labels
        - name
      x-oaiMeta:
        name: The eval label model grader object
        group: evals
        example: |
          {
            "type": "label_model",
            "model": "gpt-4o-2024-08-06",
            "input": [
              {
                "role": "system",
                "content": "Classify the sentiment of the following statement as one of 'positive', 'neutral', or 'negative'"
              },
              {
                "role": "user",
                "content": "Statement: {{item.response}}"
              }
            ],
            "passing_labels": ["positive"],
            "labels": ["positive", "neutral", "negative"],
            "name": "Sentiment label grader"
          }
    CreateEvalLogsDataSourceConfig:
      type: object
      title: LogsDataSourceConfig
      description: |
        A data source config which specifies the metadata property of your logs query.
        This is usually metadata like `usecase=chatbot` or `prompt-version=v2`, etc.
      properties:
        type:
          type: string
          enum:
            - logs
          default: logs
          description: The type of data source. Always `logs`.
          x-stainless-const: true
        metadata:
          type: object
          description: Metadata filters for the logs data source.
          additionalProperties: true
          example: |
            {
              "use_case": "customer_support_agent"
            }
      required:
        - type
      x-oaiMeta:
        name: The logs data source object for evals
        group: evals
        example: |
          {
            "type": "logs",
            "metadata": {
              "use_case": "customer_support_agent"
            }
          }
    CreateEvalRequest:
      type: object
      title: CreateEvalRequest
      properties:
        name:
          type: string
          description: The name of the evaluation.
        metadata:
          $ref: '#/components/schemas/Metadata'
        data_source_config:
          type: object
          description: >-
            The configuration for the data source used for the evaluation runs. Dictates the schema of the
            data used in the evaluation.
          oneOf:
            - $ref: '#/components/schemas/CreateEvalCustomDataSourceConfig'
            - $ref: '#/components/schemas/CreateEvalLogsDataSourceConfig'
            - $ref: '#/components/schemas/CreateEvalStoredCompletionsDataSourceConfig'
        testing_criteria:
          type: array
          description: >-
            A list of graders for all eval runs in this group. Graders can reference variables in the data
            source using double curly braces notation, like `{{item.variable_name}}`. To reference the model's
            output, use the `sample` namespace (ie, `{{sample.output_text}}`).
          items:
            oneOf:
              - $ref: '#/components/schemas/CreateEvalLabelModelGrader'
              - $ref: '#/components/schemas/EvalGraderStringCheck'
              - $ref: '#/components/schemas/EvalGraderTextSimilarity'
              - $ref: '#/components/schemas/EvalGraderPython'
              - $ref: '#/components/schemas/EvalGraderScoreModel'
      required:
        - data_source_config
        - testing_criteria
    CreateEvalResponsesRunDataSource:
      type: object
      title: ResponsesRunDataSource
      description: |
        A ResponsesRunDataSource object describing a model sampling configuration.
      properties:
        type:
          type: string
          enum:
            - responses
          default: responses
          description: The type of run data source. Always `responses`.
        input_messages:
          description: >-
            Used when sampling from a model. Dictates the structure of the messages passed into the model. Can
            either be a reference to a prebuilt trajectory (ie, `item.input_trajectory`), or a template with
            variable references to the `item` namespace.
          oneOf:
            - type: object
              title: InputMessagesTemplate
              properties:
                type:
                  type: string
                  enum:
                    - template
                  description: The type of input messages. Always `template`.
                template:
                  type: array
                  description: >-
                    A list of chat messages forming the prompt or context. May include variable references to
                    the `item` namespace, ie {{item.name}}.
                  items:
                    oneOf:
                      - type: object
                        title: ChatMessage
                        properties:
                          role:
                            type: string
                            description: The role of the message (e.g. "system", "assistant", "user").
                          content:
                            type: string
                            description: The content of the message.
                        required:
                          - role
                          - content
                      - $ref: '#/components/schemas/EvalItem'
              required:
                - type
                - template
            - type: object
              title: InputMessagesItemReference
              properties:
                type:
                  type: string
                  enum:
                    - item_reference
                  description: The type of input messages. Always `item_reference`.
                item_reference:
                  type: string
                  description: A reference to a variable in the `item` namespace. Ie, "item.name"
              required:
                - type
                - item_reference
        sampling_params:
          type: object
          properties:
            temperature:
              type: number
              description: A higher temperature increases randomness in the outputs.
              default: 1
            max_completion_tokens:
              type: integer
              description: The maximum number of tokens in the generated output.
            top_p:
              type: number
              description: An alternative to temperature for nucleus sampling; 1.0 includes all tokens.
              default: 1
            seed:
              type: integer
              description: A seed value to initialize the randomness, during sampling.
              default: 42
            tools:
              type: array
              description: |
                An array of tools the model may call while generating a response. You
                can specify which tool to use by setting the `tool_choice` parameter.

                The two categories of tools you can provide the model are:

                - **Built-in tools**: Tools that are provided by OpenAI that extend the
                  model's capabilities, like [web search](/docs/guides/tools-web-search)
                  or [file search](/docs/guides/tools-file-search). Learn more about
                  [built-in tools](/docs/guides/tools).
                - **Function calls (custom tools)**: Functions that are defined by you,
                  enabling the model to call your own code. Learn more about
                  [function calling](/docs/guides/function-calling).
              items:
                $ref: '#/components/schemas/Tool'
            text:
              type: object
              description: |
                Configuration options for a text response from the model. Can be plain
                text or structured JSON data. Learn more:
                - [Text inputs and outputs](/docs/guides/text)
                - [Structured Outputs](/docs/guides/structured-outputs)
              properties:
                format:
                  $ref: '#/components/schemas/TextResponseFormatConfiguration'
        model:
          type: string
          description: The name of the model to use for generating completions (e.g. "o3-mini").
        source:
          description: Determines what populates the `item` namespace in this run's data source.
          oneOf:
            - $ref: '#/components/schemas/EvalJsonlFileContentSource'
            - $ref: '#/components/schemas/EvalJsonlFileIdSource'
            - $ref: '#/components/schemas/EvalResponsesSource'
      required:
        - type
        - source
      x-oaiMeta:
        name: The completions data source object used to configure an individual run
        group: eval runs
        example: |
          {
            "name": "gpt-4o-mini-2024-07-18",
            "data_source": {
              "type": "responses",
              "input_messages": {
                "type": "item_reference",
                "item_reference": "item.input"
              },
              "model": "gpt-4o-mini-2024-07-18",
              "source": {
                "type": "responses",
                "model": "gpt-4o-mini-2024-07-18"
              }
            }
          }
    CreateEvalRunRequest:
      type: object
      title: CreateEvalRunRequest
      properties:
        name:
          type: string
          description: The name of the run.
        metadata:
          $ref: '#/components/schemas/Metadata'
        data_source:
          type: object
          description: Details about the run's data source.
          oneOf:
            - $ref: '#/components/schemas/CreateEvalJsonlRunDataSource'
            - $ref: '#/components/schemas/CreateEvalCompletionsRunDataSource'
            - $ref: '#/components/schemas/CreateEvalResponsesRunDataSource'
      required:
        - data_source
    CreateEvalStoredCompletionsDataSourceConfig:
      type: object
      title: StoredCompletionsDataSourceConfig
      description: |
        Deprecated in favor of LogsDataSourceConfig.
      properties:
        type:
          type: string
          enum:
            - stored_completions
          default: stored_completions
          description: The type of data source. Always `stored_completions`.
          x-stainless-const: true
        metadata:
          type: object
          description: Metadata filters for the stored completions data source.
          additionalProperties: true
          example: |
            {
              "use_case": "customer_support_agent"
            }
      required:
        - type
      deprecated: true
      x-oaiMeta:
        name: The stored completions data source object for evals
        group: evals
        example: |
          {
            "type": "stored_completions",
            "metadata": {
              "use_case": "customer_support_agent"
            }
          }
    CreateFileRequest:
      type: object
      additionalProperties: false
      properties:
        file:
          description: |
            The File object (not file name) to be uploaded.
          type: string
          format: binary
        purpose:
          description: >
            The intended purpose of the uploaded file. One of: - `assistants`: Used in the Assistants API -
            `batch`: Used in the Batch API - `fine-tune`: Used for fine-tuning - `vision`: Images used for
            vision fine-tuning - `user_data`: Flexible file type for any purpose - `evals`: Used for eval data
            sets
          type: string
          enum:
            - assistants
            - batch
            - fine-tune
            - vision
            - user_data
            - evals
      required:
        - file
        - purpose
    CreateFineTuningCheckpointPermissionRequest:
      type: object
      additionalProperties: false
      properties:
        project_ids:
          type: array
          description: The project identifiers to grant access to.
          items:
            type: string
      required:
        - project_ids
    CreateFineTuningJobRequest:
      type: object
      properties:
        model:
          description: |
            The name of the model to fine-tune. You can select one of the
            [supported models](/docs/guides/fine-tuning#which-models-can-be-fine-tuned).
          example: gpt-4o-mini
          anyOf:
            - type: string
            - type: string
              enum:
                - babbage-002
                - davinci-002
                - gpt-3.5-turbo
                - gpt-4o-mini
          x-oaiTypeLabel: string
        training_file:
          description: >
            The ID of an uploaded file that contains training data.


            See [upload file](/docs/api-reference/files/create) for how to upload a file.


            Your dataset must be formatted as a JSONL file. Additionally, you must upload your file with the
            purpose `fine-tune`.


            The contents of the file should differ depending on if the model uses the
            [chat](/docs/api-reference/fine-tuning/chat-input),
            [completions](/docs/api-reference/fine-tuning/completions-input) format, or if the fine-tuning
            method uses the [preference](/docs/api-reference/fine-tuning/preference-input) format.


            See the [fine-tuning guide](/docs/guides/model-optimization) for more details.
          type: string
          example: file-abc123
        hyperparameters:
          type: object
          description: >
            The hyperparameters used for the fine-tuning job.

            This value is now deprecated in favor of `method`, and should be passed in under the `method`
            parameter.
          properties:
            batch_size:
              description: |
                Number of examples in each batch. A larger batch size means that model parameters
                are updated less frequently, but with lower variance.
              oneOf:
                - type: string
                  enum:
                    - auto
                  x-stainless-const: true
                - type: integer
                  minimum: 1
                  maximum: 256
              default: auto
            learning_rate_multiplier:
              description: |
                Scaling factor for the learning rate. A smaller learning rate may be useful to avoid
                overfitting.
              oneOf:
                - type: string
                  enum:
                    - auto
                  x-stainless-const: true
                - type: number
                  minimum: 0
                  exclusiveMinimum: true
              default: auto
            n_epochs:
              description: |
                The number of epochs to train the model for. An epoch refers to one full cycle
                through the training dataset.
              oneOf:
                - type: string
                  enum:
                    - auto
                  x-stainless-const: true
                - type: integer
                  minimum: 1
                  maximum: 50
              default: auto
          deprecated: true
        suffix:
          description: >
            A string of up to 64 characters that will be added to your fine-tuned model name.


            For example, a `suffix` of "custom-model-name" would produce a model name like
            `ft:gpt-4o-mini:openai:custom-model-name:7p4lURel`.
          type: string
          minLength: 1
          maxLength: 64
          default: null
          nullable: true
        validation_file:
          description: >
            The ID of an uploaded file that contains validation data.


            If you provide this file, the data is used to generate validation

            metrics periodically during fine-tuning. These metrics can be viewed in

            the fine-tuning results file.

            The same data should not be present in both train and validation files.


            Your dataset must be formatted as a JSONL file. You must upload your file with the purpose
            `fine-tune`.


            See the [fine-tuning guide](/docs/guides/model-optimization) for more details.
          type: string
          nullable: true
          example: file-abc123
        integrations:
          type: array
          description: A list of integrations to enable for your fine-tuning job.
          nullable: true
          items:
            type: object
            required:
              - type
              - wandb
            properties:
              type:
                description: >
                  The type of integration to enable. Currently, only "wandb" (Weights and Biases) is
                  supported.
                oneOf:
                  - type: string
                    enum:
                      - wandb
                    x-stainless-const: true
              wandb:
                type: object
                description: >
                  The settings for your integration with Weights and Biases. This payload specifies the
                  project that

                  metrics will be sent to. Optionally, you can set an explicit display name for your run, add
                  tags

                  to your run, and set a default entity (team, username, etc) to be associated with your run.
                required:
                  - project
                properties:
                  project:
                    description: |
                      The name of the project that the new run will be created under.
                    type: string
                    example: my-wandb-project
                  name:
                    description: |
                      A display name to set for the run. If not set, we will use the Job ID as the name.
                    nullable: true
                    type: string
                  entity:
                    description: >
                      The entity to use for the run. This allows you to set the team or username of the WandB
                      user that you would

                      like associated with the run. If not set, the default entity for the registered WandB
                      API key is used.
                    nullable: true
                    type: string
                  tags:
                    description: >
                      A list of tags to be attached to the newly created run. These tags are passed through
                      directly to WandB. Some

                      default tags are generated by OpenAI: "openai/finetune", "openai/{base-model}",
                      "openai/{ftjob-abcdef}".
                    type: array
                    items:
                      type: string
                      example: custom-tag
        seed:
          description: >
            The seed controls the reproducibility of the job. Passing in the same seed and job parameters
            should produce the same results, but may differ in rare cases.

            If a seed is not specified, one will be generated for you.
          type: integer
          nullable: true
          minimum: 0
          maximum: 2147483647
          example: 42
        method:
          $ref: '#/components/schemas/FineTuneMethod'
        metadata:
          $ref: '#/components/schemas/Metadata'
      required:
        - model
        - training_file
    CreateImageEditRequest:
      type: object
      properties:
        image:
          anyOf:
            - type: string
              format: binary
            - type: array
              maxItems: 16
              items:
                type: string
                format: binary
          description: |
            The image(s) to edit. Must be a supported image file or an array of images.

            For `gpt-image-1`, each image should be a `png`, `webp`, or `jpg` file less 
            than 50MB. You can provide up to 16 images.

            For `dall-e-2`, you can only provide one image, and it should be a square 
            `png` file less than 4MB.
        prompt:
          description: >-
            A text description of the desired image(s). The maximum length is 1000 characters for `dall-e-2`,
            and 32000 characters for `gpt-image-1`.
          type: string
          example: A cute baby sea otter wearing a beret
        mask:
          description: >-
            An additional image whose fully transparent areas (e.g. where alpha is zero) indicate where
            `image` should be edited. If there are multiple images provided, the mask will be applied on the
            first image. Must be a valid PNG file, less than 4MB, and have the same dimensions as `image`.
          type: string
          format: binary
        background:
          type: string
          enum:
            - transparent
            - opaque
            - auto
          default: auto
          example: transparent
          nullable: true
          description: |
            Allows to set transparency for the background of the generated image(s). 
            This parameter is only supported for `gpt-image-1`. Must be one of 
            `transparent`, `opaque` or `auto` (default value). When `auto` is used, the 
            model will automatically determine the best background for the image.

            If `transparent`, the output format needs to support transparency, so it 
            should be set to either `png` (default value) or `webp`.
        model:
          anyOf:
            - type: string
            - type: string
              enum:
                - dall-e-2
                - gpt-image-1
              x-stainless-const: true
          x-oaiTypeLabel: string
          default: dall-e-2
          example: gpt-image-1
          nullable: true
          description: >-
            The model to use for image generation. Only `dall-e-2` and `gpt-image-1` are supported. Defaults
            to `dall-e-2` unless a parameter specific to `gpt-image-1` is used.
        'n':
          type: integer
          minimum: 1
          maximum: 10
          default: 1
          example: 1
          nullable: true
          description: The number of images to generate. Must be between 1 and 10.
        size:
          type: string
          enum:
            - 256x256
            - 512x512
            - 1024x1024
            - 1536x1024
            - 1024x1536
            - auto
          default: 1024x1024
          example: 1024x1024
          nullable: true
          description: >-
            The size of the generated images. Must be one of `1024x1024`, `1536x1024` (landscape), `1024x1536`
            (portrait), or `auto` (default value) for `gpt-image-1`, and one of `256x256`, `512x512`, or
            `1024x1024` for `dall-e-2`.
        response_format:
          type: string
          enum:
            - url
            - b64_json
          default: url
          example: url
          nullable: true
          description: >-
            The format in which the generated images are returned. Must be one of `url` or `b64_json`. URLs
            are only valid for 60 minutes after the image has been generated. This parameter is only supported
            for `dall-e-2`, as `gpt-image-1` will always return base64-encoded images.
        output_format:
          type: string
          enum:
            - png
            - jpeg
            - webp
          default: png
          example: png
          nullable: true
          description: |
            The format in which the generated images are returned. This parameter is
            only supported for `gpt-image-1`. Must be one of `png`, `jpeg`, or `webp`.
            The default value is `png`.
        output_compression:
          type: integer
          default: 100
          example: 100
          nullable: true
          description: |
            The compression level (0-100%) for the generated images. This parameter 
            is only supported for `gpt-image-1` with the `webp` or `jpeg` output 
            formats, and defaults to 100.
        user:
          type: string
          example: user-1234
          description: >
            A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse.
            [Learn more](/docs/guides/safety-best-practices#end-user-ids).
        quality:
          type: string
          enum:
            - standard
            - low
            - medium
            - high
            - auto
          default: auto
          example: high
          nullable: true
          description: >
            The quality of the image that will be generated. `high`, `medium` and `low` are only supported for
            `gpt-image-1`. `dall-e-2` only supports `standard` quality. Defaults to `auto`.
      required:
        - prompt
        - image
    CreateImageRequest:
      type: object
      properties:
        prompt:
          description: >-
            A text description of the desired image(s). The maximum length is 32000 characters for
            `gpt-image-1`, 1000 characters for `dall-e-2` and 4000 characters for `dall-e-3`.
          type: string
          example: A cute baby sea otter
        model:
          anyOf:
            - type: string
            - type: string
              enum:
                - dall-e-2
                - dall-e-3
                - gpt-image-1
          x-oaiTypeLabel: string
          default: dall-e-2
          example: gpt-image-1
          nullable: true
          description: >-
            The model to use for image generation. One of `dall-e-2`, `dall-e-3`, or `gpt-image-1`. Defaults
            to `dall-e-2` unless a parameter specific to `gpt-image-1` is used.
        'n':
          type: integer
          minimum: 1
          maximum: 10
          default: 1
          example: 1
          nullable: true
          description: >-
            The number of images to generate. Must be between 1 and 10. For `dall-e-3`, only `n=1` is
            supported.
        quality:
          type: string
          enum:
            - standard
            - hd
            - low
            - medium
            - high
            - auto
          default: auto
          example: medium
          nullable: true
          description: |
            The quality of the image that will be generated. 

            - `auto` (default value) will automatically select the best quality for the given model.
            - `high`, `medium` and `low` are supported for `gpt-image-1`.
            - `hd` and `standard` are supported for `dall-e-3`.
            - `standard` is the only option for `dall-e-2`.
        response_format:
          type: string
          enum:
            - url
            - b64_json
          default: url
          example: url
          nullable: true
          description: >-
            The format in which generated images with `dall-e-2` and `dall-e-3` are returned. Must be one of
            `url` or `b64_json`. URLs are only valid for 60 minutes after the image has been generated. This
            parameter isn't supported for `gpt-image-1` which will always return base64-encoded images.
        output_format:
          type: string
          enum:
            - png
            - jpeg
            - webp
          default: png
          example: png
          nullable: true
          description: >-
            The format in which the generated images are returned. This parameter is only supported for
            `gpt-image-1`. Must be one of `png`, `jpeg`, or `webp`.
        output_compression:
          type: integer
          default: 100
          example: 100
          nullable: true
          description: >-
            The compression level (0-100%) for the generated images. This parameter is only supported for
            `gpt-image-1` with the `webp` or `jpeg` output formats, and defaults to 100.
        size:
          type: string
          enum:
            - auto
            - 1024x1024
            - 1536x1024
            - 1024x1536
            - 256x256
            - 512x512
            - 1792x1024
            - 1024x1792
          default: auto
          example: 1024x1024
          nullable: true
          description: >-
            The size of the generated images. Must be one of `1024x1024`, `1536x1024` (landscape), `1024x1536`
            (portrait), or `auto` (default value) for `gpt-image-1`, one of `256x256`, `512x512`, or
            `1024x1024` for `dall-e-2`, and one of `1024x1024`, `1792x1024`, or `1024x1792` for `dall-e-3`.
        moderation:
          type: string
          enum:
            - low
            - auto
          default: auto
          example: low
          nullable: true
          description: >-
            Control the content-moderation level for images generated by `gpt-image-1`. Must be either `low`
            for less restrictive filtering or `auto` (default value).
        background:
          type: string
          enum:
            - transparent
            - opaque
            - auto
          default: auto
          example: transparent
          nullable: true
          description: |
            Allows to set transparency for the background of the generated image(s). 
            This parameter is only supported for `gpt-image-1`. Must be one of 
            `transparent`, `opaque` or `auto` (default value). When `auto` is used, the 
            model will automatically determine the best background for the image.

            If `transparent`, the output format needs to support transparency, so it 
            should be set to either `png` (default value) or `webp`.
        style:
          type: string
          enum:
            - vivid
            - natural
          default: vivid
          example: vivid
          nullable: true
          description: >-
            The style of the generated images. This parameter is only supported for `dall-e-3`. Must be one of
            `vivid` or `natural`. Vivid causes the model to lean towards generating hyper-real and dramatic
            images. Natural causes the model to produce more natural, less hyper-real looking images.
        user:
          type: string
          example: user-1234
          description: >
            A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse.
            [Learn more](/docs/guides/safety-best-practices#end-user-ids).
      required:
        - prompt
    CreateImageVariationRequest:
      type: object
      properties:
        image:
          description: >-
            The image to use as the basis for the variation(s). Must be a valid PNG file, less than 4MB, and
            square.
          type: string
          format: binary
        model:
          anyOf:
            - type: string
            - type: string
              enum:
                - dall-e-2
              x-stainless-const: true
          x-oaiTypeLabel: string
          default: dall-e-2
          example: dall-e-2
          nullable: true
          description: The model to use for image generation. Only `dall-e-2` is supported at this time.
        'n':
          type: integer
          minimum: 1
          maximum: 10
          default: 1
          example: 1
          nullable: true
          description: The number of images to generate. Must be between 1 and 10.
        response_format:
          type: string
          enum:
            - url
            - b64_json
          default: url
          example: url
          nullable: true
          description: >-
            The format in which the generated images are returned. Must be one of `url` or `b64_json`. URLs
            are only valid for 60 minutes after the image has been generated.
        size:
          type: string
          enum:
            - 256x256
            - 512x512
            - 1024x1024
          default: 1024x1024
          example: 1024x1024
          nullable: true
          description: The size of the generated images. Must be one of `256x256`, `512x512`, or `1024x1024`.
        user:
          type: string
          example: user-1234
          description: >
            A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse.
            [Learn more](/docs/guides/safety-best-practices#end-user-ids).
      required:
        - image
    CreateMessageRequest:
      type: object
      additionalProperties: false
      required:
        - role
        - content
      properties:
        role:
          type: string
          enum:
            - user
            - assistant
          description: >
            The role of the entity that is creating the message. Allowed values include:

            - `user`: Indicates the message is sent by an actual user and should be used in most cases to
            represent user-generated messages.

            - `assistant`: Indicates the message is generated by the assistant. Use this value to insert
            messages from the assistant into the conversation.
        content:
          oneOf:
            - type: string
              description: The text contents of the message.
              title: Text content
            - type: array
              description: >-
                An array of content parts with a defined type, each can be of type `text` or images can be
                passed with `image_url` or `image_file`. Image types are only supported on [Vision-compatible
                models](/docs/models).
              title: Array of content parts
              items:
                oneOf:
                  - $ref: '#/components/schemas/MessageContentImageFileObject'
                  - $ref: '#/components/schemas/MessageContentImageUrlObject'
                  - $ref: '#/components/schemas/MessageRequestContentTextObject'
              minItems: 1
        attachments:
          type: array
          items:
            type: object
            properties:
              file_id:
                type: string
                description: The ID of the file to attach to the message.
              tools:
                description: The tools to add this file to.
                type: array
                items:
                  oneOf:
                    - $ref: '#/components/schemas/AssistantToolsCode'
                    - $ref: '#/components/schemas/AssistantToolsFileSearchTypeOnly'
          description: A list of files attached to the message, and the tools they should be added to.
          required:
            - file_id
            - tools
          nullable: true
        metadata:
          $ref: '#/components/schemas/Metadata'
    CreateModelResponseProperties:
      allOf:
        - $ref: '#/components/schemas/ModelResponseProperties'
    CreateModerationRequest:
      type: object
      properties:
        input:
          description: |
            Input (or inputs) to classify. Can be a single string, an array of strings, or
            an array of multi-modal input objects similar to other models.
          oneOf:
            - type: string
              description: A string of text to classify for moderation.
              default: ''
              example: I want to kill them.
            - type: array
              description: An array of strings to classify for moderation.
              items:
                type: string
                default: ''
                example: I want to kill them.
            - type: array
              description: An array of multi-modal inputs to the moderation model.
              items:
                oneOf:
                  - type: object
                    description: An object describing an image to classify.
                    properties:
                      type:
                        description: Always `image_url`.
                        type: string
                        enum:
                          - image_url
                        x-stainless-const: true
                      image_url:
                        type: object
                        description: Contains either an image URL or a data URL for a base64 encoded image.
                        properties:
                          url:
                            type: string
                            description: Either a URL of the image or the base64 encoded image data.
                            format: uri
                            example: https://example.com/image.jpg
                        required:
                          - url
                    required:
                      - type
                      - image_url
                  - type: object
                    description: An object describing text to classify.
                    properties:
                      type:
                        description: Always `text`.
                        type: string
                        enum:
                          - text
                        x-stainless-const: true
                      text:
                        description: A string of text to classify.
                        type: string
                        example: I want to kill them
                    required:
                      - type
                      - text
        model:
          description: |
            The content moderation model you would like to use. Learn more in
            [the moderation guide](/docs/guides/moderation), and learn about
            available models [here](/docs/models#moderation).
          nullable: false
          default: omni-moderation-latest
          example: omni-moderation-2024-09-26
          anyOf:
            - type: string
            - type: string
              enum:
                - omni-moderation-latest
                - omni-moderation-2024-09-26
                - text-moderation-latest
                - text-moderation-stable
          x-oaiTypeLabel: string
      required:
        - input
    CreateModerationResponse:
      type: object
      description: Represents if a given text input is potentially harmful.
      properties:
        id:
          type: string
          description: The unique identifier for the moderation request.
        model:
          type: string
          description: The model used to generate the moderation results.
        results:
          type: array
          description: A list of moderation objects.
          items:
            type: object
            properties:
              flagged:
                type: boolean
                description: Whether any of the below categories are flagged.
              categories:
                type: object
                description: A list of the categories, and whether they are flagged or not.
                properties:
                  hate:
                    type: boolean
                    description: >-
                      Content that expresses, incites, or promotes hate based on race, gender, ethnicity,
                      religion, nationality, sexual orientation, disability status, or caste. Hateful content
                      aimed at non-protected groups (e.g., chess players) is harassment.
                  hate/threatening:
                    type: boolean
                    description: >-
                      Hateful content that also includes violence or serious harm towards the targeted group
                      based on race, gender, ethnicity, religion, nationality, sexual orientation, disability
                      status, or caste.
                  harassment:
                    type: boolean
                    description: Content that expresses, incites, or promotes harassing language towards any target.
                  harassment/threatening:
                    type: boolean
                    description: Harassment content that also includes violence or serious harm towards any target.
                  illicit:
                    type: boolean
                    nullable: true
                    description: >-
                      Content that includes instructions or advice that facilitate the planning or execution
                      of wrongdoing, or that gives advice or instruction on how to commit illicit acts. For
                      example, "how to shoplift" would fit this category.
                  illicit/violent:
                    type: boolean
                    nullable: true
                    description: >-
                      Content that includes instructions or advice that facilitate the planning or execution
                      of wrongdoing that also includes violence, or that gives advice or instruction on the
                      procurement of any weapon.
                  self-harm:
                    type: boolean
                    description: >-
                      Content that promotes, encourages, or depicts acts of self-harm, such as suicide,
                      cutting, and eating disorders.
                  self-harm/intent:
                    type: boolean
                    description: >-
                      Content where the speaker expresses that they are engaging or intend to engage in acts
                      of self-harm, such as suicide, cutting, and eating disorders.
                  self-harm/instructions:
                    type: boolean
                    description: >-
                      Content that encourages performing acts of self-harm, such as suicide, cutting, and
                      eating disorders, or that gives instructions or advice on how to commit such acts.
                  sexual:
                    type: boolean
                    description: >-
                      Content meant to arouse sexual excitement, such as the description of sexual activity,
                      or that promotes sexual services (excluding sex education and wellness).
                  sexual/minors:
                    type: boolean
                    description: Sexual content that includes an individual who is under 18 years old.
                  violence:
                    type: boolean
                    description: Content that depicts death, violence, or physical injury.
                  violence/graphic:
                    type: boolean
                    description: Content that depicts death, violence, or physical injury in graphic detail.
                required:
                  - hate
                  - hate/threatening
                  - harassment
                  - harassment/threatening
                  - illicit
                  - illicit/violent
                  - self-harm
                  - self-harm/intent
                  - self-harm/instructions
                  - sexual
                  - sexual/minors
                  - violence
                  - violence/graphic
              category_scores:
                type: object
                description: A list of the categories along with their scores as predicted by model.
                properties:
                  hate:
                    type: number
                    description: The score for the category 'hate'.
                  hate/threatening:
                    type: number
                    description: The score for the category 'hate/threatening'.
                  harassment:
                    type: number
                    description: The score for the category 'harassment'.
                  harassment/threatening:
                    type: number
                    description: The score for the category 'harassment/threatening'.
                  illicit:
                    type: number
                    description: The score for the category 'illicit'.
                  illicit/violent:
                    type: number
                    description: The score for the category 'illicit/violent'.
                  self-harm:
                    type: number
                    description: The score for the category 'self-harm'.
                  self-harm/intent:
                    type: number
                    description: The score for the category 'self-harm/intent'.
                  self-harm/instructions:
                    type: number
                    description: The score for the category 'self-harm/instructions'.
                  sexual:
                    type: number
                    description: The score for the category 'sexual'.
                  sexual/minors:
                    type: number
                    description: The score for the category 'sexual/minors'.
                  violence:
                    type: number
                    description: The score for the category 'violence'.
                  violence/graphic:
                    type: number
                    description: The score for the category 'violence/graphic'.
                required:
                  - hate
                  - hate/threatening
                  - harassment
                  - harassment/threatening
                  - illicit
                  - illicit/violent
                  - self-harm
                  - self-harm/intent
                  - self-harm/instructions
                  - sexual
                  - sexual/minors
                  - violence
                  - violence/graphic
              category_applied_input_types:
                type: object
                description: A list of the categories along with the input type(s) that the score applies to.
                properties:
                  hate:
                    type: array
                    description: The applied input type(s) for the category 'hate'.
                    items:
                      type: string
                      enum:
                        - text
                      x-stainless-const: true
                  hate/threatening:
                    type: array
                    description: The applied input type(s) for the category 'hate/threatening'.
                    items:
                      type: string
                      enum:
                        - text
                      x-stainless-const: true
                  harassment:
                    type: array
                    description: The applied input type(s) for the category 'harassment'.
                    items:
                      type: string
                      enum:
                        - text
                      x-stainless-const: true
                  harassment/threatening:
                    type: array
                    description: The applied input type(s) for the category 'harassment/threatening'.
                    items:
                      type: string
                      enum:
                        - text
                      x-stainless-const: true
                  illicit:
                    type: array
                    description: The applied input type(s) for the category 'illicit'.
                    items:
                      type: string
                      enum:
                        - text
                      x-stainless-const: true
                  illicit/violent:
                    type: array
                    description: The applied input type(s) for the category 'illicit/violent'.
                    items:
                      type: string
                      enum:
                        - text
                      x-stainless-const: true
                  self-harm:
                    type: array
                    description: The applied input type(s) for the category 'self-harm'.
                    items:
                      type: string
                      enum:
                        - text
                        - image
                  self-harm/intent:
                    type: array
                    description: The applied input type(s) for the category 'self-harm/intent'.
                    items:
                      type: string
                      enum:
                        - text
                        - image
                  self-harm/instructions:
                    type: array
                    description: The applied input type(s) for the category 'self-harm/instructions'.
                    items:
                      type: string
                      enum:
                        - text
                        - image
                  sexual:
                    type: array
                    description: The applied input type(s) for the category 'sexual'.
                    items:
                      type: string
                      enum:
                        - text
                        - image
                  sexual/minors:
                    type: array
                    description: The applied input type(s) for the category 'sexual/minors'.
                    items:
                      type: string
                      enum:
                        - text
                      x-stainless-const: true
                  violence:
                    type: array
                    description: The applied input type(s) for the category 'violence'.
                    items:
                      type: string
                      enum:
                        - text
                        - image
                  violence/graphic:
                    type: array
                    description: The applied input type(s) for the category 'violence/graphic'.
                    items:
                      type: string
                      enum:
                        - text
                        - image
                required:
                  - hate
                  - hate/threatening
                  - harassment
                  - harassment/threatening
                  - illicit
                  - illicit/violent
                  - self-harm
                  - self-harm/intent
                  - self-harm/instructions
                  - sexual
                  - sexual/minors
                  - violence
                  - violence/graphic
            required:
              - flagged
              - categories
              - category_scores
              - category_applied_input_types
      required:
        - id
        - model
        - results
      x-oaiMeta:
        name: The moderation object
        example: |
          {
            "id": "modr-0d9740456c391e43c445bf0f010940c7",
            "model": "omni-moderation-latest",
            "results": [
              {
                "flagged": true,
                "categories": {
                  "harassment": true,
                  "harassment/threatening": true,
                  "sexual": false,
                  "hate": false,
                  "hate/threatening": false,
                  "illicit": false,
                  "illicit/violent": false,
                  "self-harm/intent": false,
                  "self-harm/instructions": false,
                  "self-harm": false,
                  "sexual/minors": false,
                  "violence": true,
                  "violence/graphic": true
                },
                "category_scores": {
                  "harassment": 0.8189693396524255,
                  "harassment/threatening": 0.804985420696006,
                  "sexual": 1.573112165348997e-6,
                  "hate": 0.007562942636942845,
                  "hate/threatening": 0.004208854591835476,
                  "illicit": 0.030535955153511665,
                  "illicit/violent": 0.008925306722380033,
                  "self-harm/intent": 0.00023023930975076432,
                  "self-harm/instructions": 0.0002293869201073356,
                  "self-harm": 0.012598046106750154,
                  "sexual/minors": 2.212566909570261e-8,
                  "violence": 0.9999992735124786,
                  "violence/graphic": 0.843064871157054
                },
                "category_applied_input_types": {
                  "harassment": [
                    "text"
                  ],
                  "harassment/threatening": [
                    "text"
                  ],
                  "sexual": [
                    "text",
                    "image"
                  ],
                  "hate": [
                    "text"
                  ],
                  "hate/threatening": [
                    "text"
                  ],
                  "illicit": [
                    "text"
                  ],
                  "illicit/violent": [
                    "text"
                  ],
                  "self-harm/intent": [
                    "text",
                    "image"
                  ],
                  "self-harm/instructions": [
                    "text",
                    "image"
                  ],
                  "self-harm": [
                    "text",
                    "image"
                  ],
                  "sexual/minors": [
                    "text"
                  ],
                  "violence": [
                    "text",
                    "image"
                  ],
                  "violence/graphic": [
                    "text",
                    "image"
                  ]
                }
              }
            ]
          }
    CreateResponse:
      allOf:
        - $ref: '#/components/schemas/CreateModelResponseProperties'
        - $ref: '#/components/schemas/ResponseProperties'
        - type: object
          properties:
            input:
              description: |
                Text, image, or file inputs to the model, used to generate a response.

                Learn more:
                - [Text inputs and outputs](/docs/guides/text)
                - [Image inputs](/docs/guides/images)
                - [File inputs](/docs/guides/pdf-files)
                - [Conversation state](/docs/guides/conversation-state)
                - [Function calling](/docs/guides/function-calling)
              oneOf:
                - type: string
                  title: Text input
                  description: |
                    A text input to the model, equivalent to a text input with the 
                    `user` role.
                - type: array
                  title: Input item list
                  description: |
                    A list of one or many input items to the model, containing 
                    different content types.
                  items:
                    $ref: '#/components/schemas/InputItem'
            include:
              type: array
              description: |
                Specify additional output data to include in the model response. Currently
                supported values are:
                - `file_search_call.results`: Include the search results of
                  the file search tool call.
                - `message.input_image.image_url`: Include image urls from the input message.
                - `computer_call_output.output.image_url`: Include image urls from the computer call output.
                - `reasoning.encrypted_content`: Includes an encrypted version of reasoning
                  tokens in reasoning item outputs. This enables reasoning items to be used in
                  multi-turn conversations when using the Responses API statelessly (like
                  when the `store` parameter is set to `false`, or when an organization is
                  enrolled in the zero data retention program).
                - `code_interpreter_call.outputs`: Includes the outputs of python code execution
                  in code interpreter tool call items.
              items:
                $ref: '#/components/schemas/Includable'
              nullable: true
            parallel_tool_calls:
              type: boolean
              description: |
                Whether to allow the model to run tool calls in parallel.
              default: true
              nullable: true
            store:
              type: boolean
              description: |
                Whether to store the generated model response for later retrieval via
                API.
              default: true
              nullable: true
            instructions:
              type: string
              nullable: true
              description: |
                A system (or developer) message inserted into the model's context.

                When using along with `previous_response_id`, the instructions from a previous
                response will not be carried over to the next response. This makes it simple
                to swap out system (or developer) messages in new responses.
            stream:
              description: >
                If set to true, the model response data will be streamed to the client

                as it is generated using [server-sent
                events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format).

                See the [Streaming section below](/docs/api-reference/responses-streaming)

                for more information.
              type: boolean
              nullable: true
              default: false
          required: []
    CreateRunRequest:
      type: object
      additionalProperties: false
      properties:
        assistant_id:
          description: The ID of the [assistant](/docs/api-reference/assistants) to use to execute this run.
          type: string
        model:
          description: >-
            The ID of the [Model](/docs/api-reference/models) to be used to execute this run. If a value is
            provided here, it will override the model associated with the assistant. If not, the model
            associated with the assistant will be used.
          example: gpt-4o
          anyOf:
            - type: string
            - $ref: '#/components/schemas/AssistantSupportedModels'
          x-oaiTypeLabel: string
          nullable: true
        reasoning_effort:
          $ref: '#/components/schemas/ReasoningEffort'
        instructions:
          description: >-
            Overrides the [instructions](/docs/api-reference/assistants/createAssistant) of the assistant.
            This is useful for modifying the behavior on a per-run basis.
          type: string
          nullable: true
        additional_instructions:
          description: >-
            Appends additional instructions at the end of the instructions for the run. This is useful for
            modifying the behavior on a per-run basis without overriding other instructions.
          type: string
          nullable: true
        additional_messages:
          description: Adds additional messages to the thread before creating the run.
          type: array
          items:
            $ref: '#/components/schemas/CreateMessageRequest'
          nullable: true
        tools:
          description: >-
            Override the tools the assistant can use for this run. This is useful for modifying the behavior
            on a per-run basis.
          nullable: true
          type: array
          maxItems: 20
          items:
            oneOf:
              - $ref: '#/components/schemas/AssistantToolsCode'
              - $ref: '#/components/schemas/AssistantToolsFileSearch'
              - $ref: '#/components/schemas/AssistantToolsFunction'
        metadata:
          $ref: '#/components/schemas/Metadata'
        temperature:
          type: number
          minimum: 0
          maximum: 2
          default: 1
          example: 1
          nullable: true
          description: >
            What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output
            more random, while lower values like 0.2 will make it more focused and deterministic.
        top_p:
          type: number
          minimum: 0
          maximum: 1
          default: 1
          example: 1
          nullable: true
          description: >
            An alternative to sampling with temperature, called nucleus sampling, where the model considers
            the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the
            top 10% probability mass are considered.


            We generally recommend altering this or temperature but not both.
        stream:
          type: boolean
          nullable: true
          description: >
            If `true`, returns a stream of events that happen during the Run as server-sent events,
            terminating when the Run enters a terminal state with a `data: [DONE]` message.
        max_prompt_tokens:
          type: integer
          nullable: true
          description: >
            The maximum number of prompt tokens that may be used over the course of the run. The run will make
            a best effort to use only the number of prompt tokens specified, across multiple turns of the run.
            If the run exceeds the number of prompt tokens specified, the run will end with status
            `incomplete`. See `incomplete_details` for more info.
          minimum: 256
        max_completion_tokens:
          type: integer
          nullable: true
          description: >
            The maximum number of completion tokens that may be used over the course of the run. The run will
            make a best effort to use only the number of completion tokens specified, across multiple turns of
            the run. If the run exceeds the number of completion tokens specified, the run will end with
            status `incomplete`. See `incomplete_details` for more info.
          minimum: 256
        truncation_strategy:
          allOf:
            - $ref: '#/components/schemas/TruncationObject'
            - nullable: true
        tool_choice:
          allOf:
            - $ref: '#/components/schemas/AssistantsApiToolChoiceOption'
            - nullable: true
        parallel_tool_calls:
          $ref: '#/components/schemas/ParallelToolCalls'
        response_format:
          $ref: '#/components/schemas/AssistantsApiResponseFormatOption'
          nullable: true
      required:
        - assistant_id
    CreateSpeechRequest:
      type: object
      additionalProperties: false
      properties:
        model:
          description: |
            One of the available [TTS models](/docs/models#tts): `tts-1`, `tts-1-hd` or `gpt-4o-mini-tts`.
          anyOf:
            - type: string
            - type: string
              enum:
                - tts-1
                - tts-1-hd
                - gpt-4o-mini-tts
          x-oaiTypeLabel: string
        input:
          type: string
          description: The text to generate audio for. The maximum length is 4096 characters.
          maxLength: 4096
        instructions:
          type: string
          description: >-
            Control the voice of your generated audio with additional instructions. Does not work with `tts-1`
            or `tts-1-hd`.
          maxLength: 4096
        voice:
          description: >-
            The voice to use when generating the audio. Supported voices are `alloy`, `ash`, `ballad`,
            `coral`, `echo`, `fable`, `onyx`, `nova`, `sage`, `shimmer`, and `verse`. Previews of the voices
            are available in the [Text to speech guide](/docs/guides/text-to-speech#voice-options).
          $ref: '#/components/schemas/VoiceIdsShared'
        response_format:
          description: The format to audio in. Supported formats are `mp3`, `opus`, `aac`, `flac`, `wav`, and `pcm`.
          default: mp3
          type: string
          enum:
            - mp3
            - opus
            - aac
            - flac
            - wav
            - pcm
        speed:
          description: >-
            The speed of the generated audio. Select a value from `0.25` to `4.0`. `1.0` is the default. Does
            not work with `gpt-4o-mini-tts`.
          type: number
          default: 1
          minimum: 0.25
          maximum: 4
      required:
        - model
        - input
        - voice
    CreateThreadAndRunRequest:
      type: object
      additionalProperties: false
      properties:
        assistant_id:
          description: The ID of the [assistant](/docs/api-reference/assistants) to use to execute this run.
          type: string
        thread:
          $ref: '#/components/schemas/CreateThreadRequest'
        model:
          description: >-
            The ID of the [Model](/docs/api-reference/models) to be used to execute this run. If a value is
            provided here, it will override the model associated with the assistant. If not, the model
            associated with the assistant will be used.
          example: gpt-4o
          anyOf:
            - type: string
            - type: string
              enum:
                - gpt-4.1
                - gpt-4.1-mini
                - gpt-4.1-nano
                - gpt-4.1-2025-04-14
                - gpt-4.1-mini-2025-04-14
                - gpt-4.1-nano-2025-04-14
                - gpt-4o
                - gpt-4o-2024-11-20
                - gpt-4o-2024-08-06
                - gpt-4o-2024-05-13
                - gpt-4o-mini
                - gpt-4o-mini-2024-07-18
                - gpt-4.5-preview
                - gpt-4.5-preview-2025-02-27
                - gpt-4-turbo
                - gpt-4-turbo-2024-04-09
                - gpt-4-0125-preview
                - gpt-4-turbo-preview
                - gpt-4-1106-preview
                - gpt-4-vision-preview
                - gpt-4
                - gpt-4-0314
                - gpt-4-0613
                - gpt-4-32k
                - gpt-4-32k-0314
                - gpt-4-32k-0613
                - gpt-3.5-turbo
                - gpt-3.5-turbo-16k
                - gpt-3.5-turbo-0613
                - gpt-3.5-turbo-1106
                - gpt-3.5-turbo-0125
                - gpt-3.5-turbo-16k-0613
          x-oaiTypeLabel: string
          nullable: true
        instructions:
          description: >-
            Override the default system message of the assistant. This is useful for modifying the behavior on
            a per-run basis.
          type: string
          nullable: true
        tools:
          description: >-
            Override the tools the assistant can use for this run. This is useful for modifying the behavior
            on a per-run basis.
          nullable: true
          type: array
          maxItems: 20
          items:
            oneOf:
              - $ref: '#/components/schemas/AssistantToolsCode'
              - $ref: '#/components/schemas/AssistantToolsFileSearch'
              - $ref: '#/components/schemas/AssistantToolsFunction'
        tool_resources:
          type: object
          description: >
            A set of resources that are used by the assistant's tools. The resources are specific to the type
            of tool. For example, the `code_interpreter` tool requires a list of file IDs, while the
            `file_search` tool requires a list of vector store IDs.
          properties:
            code_interpreter:
              type: object
              properties:
                file_ids:
                  type: array
                  description: >
                    A list of [file](/docs/api-reference/files) IDs made available to the `code_interpreter`
                    tool. There can be a maximum of 20 files associated with the tool.
                  default: []
                  maxItems: 20
                  items:
                    type: string
            file_search:
              type: object
              properties:
                vector_store_ids:
                  type: array
                  description: >
                    The ID of the [vector store](/docs/api-reference/vector-stores/object) attached to this
                    assistant. There can be a maximum of 1 vector store attached to the assistant.
                  maxItems: 1
                  items:
                    type: string
          nullable: true
        metadata:
          $ref: '#/components/schemas/Metadata'
        temperature:
          type: number
          minimum: 0
          maximum: 2
          default: 1
          example: 1
          nullable: true
          description: >
            What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output
            more random, while lower values like 0.2 will make it more focused and deterministic.
        top_p:
          type: number
          minimum: 0
          maximum: 1
          default: 1
          example: 1
          nullable: true
          description: >
            An alternative to sampling with temperature, called nucleus sampling, where the model considers
            the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the
            top 10% probability mass are considered.


            We generally recommend altering this or temperature but not both.
        stream:
          type: boolean
          nullable: true
          description: >
            If `true`, returns a stream of events that happen during the Run as server-sent events,
            terminating when the Run enters a terminal state with a `data: [DONE]` message.
        max_prompt_tokens:
          type: integer
          nullable: true
          description: >
            The maximum number of prompt tokens that may be used over the course of the run. The run will make
            a best effort to use only the number of prompt tokens specified, across multiple turns of the run.
            If the run exceeds the number of prompt tokens specified, the run will end with status
            `incomplete`. See `incomplete_details` for more info.
          minimum: 256
        max_completion_tokens:
          type: integer
          nullable: true
          description: >
            The maximum number of completion tokens that may be used over the course of the run. The run will
            make a best effort to use only the number of completion tokens specified, across multiple turns of
            the run. If the run exceeds the number of completion tokens specified, the run will end with
            status `incomplete`. See `incomplete_details` for more info.
          minimum: 256
        truncation_strategy:
          allOf:
            - $ref: '#/components/schemas/TruncationObject'
            - nullable: true
        tool_choice:
          allOf:
            - $ref: '#/components/schemas/AssistantsApiToolChoiceOption'
            - nullable: true
        parallel_tool_calls:
          $ref: '#/components/schemas/ParallelToolCalls'
        response_format:
          $ref: '#/components/schemas/AssistantsApiResponseFormatOption'
          nullable: true
      required:
        - assistant_id
    CreateThreadRequest:
      type: object
      description: |
        Options to create a new thread. If no thread is provided when running a 
        request, an empty thread will be created.
      additionalProperties: false
      properties:
        messages:
          description: A list of [messages](/docs/api-reference/messages) to start the thread with.
          type: array
          items:
            $ref: '#/components/schemas/CreateMessageRequest'
        tool_resources:
          type: object
          description: >
            A set of resources that are made available to the assistant's tools in this thread. The resources
            are specific to the type of tool. For example, the `code_interpreter` tool requires a list of file
            IDs, while the `file_search` tool requires a list of vector store IDs.
          properties:
            code_interpreter:
              type: object
              properties:
                file_ids:
                  type: array
                  description: >
                    A list of [file](/docs/api-reference/files) IDs made available to the `code_interpreter`
                    tool. There can be a maximum of 20 files associated with the tool.
                  default: []
                  maxItems: 20
                  items:
                    type: string
            file_search:
              type: object
              properties:
                vector_store_ids:
                  type: array
                  description: >
                    The [vector store](/docs/api-reference/vector-stores/object) attached to this thread.
                    There can be a maximum of 1 vector store attached to the thread.
                  maxItems: 1
                  items:
                    type: string
                vector_stores:
                  type: array
                  description: >
                    A helper to create a [vector store](/docs/api-reference/vector-stores/object) with
                    file_ids and attach it to this thread. There can be a maximum of 1 vector store attached
                    to the thread.
                  maxItems: 1
                  items:
                    type: object
                    properties:
                      file_ids:
                        type: array
                        description: >
                          A list of [file](/docs/api-reference/files) IDs to add to the vector store. There
                          can be a maximum of 10000 files in a vector store.
                        maxItems: 10000
                        items:
                          type: string
                      chunking_strategy:
                        type: object
                        description: >-
                          The chunking strategy used to chunk the file(s). If not set, will use the `auto`
                          strategy.
                        oneOf:
                          - type: object
                            title: Auto Chunking Strategy
                            description: >-
                              The default strategy. This strategy currently uses a `max_chunk_size_tokens` of
                              `800` and `chunk_overlap_tokens` of `400`.
                            additionalProperties: false
                            properties:
                              type:
                                type: string
                                description: Always `auto`.
                                enum:
                                  - auto
                                x-stainless-const: true
                            required:
                              - type
                          - type: object
                            title: Static Chunking Strategy
                            additionalProperties: false
                            properties:
                              type:
                                type: string
                                description: Always `static`.
                                enum:
                                  - static
                                x-stainless-const: true
                              static:
                                type: object
                                additionalProperties: false
                                properties:
                                  max_chunk_size_tokens:
                                    type: integer
                                    minimum: 100
                                    maximum: 4096
                                    description: >-
                                      The maximum number of tokens in each chunk. The default value is `800`.
                                      The minimum value is `100` and the maximum value is `4096`.
                                  chunk_overlap_tokens:
                                    type: integer
                                    description: >
                                      The number of tokens that overlap between chunks. The default value is
                                      `400`.


                                      Note that the overlap must not exceed half of `max_chunk_size_tokens`.
                                required:
                                  - max_chunk_size_tokens
                                  - chunk_overlap_tokens
                            required:
                              - type
                              - static
                      metadata:
                        $ref: '#/components/schemas/Metadata'
              oneOf:
                - required:
                    - vector_store_ids
                - required:
                    - vector_stores
          nullable: true
        metadata:
          $ref: '#/components/schemas/Metadata'
    CreateTranscriptionRequest:
      type: object
      additionalProperties: false
      properties:
        file:
          description: >
            The audio file object (not file name) to transcribe, in one of these formats: flac, mp3, mp4,
            mpeg, mpga, m4a, ogg, wav, or webm.
          type: string
          x-oaiTypeLabel: file
          format: binary
        model:
          description: >
            ID of the model to use. The options are `gpt-4o-transcribe`, `gpt-4o-mini-transcribe`, and
            `whisper-1` (which is powered by our open source Whisper V2 model).
          example: gpt-4o-transcribe
          anyOf:
            - type: string
            - type: string
              enum:
                - whisper-1
                - gpt-4o-transcribe
                - gpt-4o-mini-transcribe
              x-stainless-const: true
          x-oaiTypeLabel: string
        language:
          description: >
            The language of the input audio. Supplying the input language in
            [ISO-639-1](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes) (e.g. `en`) format will improve
            accuracy and latency.
          type: string
        prompt:
          description: >
            An optional text to guide the model's style or continue a previous audio segment. The
            [prompt](/docs/guides/speech-to-text#prompting) should match the audio language.
          type: string
        response_format:
          $ref: '#/components/schemas/AudioResponseFormat'
        temperature:
          description: >
            The sampling temperature, between 0 and 1. Higher values like 0.8 will make the output more
            random, while lower values like 0.2 will make it more focused and deterministic. If set to 0, the
            model will use [log probability](https://en.wikipedia.org/wiki/Log_probability) to automatically
            increase the temperature until certain thresholds are hit.
          type: number
          default: 0
        include[]:
          description: |
            Additional information to include in the transcription response. 
            `logprobs` will return the log probabilities of the tokens in the 
            response to understand the model's confidence in the transcription. 
            `logprobs` only works with response_format set to `json` and only with 
            the models `gpt-4o-transcribe` and `gpt-4o-mini-transcribe`.
          type: array
          items:
            $ref: '#/components/schemas/TranscriptionInclude'
        timestamp_granularities[]:
          description: >
            The timestamp granularities to populate for this transcription. `response_format` must be set
            `verbose_json` to use timestamp granularities. Either or both of these options are supported:
            `word`, or `segment`. Note: There is no additional latency for segment timestamps, but generating
            word timestamps incurs additional latency.
          type: array
          items:
            type: string
            enum:
              - word
              - segment
          default:
            - segment
        stream:
          description: >
            If set to true, the model response data will be streamed to the client

            as it is generated using [server-sent
            events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format). 

            See the [Streaming section of the Speech-to-Text
            guide](/docs/guides/speech-to-text?lang=curl#streaming-transcriptions)

            for more information.


            Note: Streaming is not supported for the `whisper-1` model and will be ignored.
          type: boolean
          nullable: true
          default: false
        chunking_strategy:
          description: >-
            Controls how the audio is cut into chunks. When set to `"auto"`, the server first normalizes
            loudness and then uses voice activity detection (VAD) to choose boundaries. `server_vad` object
            can be provided to tweak VAD detection parameters manually. If unset, the audio is transcribed as
            a single block. 
          anyOf:
            - type: string
              enum:
                - auto
              default:
                - auto
              description: |
                Automatically set chunking parameters based on the audio. Must be set to `"auto"`.
              x-stainless-const: true
            - $ref: '#/components/schemas/VadConfig'
          nullable: true
          x-oaiTypeLabel: string
      required:
        - file
        - model
    CreateTranscriptionResponseJson:
      type: object
      description: Represents a transcription response returned by model, based on the provided input.
      properties:
        text:
          type: string
          description: The transcribed text.
        logprobs:
          type: array
          optional: true
          description: >
            The log probabilities of the tokens in the transcription. Only returned with the models
            `gpt-4o-transcribe` and `gpt-4o-mini-transcribe` if `logprobs` is added to the `include` array.
          items:
            type: object
            properties:
              token:
                type: string
                description: The token in the transcription.
              logprob:
                type: number
                description: The log probability of the token.
              bytes:
                type: array
                items:
                  type: number
                description: The bytes of the token.
      required:
        - text
      x-oaiMeta:
        name: The transcription object (JSON)
        group: audio
        example: |
          {
            "text": "Imagine the wildest idea that you've ever had, and you're curious about how it might scale to something that's a 100, a 1,000 times bigger. This is a place where you can get to do that."
          }
    CreateTranscriptionResponseStreamEvent:
      anyOf:
        - $ref: '#/components/schemas/TranscriptTextDeltaEvent'
        - $ref: '#/components/schemas/TranscriptTextDoneEvent'
      discriminator:
        propertyName: type
    CreateTranscriptionResponseVerboseJson:
      type: object
      description: Represents a verbose json transcription response returned by model, based on the provided input.
      properties:
        language:
          type: string
          description: The language of the input audio.
        duration:
          type: number
          description: The duration of the input audio.
        text:
          type: string
          description: The transcribed text.
        words:
          type: array
          description: Extracted words and their corresponding timestamps.
          items:
            $ref: '#/components/schemas/TranscriptionWord'
        segments:
          type: array
          description: Segments of the transcribed text and their corresponding details.
          items:
            $ref: '#/components/schemas/TranscriptionSegment'
      required:
        - language
        - duration
        - text
      x-oaiMeta:
        name: The transcription object (Verbose JSON)
        group: audio
        example: |
          {
            "task": "transcribe",
            "language": "english",
            "duration": 8.470000267028809,
            "text": "The beach was a popular spot on a hot summer day. People were swimming in the ocean, building sandcastles, and playing beach volleyball.",
            "segments": [
              {
                "id": 0,
                "seek": 0,
                "start": 0.0,
                "end": 3.319999933242798,
                "text": " The beach was a popular spot on a hot summer day.",
                "tokens": [
                  50364, 440, 7534, 390, 257, 3743, 4008, 322, 257, 2368, 4266, 786, 13, 50530
                ],
                "temperature": 0.0,
                "avg_logprob": -0.2860786020755768,
                "compression_ratio": 1.2363636493682861,
                "no_speech_prob": 0.00985979475080967
              },
              ...
            ]
          }
    CreateTranslationRequest:
      type: object
      additionalProperties: false
      properties:
        file:
          description: >
            The audio file object (not file name) translate, in one of these formats: flac, mp3, mp4, mpeg,
            mpga, m4a, ogg, wav, or webm.
          type: string
          x-oaiTypeLabel: file
          format: binary
        model:
          description: >
            ID of the model to use. Only `whisper-1` (which is powered by our open source Whisper V2 model) is
            currently available.
          example: whisper-1
          anyOf:
            - type: string
            - type: string
              enum:
                - whisper-1
              x-stainless-const: true
          x-oaiTypeLabel: string
        prompt:
          description: >
            An optional text to guide the model's style or continue a previous audio segment. The
            [prompt](/docs/guides/speech-to-text#prompting) should be in English.
          type: string
        response_format:
          description: >
            The format of the output, in one of these options: `json`, `text`, `srt`, `verbose_json`, or
            `vtt`.
          type: string
          enum:
            - json
            - text
            - srt
            - verbose_json
            - vtt
          default: json
        temperature:
          description: >
            The sampling temperature, between 0 and 1. Higher values like 0.8 will make the output more
            random, while lower values like 0.2 will make it more focused and deterministic. If set to 0, the
            model will use [log probability](https://en.wikipedia.org/wiki/Log_probability) to automatically
            increase the temperature until certain thresholds are hit.
          type: number
          default: 0
      required:
        - file
        - model
    CreateTranslationResponseJson:
      type: object
      properties:
        text:
          type: string
      required:
        - text
    CreateTranslationResponseVerboseJson:
      type: object
      properties:
        language:
          type: string
          description: The language of the output translation (always `english`).
        duration:
          type: number
          description: The duration of the input audio.
        text:
          type: string
          description: The translated text.
        segments:
          type: array
          description: Segments of the translated text and their corresponding details.
          items:
            $ref: '#/components/schemas/TranscriptionSegment'
      required:
        - language
        - duration
        - text
    CreateUploadRequest:
      type: object
      additionalProperties: false
      properties:
        filename:
          description: |
            The name of the file to upload.
          type: string
        purpose:
          description: |
            The intended purpose of the uploaded file.

            See the [documentation on File purposes](/docs/api-reference/files/create#files-create-purpose).
          type: string
          enum:
            - assistants
            - batch
            - fine-tune
            - vision
        bytes:
          description: |
            The number of bytes in the file you are uploading.
          type: integer
        mime_type:
          description: >
            The MIME type of the file.


            This must fall within the supported MIME types for your file purpose. See the supported MIME types
            for assistants and vision.
          type: string
      required:
        - filename
        - purpose
        - bytes
        - mime_type
    CreateVectorStoreFileBatchRequest:
      type: object
      additionalProperties: false
      properties:
        file_ids:
          description: >-
            A list of [File](/docs/api-reference/files) IDs that the vector store should use. Useful for tools
            like `file_search` that can access files.
          type: array
          minItems: 1
          maxItems: 500
          items:
            type: string
        chunking_strategy:
          $ref: '#/components/schemas/ChunkingStrategyRequestParam'
        attributes:
          $ref: '#/components/schemas/VectorStoreFileAttributes'
      required:
        - file_ids
    CreateVectorStoreFileRequest:
      type: object
      additionalProperties: false
      properties:
        file_id:
          description: >-
            A [File](/docs/api-reference/files) ID that the vector store should use. Useful for tools like
            `file_search` that can access files.
          type: string
        chunking_strategy:
          $ref: '#/components/schemas/ChunkingStrategyRequestParam'
        attributes:
          $ref: '#/components/schemas/VectorStoreFileAttributes'
      required:
        - file_id
    CreateVectorStoreRequest:
      type: object
      additionalProperties: false
      properties:
        file_ids:
          description: >-
            A list of [File](/docs/api-reference/files) IDs that the vector store should use. Useful for tools
            like `file_search` that can access files.
          type: array
          maxItems: 500
          items:
            type: string
        name:
          description: The name of the vector store.
          type: string
        expires_after:
          $ref: '#/components/schemas/VectorStoreExpirationAfter'
        chunking_strategy:
          type: object
          description: >-
            The chunking strategy used to chunk the file(s). If not set, will use the `auto` strategy. Only
            applicable if `file_ids` is non-empty.
          oneOf:
            - $ref: '#/components/schemas/AutoChunkingStrategyRequestParam'
            - $ref: '#/components/schemas/StaticChunkingStrategyRequestParam'
        metadata:
          $ref: '#/components/schemas/Metadata'
    DeleteAssistantResponse:
      type: object
      properties:
        id:
          type: string
        deleted:
          type: boolean
        object:
          type: string
          enum:
            - assistant.deleted
          x-stainless-const: true
      required:
        - id
        - object
        - deleted
    DeleteCertificateResponse:
      type: object
      properties:
        object:
          type: string
          description: The object type, must be `certificate.deleted`.
          enum:
            - certificate.deleted
          x-stainless-const: true
        id:
          type: string
          description: The ID of the certificate that was deleted.
      required:
        - object
        - id
    DeleteFileResponse:
      type: object
      properties:
        id:
          type: string
        object:
          type: string
          enum:
            - file
          x-stainless-const: true
        deleted:
          type: boolean
      required:
        - id
        - object
        - deleted
    DeleteFineTuningCheckpointPermissionResponse:
      type: object
      properties:
        id:
          type: string
          description: The ID of the fine-tuned model checkpoint permission that was deleted.
        object:
          type: string
          description: The object type, which is always "checkpoint.permission".
          enum:
            - checkpoint.permission
          x-stainless-const: true
        deleted:
          type: boolean
          description: Whether the fine-tuned model checkpoint permission was successfully deleted.
      required:
        - id
        - object
        - deleted
    DeleteMessageResponse:
      type: object
      properties:
        id:
          type: string
        deleted:
          type: boolean
        object:
          type: string
          enum:
            - thread.message.deleted
          x-stainless-const: true
      required:
        - id
        - object
        - deleted
    DeleteModelResponse:
      type: object
      properties:
        id:
          type: string
        deleted:
          type: boolean
        object:
          type: string
      required:
        - id
        - object
        - deleted
    DeleteThreadResponse:
      type: object
      properties:
        id:
          type: string
        deleted:
          type: boolean
        object:
          type: string
          enum:
            - thread.deleted
          x-stainless-const: true
      required:
        - id
        - object
        - deleted
    DeleteVectorStoreFileResponse:
      type: object
      properties:
        id:
          type: string
        deleted:
          type: boolean
        object:
          type: string
          enum:
            - vector_store.file.deleted
          x-stainless-const: true
      required:
        - id
        - object
        - deleted
    DeleteVectorStoreResponse:
      type: object
      properties:
        id:
          type: string
        deleted:
          type: boolean
        object:
          type: string
          enum:
            - vector_store.deleted
          x-stainless-const: true
      required:
        - id
        - object
        - deleted
    DoneEvent:
      type: object
      properties:
        event:
          type: string
          enum:
            - done
          x-stainless-const: true
        data:
          type: string
          enum:
            - '[DONE]'
          x-stainless-const: true
      required:
        - event
        - data
      description: Occurs when a stream ends.
      x-oaiMeta:
        dataDescription: '`data` is `[DONE]`'
    DoubleClick:
      type: object
      title: DoubleClick
      description: |
        A double click action.
      properties:
        type:
          type: string
          enum:
            - double_click
          default: double_click
          description: |
            Specifies the event type. For a double click action, this property is 
            always set to `double_click`.
          x-stainless-const: true
        x:
          type: integer
          description: |
            The x-coordinate where the double click occurred.
        'y':
          type: integer
          description: |
            The y-coordinate where the double click occurred.
      required:
        - type
        - x
        - 'y'
    Drag:
      type: object
      title: Drag
      description: |
        A drag action.
      properties:
        type:
          type: string
          enum:
            - drag
          default: drag
          description: |
            Specifies the event type. For a drag action, this property is 
            always set to `drag`.
          x-stainless-const: true
        path:
          type: array
          description: >
            An array of coordinates representing the path of the drag action. Coordinates will appear as an
            array

            of objects, eg

            ```

            [
              { x: 100, y: 200 },
              { x: 200, y: 300 }
            ]

            ```
          items:
            title: Drag path coordinates
            description: |
              A series of x/y coordinate pairs in the drag path.
            $ref: '#/components/schemas/Coordinate'
      required:
        - type
        - path
    EasyInputMessage:
      type: object
      title: Input message
      description: |
        A message input to the model with a role indicating instruction following
        hierarchy. Instructions given with the `developer` or `system` role take
        precedence over instructions given with the `user` role. Messages with the
        `assistant` role are presumed to have been generated by the model in previous
        interactions.
      properties:
        role:
          type: string
          description: |
            The role of the message input. One of `user`, `assistant`, `system`, or
            `developer`.
          enum:
            - user
            - assistant
            - system
            - developer
        content:
          description: |
            Text, image, or audio input to the model, used to generate a response.
            Can also contain previous assistant responses.
          oneOf:
            - type: string
              title: Text input
              description: |
                A text input to the model.
            - $ref: '#/components/schemas/InputMessageContentList'
        type:
          type: string
          description: |
            The type of the message input. Always `message`.
          enum:
            - message
          x-stainless-const: true
      required:
        - role
        - content
    Embedding:
      type: object
      description: |
        Represents an embedding vector returned by embedding endpoint.
      properties:
        index:
          type: integer
          description: The index of the embedding in the list of embeddings.
        embedding:
          type: array
          description: >
            The embedding vector, which is a list of floats. The length of vector depends on the model as
            listed in the [embedding guide](/docs/guides/embeddings).
          items:
            type: number
            format: float
        object:
          type: string
          description: The object type, which is always "embedding".
          enum:
            - embedding
          x-stainless-const: true
      required:
        - index
        - object
        - embedding
      x-oaiMeta:
        name: The embedding object
        example: |
          {
            "object": "embedding",
            "embedding": [
              0.0023064255,
              -0.009327292,
              .... (1536 floats total for ada-002)
              -0.0028842222,
            ],
            "index": 0
          }
    Error:
      type: object
      properties:
        code:
          type: string
          nullable: true
        message:
          type: string
          nullable: false
        param:
          type: string
          nullable: true
        type:
          type: string
          nullable: false
      required:
        - type
        - message
        - param
        - code
    ErrorEvent:
      type: object
      properties:
        event:
          type: string
          enum:
            - error
          x-stainless-const: true
        data:
          $ref: '#/components/schemas/Error'
      required:
        - event
        - data
      description: >-
        Occurs when an [error](/docs/guides/error-codes#api-errors) occurs. This can happen due to an internal
        server error or a timeout.
      x-oaiMeta:
        dataDescription: '`data` is an [error](/docs/guides/error-codes#api-errors)'
    ErrorResponse:
      type: object
      properties:
        error:
          $ref: '#/components/schemas/Error'
      required:
        - error
    Eval:
      type: object
      title: Eval
      description: |
        An Eval object with a data source config and testing criteria.
        An Eval represents a task to be done for your LLM integration.
        Like:
         - Improve the quality of my chatbot
         - See how well my chatbot handles customer support
         - Check if o4-mini is better at my usecase than gpt-4o
      properties:
        object:
          type: string
          enum:
            - eval
          default: eval
          description: The object type.
          x-stainless-const: true
        id:
          type: string
          description: Unique identifier for the evaluation.
        name:
          type: string
          description: The name of the evaluation.
          example: Chatbot effectiveness Evaluation
        data_source_config:
          type: object
          description: Configuration of data sources used in runs of the evaluation.
          oneOf:
            - $ref: '#/components/schemas/EvalCustomDataSourceConfig'
            - $ref: '#/components/schemas/EvalLogsDataSourceConfig'
            - $ref: '#/components/schemas/EvalStoredCompletionsDataSourceConfig'
        testing_criteria:
          default: eval
          description: A list of testing criteria.
          type: array
          items:
            oneOf:
              - $ref: '#/components/schemas/EvalGraderLabelModel'
              - $ref: '#/components/schemas/EvalGraderStringCheck'
              - $ref: '#/components/schemas/EvalGraderTextSimilarity'
              - $ref: '#/components/schemas/EvalGraderPython'
              - $ref: '#/components/schemas/EvalGraderScoreModel'
        created_at:
          type: integer
          description: The Unix timestamp (in seconds) for when the eval was created.
        metadata:
          $ref: '#/components/schemas/Metadata'
      required:
        - id
        - data_source_config
        - object
        - testing_criteria
        - name
        - created_at
        - metadata
      x-oaiMeta:
        name: The eval object
        group: evals
        example: |
          {
            "object": "eval",
            "id": "eval_67abd54d9b0081909a86353f6fb9317a",
            "data_source_config": {
              "type": "custom",
              "item_schema": {
                "type": "object",
                "properties": {
                  "label": {"type": "string"},
                },
                "required": ["label"]
              },
              "include_sample_schema": true
            },
            "testing_criteria": [
              {
                "name": "My string check grader",
                "type": "string_check",
                "input": "{{sample.output_text}}",
                "reference": "{{item.label}}",
                "operation": "eq",
              }
            ],
            "name": "External Data Eval",
            "created_at": 1739314509,
            "metadata": {
              "test": "synthetics",
            }
          }
    EvalApiError:
      type: object
      title: EvalApiError
      description: |
        An object representing an error response from the Eval API.
      properties:
        code:
          type: string
          description: The error code.
        message:
          type: string
          description: The error message.
      required:
        - code
        - message
      x-oaiMeta:
        name: The API error object
        group: evals
        example: |
          {
            "code": "internal_error",
            "message": "The eval run failed due to an internal error."
          }
    EvalCustomDataSourceConfig:
      type: object
      title: CustomDataSourceConfig
      description: |
        A CustomDataSourceConfig which specifies the schema of your `item` and optionally `sample` namespaces.
        The response schema defines the shape of the data that will be:
        - Used to define your testing criteria and
        - What data is required when creating a run
      properties:
        type:
          type: string
          enum:
            - custom
          default: custom
          description: The type of data source. Always `custom`.
          x-stainless-const: true
        schema:
          type: object
          description: |
            The json schema for the run data source items.
            Learn how to build JSON schemas [here](https://json-schema.org/).
          additionalProperties: true
          example: |
            {
              "type": "object",
              "properties": {
                "item": {
                  "type": "object",
                  "properties": {
                    "label": {"type": "string"},
                  },
                  "required": ["label"]
                }
              },
              "required": ["item"]
            }
      required:
        - type
        - schema
      x-oaiMeta:
        name: The eval custom data source config object
        group: evals
        example: |
          {
            "type": "custom",
            "schema": {
              "type": "object",
              "properties": {
                "item": {
                  "type": "object",
                  "properties": {
                    "label": {"type": "string"},
                  },
                  "required": ["label"]
                }
              },
              "required": ["item"]
            }
          }
    EvalGraderLabelModel:
      type: object
      title: LabelModelGrader
      allOf:
        - $ref: '#/components/schemas/GraderLabelModel'
    EvalGraderPython:
      type: object
      title: PythonGrader
      allOf:
        - $ref: '#/components/schemas/GraderPython'
        - type: object
          properties:
            pass_threshold:
              type: number
              description: The threshold for the score.
          x-oaiMeta:
            name: Eval Python Grader
            group: graders
            example: |
              {
                "type": "python",
                "name": "Example python grader",
                "image_tag": "2025-05-08",
                "source": """
              def grade(sample: dict, item: dict) -> float:
                  \"""
                  Returns 1.0 if `output_text` equals `label`, otherwise 0.0.
                  \"""
                  output = sample.get("output_text")
                  label = item.get("label")
                  return 1.0 if output == label else 0.0
              """,
                "pass_threshold": 0.8
              }
    EvalGraderScoreModel:
      type: object
      title: ScoreModelGrader
      allOf:
        - $ref: '#/components/schemas/GraderScoreModel'
        - type: object
          properties:
            pass_threshold:
              type: number
              description: The threshold for the score.
    EvalGraderStringCheck:
      type: object
      title: StringCheckGrader
      allOf:
        - $ref: '#/components/schemas/GraderStringCheck'
    EvalGraderTextSimilarity:
      type: object
      title: TextSimilarityGrader
      allOf:
        - $ref: '#/components/schemas/GraderTextSimilarity'
        - type: object
          properties:
            pass_threshold:
              type: number
              description: The threshold for the score.
          required:
            - pass_threshold
          x-oaiMeta:
            name: Text Similarity Grader
            group: graders
            example: |
              {
                "type": "text_similarity",
                "name": "Example text similarity grader",
                "input": "{{sample.output_text}}",
                "reference": "{{item.label}}",
                "pass_threshold": 0.8,
                "evaluation_metric": "fuzzy_match"
              }
    EvalItem:
      type: object
      title: Eval message object
      description: |
        A message input to the model with a role indicating instruction following
        hierarchy. Instructions given with the `developer` or `system` role take
        precedence over instructions given with the `user` role. Messages with the
        `assistant` role are presumed to have been generated by the model in previous
        interactions.
      properties:
        role:
          type: string
          description: |
            The role of the message input. One of `user`, `assistant`, `system`, or
            `developer`.
          enum:
            - user
            - assistant
            - system
            - developer
        content:
          description: |
            Text inputs to the model - can contain template strings.
          oneOf:
            - type: string
              title: Text input
              description: |
                A text input to the model.
            - $ref: '#/components/schemas/InputTextContent'
            - type: object
              title: Output text
              description: |
                A text output from the model.
              properties:
                type:
                  type: string
                  description: |
                    The type of the output text. Always `output_text`.
                  enum:
                    - output_text
                  x-stainless-const: true
                text:
                  type: string
                  description: |
                    The text output from the model.
              required:
                - type
                - text
        type:
          type: string
          description: |
            The type of the message input. Always `message`.
          enum:
            - message
          x-stainless-const: true
      required:
        - role
        - content
    EvalJsonlFileContentSource:
      type: object
      title: EvalJsonlFileContentSource
      properties:
        type:
          type: string
          enum:
            - file_content
          default: file_content
          description: The type of jsonl source. Always `file_content`.
          x-stainless-const: true
        content:
          type: array
          items:
            type: object
            properties:
              item:
                type: object
                additionalProperties: true
              sample:
                type: object
                additionalProperties: true
            required:
              - item
          description: The content of the jsonl file.
      required:
        - type
        - content
    EvalJsonlFileIdSource:
      type: object
      title: EvalJsonlFileIdSource
      properties:
        type:
          type: string
          enum:
            - file_id
          default: file_id
          description: The type of jsonl source. Always `file_id`.
          x-stainless-const: true
        id:
          type: string
          description: The identifier of the file.
      required:
        - type
        - id
    EvalList:
      type: object
      title: EvalList
      description: |
        An object representing a list of evals.
      properties:
        object:
          type: string
          enum:
            - list
          default: list
          description: |
            The type of this object. It is always set to "list".
          x-stainless-const: true
        data:
          type: array
          description: |
            An array of eval objects.
          items:
            $ref: '#/components/schemas/Eval'
        first_id:
          type: string
          description: The identifier of the first eval in the data array.
        last_id:
          type: string
          description: The identifier of the last eval in the data array.
        has_more:
          type: boolean
          description: Indicates whether there are more evals available.
      required:
        - object
        - data
        - first_id
        - last_id
        - has_more
      x-oaiMeta:
        name: The eval list object
        group: evals
        example: |
          {
            "object": "list",
            "data": [
              {
                "object": "eval",
                "id": "eval_67abd54d9b0081909a86353f6fb9317a",
                "data_source_config": {
                  "type": "custom",
                  "schema": {
                    "type": "object",
                    "properties": {
                      "item": {
                        "type": "object",
                        "properties": {
                          "input": {
                            "type": "string"
                          },
                          "ground_truth": {
                            "type": "string"
                          }
                        },
                        "required": [
                          "input",
                          "ground_truth"
                        ]
                      }
                    },
                    "required": [
                      "item"
                    ]
                  }
                },
                "testing_criteria": [
                  {
                    "name": "String check",
                    "id": "String check-2eaf2d8d-d649-4335-8148-9535a7ca73c2",
                    "type": "string_check",
                    "input": "{{item.input}}",
                    "reference": "{{item.ground_truth}}",
                    "operation": "eq"
                  }
                ],
                "name": "External Data Eval",
                "created_at": 1739314509,
                "metadata": {},
              }
            ],
            "first_id": "eval_67abd54d9b0081909a86353f6fb9317a",
            "last_id": "eval_67abd54d9b0081909a86353f6fb9317a",
            "has_more": true
          }
    EvalLogsDataSourceConfig:
      type: object
      title: LogsDataSourceConfig
      description: >
        A LogsDataSourceConfig which specifies the metadata property of your logs query.

        This is usually metadata like `usecase=chatbot` or `prompt-version=v2`, etc.

        The schema returned by this data source config is used to defined what variables are available in your
        evals.

        `item` and `sample` are both defined when using this data source config.
      properties:
        type:
          type: string
          enum:
            - logs
          default: logs
          description: The type of data source. Always `logs`.
          x-stainless-const: true
        metadata:
          $ref: '#/components/schemas/Metadata'
        schema:
          type: object
          description: |
            The json schema for the run data source items.
            Learn how to build JSON schemas [here](https://json-schema.org/).
          additionalProperties: true
      required:
        - type
        - schema
      x-oaiMeta:
        name: The logs data source object for evals
        group: evals
        example: |
          {
            "type": "logs",
            "metadata": {
              "language": "english"
            },
            "schema": {
              "type": "object",
              "properties": {
                "item": {
                  "type": "object"
                },
                "sample": {
                  "type": "object"
                }
              },
              "required": [
                "item",
                "sample"
              }
          }
    EvalResponsesSource:
      type: object
      title: EvalResponsesSource
      description: |
        A EvalResponsesSource object describing a run data source configuration.
      properties:
        type:
          type: string
          enum:
            - responses
          description: The type of run data source. Always `responses`.
        metadata:
          type: object
          nullable: true
          description: Metadata filter for the responses. This is a query parameter used to select responses.
        model:
          type: string
          nullable: true
          description: The name of the model to find responses for. This is a query parameter used to select responses.
        instructions_search:
          type: string
          nullable: true
          description: >-
            Optional string to search the 'instructions' field. This is a query parameter used to select
            responses.
        created_after:
          type: integer
          minimum: 0
          nullable: true
          description: >-
            Only include items created after this timestamp (inclusive). This is a query parameter used to
            select responses.
        created_before:
          type: integer
          minimum: 0
          nullable: true
          description: >-
            Only include items created before this timestamp (inclusive). This is a query parameter used to
            select responses.
        reasoning_effort:
          $ref: '#/components/schemas/ReasoningEffort'
          nullable: true
          description: Optional reasoning effort parameter. This is a query parameter used to select responses.
        temperature:
          type: number
          nullable: true
          description: Sampling temperature. This is a query parameter used to select responses.
        top_p:
          type: number
          nullable: true
          description: Nucleus sampling parameter. This is a query parameter used to select responses.
        users:
          type: array
          items:
            type: string
          nullable: true
          description: List of user identifiers. This is a query parameter used to select responses.
        tools:
          type: array
          items:
            type: string
          nullable: true
          description: List of tool names. This is a query parameter used to select responses.
      required:
        - type
      x-oaiMeta:
        name: The run data source object used to configure an individual run
        group: eval runs
        example: |
          {
            "type": "responses",
            "model": "gpt-4o-mini-2024-07-18",
            "temperature": 0.7,
            "top_p": 1.0,
            "users": ["user1", "user2"],
            "tools": ["tool1", "tool2"],
            "instructions_search": "You are a coding assistant"
          }
    EvalRun:
      type: object
      title: EvalRun
      description: |
        A schema representing an evaluation run.
      properties:
        object:
          type: string
          enum:
            - eval.run
          default: eval.run
          description: The type of the object. Always "eval.run".
          x-stainless-const: true
        id:
          type: string
          description: Unique identifier for the evaluation run.
        eval_id:
          type: string
          description: The identifier of the associated evaluation.
        status:
          type: string
          description: The status of the evaluation run.
        model:
          type: string
          description: The model that is evaluated, if applicable.
        name:
          type: string
          description: The name of the evaluation run.
        created_at:
          type: integer
          description: Unix timestamp (in seconds) when the evaluation run was created.
        report_url:
          type: string
          description: The URL to the rendered evaluation run report on the UI dashboard.
        result_counts:
          type: object
          description: Counters summarizing the outcomes of the evaluation run.
          properties:
            total:
              type: integer
              description: Total number of executed output items.
            errored:
              type: integer
              description: Number of output items that resulted in an error.
            failed:
              type: integer
              description: Number of output items that failed to pass the evaluation.
            passed:
              type: integer
              description: Number of output items that passed the evaluation.
          required:
            - total
            - errored
            - failed
            - passed
        per_model_usage:
          type: array
          description: Usage statistics for each model during the evaluation run.
          items:
            type: object
            properties:
              model_name:
                type: string
                description: The name of the model.
              invocation_count:
                type: integer
                description: The number of invocations.
              prompt_tokens:
                type: integer
                description: The number of prompt tokens used.
              completion_tokens:
                type: integer
                description: The number of completion tokens generated.
              total_tokens:
                type: integer
                description: The total number of tokens used.
              cached_tokens:
                type: integer
                description: The number of tokens retrieved from cache.
            required:
              - model_name
              - invocation_count
              - prompt_tokens
              - completion_tokens
              - total_tokens
              - cached_tokens
        per_testing_criteria_results:
          type: array
          description: Results per testing criteria applied during the evaluation run.
          items:
            type: object
            properties:
              testing_criteria:
                type: string
                description: A description of the testing criteria.
              passed:
                type: integer
                description: Number of tests passed for this criteria.
              failed:
                type: integer
                description: Number of tests failed for this criteria.
            required:
              - testing_criteria
              - passed
              - failed
        data_source:
          type: object
          description: Information about the run's data source.
          oneOf:
            - $ref: '#/components/schemas/CreateEvalJsonlRunDataSource'
            - $ref: '#/components/schemas/CreateEvalCompletionsRunDataSource'
            - $ref: '#/components/schemas/CreateEvalResponsesRunDataSource'
        metadata:
          $ref: '#/components/schemas/Metadata'
        error:
          $ref: '#/components/schemas/EvalApiError'
      required:
        - object
        - id
        - eval_id
        - status
        - model
        - name
        - created_at
        - report_url
        - result_counts
        - per_model_usage
        - per_testing_criteria_results
        - data_source
        - metadata
        - error
      x-oaiMeta:
        name: The eval run object
        group: evals
        example: |
          {
            "object": "eval.run",
            "id": "evalrun_67e57965b480819094274e3a32235e4c",
            "eval_id": "eval_67e579652b548190aaa83ada4b125f47",
            "report_url": "https://platform.openai.com/evaluations/eval_67e579652b548190aaa83ada4b125f47?run_id=evalrun_67e57965b480819094274e3a32235e4c",
            "status": "queued",
            "model": "gpt-4o-mini",
            "name": "gpt-4o-mini",
            "created_at": 1743092069,
            "result_counts": {
              "total": 0,
              "errored": 0,
              "failed": 0,
              "passed": 0
            },
            "per_model_usage": null,
            "per_testing_criteria_results": null,
            "data_source": {
              "type": "completions",
              "source": {
                "type": "file_content",
                "content": [
                  {
                    "item": {
                      "input": "Tech Company Launches Advanced Artificial Intelligence Platform",
                      "ground_truth": "Technology"
                    }
                  },
                  {
                    "item": {
                      "input": "Central Bank Increases Interest Rates Amid Inflation Concerns",
                      "ground_truth": "Markets"
                    }
                  },
                  {
                    "item": {
                      "input": "International Summit Addresses Climate Change Strategies",
                      "ground_truth": "World"
                    }
                  },
                  {
                    "item": {
                      "input": "Major Retailer Reports Record-Breaking Holiday Sales",
                      "ground_truth": "Business"
                    }
                  },
                  {
                    "item": {
                      "input": "National Team Qualifies for World Championship Finals",
                      "ground_truth": "Sports"
                    }
                  },
                  {
                    "item": {
                      "input": "Stock Markets Rally After Positive Economic Data Released",
                      "ground_truth": "Markets"
                    }
                  },
                  {
                    "item": {
                      "input": "Global Manufacturer Announces Merger with Competitor",
                      "ground_truth": "Business"
                    }
                  },
                  {
                    "item": {
                      "input": "Breakthrough in Renewable Energy Technology Unveiled",
                      "ground_truth": "Technology"
                    }
                  },
                  {
                    "item": {
                      "input": "World Leaders Sign Historic Climate Agreement",
                      "ground_truth": "World"
                    }
                  },
                  {
                    "item": {
                      "input": "Professional Athlete Sets New Record in Championship Event",
                      "ground_truth": "Sports"
                    }
                  },
                  {
                    "item": {
                      "input": "Financial Institutions Adapt to New Regulatory Requirements",
                      "ground_truth": "Business"
                    }
                  },
                  {
                    "item": {
                      "input": "Tech Conference Showcases Advances in Artificial Intelligence",
                      "ground_truth": "Technology"
                    }
                  },
                  {
                    "item": {
                      "input": "Global Markets Respond to Oil Price Fluctuations",
                      "ground_truth": "Markets"
                    }
                  },
                  {
                    "item": {
                      "input": "International Cooperation Strengthened Through New Treaty",
                      "ground_truth": "World"
                    }
                  },
                  {
                    "item": {
                      "input": "Sports League Announces Revised Schedule for Upcoming Season",
                      "ground_truth": "Sports"
                    }
                  }
                ]
              },
              "input_messages": {
                "type": "template",
                "template": [
                  {
                    "type": "message",
                    "role": "developer",
                    "content": {
                      "type": "input_text",
                      "text": "Categorize a given news headline into one of the following topics: Technology, Markets, World, Business, or Sports.\n\n# Steps\n\n1. Analyze the content of the news headline to understand its primary focus.\n2. Extract the subject matter, identifying any key indicators or keywords.\n3. Use the identified indicators to determine the most suitable category out of the five options: Technology, Markets, World, Business, or Sports.\n4. Ensure only one category is selected per headline.\n\n# Output Format\n\nRespond with the chosen category as a single word. For instance: \"Technology\", \"Markets\", \"World\", \"Business\", or \"Sports\".\n\n# Examples\n\n**Input**: \"Apple Unveils New iPhone Model, Featuring Advanced AI Features\"  \n**Output**: \"Technology\"\n\n**Input**: \"Global Stocks Mixed as Investors Await Central Bank Decisions\"  \n**Output**: \"Markets\"\n\n**Input**: \"War in Ukraine: Latest Updates on Negotiation Status\"  \n**Output**: \"World\"\n\n**Input**: \"Microsoft in Talks to Acquire Gaming Company for $2 Billion\"  \n**Output**: \"Business\"\n\n**Input**: \"Manchester United Secures Win in Premier League Football Match\"  \n**Output**: \"Sports\" \n\n# Notes\n\n- If the headline appears to fit into more than one category, choose the most dominant theme.\n- Keywords or phrases such as \"stocks\", \"company acquisition\", \"match\", or technological brands can be good indicators for classification.\n"
                    }
                  },
                  {
                    "type": "message",
                    "role": "user",
                    "content": {
                      "type": "input_text",
                      "text": "{{item.input}}"
                    }
                  }
                ]
              },
              "model": "gpt-4o-mini",
              "sampling_params": {
                "seed": 42,
                "temperature": 1.0,
                "top_p": 1.0,
                "max_completions_tokens": 2048
              }
            },
            "error": null,
            "metadata": {}
          }
    EvalRunList:
      type: object
      title: EvalRunList
      description: |
        An object representing a list of runs for an evaluation.
      properties:
        object:
          type: string
          enum:
            - list
          default: list
          description: |
            The type of this object. It is always set to "list".
          x-stainless-const: true
        data:
          type: array
          description: |
            An array of eval run objects.
          items:
            $ref: '#/components/schemas/EvalRun'
        first_id:
          type: string
          description: The identifier of the first eval run in the data array.
        last_id:
          type: string
          description: The identifier of the last eval run in the data array.
        has_more:
          type: boolean
          description: Indicates whether there are more evals available.
      required:
        - object
        - data
        - first_id
        - last_id
        - has_more
      x-oaiMeta:
        name: The eval run list object
        group: evals
        example: |
          {
            "object": "list",
            "data": [
              {
                "object": "eval.run",
                "id": "evalrun_67b7fbdad46c819092f6fe7a14189620",
                "eval_id": "eval_67b7fa9a81a88190ab4aa417e397ea21",
                "report_url": "https://platform.openai.com/evaluations/eval_67b7fa9a81a88190ab4aa417e397ea21?run_id=evalrun_67b7fbdad46c819092f6fe7a14189620",
                "status": "completed",
                "model": "o3-mini",
                "name": "Academic Assistant",
                "created_at": 1740110812,
                "result_counts": {
                  "total": 171,
                  "errored": 0,
                  "failed": 80,
                  "passed": 91
                },
                "per_model_usage": null,
                "per_testing_criteria_results": [
                  {
                    "testing_criteria": "String check grader",
                    "passed": 91,
                    "failed": 80
                  }
                ],
                "run_data_source": {
                  "type": "completions",
                  "template_messages": [
                    {
                      "type": "message",
                      "role": "system",
                      "content": {
                        "type": "input_text",
                        "text": "You are a helpful assistant."
                      }
                    },
                    {
                      "type": "message",
                      "role": "user",
                      "content": {
                        "type": "input_text",
                        "text": "Hello, can you help me with my homework?"
                      }
                    }
                  ],
                  "datasource_reference": null,
                  "model": "o3-mini",
                  "max_completion_tokens": null,
                  "seed": null,
                  "temperature": null,
                  "top_p": null
                },
                "error": null,
                "metadata": {"test": "synthetics"}
              }
            ],
            "first_id": "evalrun_67abd54d60ec8190832b46859da808f7",
            "last_id": "evalrun_67abd54d60ec8190832b46859da808f7",
            "has_more": false
          }
    EvalRunOutputItem:
      type: object
      title: EvalRunOutputItem
      description: |
        A schema representing an evaluation run output item.
      properties:
        object:
          type: string
          enum:
            - eval.run.output_item
          default: eval.run.output_item
          description: The type of the object. Always "eval.run.output_item".
          x-stainless-const: true
        id:
          type: string
          description: Unique identifier for the evaluation run output item.
        run_id:
          type: string
          description: The identifier of the evaluation run associated with this output item.
        eval_id:
          type: string
          description: The identifier of the evaluation group.
        created_at:
          type: integer
          description: Unix timestamp (in seconds) when the evaluation run was created.
        status:
          type: string
          description: The status of the evaluation run.
        datasource_item_id:
          type: integer
          description: The identifier for the data source item.
        datasource_item:
          type: object
          description: Details of the input data source item.
          additionalProperties: true
        results:
          type: array
          description: A list of results from the evaluation run.
          items:
            type: object
            description: A result object.
            additionalProperties: true
        sample:
          type: object
          description: A sample containing the input and output of the evaluation run.
          properties:
            input:
              type: array
              description: An array of input messages.
              items:
                type: object
                description: An input message.
                properties:
                  role:
                    type: string
                    description: The role of the message sender (e.g., system, user, developer).
                  content:
                    type: string
                    description: The content of the message.
                required:
                  - role
                  - content
            output:
              type: array
              description: An array of output messages.
              items:
                type: object
                properties:
                  role:
                    type: string
                    description: The role of the message (e.g. "system", "assistant", "user").
                  content:
                    type: string
                    description: The content of the message.
            finish_reason:
              type: string
              description: The reason why the sample generation was finished.
            model:
              type: string
              description: The model used for generating the sample.
            usage:
              type: object
              description: Token usage details for the sample.
              properties:
                total_tokens:
                  type: integer
                  description: The total number of tokens used.
                completion_tokens:
                  type: integer
                  description: The number of completion tokens generated.
                prompt_tokens:
                  type: integer
                  description: The number of prompt tokens used.
                cached_tokens:
                  type: integer
                  description: The number of tokens retrieved from cache.
              required:
                - total_tokens
                - completion_tokens
                - prompt_tokens
                - cached_tokens
            error:
              $ref: '#/components/schemas/EvalApiError'
            temperature:
              type: number
              description: The sampling temperature used.
            max_completion_tokens:
              type: integer
              description: The maximum number of tokens allowed for completion.
            top_p:
              type: number
              description: The top_p value used for sampling.
            seed:
              type: integer
              description: The seed used for generating the sample.
          required:
            - input
            - output
            - finish_reason
            - model
            - usage
            - error
            - temperature
            - max_completion_tokens
            - top_p
            - seed
      required:
        - object
        - id
        - run_id
        - eval_id
        - created_at
        - status
        - datasource_item_id
        - datasource_item
        - results
        - sample
      x-oaiMeta:
        name: The eval run output item object
        group: evals
        example: |
          {
            "object": "eval.run.output_item",
            "id": "outputitem_67abd55eb6548190bb580745d5644a33",
            "run_id": "evalrun_67abd54d60ec8190832b46859da808f7",
            "eval_id": "eval_67abd54d9b0081909a86353f6fb9317a",
            "created_at": 1739314509,
            "status": "pass",
            "datasource_item_id": 137,
            "datasource_item": {
                "teacher": "To grade essays, I only check for style, content, and grammar.",
                "student": "I am a student who is trying to write the best essay."
            },
            "results": [
              {
                "name": "String Check Grader",
                "type": "string-check-grader",
                "score": 1.0,
                "passed": true,
              }
            ],
            "sample": {
              "input": [
                {
                  "role": "system",
                  "content": "You are an evaluator bot..."
                },
                {
                  "role": "user",
                  "content": "You are assessing..."
                }
              ],
              "output": [
                {
                  "role": "assistant",
                  "content": "The rubric is not clear nor concise."
                }
              ],
              "finish_reason": "stop",
              "model": "gpt-4o-2024-08-06",
              "usage": {
                "total_tokens": 521,
                "completion_tokens": 2,
                "prompt_tokens": 519,
                "cached_tokens": 0
              },
              "error": null,
              "temperature": 1.0,
              "max_completion_tokens": 2048,
              "top_p": 1.0,
              "seed": 42
            }
          }
    EvalRunOutputItemList:
      type: object
      title: EvalRunOutputItemList
      description: |
        An object representing a list of output items for an evaluation run.
      properties:
        object:
          type: string
          enum:
            - list
          default: list
          description: |
            The type of this object. It is always set to "list".
          x-stainless-const: true
        data:
          type: array
          description: |
            An array of eval run output item objects.
          items:
            $ref: '#/components/schemas/EvalRunOutputItem'
        first_id:
          type: string
          description: The identifier of the first eval run output item in the data array.
        last_id:
          type: string
          description: The identifier of the last eval run output item in the data array.
        has_more:
          type: boolean
          description: Indicates whether there are more eval run output items available.
      required:
        - object
        - data
        - first_id
        - last_id
        - has_more
      x-oaiMeta:
        name: The eval run output item list object
        group: evals
        example: |
          {
            "object": "list",
            "data": [
              {
                "object": "eval.run.output_item",
                "id": "outputitem_67abd55eb6548190bb580745d5644a33",
                "run_id": "evalrun_67abd54d60ec8190832b46859da808f7",
                "eval_id": "eval_67abd54d9b0081909a86353f6fb9317a",
                "created_at": 1739314509,
                "status": "pass",
                "datasource_item_id": 137,
                "datasource_item": {
                    "teacher": "To grade essays, I only check for style, content, and grammar.",
                    "student": "I am a student who is trying to write the best essay."
                },
                "results": [
                  {
                    "name": "String Check Grader",
                    "type": "string-check-grader",
                    "score": 1.0,
                    "passed": true,
                  }
                ],
                "sample": {
                  "input": [
                    {
                      "role": "system",
                      "content": "You are an evaluator bot..."
                    },
                    {
                      "role": "user",
                      "content": "You are assessing..."
                    }
                  ],
                  "output": [
                    {
                      "role": "assistant",
                      "content": "The rubric is not clear nor concise."
                    }
                  ],
                  "finish_reason": "stop",
                  "model": "gpt-4o-2024-08-06",
                  "usage": {
                    "total_tokens": 521,
                    "completion_tokens": 2,
                    "prompt_tokens": 519,
                    "cached_tokens": 0
                  },
                  "error": null,
                  "temperature": 1.0,
                  "max_completion_tokens": 2048,
                  "top_p": 1.0,
                  "seed": 42
                }
              },
            ],
            "first_id": "outputitem_67abd55eb6548190bb580745d5644a33",
            "last_id": "outputitem_67abd55eb6548190bb580745d5644a33",
            "has_more": false
          }
    EvalStoredCompletionsDataSourceConfig:
      type: object
      title: StoredCompletionsDataSourceConfig
      description: |
        Deprecated in favor of LogsDataSourceConfig.
      properties:
        type:
          type: string
          enum:
            - stored_completions
          default: stored_completions
          description: The type of data source. Always `stored_completions`.
          x-stainless-const: true
        metadata:
          $ref: '#/components/schemas/Metadata'
        schema:
          type: object
          description: |
            The json schema for the run data source items.
            Learn how to build JSON schemas [here](https://json-schema.org/).
          additionalProperties: true
      required:
        - type
        - schema
      deprecated: true
      x-oaiMeta:
        name: The stored completions data source object for evals
        group: evals
        example: |
          {
            "type": "stored_completions",
            "metadata": {
              "language": "english"
            },
            "schema": {
              "type": "object",
              "properties": {
                "item": {
                  "type": "object"
                },
                "sample": {
                  "type": "object"
                }
              },
              "required": [
                "item",
                "sample"
              }
          }
    EvalStoredCompletionsSource:
      type: object
      title: StoredCompletionsRunDataSource
      description: |
        A StoredCompletionsRunDataSource configuration describing a set of filters
      properties:
        type:
          type: string
          enum:
            - stored_completions
          default: stored_completions
          description: The type of source. Always `stored_completions`.
          x-stainless-const: true
        metadata:
          $ref: '#/components/schemas/Metadata'
        model:
          type: string
          nullable: true
          description: An optional model to filter by (e.g., 'gpt-4o').
        created_after:
          type: integer
          nullable: true
          description: An optional Unix timestamp to filter items created after this time.
        created_before:
          type: integer
          nullable: true
          description: An optional Unix timestamp to filter items created before this time.
        limit:
          type: integer
          nullable: true
          description: An optional maximum number of items to return.
      required:
        - type
      x-oaiMeta:
        name: The stored completions data source object used to configure an individual run
        group: eval runs
        example: |
          {
            "type": "stored_completions",
            "model": "gpt-4o",
            "created_after": 1668124800,
            "created_before": 1668124900,
            "limit": 100,
            "metadata": {}
          }
    FilePath:
      type: object
      title: File path
      description: |
        A path to a file.
      properties:
        type:
          type: string
          description: |
            The type of the file path. Always `file_path`.
          enum:
            - file_path
          x-stainless-const: true
        file_id:
          type: string
          description: |
            The ID of the file.
        index:
          type: integer
          description: |
            The index of the file in the list of files.
      required:
        - type
        - file_id
        - index
    FileSearchRanker:
      type: string
      description: The ranker to use for the file search. If not specified will use the `auto` ranker.
      enum:
        - auto
        - default_2024_08_21
    FileSearchRankingOptions:
      title: File search tool call ranking options
      type: object
      description: >
        The ranking options for the file search. If not specified, the file search tool will use the `auto`
        ranker and a score_threshold of 0.


        See the [file search tool
        documentation](/docs/assistants/tools/file-search#customizing-file-search-settings) for more
        information.
      properties:
        ranker:
          $ref: '#/components/schemas/FileSearchRanker'
        score_threshold:
          type: number
          description: >-
            The score threshold for the file search. All values must be a floating point number between 0 and
            1.
          minimum: 0
          maximum: 1
      required:
        - score_threshold
    FileSearchToolCall:
      type: object
      title: File search tool call
      description: |
        The results of a file search tool call. See the 
        [file search guide](/docs/guides/tools-file-search) for more information.
      properties:
        id:
          type: string
          description: |
            The unique ID of the file search tool call.
        type:
          type: string
          enum:
            - file_search_call
          description: |
            The type of the file search tool call. Always `file_search_call`.
          x-stainless-const: true
        status:
          type: string
          description: |
            The status of the file search tool call. One of `in_progress`, 
            `searching`, `incomplete` or `failed`,
          enum:
            - in_progress
            - searching
            - completed
            - incomplete
            - failed
        queries:
          type: array
          items:
            type: string
          description: |
            The queries used to search for files.
        results:
          type: array
          description: |
            The results of the file search tool call.
          items:
            type: object
            properties:
              file_id:
                type: string
                description: |
                  The unique ID of the file.
              text:
                type: string
                description: |
                  The text that was retrieved from the file.
              filename:
                type: string
                description: |
                  The name of the file.
              attributes:
                $ref: '#/components/schemas/VectorStoreFileAttributes'
              score:
                type: number
                format: float
                description: |
                  The relevance score of the file - a value between 0 and 1.
          nullable: true
      required:
        - id
        - type
        - status
        - queries
    FineTuneChatCompletionRequestAssistantMessage:
      allOf:
        - type: object
          title: Assistant message
          deprecated: false
          properties:
            weight:
              type: integer
              enum:
                - 0
                - 1
              description: Controls whether the assistant message is trained against (0 or 1)
        - $ref: '#/components/schemas/ChatCompletionRequestAssistantMessage'
      required:
        - role
    FineTuneChatRequestInput:
      type: object
      description: |
        The per-line training example of a fine-tuning input file for chat models using the supervised method.
        Input messages may contain text or image content only. Audio and file input messages
        are not currently supported for fine-tuning.
      properties:
        messages:
          type: array
          minItems: 1
          items:
            oneOf:
              - $ref: '#/components/schemas/ChatCompletionRequestSystemMessage'
              - $ref: '#/components/schemas/ChatCompletionRequestUserMessage'
              - $ref: '#/components/schemas/FineTuneChatCompletionRequestAssistantMessage'
              - $ref: '#/components/schemas/ChatCompletionRequestToolMessage'
              - $ref: '#/components/schemas/ChatCompletionRequestFunctionMessage'
        tools:
          type: array
          description: A list of tools the model may generate JSON inputs for.
          items:
            $ref: '#/components/schemas/ChatCompletionTool'
        parallel_tool_calls:
          $ref: '#/components/schemas/ParallelToolCalls'
        functions:
          deprecated: true
          description: A list of functions the model may generate JSON inputs for.
          type: array
          minItems: 1
          maxItems: 128
          items:
            $ref: '#/components/schemas/ChatCompletionFunctions'
      x-oaiMeta:
        name: Training format for chat models using the supervised method
        example: |
          {
            "messages": [
              { "role": "user", "content": "What is the weather in San Francisco?" },
              {
                "role": "assistant",
                "tool_calls": [
                  {
                    "id": "call_id",
                    "type": "function",
                    "function": {
                      "name": "get_current_weather",
                      "arguments": "{\"location\": \"San Francisco, USA\", \"format\": \"celsius\"}"
                    }
                  }
                ]
              }
            ],
            "parallel_tool_calls": false,
            "tools": [
              {
                "type": "function",
                "function": {
                  "name": "get_current_weather",
                  "description": "Get the current weather",
                  "parameters": {
                    "type": "object",
                    "properties": {
                      "location": {
                          "type": "string",
                          "description": "The city and country, eg. San Francisco, USA"
                      },
                      "format": { "type": "string", "enum": ["celsius", "fahrenheit"] }
                    },
                    "required": ["location", "format"]
                  }
                }
              }
            ]
          }
    FineTuneDPOHyperparameters:
      type: object
      description: The hyperparameters used for the DPO fine-tuning job.
      properties:
        beta:
          description: >
            The beta value for the DPO method. A higher beta value will increase the weight of the penalty
            between the policy and reference model.
          oneOf:
            - type: string
              enum:
                - auto
              x-stainless-const: true
            - type: number
              minimum: 0
              maximum: 2
              exclusiveMinimum: true
          default: auto
        batch_size:
          description: >
            Number of examples in each batch. A larger batch size means that model parameters are updated less
            frequently, but with lower variance.
          oneOf:
            - type: string
              enum:
                - auto
              x-stainless-const: true
            - type: integer
              minimum: 1
              maximum: 256
          default: auto
        learning_rate_multiplier:
          description: |
            Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
          oneOf:
            - type: string
              enum:
                - auto
              x-stainless-const: true
            - type: number
              minimum: 0
              exclusiveMinimum: true
          default: auto
        n_epochs:
          description: >
            The number of epochs to train the model for. An epoch refers to one full cycle through the
            training dataset.
          oneOf:
            - type: string
              enum:
                - auto
              x-stainless-const: true
            - type: integer
              minimum: 1
              maximum: 50
          default: auto
    FineTuneDPOMethod:
      type: object
      description: Configuration for the DPO fine-tuning method.
      properties:
        hyperparameters:
          $ref: '#/components/schemas/FineTuneDPOHyperparameters'
    FineTuneMethod:
      type: object
      description: The method used for fine-tuning.
      properties:
        type:
          type: string
          description: The type of method. Is either `supervised`, `dpo`, or `reinforcement`.
          enum:
            - supervised
            - dpo
            - reinforcement
        supervised:
          $ref: '#/components/schemas/FineTuneSupervisedMethod'
        dpo:
          $ref: '#/components/schemas/FineTuneDPOMethod'
        reinforcement:
          $ref: '#/components/schemas/FineTuneReinforcementMethod'
      required:
        - type
    FineTunePreferenceRequestInput:
      type: object
      description: |
        The per-line training example of a fine-tuning input file for chat models using the dpo method.
        Input messages may contain text or image content only. Audio and file input messages
        are not currently supported for fine-tuning.
      properties:
        input:
          type: object
          properties:
            messages:
              type: array
              minItems: 1
              items:
                oneOf:
                  - $ref: '#/components/schemas/ChatCompletionRequestSystemMessage'
                  - $ref: '#/components/schemas/ChatCompletionRequestUserMessage'
                  - $ref: '#/components/schemas/FineTuneChatCompletionRequestAssistantMessage'
                  - $ref: '#/components/schemas/ChatCompletionRequestToolMessage'
                  - $ref: '#/components/schemas/ChatCompletionRequestFunctionMessage'
            tools:
              type: array
              description: A list of tools the model may generate JSON inputs for.
              items:
                $ref: '#/components/schemas/ChatCompletionTool'
            parallel_tool_calls:
              $ref: '#/components/schemas/ParallelToolCalls'
        preferred_output:
          type: array
          description: The preferred completion message for the output.
          maxItems: 1
          items:
            oneOf:
              - $ref: '#/components/schemas/ChatCompletionRequestAssistantMessage'
        non_preferred_output:
          type: array
          description: The non-preferred completion message for the output.
          maxItems: 1
          items:
            oneOf:
              - $ref: '#/components/schemas/ChatCompletionRequestAssistantMessage'
      x-oaiMeta:
        name: Training format for chat models using the preference method
        example: |
          {
            "input": {
              "messages": [
                { "role": "user", "content": "What is the weather in San Francisco?" }
              ]
            },
            "preferred_output": [
              {
                "role": "assistant",
                "content": "The weather in San Francisco is 70 degrees Fahrenheit."
              }
            ],
            "non_preferred_output": [
              {
                "role": "assistant",
                "content": "The weather in San Francisco is 21 degrees Celsius."
              }
            ]
          }
    FineTuneReinforcementHyperparameters:
      type: object
      description: The hyperparameters used for the reinforcement fine-tuning job.
      properties:
        batch_size:
          description: >
            Number of examples in each batch. A larger batch size means that model parameters are updated less
            frequently, but with lower variance.
          oneOf:
            - type: string
              enum:
                - auto
              x-stainless-const: true
            - type: integer
              minimum: 1
              maximum: 256
          default: auto
        learning_rate_multiplier:
          description: |
            Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
          oneOf:
            - type: string
              enum:
                - auto
              x-stainless-const: true
            - type: number
              minimum: 0
              exclusiveMinimum: true
          default: auto
        n_epochs:
          description: >
            The number of epochs to train the model for. An epoch refers to one full cycle through the
            training dataset.
          oneOf:
            - type: string
              enum:
                - auto
              x-stainless-const: true
            - type: integer
              minimum: 1
              maximum: 50
          default: auto
        reasoning_effort:
          description: |
            Level of reasoning effort.
          type: string
          enum:
            - default
            - low
            - medium
            - high
          default: default
        compute_multiplier:
          description: |
            Multiplier on amount of compute used for exploring search space during training.
          oneOf:
            - type: string
              enum:
                - auto
              x-stainless-const: true
            - type: number
              minimum: 0.00001
              maximum: 10
              exclusiveMinimum: true
          default: auto
        eval_interval:
          description: |
            The number of training steps between evaluation runs.
          oneOf:
            - type: string
              enum:
                - auto
              x-stainless-const: true
            - type: integer
              minimum: 1
          default: auto
        eval_samples:
          description: |
            Number of evaluation samples to generate per training step.
          oneOf:
            - type: string
              enum:
                - auto
              x-stainless-const: true
            - type: integer
              minimum: 1
          default: auto
    FineTuneReinforcementMethod:
      type: object
      description: Configuration for the reinforcement fine-tuning method.
      properties:
        grader:
          type: object
          description: The grader used for the fine-tuning job.
          oneOf:
            - $ref: '#/components/schemas/GraderStringCheck'
            - $ref: '#/components/schemas/GraderTextSimilarity'
            - $ref: '#/components/schemas/GraderPython'
            - $ref: '#/components/schemas/GraderScoreModel'
            - $ref: '#/components/schemas/GraderMulti'
        hyperparameters:
          $ref: '#/components/schemas/FineTuneReinforcementHyperparameters'
      required:
        - grader
    FineTuneReinforcementRequestInput:
      type: object
      unevaluatedProperties: true
      description: >
        Per-line training example for reinforcement fine-tuning. Note that `messages` and `tools` are the only
        reserved keywords.

        Any other arbitrary key-value data can be included on training datapoints and will be available to
        reference during grading under the `{{ item.XXX }}` template variable.

        Input messages may contain text or image content only. Audio and file input messages

        are not currently supported for fine-tuning.
      required:
        - messages
      properties:
        messages:
          type: array
          minItems: 1
          items:
            oneOf:
              - $ref: '#/components/schemas/ChatCompletionRequestDeveloperMessage'
              - $ref: '#/components/schemas/ChatCompletionRequestUserMessage'
              - $ref: '#/components/schemas/FineTuneChatCompletionRequestAssistantMessage'
              - $ref: '#/components/schemas/ChatCompletionRequestToolMessage'
        tools:
          type: array
          description: A list of tools the model may generate JSON inputs for.
          items:
            $ref: '#/components/schemas/ChatCompletionTool'
      x-oaiMeta:
        name: Training format for reasoning models using the reinforcement method
        example: |
          {
            "messages": [
              {
                "role": "user",
                "content": "Your task is to take a chemical in SMILES format and predict the number of hydrobond bond donors and acceptors according to Lipinkski's rule. CCN(CC)CCC(=O)c1sc(N)nc1C"
              },
            ],
            # Any other JSON data can be inserted into an example and referenced during RFT grading
            "reference_answer": {
              "donor_bond_counts": 5,
              "acceptor_bond_counts": 7
            }
          }
    FineTuneSupervisedHyperparameters:
      type: object
      description: The hyperparameters used for the fine-tuning job.
      properties:
        batch_size:
          description: >
            Number of examples in each batch. A larger batch size means that model parameters are updated less
            frequently, but with lower variance.
          oneOf:
            - type: string
              enum:
                - auto
              x-stainless-const: true
            - type: integer
              minimum: 1
              maximum: 256
          default: auto
        learning_rate_multiplier:
          description: |
            Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting.
          oneOf:
            - type: string
              enum:
                - auto
              x-stainless-const: true
            - type: number
              minimum: 0
              exclusiveMinimum: true
          default: auto
        n_epochs:
          description: >
            The number of epochs to train the model for. An epoch refers to one full cycle through the
            training dataset.
          oneOf:
            - type: string
              enum:
                - auto
              x-stainless-const: true
            - type: integer
              minimum: 1
              maximum: 50
          default: auto
    FineTuneSupervisedMethod:
      type: object
      description: Configuration for the supervised fine-tuning method.
      properties:
        hyperparameters:
          $ref: '#/components/schemas/FineTuneSupervisedHyperparameters'
    FineTuningCheckpointPermission:
      type: object
      title: FineTuningCheckpointPermission
      description: |
        The `checkpoint.permission` object represents a permission for a fine-tuned model checkpoint.
      properties:
        id:
          type: string
          description: The permission identifier, which can be referenced in the API endpoints.
        created_at:
          type: integer
          description: The Unix timestamp (in seconds) for when the permission was created.
        project_id:
          type: string
          description: The project identifier that the permission is for.
        object:
          type: string
          description: The object type, which is always "checkpoint.permission".
          enum:
            - checkpoint.permission
          x-stainless-const: true
      required:
        - created_at
        - id
        - object
        - project_id
      x-oaiMeta:
        name: The fine-tuned model checkpoint permission object
        example: |
          {
            "object": "checkpoint.permission",
            "id": "cp_zc4Q7MP6XxulcVzj4MZdwsAB",
            "created_at": 1712211699,
            "project_id": "proj_abGMw1llN8IrBb6SvvY5A1iH"
          }
    FineTuningIntegration:
      type: object
      title: Fine-Tuning Job Integration
      required:
        - type
        - wandb
      properties:
        type:
          type: string
          description: The type of the integration being enabled for the fine-tuning job
          enum:
            - wandb
          x-stainless-const: true
        wandb:
          type: object
          description: |
            The settings for your integration with Weights and Biases. This payload specifies the project that
            metrics will be sent to. Optionally, you can set an explicit display name for your run, add tags
            to your run, and set a default entity (team, username, etc) to be associated with your run.
          required:
            - project
          properties:
            project:
              description: |
                The name of the project that the new run will be created under.
              type: string
              example: my-wandb-project
            name:
              description: |
                A display name to set for the run. If not set, we will use the Job ID as the name.
              nullable: true
              type: string
            entity:
              description: >
                The entity to use for the run. This allows you to set the team or username of the WandB user
                that you would

                like associated with the run. If not set, the default entity for the registered WandB API key
                is used.
              nullable: true
              type: string
            tags:
              description: >
                A list of tags to be attached to the newly created run. These tags are passed through directly
                to WandB. Some

                default tags are generated by OpenAI: "openai/finetune", "openai/{base-model}",
                "openai/{ftjob-abcdef}".
              type: array
              items:
                type: string
                example: custom-tag
    FineTuningJob:
      type: object
      title: FineTuningJob
      description: |
        The `fine_tuning.job` object represents a fine-tuning job that has been created through the API.
      properties:
        id:
          type: string
          description: The object identifier, which can be referenced in the API endpoints.
        created_at:
          type: integer
          description: The Unix timestamp (in seconds) for when the fine-tuning job was created.
        error:
          type: object
          nullable: true
          description: >-
            For fine-tuning jobs that have `failed`, this will contain more information on the cause of the
            failure.
          properties:
            code:
              type: string
              description: A machine-readable error code.
            message:
              type: string
              description: A human-readable error message.
            param:
              type: string
              description: >-
                The parameter that was invalid, usually `training_file` or `validation_file`. This field will
                be null if the failure was not parameter-specific.
              nullable: true
          required:
            - code
            - message
            - param
        fine_tuned_model:
          type: string
          nullable: true
          description: >-
            The name of the fine-tuned model that is being created. The value will be null if the fine-tuning
            job is still running.
        finished_at:
          type: integer
          nullable: true
          description: >-
            The Unix timestamp (in seconds) for when the fine-tuning job was finished. The value will be null
            if the fine-tuning job is still running.
        hyperparameters:
          type: object
          description: >-
            The hyperparameters used for the fine-tuning job. This value will only be returned when running
            `supervised` jobs.
          properties:
            batch_size:
              nullable: true
              description: |
                Number of examples in each batch. A larger batch size means that model parameters
                are updated less frequently, but with lower variance.
              oneOf:
                - type: string
                  enum:
                    - auto
                  x-stainless-const: true
                - type: integer
                  minimum: 1
                  maximum: 256
              default: auto
            learning_rate_multiplier:
              description: |
                Scaling factor for the learning rate. A smaller learning rate may be useful to avoid
                overfitting.
              oneOf:
                - type: string
                  enum:
                    - auto
                  x-stainless-const: true
                - type: number
                  minimum: 0
                  exclusiveMinimum: true
              default: auto
            n_epochs:
              description: |
                The number of epochs to train the model for. An epoch refers to one full cycle
                through the training dataset.
              oneOf:
                - type: string
                  enum:
                    - auto
                  x-stainless-const: true
                - type: integer
                  minimum: 1
                  maximum: 50
              default: auto
        model:
          type: string
          description: The base model that is being fine-tuned.
        object:
          type: string
          description: The object type, which is always "fine_tuning.job".
          enum:
            - fine_tuning.job
          x-stainless-const: true
        organization_id:
          type: string
          description: The organization that owns the fine-tuning job.
        result_files:
          type: array
          description: >-
            The compiled results file ID(s) for the fine-tuning job. You can retrieve the results with the
            [Files API](/docs/api-reference/files/retrieve-contents).
          items:
            type: string
            example: file-abc123
        status:
          type: string
          description: >-
            The current status of the fine-tuning job, which can be either `validating_files`, `queued`,
            `running`, `succeeded`, `failed`, or `cancelled`.
          enum:
            - validating_files
            - queued
            - running
            - succeeded
            - failed
            - cancelled
        trained_tokens:
          type: integer
          nullable: true
          description: >-
            The total number of billable tokens processed by this fine-tuning job. The value will be null if
            the fine-tuning job is still running.
        training_file:
          type: string
          description: >-
            The file ID used for training. You can retrieve the training data with the [Files
            API](/docs/api-reference/files/retrieve-contents).
        validation_file:
          type: string
          nullable: true
          description: >-
            The file ID used for validation. You can retrieve the validation results with the [Files
            API](/docs/api-reference/files/retrieve-contents).
        integrations:
          type: array
          nullable: true
          description: A list of integrations to enable for this fine-tuning job.
          maxItems: 5
          items:
            oneOf:
              - $ref: '#/components/schemas/FineTuningIntegration'
        seed:
          type: integer
          description: The seed used for the fine-tuning job.
        estimated_finish:
          type: integer
          nullable: true
          description: >-
            The Unix timestamp (in seconds) for when the fine-tuning job is estimated to finish. The value
            will be null if the fine-tuning job is not running.
        method:
          $ref: '#/components/schemas/FineTuneMethod'
        metadata:
          $ref: '#/components/schemas/Metadata'
      required:
        - created_at
        - error
        - finished_at
        - fine_tuned_model
        - hyperparameters
        - id
        - model
        - object
        - organization_id
        - result_files
        - status
        - trained_tokens
        - training_file
        - validation_file
        - seed
      x-oaiMeta:
        name: The fine-tuning job object
        example: |
          {
            "object": "fine_tuning.job",
            "id": "ftjob-abc123",
            "model": "davinci-002",
            "created_at": 1692661014,
            "finished_at": 1692661190,
            "fine_tuned_model": "ft:davinci-002:my-org:custom_suffix:7q8mpxmy",
            "organization_id": "org-123",
            "result_files": [
                "file-abc123"
            ],
            "status": "succeeded",
            "validation_file": null,
            "training_file": "file-abc123",
            "hyperparameters": {
                "n_epochs": 4,
                "batch_size": 1,
                "learning_rate_multiplier": 1.0
            },
            "trained_tokens": 5768,
            "integrations": [],
            "seed": 0,
            "estimated_finish": 0,
            "method": {
              "type": "supervised",
              "supervised": {
                "hyperparameters": {
                  "n_epochs": 4,
                  "batch_size": 1,
                  "learning_rate_multiplier": 1.0
                }
              }
            },
            "metadata": {
              "key": "value"
            }
          }
    FineTuningJobCheckpoint:
      type: object
      title: FineTuningJobCheckpoint
      description: >
        The `fine_tuning.job.checkpoint` object represents a model checkpoint for a fine-tuning job that is
        ready to use.
      properties:
        id:
          type: string
          description: The checkpoint identifier, which can be referenced in the API endpoints.
        created_at:
          type: integer
          description: The Unix timestamp (in seconds) for when the checkpoint was created.
        fine_tuned_model_checkpoint:
          type: string
          description: The name of the fine-tuned checkpoint model that is created.
        step_number:
          type: integer
          description: The step number that the checkpoint was created at.
        metrics:
          type: object
          description: Metrics at the step number during the fine-tuning job.
          properties:
            step:
              type: number
            train_loss:
              type: number
            train_mean_token_accuracy:
              type: number
            valid_loss:
              type: number
            valid_mean_token_accuracy:
              type: number
            full_valid_loss:
              type: number
            full_valid_mean_token_accuracy:
              type: number
        fine_tuning_job_id:
          type: string
          description: The name of the fine-tuning job that this checkpoint was created from.
        object:
          type: string
          description: The object type, which is always "fine_tuning.job.checkpoint".
          enum:
            - fine_tuning.job.checkpoint
          x-stainless-const: true
      required:
        - created_at
        - fine_tuning_job_id
        - fine_tuned_model_checkpoint
        - id
        - metrics
        - object
        - step_number
      x-oaiMeta:
        name: The fine-tuning job checkpoint object
        example: |
          {
            "object": "fine_tuning.job.checkpoint",
            "id": "ftckpt_qtZ5Gyk4BLq1SfLFWp3RtO3P",
            "created_at": 1712211699,
            "fine_tuned_model_checkpoint": "ft:gpt-4o-mini-2024-07-18:my-org:custom_suffix:9ABel2dg:ckpt-step-88",
            "fine_tuning_job_id": "ftjob-fpbNQ3H1GrMehXRf8cO97xTN",
            "metrics": {
              "step": 88,
              "train_loss": 0.478,
              "train_mean_token_accuracy": 0.924,
              "valid_loss": 10.112,
              "valid_mean_token_accuracy": 0.145,
              "full_valid_loss": 0.567,
              "full_valid_mean_token_accuracy": 0.944
            },
            "step_number": 88
          }
    FineTuningJobEvent:
      type: object
      description: Fine-tuning job event object
      properties:
        object:
          type: string
          description: The object type, which is always "fine_tuning.job.event".
          enum:
            - fine_tuning.job.event
          x-stainless-const: true
        id:
          type: string
          description: The object identifier.
        created_at:
          type: integer
          description: The Unix timestamp (in seconds) for when the fine-tuning job was created.
        level:
          type: string
          description: The log level of the event.
          enum:
            - info
            - warn
            - error
        message:
          type: string
          description: The message of the event.
        type:
          type: string
          description: The type of event.
          enum:
            - message
            - metrics
        data:
          type: object
          description: The data associated with the event.
      required:
        - id
        - object
        - created_at
        - level
        - message
      x-oaiMeta:
        name: The fine-tuning job event object
        example: |
          {
            "object": "fine_tuning.job.event",
            "id": "ftevent-abc123"
            "created_at": 1677610602,
            "level": "info",
            "message": "Created fine-tuning job",
            "data": {},
            "type": "message"
          }
    FunctionObject:
      type: object
      properties:
        description:
          type: string
          description: >-
            A description of what the function does, used by the model to choose when and how to call the
            function.
        name:
          type: string
          description: >-
            The name of the function to be called. Must be a-z, A-Z, 0-9, or contain underscores and dashes,
            with a maximum length of 64.
        parameters:
          $ref: '#/components/schemas/FunctionParameters'
        strict:
          type: boolean
          nullable: true
          default: false
          description: >-
            Whether to enable strict schema adherence when generating the function call. If set to true, the
            model will follow the exact schema defined in the `parameters` field. Only a subset of JSON Schema
            is supported when `strict` is `true`. Learn more about Structured Outputs in the [function calling
            guide](docs/guides/function-calling).
      required:
        - name
    FunctionParameters:
      type: object
      description: >-
        The parameters the functions accepts, described as a JSON Schema object. See the
        [guide](/docs/guides/function-calling) for examples, and the [JSON Schema
        reference](https://json-schema.org/understanding-json-schema/) for documentation about the format. 


        Omitting `parameters` defines a function with an empty parameter list.
      additionalProperties: true
    FunctionToolCall:
      type: object
      title: Function tool call
      description: |
        A tool call to run a function. See the 
        [function calling guide](/docs/guides/function-calling) for more information.
      properties:
        id:
          type: string
          description: |
            The unique ID of the function tool call.
        type:
          type: string
          enum:
            - function_call
          description: |
            The type of the function tool call. Always `function_call`.
          x-stainless-const: true
        call_id:
          type: string
          description: |
            The unique ID of the function tool call generated by the model.
        name:
          type: string
          description: |
            The name of the function to run.
        arguments:
          type: string
          description: |
            A JSON string of the arguments to pass to the function.
        status:
          type: string
          description: |
            The status of the item. One of `in_progress`, `completed`, or
            `incomplete`. Populated when items are returned via API.
          enum:
            - in_progress
            - completed
            - incomplete
      required:
        - type
        - call_id
        - name
        - arguments
    FunctionToolCallOutput:
      type: object
      title: Function tool call output
      description: |
        The output of a function tool call.
      properties:
        id:
          type: string
          description: |
            The unique ID of the function tool call output. Populated when this item
            is returned via API.
        type:
          type: string
          enum:
            - function_call_output
          description: |
            The type of the function tool call output. Always `function_call_output`.
          x-stainless-const: true
        call_id:
          type: string
          description: |
            The unique ID of the function tool call generated by the model.
        output:
          type: string
          description: |
            A JSON string of the output of the function tool call.
        status:
          type: string
          description: |
            The status of the item. One of `in_progress`, `completed`, or
            `incomplete`. Populated when items are returned via API.
          enum:
            - in_progress
            - completed
            - incomplete
      required:
        - type
        - call_id
        - output
    FunctionToolCallOutputResource:
      allOf:
        - $ref: '#/components/schemas/FunctionToolCallOutput'
        - type: object
          properties:
            id:
              type: string
              description: |
                The unique ID of the function call tool output.
          required:
            - id
    FunctionToolCallResource:
      allOf:
        - $ref: '#/components/schemas/FunctionToolCall'
        - type: object
          properties:
            id:
              type: string
              description: |
                The unique ID of the function tool call.
          required:
            - id
    GraderLabelModel:
      type: object
      title: LabelModelGrader
      description: |
        A LabelModelGrader object which uses a model to assign labels to each item
        in the evaluation.
      properties:
        type:
          description: The object type, which is always `label_model`.
          type: string
          enum:
            - label_model
          x-stainless-const: true
        name:
          type: string
          description: The name of the grader.
        model:
          type: string
          description: The model to use for the evaluation. Must support structured outputs.
        input:
          type: array
          items:
            $ref: '#/components/schemas/EvalItem'
        labels:
          type: array
          items:
            type: string
          description: The labels to assign to each item in the evaluation.
        passing_labels:
          type: array
          items:
            type: string
          description: The labels that indicate a passing result. Must be a subset of labels.
      required:
        - type
        - model
        - input
        - passing_labels
        - labels
        - name
      x-oaiMeta:
        name: Label Model Grader
        group: graders
        example: |
          {
            "name": "First label grader",
            "type": "label_model",
            "model": "gpt-4o-2024-08-06",
            "input": [
              {
                "type": "message",
                "role": "system",
                "content": {
                  "type": "input_text",
                  "text": "Classify the sentiment of the following statement as one of positive, neutral, or negative"
                }
              },
              {
                "type": "message",
                "role": "user",
                "content": {
                  "type": "input_text",
                  "text": "Statement: {{item.response}}"
                }
              }
            ],
            "passing_labels": [
              "positive"
            ],
            "labels": [
              "positive",
              "neutral",
              "negative"
            ]
          }
    GraderMulti:
      type: object
      title: MultiGrader
      description: A MultiGrader object combines the output of multiple graders to produce a single score.
      properties:
        type:
          type: string
          enum:
            - multi
          default: multi
          description: The object type, which is always `multi`.
          x-stainless-const: true
        name:
          type: string
          description: The name of the grader.
        graders:
          oneOf:
            - $ref: '#/components/schemas/GraderStringCheck'
            - $ref: '#/components/schemas/GraderTextSimilarity'
            - $ref: '#/components/schemas/GraderPython'
            - $ref: '#/components/schemas/GraderScoreModel'
            - $ref: '#/components/schemas/GraderLabelModel'
        calculate_output:
          type: string
          description: A formula to calculate the output based on grader results.
      required:
        - name
        - type
        - graders
        - calculate_output
      x-oaiMeta:
        name: Multi Grader
        group: graders
        example: |
          {
            "type": "multi",
            "name": "example multi grader",
            "graders": [
              {
                "type": "text_similarity",
                "name": "example text similarity grader",
                "input": "The graded text",
                "reference": "The reference text",
                "evaluation_metric": "fuzzy_match"
              },
              {
                "type": "string_check",
                "name": "Example string check grader",
                "input": "{{sample.output_text}}",
                "reference": "{{item.label}}",
                "operation": "eq"
              }
            ],
            "calculate_output": "0.5 * text_similarity_score +  0.5 * string_check_score)"
          }
    GraderPython:
      type: object
      title: PythonGrader
      description: |
        A PythonGrader object that runs a python script on the input.
      properties:
        type:
          type: string
          enum:
            - python
          description: The object type, which is always `python`.
          x-stainless-const: true
        name:
          type: string
          description: The name of the grader.
        source:
          type: string
          description: The source code of the python script.
        image_tag:
          type: string
          description: The image tag to use for the python script.
      required:
        - type
        - name
        - source
      x-oaiMeta:
        name: Python Grader
        group: graders
        example: |
          {
            "type": "python",
            "name": "Example python grader",
            "image_tag": "2025-05-08",
            "source": """
          def grade(sample: dict, item: dict) -> float:
              \"""
              Returns 1.0 if `output_text` equals `label`, otherwise 0.0.
              \"""
              output = sample.get("output_text")
              label = item.get("label")
              return 1.0 if output == label else 0.0
          """,
          }
    GraderScoreModel:
      type: object
      title: ScoreModelGrader
      description: |
        A ScoreModelGrader object that uses a model to assign a score to the input.
      properties:
        type:
          type: string
          enum:
            - score_model
          description: The object type, which is always `score_model`.
          x-stainless-const: true
        name:
          type: string
          description: The name of the grader.
        model:
          type: string
          description: The model to use for the evaluation.
        sampling_params:
          type: object
          description: The sampling parameters for the model.
        input:
          type: array
          items:
            $ref: '#/components/schemas/EvalItem'
          description: The input text. This may include template strings.
        range:
          type: array
          items:
            type: number
            min_items: 2
            max_items: 2
          description: The range of the score. Defaults to `[0, 1]`.
      required:
        - type
        - name
        - input
        - model
      x-oaiMeta:
        name: Score Model Grader
        group: graders
        example: |
          {
              "type": "score_model",
              "name": "Example score model grader",
              "input": [
                  {
                      "role": "user",
                      "content": (
                          "Score how close the reference answer is to the model answer. Score 1.0 if they are the same and 0.0 if they are different."
                          " Return just a floating point score\n\n"
                          " Reference answer: {{item.label}}\n\n"
                          " Model answer: {{sample.output_text}}"
                      ),
                  }
              ],
              "model": "gpt-4o-2024-08-06",
              "sampling_params": {
                  "temperature": 1,
                  "top_p": 1,
                  "seed": 42,
              },
          }
    GraderStringCheck:
      type: object
      title: StringCheckGrader
      description: >
        A StringCheckGrader object that performs a string comparison between input and reference using a
        specified operation.
      properties:
        type:
          type: string
          enum:
            - string_check
          description: The object type, which is always `string_check`.
          x-stainless-const: true
        name:
          type: string
          description: The name of the grader.
        input:
          type: string
          description: The input text. This may include template strings.
        reference:
          type: string
          description: The reference text. This may include template strings.
        operation:
          type: string
          enum:
            - eq
            - ne
            - like
            - ilike
          description: The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`.
      required:
        - type
        - name
        - input
        - reference
        - operation
      x-oaiMeta:
        name: String Check Grader
        group: graders
        example: |
          {
            "type": "string_check",
            "name": "Example string check grader",
            "input": "{{sample.output_text}}",
            "reference": "{{item.label}}",
            "operation": "eq"
          }
    GraderTextSimilarity:
      type: object
      title: TextSimilarityGrader
      description: |
        A TextSimilarityGrader object which grades text based on similarity metrics.
      properties:
        type:
          type: string
          enum:
            - text_similarity
          default: text_similarity
          description: The type of grader.
          x-stainless-const: true
        name:
          type: string
          description: The name of the grader.
        input:
          type: string
          description: The text being graded.
        reference:
          type: string
          description: The text being graded against.
        evaluation_metric:
          type: string
          enum:
            - fuzzy_match
            - bleu
            - gleu
            - meteor
            - rouge_1
            - rouge_2
            - rouge_3
            - rouge_4
            - rouge_5
            - rouge_l
          description: >-
            The evaluation metric to use. One of `fuzzy_match`, `bleu`, `gleu`, `meteor`, `rouge_1`,
            `rouge_2`, `rouge_3`, `rouge_4`, `rouge_5`, or `rouge_l`.
      required:
        - type
        - name
        - input
        - reference
        - evaluation_metric
      x-oaiMeta:
        name: Text Similarity Grader
        group: graders
        example: |
          {
            "type": "text_similarity",
            "name": "Example text similarity grader",
            "input": "{{sample.output_text}}",
            "reference": "{{item.label}}",
            "evaluation_metric": "fuzzy_match"
          }
    Image:
      type: object
      description: Represents the content or the URL of an image generated by the OpenAI API.
      properties:
        b64_json:
          type: string
          description: >-
            The base64-encoded JSON of the generated image. Default value for `gpt-image-1`, and only present
            if `response_format` is set to `b64_json` for `dall-e-2` and `dall-e-3`.
        url:
          type: string
          description: >-
            When using `dall-e-2` or `dall-e-3`, the URL of the generated image if `response_format` is set to
            `url` (default value). Unsupported for `gpt-image-1`.
        revised_prompt:
          type: string
          description: For `dall-e-3` only, the revised prompt that was used to generate the image.
    ImageGenTool:
      type: object
      title: Image generation tool
      description: |
        A tool that generates images using a model like `gpt-image-1`.
      properties:
        type:
          type: string
          enum:
            - image_generation
          description: |
            The type of the image generation tool. Always `image_generation`.
          x-stainless-const: true
        model:
          type: string
          enum:
            - gpt-image-1
          description: |
            The image generation model to use. Default: `gpt-image-1`.
          default: gpt-image-1
        quality:
          type: string
          enum:
            - low
            - medium
            - high
            - auto
          description: |
            The quality of the generated image. One of `low`, `medium`, `high`, 
            or `auto`. Default: `auto`.
          default: auto
        size:
          type: string
          enum:
            - 1024x1024
            - 1024x1536
            - 1536x1024
            - auto
          description: |
            The size of the generated image. One of `1024x1024`, `1024x1536`, 
            `1536x1024`, or `auto`. Default: `auto`.
          default: auto
        output_format:
          type: string
          enum:
            - png
            - webp
            - jpeg
          description: |
            The output format of the generated image. One of `png`, `webp`, or 
            `jpeg`. Default: `png`.
          default: png
        output_compression:
          type: integer
          minimum: 0
          maximum: 100
          description: |
            Compression level for the output image. Default: 100.
          default: 100
        moderation:
          type: string
          enum:
            - auto
            - low
          description: |
            Moderation level for the generated image. Default: `auto`.
          default: auto
        background:
          type: string
          enum:
            - transparent
            - opaque
            - auto
          description: |
            Background type for the generated image. One of `transparent`, 
            `opaque`, or `auto`. Default: `auto`.
          default: auto
        input_image_mask:
          type: object
          description: |
            Optional mask for inpainting. Contains `image_url` 
            (string, optional) and `file_id` (string, optional).
          properties:
            image_url:
              type: string
              description: |
                Base64-encoded mask image.
            file_id:
              type: string
              description: |
                File ID for the mask image.
          required: []
          additionalProperties: false
        partial_images:
          type: integer
          minimum: 0
          maximum: 3
          description: |
            Number of partial images to generate in streaming mode, from 0 (default value) to 3.
          default: 0
      required:
        - type
    ImageGenToolCall:
      type: object
      title: Image generation call
      description: |
        An image generation request made by the model.
      properties:
        type:
          type: string
          enum:
            - image_generation_call
          description: |
            The type of the image generation call. Always `image_generation_call`.
          x-stainless-const: true
        id:
          type: string
          description: |
            The unique ID of the image generation call.
        status:
          type: string
          enum:
            - in_progress
            - completed
            - generating
            - failed
          description: |
            The status of the image generation call.
        result:
          type: string
          description: |
            The generated image encoded in base64.
          nullable: true
      required:
        - type
        - id
        - status
        - result
    ImagesResponse:
      type: object
      title: Image generation response
      description: The response from the image generation endpoint.
      properties:
        created:
          type: integer
          description: The Unix timestamp (in seconds) of when the image was created.
        data:
          type: array
          description: The list of generated images.
          items:
            $ref: '#/components/schemas/Image'
        usage:
          type: object
          description: |
            For `gpt-image-1` only, the token usage information for the image generation.
          required:
            - total_tokens
            - input_tokens
            - output_tokens
            - input_tokens_details
          properties:
            total_tokens:
              type: integer
              description: The total number of tokens (images and text) used for the image generation.
            input_tokens:
              type: integer
              description: The number of tokens (images and text) in the input prompt.
            output_tokens:
              type: integer
              description: The number of image tokens in the output image.
            input_tokens_details:
              type: object
              description: The input tokens detailed information for the image generation.
              required:
                - text_tokens
                - image_tokens
              properties:
                text_tokens:
                  type: integer
                  description: The number of text tokens in the input prompt.
                image_tokens:
                  type: integer
                  description: The number of image tokens in the input prompt.
      required:
        - created
      x-oaiMeta:
        name: The image generation response
        group: images
        example: |
          {
            "created": 1713833628,
            "data": [
              {
                "b64_json": "..."
              }
            ],
            "usage": {
              "total_tokens": 100,
              "input_tokens": 50,
              "output_tokens": 50,
              "input_tokens_details": {
                "text_tokens": 10,
                "image_tokens": 40
              }
            }
          }
    Includable:
      type: string
      description: |
        Specify additional output data to include in the model response. Currently
        supported values are:
        - `file_search_call.results`: Include the search results of
          the file search tool call.
        - `message.input_image.image_url`: Include image urls from the input message.
        - `computer_call_output.output.image_url`: Include image urls from the computer call output.
        - `reasoning.encrypted_content`: Includes an encrypted version of reasoning
          tokens in reasoning item outputs. This enables reasoning items to be used in
          multi-turn conversations when using the Responses API statelessly (like
          when the `store` parameter is set to `false`, or when an organization is
          enrolled in the zero data retention program).
        - `code_interpreter_call.outputs`: Includes the outputs of python code execution
          in code interpreter tool call items.
      enum:
        - file_search_call.results
        - message.input_image.image_url
        - computer_call_output.output.image_url
        - reasoning.encrypted_content
        - code_interpreter_call.outputs
    InputAudio:
      type: object
      title: Audio input
      description: |
        An audio input to the model.
      properties:
        type:
          type: string
          description: |
            The type of the input item. Always `input_audio`.
          enum:
            - input_audio
          x-stainless-const: true
        data:
          type: string
          description: |
            Base64-encoded audio data.
        format:
          type: string
          description: |
            The format of the audio data. Currently supported formats are `mp3` and
            `wav`.
          enum:
            - mp3
            - wav
      required:
        - type
        - data
        - format
    InputContent:
      oneOf:
        - $ref: '#/components/schemas/InputTextContent'
        - $ref: '#/components/schemas/InputImageContent'
        - $ref: '#/components/schemas/InputFileContent'
    InputItem:
      oneOf:
        - $ref: '#/components/schemas/EasyInputMessage'
        - type: object
          title: Item
          description: |
            An item representing part of the context for the response to be 
            generated by the model. Can contain text, images, and audio inputs,
            as well as previous assistant responses and tool call outputs.
          $ref: '#/components/schemas/Item'
        - $ref: '#/components/schemas/ItemReferenceParam'
      discriminator:
        propertyName: type
    InputMessage:
      type: object
      title: Input message
      description: |
        A message input to the model with a role indicating instruction following
        hierarchy. Instructions given with the `developer` or `system` role take
        precedence over instructions given with the `user` role.
      properties:
        type:
          type: string
          description: |
            The type of the message input. Always set to `message`.
          enum:
            - message
          x-stainless-const: true
        role:
          type: string
          description: |
            The role of the message input. One of `user`, `system`, or `developer`.
          enum:
            - user
            - system
            - developer
        status:
          type: string
          description: |
            The status of item. One of `in_progress`, `completed`, or
            `incomplete`. Populated when items are returned via API.
          enum:
            - in_progress
            - completed
            - incomplete
        content:
          $ref: '#/components/schemas/InputMessageContentList'
      required:
        - role
        - content
    InputMessageContentList:
      type: array
      title: Input item content list
      description: |
        A list of one or many input items to the model, containing different content 
        types.
      items:
        $ref: '#/components/schemas/InputContent'
    InputMessageResource:
      allOf:
        - $ref: '#/components/schemas/InputMessage'
        - type: object
          properties:
            id:
              type: string
              description: |
                The unique ID of the message input.
          required:
            - id
    Invite:
      type: object
      description: Represents an individual `invite` to the organization.
      properties:
        object:
          type: string
          enum:
            - organization.invite
          description: The object type, which is always `organization.invite`
          x-stainless-const: true
        id:
          type: string
          description: The identifier, which can be referenced in API endpoints
        email:
          type: string
          description: The email address of the individual to whom the invite was sent
        role:
          type: string
          enum:
            - owner
            - reader
          description: '`owner` or `reader`'
        status:
          type: string
          enum:
            - accepted
            - expired
            - pending
          description: '`accepted`,`expired`, or `pending`'
        invited_at:
          type: integer
          description: The Unix timestamp (in seconds) of when the invite was sent.
        expires_at:
          type: integer
          description: The Unix timestamp (in seconds) of when the invite expires.
        accepted_at:
          type: integer
          description: The Unix timestamp (in seconds) of when the invite was accepted.
        projects:
          type: array
          description: The projects that were granted membership upon acceptance of the invite.
          items:
            type: object
            properties:
              id:
                type: string
                description: Project's public ID
              role:
                type: string
                enum:
                  - member
                  - owner
                description: Project membership role
      required:
        - object
        - id
        - email
        - role
        - status
        - invited_at
        - expires_at
      x-oaiMeta:
        name: The invite object
        example: |
          {
            "object": "organization.invite",
            "id": "invite-abc",
            "email": "user@example.com",
            "role": "owner",
            "status": "accepted",
            "invited_at": 1711471533,
            "expires_at": 1711471533,
            "accepted_at": 1711471533,
            "projects": [
              {
                "id": "project-xyz",
                "role": "member"
              }
            ]
          }
    InviteDeleteResponse:
      type: object
      properties:
        object:
          type: string
          enum:
            - organization.invite.deleted
          description: The object type, which is always `organization.invite.deleted`
          x-stainless-const: true
        id:
          type: string
        deleted:
          type: boolean
      required:
        - object
        - id
        - deleted
    InviteListResponse:
      type: object
      properties:
        object:
          type: string
          enum:
            - list
          description: The object type, which is always `list`
          x-stainless-const: true
        data:
          type: array
          items:
            $ref: '#/components/schemas/Invite'
        first_id:
          type: string
          description: The first `invite_id` in the retrieved `list`
        last_id:
          type: string
          description: The last `invite_id` in the retrieved `list`
        has_more:
          type: boolean
          description: The `has_more` property is used for pagination to indicate there are additional results.
      required:
        - object
        - data
    InviteRequest:
      type: object
      properties:
        email:
          type: string
          description: Send an email to this address
        role:
          type: string
          enum:
            - reader
            - owner
          description: '`owner` or `reader`'
        projects:
          type: array
          description: >-
            An array of projects to which membership is granted at the same time the org invite is accepted.
            If omitted, the user will be invited to the default project for compatibility with legacy
            behavior.
          items:
            type: object
            properties:
              id:
                type: string
                description: Project's public ID
              role:
                type: string
                enum:
                  - member
                  - owner
                description: Project membership role
            required:
              - id
              - role
      required:
        - email
        - role
    Item:
      type: object
      description: |
        Content item used to generate a response.
      oneOf:
        - $ref: '#/components/schemas/InputMessage'
        - $ref: '#/components/schemas/OutputMessage'
        - $ref: '#/components/schemas/FileSearchToolCall'
        - $ref: '#/components/schemas/ComputerToolCall'
        - $ref: '#/components/schemas/ComputerCallOutputItemParam'
        - $ref: '#/components/schemas/WebSearchToolCall'
        - $ref: '#/components/schemas/FunctionToolCall'
        - $ref: '#/components/schemas/FunctionCallOutputItemParam'
        - $ref: '#/components/schemas/ReasoningItem'
        - $ref: '#/components/schemas/ImageGenToolCall'
        - $ref: '#/components/schemas/CodeInterpreterToolCall'
        - $ref: '#/components/schemas/LocalShellToolCall'
        - $ref: '#/components/schemas/LocalShellToolCallOutput'
        - $ref: '#/components/schemas/MCPListTools'
        - $ref: '#/components/schemas/MCPApprovalRequest'
        - $ref: '#/components/schemas/MCPApprovalResponse'
        - $ref: '#/components/schemas/MCPToolCall'
      discriminator:
        propertyName: type
    ItemResource:
      description: |
        Content item used to generate a response.
      oneOf:
        - $ref: '#/components/schemas/InputMessageResource'
        - $ref: '#/components/schemas/OutputMessage'
        - $ref: '#/components/schemas/FileSearchToolCall'
        - $ref: '#/components/schemas/ComputerToolCall'
        - $ref: '#/components/schemas/ComputerToolCallOutputResource'
        - $ref: '#/components/schemas/WebSearchToolCall'
        - $ref: '#/components/schemas/FunctionToolCallResource'
        - $ref: '#/components/schemas/FunctionToolCallOutputResource'
        - $ref: '#/components/schemas/ImageGenToolCall'
        - $ref: '#/components/schemas/CodeInterpreterToolCall'
        - $ref: '#/components/schemas/LocalShellToolCall'
        - $ref: '#/components/schemas/LocalShellToolCallOutput'
        - $ref: '#/components/schemas/MCPListTools'
        - $ref: '#/components/schemas/MCPApprovalRequest'
        - $ref: '#/components/schemas/MCPApprovalResponseResource'
        - $ref: '#/components/schemas/MCPToolCall'
      discriminator:
        propertyName: type
    KeyPress:
      type: object
      title: KeyPress
      description: |
        A collection of keypresses the model would like to perform.
      properties:
        type:
          type: string
          enum:
            - keypress
          default: keypress
          description: |
            Specifies the event type. For a keypress action, this property is 
            always set to `keypress`.
          x-stainless-const: true
        keys:
          type: array
          items:
            type: string
            description: |
              One of the keys the model is requesting to be pressed.
          description: |
            The combination of keys the model is requesting to be pressed. This is an
            array of strings, each representing a key.
      required:
        - type
        - keys
    ListAssistantsResponse:
      type: object
      properties:
        object:
          type: string
          example: list
        data:
          type: array
          items:
            $ref: '#/components/schemas/AssistantObject'
        first_id:
          type: string
          example: asst_abc123
        last_id:
          type: string
          example: asst_abc456
        has_more:
          type: boolean
          example: false
      required:
        - object
        - data
        - first_id
        - last_id
        - has_more
      x-oaiMeta:
        name: List assistants response object
        group: chat
        example: |
          {
            "object": "list",
            "data": [
              {
                "id": "asst_abc123",
                "object": "assistant",
                "created_at": 1698982736,
                "name": "Coding Tutor",
                "description": null,
                "model": "gpt-4o",
                "instructions": "You are a helpful assistant designed to make me better at coding!",
                "tools": [],
                "tool_resources": {},
                "metadata": {},
                "top_p": 1.0,
                "temperature": 1.0,
                "response_format": "auto"
              },
              {
                "id": "asst_abc456",
                "object": "assistant",
                "created_at": 1698982718,
                "name": "My Assistant",
                "description": null,
                "model": "gpt-4o",
                "instructions": "You are a helpful assistant designed to make me better at coding!",
                "tools": [],
                "tool_resources": {},
                "metadata": {},
                "top_p": 1.0,
                "temperature": 1.0,
                "response_format": "auto"
              },
              {
                "id": "asst_abc789",
                "object": "assistant",
                "created_at": 1698982643,
                "name": null,
                "description": null,
                "model": "gpt-4o",
                "instructions": null,
                "tools": [],
                "tool_resources": {},
                "metadata": {},
                "top_p": 1.0,
                "temperature": 1.0,
                "response_format": "auto"
              }
            ],
            "first_id": "asst_abc123",
            "last_id": "asst_abc789",
            "has_more": false
          }
    ListAuditLogsResponse:
      type: object
      properties:
        object:
          type: string
          enum:
            - list
          x-stainless-const: true
        data:
          type: array
          items:
            $ref: '#/components/schemas/AuditLog'
        first_id:
          type: string
          example: audit_log-defb456h8dks
        last_id:
          type: string
          example: audit_log-hnbkd8s93s
        has_more:
          type: boolean
      required:
        - object
        - data
        - first_id
        - last_id
        - has_more
    ListBatchesResponse:
      type: object
      properties:
        data:
          type: array
          items:
            $ref: '#/components/schemas/Batch'
        first_id:
          type: string
          example: batch_abc123
        last_id:
          type: string
          example: batch_abc456
        has_more:
          type: boolean
        object:
          type: string
          enum:
            - list
          x-stainless-const: true
      required:
        - object
        - data
        - has_more
    ListCertificatesResponse:
      type: object
      properties:
        data:
          type: array
          items:
            $ref: '#/components/schemas/Certificate'
        first_id:
          type: string
          example: cert_abc
        last_id:
          type: string
          example: cert_abc
        has_more:
          type: boolean
        object:
          type: string
          enum:
            - list
          x-stainless-const: true
      required:
        - object
        - data
        - has_more
    ListFilesResponse:
      type: object
      properties:
        object:
          type: string
          example: list
        data:
          type: array
          items:
            $ref: '#/components/schemas/OpenAIFile'
        first_id:
          type: string
          example: file-abc123
        last_id:
          type: string
          example: file-abc456
        has_more:
          type: boolean
          example: false
      required:
        - object
        - data
        - first_id
        - last_id
        - has_more
    ListFineTuningCheckpointPermissionResponse:
      type: object
      properties:
        data:
          type: array
          items:
            $ref: '#/components/schemas/FineTuningCheckpointPermission'
        object:
          type: string
          enum:
            - list
          x-stainless-const: true
        first_id:
          type: string
          nullable: true
        last_id:
          type: string
          nullable: true
        has_more:
          type: boolean
      required:
        - object
        - data
        - has_more
    ListFineTuningJobCheckpointsResponse:
      type: object
      properties:
        data:
          type: array
          items:
            $ref: '#/components/schemas/FineTuningJobCheckpoint'
        object:
          type: string
          enum:
            - list
          x-stainless-const: true
        first_id:
          type: string
          nullable: true
        last_id:
          type: string
          nullable: true
        has_more:
          type: boolean
      required:
        - object
        - data
        - has_more
    ListFineTuningJobEventsResponse:
      type: object
      properties:
        data:
          type: array
          items:
            $ref: '#/components/schemas/FineTuningJobEvent'
        object:
          type: string
          enum:
            - list
          x-stainless-const: true
        has_more:
          type: boolean
      required:
        - object
        - data
        - has_more
    ListMessagesResponse:
      properties:
        object:
          type: string
          example: list
        data:
          type: array
          items:
            $ref: '#/components/schemas/MessageObject'
        first_id:
          type: string
          example: msg_abc123
        last_id:
          type: string
          example: msg_abc123
        has_more:
          type: boolean
          example: false
      required:
        - object
        - data
        - first_id
        - last_id
        - has_more
    ListModelsResponse:
      type: object
      properties:
        object:
          type: string
          enum:
            - list
          x-stainless-const: true
        data:
          type: array
          items:
            $ref: '#/components/schemas/Model'
      required:
        - object
        - data
    ListPaginatedFineTuningJobsResponse:
      type: object
      properties:
        data:
          type: array
          items:
            $ref: '#/components/schemas/FineTuningJob'
        has_more:
          type: boolean
        object:
          type: string
          enum:
            - list
          x-stainless-const: true
      required:
        - object
        - data
        - has_more
    ListRunStepsResponse:
      properties:
        object:
          type: string
          example: list
        data:
          type: array
          items:
            $ref: '#/components/schemas/RunStepObject'
        first_id:
          type: string
          example: step_abc123
        last_id:
          type: string
          example: step_abc456
        has_more:
          type: boolean
          example: false
      required:
        - object
        - data
        - first_id
        - last_id
        - has_more
    ListRunsResponse:
      type: object
      properties:
        object:
          type: string
          example: list
        data:
          type: array
          items:
            $ref: '#/components/schemas/RunObject'
        first_id:
          type: string
          example: run_abc123
        last_id:
          type: string
          example: run_abc456
        has_more:
          type: boolean
          example: false
      required:
        - object
        - data
        - first_id
        - last_id
        - has_more
    ListVectorStoreFilesResponse:
      properties:
        object:
          type: string
          example: list
        data:
          type: array
          items:
            $ref: '#/components/schemas/VectorStoreFileObject'
        first_id:
          type: string
          example: file-abc123
        last_id:
          type: string
          example: file-abc456
        has_more:
          type: boolean
          example: false
      required:
        - object
        - data
        - first_id
        - last_id
        - has_more
    ListVectorStoresResponse:
      properties:
        object:
          type: string
          example: list
        data:
          type: array
          items:
            $ref: '#/components/schemas/VectorStoreObject'
        first_id:
          type: string
          example: vs_abc123
        last_id:
          type: string
          example: vs_abc456
        has_more:
          type: boolean
          example: false
      required:
        - object
        - data
        - first_id
        - last_id
        - has_more
    LocalShellExecAction:
      type: object
      title: Local shell exec action
      description: |
        Execute a shell command on the server.
      properties:
        type:
          type: string
          enum:
            - exec
          description: |
            The type of the local shell action. Always `exec`.
          x-stainless-const: true
        command:
          type: array
          items:
            type: string
          description: |
            The command to run.
        timeout_ms:
          type: integer
          description: |
            Optional timeout in milliseconds for the command.
          nullable: true
        working_directory:
          type: string
          description: |
            Optional working directory to run the command in.
          nullable: true
        env:
          type: object
          additionalProperties:
            type: string
          description: |
            Environment variables to set for the command.
        user:
          type: string
          description: |
            Optional user to run the command as.
          nullable: true
      required:
        - type
        - command
        - env
    LocalShellTool:
      type: object
      title: Local shell tool
      description: |
        A tool that allows the model to execute shell commands in a local environment.
      properties:
        type:
          type: string
          enum:
            - local_shell
          description: The type of the local shell tool. Always `local_shell`.
          x-stainless-const: true
      required:
        - type
    LocalShellToolCall:
      type: object
      title: Local shell call
      description: |
        A tool call to run a command on the local shell.
      properties:
        type:
          type: string
          enum:
            - local_shell_call
          description: |
            The type of the local shell call. Always `local_shell_call`.
          x-stainless-const: true
        id:
          type: string
          description: |
            The unique ID of the local shell call.
        call_id:
          type: string
          description: |
            The unique ID of the local shell tool call generated by the model.
        action:
          $ref: '#/components/schemas/LocalShellExecAction'
        status:
          type: string
          enum:
            - in_progress
            - completed
            - incomplete
          description: |
            The status of the local shell call.
      required:
        - type
        - id
        - call_id
        - action
        - status
    LocalShellToolCallOutput:
      type: object
      title: Local shell call output
      description: |
        The output of a local shell tool call.
      properties:
        type:
          type: string
          enum:
            - local_shell_call_output
          description: |
            The type of the local shell tool call output. Always `local_shell_call_output`.
          x-stainless-const: true
        id:
          type: string
          description: |
            The unique ID of the local shell tool call generated by the model.
        output:
          type: string
          description: |
            A JSON string of the output of the local shell tool call.
        status:
          type: string
          enum:
            - in_progress
            - completed
            - incomplete
          description: |
            The status of the item. One of `in_progress`, `completed`, or `incomplete`.
          nullable: true
      required:
        - id
        - type
        - call_id
        - output
    LogProbProperties:
      type: object
      description: |
        A log probability object.
      properties:
        token:
          type: string
          description: |
            The token that was used to generate the log probability.
        logprob:
          type: number
          description: |
            The log probability of the token.
        bytes:
          type: array
          items:
            type: integer
          description: |
            The bytes that were used to generate the log probability.
      required:
        - token
        - logprob
        - bytes
    MCPApprovalRequest:
      type: object
      title: MCP approval request
      description: |
        A request for human approval of a tool invocation.
      properties:
        type:
          type: string
          enum:
            - mcp_approval_request
          description: |
            The type of the item. Always `mcp_approval_request`.
          x-stainless-const: true
        id:
          type: string
          description: |
            The unique ID of the approval request.
        server_label:
          type: string
          description: |
            The label of the MCP server making the request.
        name:
          type: string
          description: |
            The name of the tool to run.
        arguments:
          type: string
          description: |
            A JSON string of arguments for the tool.
      required:
        - type
        - id
        - server_label
        - name
        - arguments
    MCPApprovalResponse:
      type: object
      title: MCP approval response
      description: |
        A response to an MCP approval request.
      properties:
        type:
          type: string
          enum:
            - mcp_approval_response
          description: |
            The type of the item. Always `mcp_approval_response`.
          x-stainless-const: true
        id:
          type: string
          description: |
            The unique ID of the approval response
          nullable: true
        approval_request_id:
          type: string
          description: |
            The ID of the approval request being answered.
        approve:
          type: boolean
          description: |
            Whether the request was approved.
        reason:
          type: string
          description: |
            Optional reason for the decision.
          nullable: true
      required:
        - type
        - request_id
        - approve
        - approval_request_id
    MCPApprovalResponseResource:
      type: object
      title: MCP approval response
      description: |
        A response to an MCP approval request.
      properties:
        type:
          type: string
          enum:
            - mcp_approval_response
          description: |
            The type of the item. Always `mcp_approval_response`.
          x-stainless-const: true
        id:
          type: string
          description: |
            The unique ID of the approval response
        approval_request_id:
          type: string
          description: |
            The ID of the approval request being answered.
        approve:
          type: boolean
          description: |
            Whether the request was approved.
        reason:
          type: string
          description: |
            Optional reason for the decision.
          nullable: true
      required:
        - type
        - id
        - request_id
        - approve
        - approval_request_id
    MCPListTools:
      type: object
      title: MCP list tools
      description: |
        A list of tools available on an MCP server.
      properties:
        type:
          type: string
          enum:
            - mcp_list_tools
          description: |
            The type of the item. Always `mcp_list_tools`.
          x-stainless-const: true
        id:
          type: string
          description: |
            The unique ID of the list.
        server_label:
          type: string
          description: |
            The label of the MCP server.
        tools:
          type: array
          items:
            $ref: '#/components/schemas/MCPListToolsTool'
          description: |
            The tools available on the server.
        error:
          type: string
          description: |
            Error message if the server could not list tools.
          nullable: true
      required:
        - type
        - id
        - server_label
        - tools
    MCPListToolsTool:
      type: object
      title: MCP list tools tool
      description: |
        A tool available on an MCP server.
      properties:
        name:
          type: string
          description: |
            The name of the tool.
        description:
          type: string
          description: |
            The description of the tool.
          nullable: true
        input_schema:
          type: object
          description: |
            The JSON schema describing the tool's input.
        annotations:
          type: object
          description: |
            Additional annotations about the tool.
          nullable: true
      required:
        - name
        - input_schema
    MCPTool:
      type: object
      title: MCP tool
      description: |
        Give the model access to additional tools via remote Model Context Protocol 
        (MCP) servers. [Learn more about MCP](/docs/guides/tools-remote-mcp).
      properties:
        type:
          type: string
          enum:
            - mcp
          description: The type of the MCP tool. Always `mcp`.
          x-stainless-const: true
        server_label:
          type: string
          description: |
            A label for this MCP server, used to identify it in tool calls.
        server_url:
          type: string
          description: |
            The URL for the MCP server.
        headers:
          type: object
          additionalProperties:
            type: string
          nullable: true
          description: |
            Optional HTTP headers to send to the MCP server. Use for authentication
            or other purposes.
        allowed_tools:
          description: |
            List of allowed tool names or a filter object.
          oneOf:
            - type: array
              title: MCP allowed tools
              description: A string array of allowed tool names
              items:
                type: string
            - type: object
              title: MCP allowed tools filter
              description: |
                A filter object to specify which tools are allowed.
              properties:
                tool_names:
                  type: array
                  title: MCP allowed tools
                  items:
                    type: string
                  description: List of allowed tool names.
              required: []
              additionalProperties: false
          nullable: true
        require_approval:
          description: Specify which of the MCP server's tools require approval.
          oneOf:
            - type: object
              title: MCP tool approval filter
              properties:
                always:
                  type: object
                  description: |
                    A list of tools that always require approval.
                  properties:
                    tool_names:
                      type: array
                      items:
                        type: string
                      description: List of tools that require approval.
                never:
                  type: object
                  description: |
                    A list of tools that never require approval.
                  properties:
                    tool_names:
                      type: array
                      items:
                        type: string
                      description: List of tools that do not require approval.
              additionalProperties: false
            - type: string
              title: MCP tool approval setting
              description: |
                Specify a single approval policy for all tools. One of `always` or 
                `never`. When set to `always`, all tools will require approval. When 
                set to `never`, all tools will not require approval.
              enum:
                - always
                - never
          default: always
          nullable: true
      required:
        - type
        - server_label
        - server_url
    MCPToolCall:
      type: object
      title: MCP tool call
      description: |
        An invocation of a tool on an MCP server.
      properties:
        type:
          type: string
          enum:
            - mcp_call
          description: |
            The type of the item. Always `mcp_call`.
          x-stainless-const: true
        id:
          type: string
          description: |
            The unique ID of the tool call.
        server_label:
          type: string
          description: |
            The label of the MCP server running the tool.
        name:
          type: string
          description: |
            The name of the tool that was run.
        arguments:
          type: string
          description: |
            A JSON string of the arguments passed to the tool.
        output:
          type: string
          description: |
            The output from the tool call.
          nullable: true
        error:
          type: string
          description: |
            The error from the tool call, if any.
          nullable: true
      required:
        - type
        - id
        - server_label
        - name
        - arguments
    MessageContentImageFileObject:
      title: Image file
      type: object
      description: References an image [File](/docs/api-reference/files) in the content of a message.
      properties:
        type:
          description: Always `image_file`.
          type: string
          enum:
            - image_file
          x-stainless-const: true
        image_file:
          type: object
          properties:
            file_id:
              description: >-
                The [File](/docs/api-reference/files) ID of the image in the message content. Set
                `purpose="vision"` when uploading the File if you need to later display the file content.
              type: string
            detail:
              type: string
              description: >-
                Specifies the detail level of the image if specified by the user. `low` uses fewer tokens, you
                can opt in to high resolution using `high`.
              enum:
                - auto
                - low
                - high
              default: auto
          required:
            - file_id
      required:
        - type
        - image_file
    MessageContentImageUrlObject:
      title: Image URL
      type: object
      description: References an image URL in the content of a message.
      properties:
        type:
          type: string
          enum:
            - image_url
          description: The type of the content part.
          x-stainless-const: true
        image_url:
          type: object
          properties:
            url:
              type: string
              description: 'The external URL of the image, must be a supported image types: jpeg, jpg, png, gif, webp.'
              format: uri
            detail:
              type: string
              description: >-
                Specifies the detail level of the image. `low` uses fewer tokens, you can opt in to high
                resolution using `high`. Default value is `auto`
              enum:
                - auto
                - low
                - high
              default: auto
          required:
            - url
      required:
        - type
        - image_url
    MessageContentRefusalObject:
      title: Refusal
      type: object
      description: The refusal content generated by the assistant.
      properties:
        type:
          description: Always `refusal`.
          type: string
          enum:
            - refusal
          x-stainless-const: true
        refusal:
          type: string
          nullable: false
      required:
        - type
        - refusal
    MessageContentTextAnnotationsFileCitationObject:
      title: File citation
      type: object
      description: >-
        A citation within the message that points to a specific quote from a specific File associated with the
        assistant or the message. Generated when the assistant uses the "file_search" tool to search files.
      properties:
        type:
          description: Always `file_citation`.
          type: string
          enum:
            - file_citation
          x-stainless-const: true
        text:
          description: The text in the message content that needs to be replaced.
          type: string
        file_citation:
          type: object
          properties:
            file_id:
              description: The ID of the specific File the citation is from.
              type: string
          required:
            - file_id
        start_index:
          type: integer
          minimum: 0
        end_index:
          type: integer
          minimum: 0
      required:
        - type
        - text
        - file_citation
        - start_index
        - end_index
    MessageContentTextAnnotationsFilePathObject:
      title: File path
      type: object
      description: >-
        A URL for the file that's generated when the assistant used the `code_interpreter` tool to generate a
        file.
      properties:
        type:
          description: Always `file_path`.
          type: string
          enum:
            - file_path
          x-stainless-const: true
        text:
          description: The text in the message content that needs to be replaced.
          type: string
        file_path:
          type: object
          properties:
            file_id:
              description: The ID of the file that was generated.
              type: string
          required:
            - file_id
        start_index:
          type: integer
          minimum: 0
        end_index:
          type: integer
          minimum: 0
      required:
        - type
        - text
        - file_path
        - start_index
        - end_index
    MessageContentTextObject:
      title: Text
      type: object
      description: The text content that is part of a message.
      properties:
        type:
          description: Always `text`.
          type: string
          enum:
            - text
          x-stainless-const: true
        text:
          type: object
          properties:
            value:
              description: The data that makes up the text.
              type: string
            annotations:
              type: array
              items:
                oneOf:
                  - $ref: '#/components/schemas/MessageContentTextAnnotationsFileCitationObject'
                  - $ref: '#/components/schemas/MessageContentTextAnnotationsFilePathObject'
          required:
            - value
            - annotations
      required:
        - type
        - text
    MessageDeltaContentImageFileObject:
      title: Image file
      type: object
      description: References an image [File](/docs/api-reference/files) in the content of a message.
      properties:
        index:
          type: integer
          description: The index of the content part in the message.
        type:
          description: Always `image_file`.
          type: string
          enum:
            - image_file
          x-stainless-const: true
        image_file:
          type: object
          properties:
            file_id:
              description: >-
                The [File](/docs/api-reference/files) ID of the image in the message content. Set
                `purpose="vision"` when uploading the File if you need to later display the file content.
              type: string
            detail:
              type: string
              description: >-
                Specifies the detail level of the image if specified by the user. `low` uses fewer tokens, you
                can opt in to high resolution using `high`.
              enum:
                - auto
                - low
                - high
              default: auto
      required:
        - index
        - type
    MessageDeltaContentImageUrlObject:
      title: Image URL
      type: object
      description: References an image URL in the content of a message.
      properties:
        index:
          type: integer
          description: The index of the content part in the message.
        type:
          description: Always `image_url`.
          type: string
          enum:
            - image_url
          x-stainless-const: true
        image_url:
          type: object
          properties:
            url:
              description: 'The URL of the image, must be a supported image types: jpeg, jpg, png, gif, webp.'
              type: string
            detail:
              type: string
              description: >-
                Specifies the detail level of the image. `low` uses fewer tokens, you can opt in to high
                resolution using `high`.
              enum:
                - auto
                - low
                - high
              default: auto
      required:
        - index
        - type
    MessageDeltaContentRefusalObject:
      title: Refusal
      type: object
      description: The refusal content that is part of a message.
      properties:
        index:
          type: integer
          description: The index of the refusal part in the message.
        type:
          description: Always `refusal`.
          type: string
          enum:
            - refusal
          x-stainless-const: true
        refusal:
          type: string
      required:
        - index
        - type
    MessageDeltaContentTextAnnotationsFileCitationObject:
      title: File citation
      type: object
      description: >-
        A citation within the message that points to a specific quote from a specific File associated with the
        assistant or the message. Generated when the assistant uses the "file_search" tool to search files.
      properties:
        index:
          type: integer
          description: The index of the annotation in the text content part.
        type:
          description: Always `file_citation`.
          type: string
          enum:
            - file_citation
          x-stainless-const: true
        text:
          description: The text in the message content that needs to be replaced.
          type: string
        file_citation:
          type: object
          properties:
            file_id:
              description: The ID of the specific File the citation is from.
              type: string
            quote:
              description: The specific quote in the file.
              type: string
        start_index:
          type: integer
          minimum: 0
        end_index:
          type: integer
          minimum: 0
      required:
        - index
        - type
    MessageDeltaContentTextAnnotationsFilePathObject:
      title: File path
      type: object
      description: >-
        A URL for the file that's generated when the assistant used the `code_interpreter` tool to generate a
        file.
      properties:
        index:
          type: integer
          description: The index of the annotation in the text content part.
        type:
          description: Always `file_path`.
          type: string
          enum:
            - file_path
          x-stainless-const: true
        text:
          description: The text in the message content that needs to be replaced.
          type: string
        file_path:
          type: object
          properties:
            file_id:
              description: The ID of the file that was generated.
              type: string
        start_index:
          type: integer
          minimum: 0
        end_index:
          type: integer
          minimum: 0
      required:
        - index
        - type
    MessageDeltaContentTextObject:
      title: Text
      type: object
      description: The text content that is part of a message.
      properties:
        index:
          type: integer
          description: The index of the content part in the message.
        type:
          description: Always `text`.
          type: string
          enum:
            - text
          x-stainless-const: true
        text:
          type: object
          properties:
            value:
              description: The data that makes up the text.
              type: string
            annotations:
              type: array
              items:
                oneOf:
                  - $ref: '#/components/schemas/MessageDeltaContentTextAnnotationsFileCitationObject'
                  - $ref: '#/components/schemas/MessageDeltaContentTextAnnotationsFilePathObject'
      required:
        - index
        - type
    MessageDeltaObject:
      type: object
      title: Message delta object
      description: |
        Represents a message delta i.e. any changed fields on a message during streaming.
      properties:
        id:
          description: The identifier of the message, which can be referenced in API endpoints.
          type: string
        object:
          description: The object type, which is always `thread.message.delta`.
          type: string
          enum:
            - thread.message.delta
          x-stainless-const: true
        delta:
          description: The delta containing the fields that have changed on the Message.
          type: object
          properties:
            role:
              description: The entity that produced the message. One of `user` or `assistant`.
              type: string
              enum:
                - user
                - assistant
            content:
              description: The content of the message in array of text and/or images.
              type: array
              items:
                oneOf:
                  - $ref: '#/components/schemas/MessageDeltaContentImageFileObject'
                  - $ref: '#/components/schemas/MessageDeltaContentTextObject'
                  - $ref: '#/components/schemas/MessageDeltaContentRefusalObject'
                  - $ref: '#/components/schemas/MessageDeltaContentImageUrlObject'
      required:
        - id
        - object
        - delta
      x-oaiMeta:
        name: The message delta object
        beta: true
        example: |
          {
            "id": "msg_123",
            "object": "thread.message.delta",
            "delta": {
              "content": [
                {
                  "index": 0,
                  "type": "text",
                  "text": { "value": "Hello", "annotations": [] }
                }
              ]
            }
          }
    MessageObject:
      type: object
      title: The message object
      description: Represents a message within a [thread](/docs/api-reference/threads).
      properties:
        id:
          description: The identifier, which can be referenced in API endpoints.
          type: string
        object:
          description: The object type, which is always `thread.message`.
          type: string
          enum:
            - thread.message
          x-stainless-const: true
        created_at:
          description: The Unix timestamp (in seconds) for when the message was created.
          type: integer
        thread_id:
          description: The [thread](/docs/api-reference/threads) ID that this message belongs to.
          type: string
        status:
          description: The status of the message, which can be either `in_progress`, `incomplete`, or `completed`.
          type: string
          enum:
            - in_progress
            - incomplete
            - completed
        incomplete_details:
          description: On an incomplete message, details about why the message is incomplete.
          type: object
          properties:
            reason:
              type: string
              description: The reason the message is incomplete.
              enum:
                - content_filter
                - max_tokens
                - run_cancelled
                - run_expired
                - run_failed
          nullable: true
          required:
            - reason
        completed_at:
          description: The Unix timestamp (in seconds) for when the message was completed.
          type: integer
          nullable: true
        incomplete_at:
          description: The Unix timestamp (in seconds) for when the message was marked as incomplete.
          type: integer
          nullable: true
        role:
          description: The entity that produced the message. One of `user` or `assistant`.
          type: string
          enum:
            - user
            - assistant
        content:
          description: The content of the message in array of text and/or images.
          type: array
          items:
            oneOf:
              - $ref: '#/components/schemas/MessageContentImageFileObject'
              - $ref: '#/components/schemas/MessageContentImageUrlObject'
              - $ref: '#/components/schemas/MessageContentTextObject'
              - $ref: '#/components/schemas/MessageContentRefusalObject'
        assistant_id:
          description: >-
            If applicable, the ID of the [assistant](/docs/api-reference/assistants) that authored this
            message.
          type: string
          nullable: true
        run_id:
          description: >-
            The ID of the [run](/docs/api-reference/runs) associated with the creation of this message. Value
            is `null` when messages are created manually using the create message or create thread endpoints.
          type: string
          nullable: true
        attachments:
          type: array
          items:
            type: object
            properties:
              file_id:
                type: string
                description: The ID of the file to attach to the message.
              tools:
                description: The tools to add this file to.
                type: array
                items:
                  oneOf:
                    - $ref: '#/components/schemas/AssistantToolsCode'
                    - $ref: '#/components/schemas/AssistantToolsFileSearchTypeOnly'
          description: A list of files attached to the message, and the tools they were added to.
          nullable: true
        metadata:
          $ref: '#/components/schemas/Metadata'
      required:
        - id
        - object
        - created_at
        - thread_id
        - status
        - incomplete_details
        - completed_at
        - incomplete_at
        - role
        - content
        - assistant_id
        - run_id
        - attachments
        - metadata
      x-oaiMeta:
        name: The message object
        beta: true
        example: |
          {
            "id": "msg_abc123",
            "object": "thread.message",
            "created_at": 1698983503,
            "thread_id": "thread_abc123",
            "role": "assistant",
            "content": [
              {
                "type": "text",
                "text": {
                  "value": "Hi! How can I help you today?",
                  "annotations": []
                }
              }
            ],
            "assistant_id": "asst_abc123",
            "run_id": "run_abc123",
            "attachments": [],
            "metadata": {}
          }
    MessageRequestContentTextObject:
      title: Text
      type: object
      description: The text content that is part of a message.
      properties:
        type:
          description: Always `text`.
          type: string
          enum:
            - text
          x-stainless-const: true
        text:
          type: string
          description: Text content to be sent to the model
      required:
        - type
        - text
    MessageStreamEvent:
      oneOf:
        - type: object
          properties:
            event:
              type: string
              enum:
                - thread.message.created
              x-stainless-const: true
            data:
              $ref: '#/components/schemas/MessageObject'
          required:
            - event
            - data
          description: Occurs when a [message](/docs/api-reference/messages/object) is created.
          x-oaiMeta:
            dataDescription: '`data` is a [message](/docs/api-reference/messages/object)'
        - type: object
          properties:
            event:
              type: string
              enum:
                - thread.message.in_progress
              x-stainless-const: true
            data:
              $ref: '#/components/schemas/MessageObject'
          required:
            - event
            - data
          description: Occurs when a [message](/docs/api-reference/messages/object) moves to an `in_progress` state.
          x-oaiMeta:
            dataDescription: '`data` is a [message](/docs/api-reference/messages/object)'
        - type: object
          properties:
            event:
              type: string
              enum:
                - thread.message.delta
              x-stainless-const: true
            data:
              $ref: '#/components/schemas/MessageDeltaObject'
          required:
            - event
            - data
          description: Occurs when parts of a [Message](/docs/api-reference/messages/object) are being streamed.
          x-oaiMeta:
            dataDescription: '`data` is a [message delta](/docs/api-reference/assistants-streaming/message-delta-object)'
        - type: object
          properties:
            event:
              type: string
              enum:
                - thread.message.completed
              x-stainless-const: true
            data:
              $ref: '#/components/schemas/MessageObject'
          required:
            - event
            - data
          description: Occurs when a [message](/docs/api-reference/messages/object) is completed.
          x-oaiMeta:
            dataDescription: '`data` is a [message](/docs/api-reference/messages/object)'
        - type: object
          properties:
            event:
              type: string
              enum:
                - thread.message.incomplete
              x-stainless-const: true
            data:
              $ref: '#/components/schemas/MessageObject'
          required:
            - event
            - data
          description: Occurs when a [message](/docs/api-reference/messages/object) ends before it is completed.
          x-oaiMeta:
            dataDescription: '`data` is a [message](/docs/api-reference/messages/object)'
    Metadata:
      type: object
      description: |
        Set of 16 key-value pairs that can be attached to an object. This can be
        useful for storing additional information about the object in a structured
        format, and querying for objects via API or the dashboard. 

        Keys are strings with a maximum length of 64 characters. Values are strings
        with a maximum length of 512 characters.
      additionalProperties:
        type: string
      x-oaiTypeLabel: map
      nullable: true
    Model:
      title: Model
      description: Describes an OpenAI model offering that can be used with the API.
      properties:
        id:
          type: string
          description: The model identifier, which can be referenced in the API endpoints.
        created:
          type: integer
          description: The Unix timestamp (in seconds) when the model was created.
        object:
          type: string
          description: The object type, which is always "model".
          enum:
            - model
          x-stainless-const: true
        owned_by:
          type: string
          description: The organization that owns the model.
      required:
        - id
        - object
        - created
        - owned_by
      x-oaiMeta:
        name: The model object
        example: |
          {
            "id": "VAR_chat_model_id",
            "object": "model",
            "created": 1686935002,
            "owned_by": "openai"
          }
    ModelIds:
      anyOf:
        - $ref: '#/components/schemas/ModelIdsShared'
        - $ref: '#/components/schemas/ModelIdsResponses'
    ModelIdsResponses:
      example: gpt-4o
      anyOf:
        - $ref: '#/components/schemas/ModelIdsShared'
        - type: string
          title: ResponsesOnlyModel
          enum:
            - o1-pro
            - o1-pro-2025-03-19
            - o3-pro
            - o3-pro-2025-06-10
            - computer-use-preview
            - computer-use-preview-2025-03-11
    ModelIdsShared:
      example: gpt-4o
      anyOf:
        - type: string
        - type: string
          enum:
            - gpt-4.1
            - gpt-4.1-mini
            - gpt-4.1-nano
            - gpt-4.1-2025-04-14
            - gpt-4.1-mini-2025-04-14
            - gpt-4.1-nano-2025-04-14
            - o4-mini
            - o4-mini-2025-04-16
            - o3
            - o3-2025-04-16
            - o3-mini
            - o3-mini-2025-01-31
            - o1
            - o1-2024-12-17
            - o1-preview
            - o1-preview-2024-09-12
            - o1-mini
            - o1-mini-2024-09-12
            - gpt-4o
            - gpt-4o-2024-11-20
            - gpt-4o-2024-08-06
            - gpt-4o-2024-05-13
            - gpt-4o-audio-preview
            - gpt-4o-audio-preview-2024-10-01
            - gpt-4o-audio-preview-2024-12-17
            - gpt-4o-audio-preview-2025-06-03
            - gpt-4o-mini-audio-preview
            - gpt-4o-mini-audio-preview-2024-12-17
            - gpt-4o-search-preview
            - gpt-4o-mini-search-preview
            - gpt-4o-search-preview-2025-03-11
            - gpt-4o-mini-search-preview-2025-03-11
            - chatgpt-4o-latest
            - codex-mini-latest
            - gpt-4o-mini
            - gpt-4o-mini-2024-07-18
            - gpt-4-turbo
            - gpt-4-turbo-2024-04-09
            - gpt-4-0125-preview
            - gpt-4-turbo-preview
            - gpt-4-1106-preview
            - gpt-4-vision-preview
            - gpt-4
            - gpt-4-0314
            - gpt-4-0613
            - gpt-4-32k
            - gpt-4-32k-0314
            - gpt-4-32k-0613
            - gpt-3.5-turbo
            - gpt-3.5-turbo-16k
            - gpt-3.5-turbo-0301
            - gpt-3.5-turbo-0613
            - gpt-3.5-turbo-1106
            - gpt-3.5-turbo-0125
            - gpt-3.5-turbo-16k-0613
    ModelResponseProperties:
      type: object
      properties:
        metadata:
          $ref: '#/components/schemas/Metadata'
        temperature:
          type: number
          minimum: 0
          maximum: 2
          default: 1
          example: 1
          nullable: true
          description: >
            What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output
            more random, while lower values like 0.2 will make it more focused and deterministic.

            We generally recommend altering this or `top_p` but not both.
        top_p:
          type: number
          minimum: 0
          maximum: 1
          default: 1
          example: 1
          nullable: true
          description: |
            An alternative to sampling with temperature, called nucleus sampling,
            where the model considers the results of the tokens with top_p probability
            mass. So 0.1 means only the tokens comprising the top 10% probability mass
            are considered.

            We generally recommend altering this or `temperature` but not both.
        user:
          type: string
          example: user-1234
          description: >
            A stable identifier for your end-users. 

            Used to boost cache hit rates by better bucketing similar requests and  to help OpenAI detect and
            prevent abuse. [Learn more](/docs/guides/safety-best-practices#end-user-ids).
        service_tier:
          $ref: '#/components/schemas/ServiceTier'
    ModifyAssistantRequest:
      type: object
      additionalProperties: false
      properties:
        model:
          description: >
            ID of the model to use. You can use the [List models](/docs/api-reference/models/list) API to see
            all of your available models, or see our [Model overview](/docs/models) for descriptions of them.
          anyOf:
            - type: string
            - $ref: '#/components/schemas/AssistantSupportedModels'
        reasoning_effort:
          $ref: '#/components/schemas/ReasoningEffort'
        name:
          description: |
            The name of the assistant. The maximum length is 256 characters.
          type: string
          nullable: true
          maxLength: 256
        description:
          description: |
            The description of the assistant. The maximum length is 512 characters.
          type: string
          nullable: true
          maxLength: 512
        instructions:
          description: |
            The system instructions that the assistant uses. The maximum length is 256,000 characters.
          type: string
          nullable: true
          maxLength: 256000
        tools:
          description: >
            A list of tool enabled on the assistant. There can be a maximum of 128 tools per assistant. Tools
            can be of types `code_interpreter`, `file_search`, or `function`.
          default: []
          type: array
          maxItems: 128
          items:
            oneOf:
              - $ref: '#/components/schemas/AssistantToolsCode'
              - $ref: '#/components/schemas/AssistantToolsFileSearch'
              - $ref: '#/components/schemas/AssistantToolsFunction'
        tool_resources:
          type: object
          description: >
            A set of resources that are used by the assistant's tools. The resources are specific to the type
            of tool. For example, the `code_interpreter` tool requires a list of file IDs, while the
            `file_search` tool requires a list of vector store IDs.
          properties:
            code_interpreter:
              type: object
              properties:
                file_ids:
                  type: array
                  description: >
                    Overrides the list of [file](/docs/api-reference/files) IDs made available to the
                    `code_interpreter` tool. There can be a maximum of 20 files associated with the tool.
                  default: []
                  maxItems: 20
                  items:
                    type: string
            file_search:
              type: object
              properties:
                vector_store_ids:
                  type: array
                  description: >
                    Overrides the [vector store](/docs/api-reference/vector-stores/object) attached to this
                    assistant. There can be a maximum of 1 vector store attached to the assistant.
                  maxItems: 1
                  items:
                    type: string
          nullable: true
        metadata:
          $ref: '#/components/schemas/Metadata'
        temperature:
          description: >
            What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output
            more random, while lower values like 0.2 will make it more focused and deterministic.
          type: number
          minimum: 0
          maximum: 2
          default: 1
          example: 1
          nullable: true
        top_p:
          type: number
          minimum: 0
          maximum: 1
          default: 1
          example: 1
          nullable: true
          description: >
            An alternative to sampling with temperature, called nucleus sampling, where the model considers
            the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the
            top 10% probability mass are considered.


            We generally recommend altering this or temperature but not both.
        response_format:
          $ref: '#/components/schemas/AssistantsApiResponseFormatOption'
          nullable: true
    ModifyCertificateRequest:
      type: object
      properties:
        name:
          type: string
          description: The updated name for the certificate
      required:
        - name
    ModifyMessageRequest:
      type: object
      additionalProperties: false
      properties:
        metadata:
          $ref: '#/components/schemas/Metadata'
    ModifyRunRequest:
      type: object
      additionalProperties: false
      properties:
        metadata:
          $ref: '#/components/schemas/Metadata'
    ModifyThreadRequest:
      type: object
      additionalProperties: false
      properties:
        tool_resources:
          type: object
          description: >
            A set of resources that are made available to the assistant's tools in this thread. The resources
            are specific to the type of tool. For example, the `code_interpreter` tool requires a list of file
            IDs, while the `file_search` tool requires a list of vector store IDs.
          properties:
            code_interpreter:
              type: object
              properties:
                file_ids:
                  type: array
                  description: >
                    A list of [file](/docs/api-reference/files) IDs made available to the `code_interpreter`
                    tool. There can be a maximum of 20 files associated with the tool.
                  default: []
                  maxItems: 20
                  items:
                    type: string
            file_search:
              type: object
              properties:
                vector_store_ids:
                  type: array
                  description: >
                    The [vector store](/docs/api-reference/vector-stores/object) attached to this thread.
                    There can be a maximum of 1 vector store attached to the thread.
                  maxItems: 1
                  items:
                    type: string
          nullable: true
        metadata:
          $ref: '#/components/schemas/Metadata'
    Move:
      type: object
      title: Move
      description: |
        A mouse move action.
      properties:
        type:
          type: string
          enum:
            - move
          default: move
          description: |
            Specifies the event type. For a move action, this property is 
            always set to `move`.
          x-stainless-const: true
        x:
          type: integer
          description: |
            The x-coordinate to move to.
        'y':
          type: integer
          description: |
            The y-coordinate to move to.
      required:
        - type
        - x
        - 'y'
    OpenAIFile:
      title: OpenAIFile
      description: The `File` object represents a document that has been uploaded to OpenAI.
      properties:
        id:
          type: string
          description: The file identifier, which can be referenced in the API endpoints.
        bytes:
          type: integer
          description: The size of the file, in bytes.
        created_at:
          type: integer
          description: The Unix timestamp (in seconds) for when the file was created.
        expires_at:
          type: integer
          description: The Unix timestamp (in seconds) for when the file will expire.
        filename:
          type: string
          description: The name of the file.
        object:
          type: string
          description: The object type, which is always `file`.
          enum:
            - file
          x-stainless-const: true
        purpose:
          type: string
          description: >-
            The intended purpose of the file. Supported values are `assistants`, `assistants_output`, `batch`,
            `batch_output`, `fine-tune`, `fine-tune-results` and `vision`.
          enum:
            - assistants
            - assistants_output
            - batch
            - batch_output
            - fine-tune
            - fine-tune-results
            - vision
        status:
          type: string
          deprecated: true
          description: >-
            Deprecated. The current status of the file, which can be either `uploaded`, `processed`, or
            `error`.
          enum:
            - uploaded
            - processed
            - error
        status_details:
          type: string
          deprecated: true
          description: >-
            Deprecated. For details on why a fine-tuning training file failed validation, see the `error`
            field on `fine_tuning.job`.
      required:
        - id
        - object
        - bytes
        - created_at
        - filename
        - purpose
        - status
      x-oaiMeta:
        name: The file object
        example: |
          {
            "id": "file-abc123",
            "object": "file",
            "bytes": 120000,
            "created_at": 1677610602,
            "expires_at": 1680202602,
            "filename": "salesOverview.pdf",
            "purpose": "assistants",
          }
    OtherChunkingStrategyResponseParam:
      type: object
      title: Other Chunking Strategy
      description: >-
        This is returned when the chunking strategy is unknown. Typically, this is because the file was
        indexed before the `chunking_strategy` concept was introduced in the API.
      additionalProperties: false
      properties:
        type:
          type: string
          description: Always `other`.
          enum:
            - other
          x-stainless-const: true
      required:
        - type
    OutputAudio:
      type: object
      title: Output audio
      description: |
        An audio output from the model.
      properties:
        type:
          type: string
          description: |
            The type of the output audio. Always `output_audio`.
          enum:
            - output_audio
          x-stainless-const: true
        data:
          type: string
          description: |
            Base64-encoded audio data from the model.
        transcript:
          type: string
          description: |
            The transcript of the audio data from the model.
      required:
        - type
        - data
        - transcript
    OutputContent:
      oneOf:
        - $ref: '#/components/schemas/OutputTextContent'
        - $ref: '#/components/schemas/RefusalContent'
    OutputItem:
      anyOf:
        - $ref: '#/components/schemas/OutputMessage'
        - $ref: '#/components/schemas/FileSearchToolCall'
        - $ref: '#/components/schemas/FunctionToolCall'
        - $ref: '#/components/schemas/WebSearchToolCall'
        - $ref: '#/components/schemas/ComputerToolCall'
        - $ref: '#/components/schemas/ReasoningItem'
        - $ref: '#/components/schemas/ImageGenToolCall'
        - $ref: '#/components/schemas/CodeInterpreterToolCall'
        - $ref: '#/components/schemas/LocalShellToolCall'
        - $ref: '#/components/schemas/MCPToolCall'
        - $ref: '#/components/schemas/MCPListTools'
        - $ref: '#/components/schemas/MCPApprovalRequest'
      discriminator:
        propertyName: type
    OutputMessage:
      type: object
      title: Output message
      description: |
        An output message from the model.
      properties:
        id:
          type: string
          description: |
            The unique ID of the output message.
        type:
          type: string
          description: |
            The type of the output message. Always `message`.
          enum:
            - message
          x-stainless-const: true
        role:
          type: string
          description: |
            The role of the output message. Always `assistant`.
          enum:
            - assistant
          x-stainless-const: true
        content:
          type: array
          description: |
            The content of the output message.
          items:
            $ref: '#/components/schemas/OutputContent'
        status:
          type: string
          description: |
            The status of the message input. One of `in_progress`, `completed`, or
            `incomplete`. Populated when input items are returned via API.
          enum:
            - in_progress
            - completed
            - incomplete
      required:
        - id
        - type
        - role
        - content
        - status
    ParallelToolCalls:
      description: >-
        Whether to enable [parallel function
        calling](/docs/guides/function-calling#configuring-parallel-function-calling) during tool use.
      type: boolean
      default: true
    PredictionContent:
      type: object
      title: Static Content
      description: |
        Static predicted output content, such as the content of a text file that is
        being regenerated.
      required:
        - type
        - content
      properties:
        type:
          type: string
          enum:
            - content
          description: |
            The type of the predicted content you want to provide. This type is
            currently always `content`.
          x-stainless-const: true
        content:
          description: |
            The content that should be matched when generating a model response.
            If generated tokens would match this content, the entire model response
            can be returned much more quickly.
          oneOf:
            - type: string
              title: Text content
              description: |
                The content used for a Predicted Output. This is often the
                text of a file you are regenerating with minor changes.
            - type: array
              description: >-
                An array of content parts with a defined type. Supported options differ based on the
                [model](/docs/models) being used to generate the response. Can contain text inputs.
              title: Array of content parts
              items:
                $ref: '#/components/schemas/ChatCompletionRequestMessageContentPartText'
              minItems: 1
    Project:
      type: object
      description: Represents an individual project.
      properties:
        id:
          type: string
          description: The identifier, which can be referenced in API endpoints
        object:
          type: string
          enum:
            - organization.project
          description: The object type, which is always `organization.project`
          x-stainless-const: true
        name:
          type: string
          description: The name of the project. This appears in reporting.
        created_at:
          type: integer
          description: The Unix timestamp (in seconds) of when the project was created.
        archived_at:
          type: integer
          nullable: true
          description: The Unix timestamp (in seconds) of when the project was archived or `null`.
        status:
          type: string
          enum:
            - active
            - archived
          description: '`active` or `archived`'
      required:
        - id
        - object
        - name
        - created_at
        - status
      x-oaiMeta:
        name: The project object
        example: |
          {
              "id": "proj_abc",
              "object": "organization.project",
              "name": "Project example",
              "created_at": 1711471533,
              "archived_at": null,
              "status": "active"
          }
    ProjectApiKey:
      type: object
      description: Represents an individual API key in a project.
      properties:
        object:
          type: string
          enum:
            - organization.project.api_key
          description: The object type, which is always `organization.project.api_key`
          x-stainless-const: true
        redacted_value:
          type: string
          description: The redacted value of the API key
        name:
          type: string
          description: The name of the API key
        created_at:
          type: integer
          description: The Unix timestamp (in seconds) of when the API key was created
        last_used_at:
          type: integer
          description: The Unix timestamp (in seconds) of when the API key was last used.
        id:
          type: string
          description: The identifier, which can be referenced in API endpoints
        owner:
          type: object
          properties:
            type:
              type: string
              enum:
                - user
                - service_account
              description: '`user` or `service_account`'
            user:
              $ref: '#/components/schemas/ProjectUser'
            service_account:
              $ref: '#/components/schemas/ProjectServiceAccount'
      required:
        - object
        - redacted_value
        - name
        - created_at
        - last_used_at
        - id
        - owner
      x-oaiMeta:
        name: The project API key object
        example: |
          {
              "object": "organization.project.api_key",
              "redacted_value": "sk-abc...def",
              "name": "My API Key",
              "created_at": 1711471533,
              "last_used_at": 1711471534,
              "id": "key_abc",
              "owner": {
                  "type": "user",
                  "user": {
                      "object": "organization.project.user",
                      "id": "user_abc",
                      "name": "First Last",
                      "email": "user@example.com",
                      "role": "owner",
                      "created_at": 1711471533
                  }
              }
          }
    ProjectApiKeyDeleteResponse:
      type: object
      properties:
        object:
          type: string
          enum:
            - organization.project.api_key.deleted
          x-stainless-const: true
        id:
          type: string
        deleted:
          type: boolean
      required:
        - object
        - id
        - deleted
    ProjectApiKeyListResponse:
      type: object
      properties:
        object:
          type: string
          enum:
            - list
          x-stainless-const: true
        data:
          type: array
          items:
            $ref: '#/components/schemas/ProjectApiKey'
        first_id:
          type: string
        last_id:
          type: string
        has_more:
          type: boolean
      required:
        - object
        - data
        - first_id
        - last_id
        - has_more
    ProjectCreateRequest:
      type: object
      properties:
        name:
          type: string
          description: The friendly name of the project, this name appears in reports.
      required:
        - name
    ProjectListResponse:
      type: object
      properties:
        object:
          type: string
          enum:
            - list
          x-stainless-const: true
        data:
          type: array
          items:
            $ref: '#/components/schemas/Project'
        first_id:
          type: string
        last_id:
          type: string
        has_more:
          type: boolean
      required:
        - object
        - data
        - first_id
        - last_id
        - has_more
    ProjectRateLimit:
      type: object
      description: Represents a project rate limit config.
      properties:
        object:
          type: string
          enum:
            - project.rate_limit
          description: The object type, which is always `project.rate_limit`
          x-stainless-const: true
        id:
          type: string
          description: The identifier, which can be referenced in API endpoints.
        model:
          type: string
          description: The model this rate limit applies to.
        max_requests_per_1_minute:
          type: integer
          description: The maximum requests per minute.
        max_tokens_per_1_minute:
          type: integer
          description: The maximum tokens per minute.
        max_images_per_1_minute:
          type: integer
          description: The maximum images per minute. Only present for relevant models.
        max_audio_megabytes_per_1_minute:
          type: integer
          description: The maximum audio megabytes per minute. Only present for relevant models.
        max_requests_per_1_day:
          type: integer
          description: The maximum requests per day. Only present for relevant models.
        batch_1_day_max_input_tokens:
          type: integer
          description: The maximum batch input tokens per day. Only present for relevant models.
      required:
        - object
        - id
        - model
        - max_requests_per_1_minute
        - max_tokens_per_1_minute
      x-oaiMeta:
        name: The project rate limit object
        example: |
          {
              "object": "project.rate_limit",
              "id": "rl_ada",
              "model": "ada",
              "max_requests_per_1_minute": 600,
              "max_tokens_per_1_minute": 150000,
              "max_images_per_1_minute": 10
          }
    ProjectRateLimitListResponse:
      type: object
      properties:
        object:
          type: string
          enum:
            - list
          x-stainless-const: true
        data:
          type: array
          items:
            $ref: '#/components/schemas/ProjectRateLimit'
        first_id:
          type: string
        last_id:
          type: string
        has_more:
          type: boolean
      required:
        - object
        - data
        - first_id
        - last_id
        - has_more
    ProjectRateLimitUpdateRequest:
      type: object
      properties:
        max_requests_per_1_minute:
          type: integer
          description: The maximum requests per minute.
        max_tokens_per_1_minute:
          type: integer
          description: The maximum tokens per minute.
        max_images_per_1_minute:
          type: integer
          description: The maximum images per minute. Only relevant for certain models.
        max_audio_megabytes_per_1_minute:
          type: integer
          description: The maximum audio megabytes per minute. Only relevant for certain models.
        max_requests_per_1_day:
          type: integer
          description: The maximum requests per day. Only relevant for certain models.
        batch_1_day_max_input_tokens:
          type: integer
          description: The maximum batch input tokens per day. Only relevant for certain models.
    ProjectServiceAccount:
      type: object
      description: Represents an individual service account in a project.
      properties:
        object:
          type: string
          enum:
            - organization.project.service_account
          description: The object type, which is always `organization.project.service_account`
          x-stainless-const: true
        id:
          type: string
          description: The identifier, which can be referenced in API endpoints
        name:
          type: string
          description: The name of the service account
        role:
          type: string
          enum:
            - owner
            - member
          description: '`owner` or `member`'
        created_at:
          type: integer
          description: The Unix timestamp (in seconds) of when the service account was created
      required:
        - object
        - id
        - name
        - role
        - created_at
      x-oaiMeta:
        name: The project service account object
        example: |
          {
              "object": "organization.project.service_account",
              "id": "svc_acct_abc",
              "name": "Service Account",
              "role": "owner",
              "created_at": 1711471533
          }
    ProjectServiceAccountApiKey:
      type: object
      properties:
        object:
          type: string
          enum:
            - organization.project.service_account.api_key
          description: The object type, which is always `organization.project.service_account.api_key`
          x-stainless-const: true
        value:
          type: string
        name:
          type: string
        created_at:
          type: integer
        id:
          type: string
      required:
        - object
        - value
        - name
        - created_at
        - id
    ProjectServiceAccountCreateRequest:
      type: object
      properties:
        name:
          type: string
          description: The name of the service account being created.
      required:
        - name
    ProjectServiceAccountCreateResponse:
      type: object
      properties:
        object:
          type: string
          enum:
            - organization.project.service_account
          x-stainless-const: true
        id:
          type: string
        name:
          type: string
        role:
          type: string
          enum:
            - member
          description: Service accounts can only have one role of type `member`
          x-stainless-const: true
        created_at:
          type: integer
        api_key:
          $ref: '#/components/schemas/ProjectServiceAccountApiKey'
      required:
        - object
        - id
        - name
        - role
        - created_at
        - api_key
    ProjectServiceAccountDeleteResponse:
      type: object
      properties:
        object:
          type: string
          enum:
            - organization.project.service_account.deleted
          x-stainless-const: true
        id:
          type: string
        deleted:
          type: boolean
      required:
        - object
        - id
        - deleted
    ProjectServiceAccountListResponse:
      type: object
      properties:
        object:
          type: string
          enum:
            - list
          x-stainless-const: true
        data:
          type: array
          items:
            $ref: '#/components/schemas/ProjectServiceAccount'
        first_id:
          type: string
        last_id:
          type: string
        has_more:
          type: boolean
      required:
        - object
        - data
        - first_id
        - last_id
        - has_more
    ProjectUpdateRequest:
      type: object
      properties:
        name:
          type: string
          description: The updated name of the project, this name appears in reports.
      required:
        - name
    ProjectUser:
      type: object
      description: Represents an individual user in a project.
      properties:
        object:
          type: string
          enum:
            - organization.project.user
          description: The object type, which is always `organization.project.user`
          x-stainless-const: true
        id:
          type: string
          description: The identifier, which can be referenced in API endpoints
        name:
          type: string
          description: The name of the user
        email:
          type: string
          description: The email address of the user
        role:
          type: string
          enum:
            - owner
            - member
          description: '`owner` or `member`'
        added_at:
          type: integer
          description: The Unix timestamp (in seconds) of when the project was added.
      required:
        - object
        - id
        - name
        - email
        - role
        - added_at
      x-oaiMeta:
        name: The project user object
        example: |
          {
              "object": "organization.project.user",
              "id": "user_abc",
              "name": "First Last",
              "email": "user@example.com",
              "role": "owner",
              "added_at": 1711471533
          }
    ProjectUserCreateRequest:
      type: object
      properties:
        user_id:
          type: string
          description: The ID of the user.
        role:
          type: string
          enum:
            - owner
            - member
          description: '`owner` or `member`'
      required:
        - user_id
        - role
    ProjectUserDeleteResponse:
      type: object
      properties:
        object:
          type: string
          enum:
            - organization.project.user.deleted
          x-stainless-const: true
        id:
          type: string
        deleted:
          type: boolean
      required:
        - object
        - id
        - deleted
    ProjectUserListResponse:
      type: object
      properties:
        object:
          type: string
        data:
          type: array
          items:
            $ref: '#/components/schemas/ProjectUser'
        first_id:
          type: string
        last_id:
          type: string
        has_more:
          type: boolean
      required:
        - object
        - data
        - first_id
        - last_id
        - has_more
    ProjectUserUpdateRequest:
      type: object
      properties:
        role:
          type: string
          enum:
            - owner
            - member
          description: '`owner` or `member`'
      required:
        - role
    Prompt:
      type: object
      nullable: true
      description: |
        Reference to a prompt template and its variables. 
        [Learn more](/docs/guides/text?api-mode=responses#reusable-prompts).
      required:
        - id
      properties:
        id:
          type: string
          description: The unique identifier of the prompt template to use.
        version:
          type: string
          description: Optional version of the prompt template.
          nullable: true
        variables:
          $ref: '#/components/schemas/ResponsePromptVariables'
    RealtimeClientEvent:
      discriminator:
        propertyName: type
      description: |
        A realtime client event.
      anyOf:
        - $ref: '#/components/schemas/RealtimeClientEventConversationItemCreate'
        - $ref: '#/components/schemas/RealtimeClientEventConversationItemDelete'
        - $ref: '#/components/schemas/RealtimeClientEventConversationItemRetrieve'
        - $ref: '#/components/schemas/RealtimeClientEventConversationItemTruncate'
        - $ref: '#/components/schemas/RealtimeClientEventInputAudioBufferAppend'
        - $ref: '#/components/schemas/RealtimeClientEventInputAudioBufferClear'
        - $ref: '#/components/schemas/RealtimeClientEventOutputAudioBufferClear'
        - $ref: '#/components/schemas/RealtimeClientEventInputAudioBufferCommit'
        - $ref: '#/components/schemas/RealtimeClientEventResponseCancel'
        - $ref: '#/components/schemas/RealtimeClientEventResponseCreate'
        - $ref: '#/components/schemas/RealtimeClientEventSessionUpdate'
        - $ref: '#/components/schemas/RealtimeClientEventTranscriptionSessionUpdate'
    RealtimeClientEventConversationItemCreate:
      type: object
      description: |
        Add a new Item to the Conversation's context, including messages, function 
        calls, and function call responses. This event can be used both to populate a 
        "history" of the conversation and to add new items mid-stream, but has the 
        current limitation that it cannot populate assistant audio messages.

        If successful, the server will respond with a `conversation.item.created` 
        event, otherwise an `error` event will be sent.
      properties:
        event_id:
          type: string
          description: Optional client-generated ID used to identify this event.
        type:
          type: string
          enum:
            - conversation.item.create
          description: The event type, must be `conversation.item.create`.
          x-stainless-const: true
        previous_item_id:
          type: string
          description: |
            The ID of the preceding item after which the new item will be inserted. 
            If not set, the new item will be appended to the end of the conversation.
            If set to `root`, the new item will be added to the beginning of the conversation.
            If set to an existing ID, it allows an item to be inserted mid-conversation. If the
            ID cannot be found, an error will be returned and the item will not be added.
        item:
          $ref: '#/components/schemas/RealtimeConversationItem'
      required:
        - type
        - item
      x-oaiMeta:
        name: conversation.item.create
        group: realtime
        example: |
          {
              "event_id": "event_345",
              "type": "conversation.item.create",
              "previous_item_id": null,
              "item": {
                  "id": "msg_001",
                  "type": "message",
                  "role": "user",
                  "content": [
                      {
                          "type": "input_text",
                          "text": "Hello, how are you?"
                      }
                  ]
              }
          }
    RealtimeClientEventConversationItemDelete:
      type: object
      description: |
        Send this event when you want to remove any item from the conversation 
        history. The server will respond with a `conversation.item.deleted` event, 
        unless the item does not exist in the conversation history, in which case the 
        server will respond with an error.
      properties:
        event_id:
          type: string
          description: Optional client-generated ID used to identify this event.
        type:
          type: string
          enum:
            - conversation.item.delete
          description: The event type, must be `conversation.item.delete`.
          x-stainless-const: true
        item_id:
          type: string
          description: The ID of the item to delete.
      required:
        - type
        - item_id
      x-oaiMeta:
        name: conversation.item.delete
        group: realtime
        example: |
          {
              "event_id": "event_901",
              "type": "conversation.item.delete",
              "item_id": "msg_003"
          }
    RealtimeClientEventConversationItemRetrieve:
      type: object
      description: >
        Send this event when you want to retrieve the server's representation of a specific item in the
        conversation history. This is useful, for example, to inspect user audio after noise cancellation and
        VAD.

        The server will respond with a `conversation.item.retrieved` event, 

        unless the item does not exist in the conversation history, in which case the 

        server will respond with an error.
      properties:
        event_id:
          type: string
          description: Optional client-generated ID used to identify this event.
        type:
          type: string
          enum:
            - conversation.item.retrieve
          description: The event type, must be `conversation.item.retrieve`.
          x-stainless-const: true
        item_id:
          type: string
          description: The ID of the item to retrieve.
      required:
        - type
        - item_id
      x-oaiMeta:
        name: conversation.item.retrieve
        group: realtime
        example: |
          {
              "event_id": "event_901",
              "type": "conversation.item.retrieve",
              "item_id": "msg_003"
          }
    RealtimeClientEventConversationItemTruncate:
      type: object
      description: |
        Send this event to truncate a previous assistant message’s audio. The server 
        will produce audio faster than realtime, so this event is useful when the user 
        interrupts to truncate audio that has already been sent to the client but not 
        yet played. This will synchronize the server's understanding of the audio with 
        the client's playback.

        Truncating audio will delete the server-side text transcript to ensure there 
        is not text in the context that hasn't been heard by the user.

        If successful, the server will respond with a `conversation.item.truncated` 
        event. 
      properties:
        event_id:
          type: string
          description: Optional client-generated ID used to identify this event.
        type:
          type: string
          enum:
            - conversation.item.truncate
          description: The event type, must be `conversation.item.truncate`.
          x-stainless-const: true
        item_id:
          type: string
          description: |
            The ID of the assistant message item to truncate. Only assistant message 
            items can be truncated.
        content_index:
          type: integer
          description: The index of the content part to truncate. Set this to 0.
        audio_end_ms:
          type: integer
          description: |
            Inclusive duration up to which audio is truncated, in milliseconds. If 
            the audio_end_ms is greater than the actual audio duration, the server 
            will respond with an error.
      required:
        - type
        - item_id
        - content_index
        - audio_end_ms
      x-oaiMeta:
        name: conversation.item.truncate
        group: realtime
        example: |
          {
              "event_id": "event_678",
              "type": "conversation.item.truncate",
              "item_id": "msg_002",
              "content_index": 0,
              "audio_end_ms": 1500
          }
    RealtimeClientEventInputAudioBufferAppend:
      type: object
      description: |
        Send this event to append audio bytes to the input audio buffer. The audio 
        buffer is temporary storage you can write to and later commit. In Server VAD 
        mode, the audio buffer is used to detect speech and the server will decide 
        when to commit. When Server VAD is disabled, you must commit the audio buffer
        manually.

        The client may choose how much audio to place in each event up to a maximum 
        of 15 MiB, for example streaming smaller chunks from the client may allow the 
        VAD to be more responsive. Unlike made other client events, the server will 
        not send a confirmation response to this event.
      properties:
        event_id:
          type: string
          description: Optional client-generated ID used to identify this event.
        type:
          type: string
          enum:
            - input_audio_buffer.append
          description: The event type, must be `input_audio_buffer.append`.
          x-stainless-const: true
        audio:
          type: string
          description: |
            Base64-encoded audio bytes. This must be in the format specified by the 
            `input_audio_format` field in the session configuration.
      required:
        - type
        - audio
      x-oaiMeta:
        name: input_audio_buffer.append
        group: realtime
        example: |
          {
              "event_id": "event_456",
              "type": "input_audio_buffer.append",
              "audio": "Base64EncodedAudioData"
          }
    RealtimeClientEventInputAudioBufferClear:
      type: object
      description: |
        Send this event to clear the audio bytes in the buffer. The server will 
        respond with an `input_audio_buffer.cleared` event.
      properties:
        event_id:
          type: string
          description: Optional client-generated ID used to identify this event.
        type:
          type: string
          enum:
            - input_audio_buffer.clear
          description: The event type, must be `input_audio_buffer.clear`.
          x-stainless-const: true
      required:
        - type
      x-oaiMeta:
        name: input_audio_buffer.clear
        group: realtime
        example: |
          {
              "event_id": "event_012",
              "type": "input_audio_buffer.clear"
          }
    RealtimeClientEventInputAudioBufferCommit:
      type: object
      description: |
        Send this event to commit the user input audio buffer, which will create a 
        new user message item in the conversation. This event will produce an error 
        if the input audio buffer is empty. When in Server VAD mode, the client does 
        not need to send this event, the server will commit the audio buffer 
        automatically.

        Committing the input audio buffer will trigger input audio transcription 
        (if enabled in session configuration), but it will not create a response 
        from the model. The server will respond with an `input_audio_buffer.committed` 
        event.
      properties:
        event_id:
          type: string
          description: Optional client-generated ID used to identify this event.
        type:
          type: string
          enum:
            - input_audio_buffer.commit
          description: The event type, must be `input_audio_buffer.commit`.
          x-stainless-const: true
      required:
        - type
      x-oaiMeta:
        name: input_audio_buffer.commit
        group: realtime
        example: |
          {
              "event_id": "event_789",
              "type": "input_audio_buffer.commit"
          }
    RealtimeClientEventOutputAudioBufferClear:
      type: object
      description: |
        **WebRTC Only:** Emit to cut off the current audio response. This will trigger the server to
        stop generating audio and emit a `output_audio_buffer.cleared` event. This 
        event should be preceded by a `response.cancel` client event to stop the 
        generation of the current response.
        [Learn more](/docs/guides/realtime-conversations#client-and-server-events-for-audio-in-webrtc).
      properties:
        event_id:
          type: string
          description: The unique ID of the client event used for error handling.
        type:
          type: string
          enum:
            - output_audio_buffer.clear
          description: The event type, must be `output_audio_buffer.clear`.
          x-stainless-const: true
      required:
        - type
      x-oaiMeta:
        name: output_audio_buffer.clear
        group: realtime
        example: |
          {
              "event_id": "optional_client_event_id",
              "type": "output_audio_buffer.clear"
          }
    RealtimeClientEventResponseCancel:
      type: object
      description: |
        Send this event to cancel an in-progress response. The server will respond 
        with a `response.cancelled` event or an error if there is no response to 
        cancel.
      properties:
        event_id:
          type: string
          description: Optional client-generated ID used to identify this event.
        type:
          type: string
          enum:
            - response.cancel
          description: The event type, must be `response.cancel`.
          x-stainless-const: true
        response_id:
          type: string
          description: |
            A specific response ID to cancel - if not provided, will cancel an 
            in-progress response in the default conversation.
      required:
        - type
      x-oaiMeta:
        name: response.cancel
        group: realtime
        example: |
          {
              "event_id": "event_567",
              "type": "response.cancel"
          }
    RealtimeClientEventResponseCreate:
      type: object
      description: |
        This event instructs the server to create a Response, which means triggering 
        model inference. When in Server VAD mode, the server will create Responses 
        automatically.

        A Response will include at least one Item, and may have two, in which case 
        the second will be a function call. These Items will be appended to the 
        conversation history.

        The server will respond with a `response.created` event, events for Items 
        and content created, and finally a `response.done` event to indicate the 
        Response is complete.

        The `response.create` event includes inference configuration like 
        `instructions`, and `temperature`. These fields will override the Session's 
        configuration for this Response only.
      properties:
        event_id:
          type: string
          description: Optional client-generated ID used to identify this event.
        type:
          type: string
          enum:
            - response.create
          description: The event type, must be `response.create`.
          x-stainless-const: true
        response:
          $ref: '#/components/schemas/RealtimeResponseCreateParams'
      required:
        - type
      x-oaiMeta:
        name: response.create
        group: realtime
        example: |
          {
              "event_id": "event_234",
              "type": "response.create",
              "response": {
                  "modalities": ["text", "audio"],
                  "instructions": "Please assist the user.",
                  "voice": "sage",
                  "output_audio_format": "pcm16",
                  "tools": [
                      {
                          "type": "function",
                          "name": "calculate_sum",
                          "description": "Calculates the sum of two numbers.",
                          "parameters": {
                              "type": "object",
                              "properties": {
                                  "a": { "type": "number" },
                                  "b": { "type": "number" }
                              },
                              "required": ["a", "b"]
                          }
                      }
                  ],
                  "tool_choice": "auto",
                  "temperature": 0.8,
                  "max_output_tokens": 1024
              }
          }
    RealtimeClientEventSessionUpdate:
      type: object
      description: |
        Send this event to update the session’s default configuration.
        The client may send this event at any time to update any field,
        except for `voice`. However, note that once a session has been
        initialized with a particular `model`, it can’t be changed to
        another model using `session.update`.

        When the server receives a `session.update`, it will respond
        with a `session.updated` event showing the full, effective configuration.
        Only the fields that are present are updated. To clear a field like
        `instructions`, pass an empty string.
      properties:
        event_id:
          type: string
          description: Optional client-generated ID used to identify this event.
        type:
          type: string
          enum:
            - session.update
          description: The event type, must be `session.update`.
          x-stainless-const: true
        session:
          $ref: '#/components/schemas/RealtimeSessionCreateRequest'
      required:
        - type
        - session
      x-oaiMeta:
        name: session.update
        group: realtime
        example: |
          {
              "event_id": "event_123",
              "type": "session.update",
              "session": {
                  "modalities": ["text", "audio"],
                  "instructions": "You are a helpful assistant.",
                  "voice": "sage",
                  "input_audio_format": "pcm16",
                  "output_audio_format": "pcm16",
                  "input_audio_transcription": {
                      "model": "whisper-1"
                  },
                  "turn_detection": {
                      "type": "server_vad",
                      "threshold": 0.5,
                      "prefix_padding_ms": 300,
                      "silence_duration_ms": 500,
                      "create_response": true
                  },
                  "tools": [
                      {
                          "type": "function",
                          "name": "get_weather",
                          "description": "Get the current weather...",
                          "parameters": {
                              "type": "object",
                              "properties": {
                                  "location": { "type": "string" }
                              },
                              "required": ["location"]
                          }
                      }
                  ],
                  "tool_choice": "auto",
                  "temperature": 0.8,
                  "max_response_output_tokens": "inf",
                  "speed": 1.1,
                  "tracing": "auto"
              }
          }
    RealtimeClientEventTranscriptionSessionUpdate:
      type: object
      description: |
        Send this event to update a transcription session.
      properties:
        event_id:
          type: string
          description: Optional client-generated ID used to identify this event.
        type:
          type: string
          enum:
            - transcription_session.update
          description: The event type, must be `transcription_session.update`.
          x-stainless-const: true
        session:
          $ref: '#/components/schemas/RealtimeTranscriptionSessionCreateRequest'
      required:
        - type
        - session
      x-oaiMeta:
        name: transcription_session.update
        group: realtime
        example: |
          {
            "type": "transcription_session.update",
            "session": {
              "input_audio_format": "pcm16",
              "input_audio_transcription": {
                "model": "gpt-4o-transcribe",
                "prompt": "",
                "language": ""
              },
              "turn_detection": {
                "type": "server_vad",
                "threshold": 0.5,
                "prefix_padding_ms": 300,
                "silence_duration_ms": 500,
                "create_response": true,
              },
              "input_audio_noise_reduction": {
                "type": "near_field"
              },
              "include": [
                "item.input_audio_transcription.logprobs",
              ]
            }
          }
    RealtimeConversationItem:
      type: object
      description: The item to add to the conversation.
      properties:
        id:
          type: string
          description: |
            The unique ID of the item, this can be generated by the client to help 
            manage server-side context, but is not required because the server will 
            generate one if not provided.
        type:
          type: string
          enum:
            - message
            - function_call
            - function_call_output
          description: |
            The type of the item (`message`, `function_call`, `function_call_output`).
        object:
          type: string
          enum:
            - realtime.item
          description: |
            Identifier for the API object being returned - always `realtime.item`.
          x-stainless-const: true
        status:
          type: string
          enum:
            - completed
            - incomplete
          description: |
            The status of the item (`completed`, `incomplete`). These have no effect 
            on the conversation, but are accepted for consistency with the 
            `conversation.item.created` event.
        role:
          type: string
          enum:
            - user
            - assistant
            - system
          description: |
            The role of the message sender (`user`, `assistant`, `system`), only 
            applicable for `message` items.
        content:
          type: array
          description: |
            The content of the message, applicable for `message` items. 
            - Message items of role `system` support only `input_text` content
            - Message items of role `user` support `input_text` and `input_audio` 
              content
            - Message items of role `assistant` support `text` content.
          items:
            type: object
            properties:
              type:
                type: string
                enum:
                  - input_audio
                  - input_text
                  - item_reference
                  - text
                description: |
                  The content type (`input_text`, `input_audio`, `item_reference`, `text`).
              text:
                type: string
                description: |
                  The text content, used for `input_text` and `text` content types.
              id:
                type: string
                description: |
                  ID of a previous conversation item to reference (for `item_reference`
                  content types in `response.create` events). These can reference both
                  client and server created items.
              audio:
                type: string
                description: |
                  Base64-encoded audio bytes, used for `input_audio` content type.
              transcript:
                type: string
                description: |
                  The transcript of the audio, used for `input_audio` content type.
        call_id:
          type: string
          description: |
            The ID of the function call (for `function_call` and 
            `function_call_output` items). If passed on a `function_call_output` 
            item, the server will check that a `function_call` item with the same 
            ID exists in the conversation history.
        name:
          type: string
          description: |
            The name of the function being called (for `function_call` items).
        arguments:
          type: string
          description: |
            The arguments of the function call (for `function_call` items).
        output:
          type: string
          description: |
            The output of the function call (for `function_call_output` items).
    RealtimeConversationItemWithReference:
      type: object
      description: The item to add to the conversation.
      properties:
        id:
          type: string
          description: |
            For an item of type (`message` | `function_call` | `function_call_output`)
            this field allows the client to assign the unique ID of the item. It is
            not required because the server will generate one if not provided.

            For an item of type `item_reference`, this field is required and is a
            reference to any item that has previously existed in the conversation.
        type:
          type: string
          enum:
            - message
            - function_call
            - function_call_output
          description: |
            The type of the item (`message`, `function_call`, `function_call_output`, `item_reference`).
        object:
          type: string
          enum:
            - realtime.item
          description: |
            Identifier for the API object being returned - always `realtime.item`.
          x-stainless-const: true
        status:
          type: string
          enum:
            - completed
            - incomplete
          description: |
            The status of the item (`completed`, `incomplete`). These have no effect 
            on the conversation, but are accepted for consistency with the 
            `conversation.item.created` event.
        role:
          type: string
          enum:
            - user
            - assistant
            - system
          description: |
            The role of the message sender (`user`, `assistant`, `system`), only 
            applicable for `message` items.
        content:
          type: array
          description: |
            The content of the message, applicable for `message` items. 
            - Message items of role `system` support only `input_text` content
            - Message items of role `user` support `input_text` and `input_audio` 
              content
            - Message items of role `assistant` support `text` content.
          items:
            type: object
            properties:
              type:
                type: string
                enum:
                  - input_audio
                  - input_text
                  - item_reference
                  - text
                description: |
                  The content type (`input_text`, `input_audio`, `item_reference`, `text`).
              text:
                type: string
                description: |
                  The text content, used for `input_text` and `text` content types.
              id:
                type: string
                description: |
                  ID of a previous conversation item to reference (for `item_reference`
                  content types in `response.create` events). These can reference both
                  client and server created items.
              audio:
                type: string
                description: |
                  Base64-encoded audio bytes, used for `input_audio` content type.
              transcript:
                type: string
                description: |
                  The transcript of the audio, used for `input_audio` content type.
        call_id:
          type: string
          description: |
            The ID of the function call (for `function_call` and 
            `function_call_output` items). If passed on a `function_call_output` 
            item, the server will check that a `function_call` item with the same 
            ID exists in the conversation history.
        name:
          type: string
          description: |
            The name of the function being called (for `function_call` items).
        arguments:
          type: string
          description: |
            The arguments of the function call (for `function_call` items).
        output:
          type: string
          description: |
            The output of the function call (for `function_call_output` items).
    RealtimeResponse:
      type: object
      description: The response resource.
      properties:
        id:
          type: string
          description: The unique ID of the response.
        object:
          type: string
          enum:
            - realtime.response
          description: The object type, must be `realtime.response`.
          x-stainless-const: true
        status:
          type: string
          enum:
            - completed
            - cancelled
            - failed
            - incomplete
          description: |
            The final status of the response (`completed`, `cancelled`, `failed`, or 
            `incomplete`).
        status_details:
          type: object
          description: Additional details about the status.
          properties:
            type:
              type: string
              enum:
                - completed
                - cancelled
                - failed
                - incomplete
              description: |
                The type of error that caused the response to fail, corresponding 
                with the `status` field (`completed`, `cancelled`, `incomplete`, 
                `failed`).
            reason:
              type: string
              enum:
                - turn_detected
                - client_cancelled
                - max_output_tokens
                - content_filter
              description: |
                The reason the Response did not complete. For a `cancelled` Response, 
                one of `turn_detected` (the server VAD detected a new start of speech) 
                or `client_cancelled` (the client sent a cancel event). For an 
                `incomplete` Response, one of `max_output_tokens` or `content_filter` 
                (the server-side safety filter activated and cut off the response).
            error:
              type: object
              description: |
                A description of the error that caused the response to fail, 
                populated when the `status` is `failed`.
              properties:
                type:
                  type: string
                  description: The type of error.
                code:
                  type: string
                  description: Error code, if any.
        output:
          type: array
          description: The list of output items generated by the response.
          items:
            $ref: '#/components/schemas/RealtimeConversationItem'
        metadata:
          $ref: '#/components/schemas/Metadata'
        usage:
          type: object
          description: |
            Usage statistics for the Response, this will correspond to billing. A 
            Realtime API session will maintain a conversation context and append new 
            Items to the Conversation, thus output from previous turns (text and 
            audio tokens) will become the input for later turns.
          properties:
            total_tokens:
              type: integer
              description: |
                The total number of tokens in the Response including input and output 
                text and audio tokens.
            input_tokens:
              type: integer
              description: |
                The number of input tokens used in the Response, including text and 
                audio tokens.
            output_tokens:
              type: integer
              description: |
                The number of output tokens sent in the Response, including text and 
                audio tokens.
            input_token_details:
              type: object
              description: Details about the input tokens used in the Response.
              properties:
                cached_tokens:
                  type: integer
                  description: The number of cached tokens used in the Response.
                text_tokens:
                  type: integer
                  description: The number of text tokens used in the Response.
                audio_tokens:
                  type: integer
                  description: The number of audio tokens used in the Response.
            output_token_details:
              type: object
              description: Details about the output tokens used in the Response.
              properties:
                text_tokens:
                  type: integer
                  description: The number of text tokens used in the Response.
                audio_tokens:
                  type: integer
                  description: The number of audio tokens used in the Response.
        conversation_id:
          description: |
            Which conversation the response is added to, determined by the `conversation`
            field in the `response.create` event. If `auto`, the response will be added to
            the default conversation and the value of `conversation_id` will be an id like
            `conv_1234`. If `none`, the response will not be added to any conversation and
            the value of `conversation_id` will be `null`. If responses are being triggered
            by server VAD, the response will be added to the default conversation, thus
            the `conversation_id` will be an id like `conv_1234`.
          type: string
        voice:
          $ref: '#/components/schemas/VoiceIdsShared'
          description: |
            The voice the model used to respond.
            Current voice options are `alloy`, `ash`, `ballad`, `coral`, `echo`, `fable`,
            `onyx`, `nova`, `sage`, `shimmer`, and `verse`.
        modalities:
          type: array
          description: |
            The set of modalities the model used to respond. If there are multiple modalities,
            the model will pick one, for example if `modalities` is `["text", "audio"]`, the model
            could be responding in either text or audio.
          items:
            type: string
            enum:
              - text
              - audio
        output_audio_format:
          type: string
          enum:
            - pcm16
            - g711_ulaw
            - g711_alaw
          description: |
            The format of output audio. Options are `pcm16`, `g711_ulaw`, or `g711_alaw`.
        temperature:
          type: number
          description: |
            Sampling temperature for the model, limited to [0.6, 1.2]. Defaults to 0.8.
        max_output_tokens:
          oneOf:
            - type: integer
            - type: string
              enum:
                - inf
              x-stainless-const: true
          description: |
            Maximum number of output tokens for a single assistant response,
            inclusive of tool calls, that was used in this response.
    RealtimeResponseCreateParams:
      type: object
      description: Create a new Realtime response with these parameters
      properties:
        modalities:
          type: array
          description: |
            The set of modalities the model can respond with. To disable audio,
            set this to ["text"].
          items:
            type: string
            enum:
              - text
              - audio
        instructions:
          type: string
          description: |
            The default system instructions (i.e. system message) prepended to model 
            calls. This field allows the client to guide the model on desired 
            responses. The model can be instructed on response content and format, 
            (e.g. "be extremely succinct", "act friendly", "here are examples of good 
            responses") and on audio behavior (e.g. "talk quickly", "inject emotion 
            into your voice", "laugh frequently"). The instructions are not guaranteed 
            to be followed by the model, but they provide guidance to the model on the 
            desired behavior.

            Note that the server sets default instructions which will be used if this 
            field is not set and are visible in the `session.created` event at the 
            start of the session.
        voice:
          $ref: '#/components/schemas/VoiceIdsShared'
          description: |
            The voice the model uses to respond. Voice cannot be changed during the 
            session once the model has responded with audio at least once. Current 
            voice options are `alloy`, `ash`, `ballad`, `coral`, `echo`, `fable`,
            `onyx`, `nova`, `sage`, `shimmer`, and `verse`.
        output_audio_format:
          type: string
          enum:
            - pcm16
            - g711_ulaw
            - g711_alaw
          description: |
            The format of output audio. Options are `pcm16`, `g711_ulaw`, or `g711_alaw`.
        tools:
          type: array
          description: Tools (functions) available to the model.
          items:
            type: object
            properties:
              type:
                type: string
                enum:
                  - function
                description: The type of the tool, i.e. `function`.
                x-stainless-const: true
              name:
                type: string
                description: The name of the function.
              description:
                type: string
                description: |
                  The description of the function, including guidance on when and how 
                  to call it, and guidance about what to tell the user when calling 
                  (if anything).
              parameters:
                type: object
                description: Parameters of the function in JSON Schema.
        tool_choice:
          type: string
          description: |
            How the model chooses tools. Options are `auto`, `none`, `required`, or 
            specify a function, like `{"type": "function", "function": {"name": "my_function"}}`.
        temperature:
          type: number
          description: |
            Sampling temperature for the model, limited to [0.6, 1.2]. Defaults to 0.8.
        max_response_output_tokens:
          oneOf:
            - type: integer
            - type: string
              enum:
                - inf
              x-stainless-const: true
          description: |
            Maximum number of output tokens for a single assistant response,
            inclusive of tool calls. Provide an integer between 1 and 4096 to
            limit output tokens, or `inf` for the maximum available tokens for a
            given model. Defaults to `inf`.
        conversation:
          description: |
            Controls which conversation the response is added to. Currently supports
            `auto` and `none`, with `auto` as the default value. The `auto` value
            means that the contents of the response will be added to the default
            conversation. Set this to `none` to create an out-of-band response which 
            will not add items to default conversation.
          oneOf:
            - type: string
            - type: string
              default: auto
              enum:
                - auto
                - none
        metadata:
          $ref: '#/components/schemas/Metadata'
        input:
          type: array
          description: |
            Input items to include in the prompt for the model. Using this field
            creates a new context for this Response instead of using the default
            conversation. An empty array `[]` will clear the context for this Response.
            Note that this can include references to items from the default conversation.
          items:
            $ref: '#/components/schemas/RealtimeConversationItemWithReference'
    RealtimeServerEvent:
      discriminator:
        propertyName: type
      description: |
        A realtime server event.
      anyOf:
        - $ref: '#/components/schemas/RealtimeServerEventConversationCreated'
        - $ref: '#/components/schemas/RealtimeServerEventConversationItemCreated'
        - $ref: '#/components/schemas/RealtimeServerEventConversationItemDeleted'
        - $ref: '#/components/schemas/RealtimeServerEventConversationItemInputAudioTranscriptionCompleted'
        - $ref: '#/components/schemas/RealtimeServerEventConversationItemInputAudioTranscriptionDelta'
        - $ref: '#/components/schemas/RealtimeServerEventConversationItemInputAudioTranscriptionFailed'
        - $ref: '#/components/schemas/RealtimeServerEventConversationItemRetrieved'
        - $ref: '#/components/schemas/RealtimeServerEventConversationItemTruncated'
        - $ref: '#/components/schemas/RealtimeServerEventError'
        - $ref: '#/components/schemas/RealtimeServerEventInputAudioBufferCleared'
        - $ref: '#/components/schemas/RealtimeServerEventInputAudioBufferCommitted'
        - $ref: '#/components/schemas/RealtimeServerEventInputAudioBufferSpeechStarted'
        - $ref: '#/components/schemas/RealtimeServerEventInputAudioBufferSpeechStopped'
        - $ref: '#/components/schemas/RealtimeServerEventRateLimitsUpdated'
        - $ref: '#/components/schemas/RealtimeServerEventResponseAudioDelta'
        - $ref: '#/components/schemas/RealtimeServerEventResponseAudioDone'
        - $ref: '#/components/schemas/RealtimeServerEventResponseAudioTranscriptDelta'
        - $ref: '#/components/schemas/RealtimeServerEventResponseAudioTranscriptDone'
        - $ref: '#/components/schemas/RealtimeServerEventResponseContentPartAdded'
        - $ref: '#/components/schemas/RealtimeServerEventResponseContentPartDone'
        - $ref: '#/components/schemas/RealtimeServerEventResponseCreated'
        - $ref: '#/components/schemas/RealtimeServerEventResponseDone'
        - $ref: '#/components/schemas/RealtimeServerEventResponseFunctionCallArgumentsDelta'
        - $ref: '#/components/schemas/RealtimeServerEventResponseFunctionCallArgumentsDone'
        - $ref: '#/components/schemas/RealtimeServerEventResponseOutputItemAdded'
        - $ref: '#/components/schemas/RealtimeServerEventResponseOutputItemDone'
        - $ref: '#/components/schemas/RealtimeServerEventResponseTextDelta'
        - $ref: '#/components/schemas/RealtimeServerEventResponseTextDone'
        - $ref: '#/components/schemas/RealtimeServerEventSessionCreated'
        - $ref: '#/components/schemas/RealtimeServerEventSessionUpdated'
        - $ref: '#/components/schemas/RealtimeServerEventTranscriptionSessionUpdated'
        - $ref: '#/components/schemas/RealtimeServerEventOutputAudioBufferStarted'
        - $ref: '#/components/schemas/RealtimeServerEventOutputAudioBufferStopped'
        - $ref: '#/components/schemas/RealtimeServerEventOutputAudioBufferCleared'
    RealtimeServerEventConversationCreated:
      type: object
      description: |
        Returned when a conversation is created. Emitted right after session creation.
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - conversation.created
          description: The event type, must be `conversation.created`.
          x-stainless-const: true
        conversation:
          type: object
          description: The conversation resource.
          properties:
            id:
              type: string
              description: The unique ID of the conversation.
            object:
              type: string
              description: The object type, must be `realtime.conversation`.
      required:
        - event_id
        - type
        - conversation
      x-oaiMeta:
        name: conversation.created
        group: realtime
        example: |
          {
              "event_id": "event_9101",
              "type": "conversation.created",
              "conversation": {
                  "id": "conv_001",
                  "object": "realtime.conversation"
              }
          }
    RealtimeServerEventConversationItemCreated:
      type: object
      description: |
        Returned when a conversation item is created. There are several scenarios that produce this event:
          - The server is generating a Response, which if successful will produce 
            either one or two Items, which will be of type `message` 
            (role `assistant`) or type `function_call`.
          - The input audio buffer has been committed, either by the client or the 
            server (in `server_vad` mode). The server will take the content of the 
            input audio buffer and add it to a new user message Item.
          - The client has sent a `conversation.item.create` event to add a new Item 
            to the Conversation.
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - conversation.item.created
          description: The event type, must be `conversation.item.created`.
          x-stainless-const: true
        previous_item_id:
          type: string
          description: |
            The ID of the preceding item in the Conversation context, allows the 
            client to understand the order of the conversation.
        item:
          $ref: '#/components/schemas/RealtimeConversationItem'
      required:
        - event_id
        - type
        - previous_item_id
        - item
      x-oaiMeta:
        name: conversation.item.created
        group: realtime
        example: |
          {
              "event_id": "event_1920",
              "type": "conversation.item.created",
              "previous_item_id": "msg_002",
              "item": {
                  "id": "msg_003",
                  "object": "realtime.item",
                  "type": "message",
                  "status": "completed",
                  "role": "user",
                  "content": []
              }
          }
    RealtimeServerEventConversationItemDeleted:
      type: object
      description: |
        Returned when an item in the conversation is deleted by the client with a 
        `conversation.item.delete` event. This event is used to synchronize the 
        server's understanding of the conversation history with the client's view.
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - conversation.item.deleted
          description: The event type, must be `conversation.item.deleted`.
          x-stainless-const: true
        item_id:
          type: string
          description: The ID of the item that was deleted.
      required:
        - event_id
        - type
        - item_id
      x-oaiMeta:
        name: conversation.item.deleted
        group: realtime
        example: |
          {
              "event_id": "event_2728",
              "type": "conversation.item.deleted",
              "item_id": "msg_005"
          }
    RealtimeServerEventConversationItemInputAudioTranscriptionCompleted:
      type: object
      description: |
        This event is the output of audio transcription for user audio written to the 
        user audio buffer. Transcription begins when the input audio buffer is 
        committed by the client or server (in `server_vad` mode). Transcription runs 
        asynchronously with Response creation, so this event may come before or after 
        the Response events.

        Realtime API models accept audio natively, and thus input transcription is a 
        separate process run on a separate ASR (Automatic Speech Recognition) model, 
        currently always `whisper-1`. Thus the transcript may diverge somewhat from 
        the model's interpretation, and should be treated as a rough guide.
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - conversation.item.input_audio_transcription.completed
          description: |
            The event type, must be
            `conversation.item.input_audio_transcription.completed`.
          x-stainless-const: true
        item_id:
          type: string
          description: The ID of the user message item containing the audio.
        content_index:
          type: integer
          description: The index of the content part containing the audio.
        transcript:
          type: string
          description: The transcribed text.
        logprobs:
          type: array
          description: The log probabilities of the transcription.
          nullable: true
          items:
            $ref: '#/components/schemas/LogProbProperties'
      required:
        - event_id
        - type
        - item_id
        - content_index
        - transcript
      x-oaiMeta:
        name: conversation.item.input_audio_transcription.completed
        group: realtime
        example: |
          {
              "event_id": "event_2122",
              "type": "conversation.item.input_audio_transcription.completed",
              "item_id": "msg_003",
              "content_index": 0,
              "transcript": "Hello, how are you?"
          }
    RealtimeServerEventConversationItemInputAudioTranscriptionDelta:
      type: object
      description: |
        Returned when the text value of an input audio transcription content part is updated.
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - conversation.item.input_audio_transcription.delta
          description: The event type, must be `conversation.item.input_audio_transcription.delta`.
          x-stainless-const: true
        item_id:
          type: string
          description: The ID of the item.
        content_index:
          type: integer
          description: The index of the content part in the item's content array.
        delta:
          type: string
          description: The text delta.
        logprobs:
          type: array
          description: The log probabilities of the transcription.
          nullable: true
          items:
            $ref: '#/components/schemas/LogProbProperties'
      required:
        - event_id
        - type
        - item_id
      x-oaiMeta:
        name: conversation.item.input_audio_transcription.delta
        group: realtime
        example: |
          {
            "type": "conversation.item.input_audio_transcription.delta",
            "event_id": "event_001",
            "item_id": "item_001",
            "content_index": 0,
            "delta": "Hello"
          }
    RealtimeServerEventConversationItemInputAudioTranscriptionFailed:
      type: object
      description: |
        Returned when input audio transcription is configured, and a transcription 
        request for a user message failed. These events are separate from other 
        `error` events so that the client can identify the related Item.
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - conversation.item.input_audio_transcription.failed
          description: |
            The event type, must be
            `conversation.item.input_audio_transcription.failed`.
          x-stainless-const: true
        item_id:
          type: string
          description: The ID of the user message item.
        content_index:
          type: integer
          description: The index of the content part containing the audio.
        error:
          type: object
          description: Details of the transcription error.
          properties:
            type:
              type: string
              description: The type of error.
            code:
              type: string
              description: Error code, if any.
            message:
              type: string
              description: A human-readable error message.
            param:
              type: string
              description: Parameter related to the error, if any.
      required:
        - event_id
        - type
        - item_id
        - content_index
        - error
      x-oaiMeta:
        name: conversation.item.input_audio_transcription.failed
        group: realtime
        example: |
          {
              "event_id": "event_2324",
              "type": "conversation.item.input_audio_transcription.failed",
              "item_id": "msg_003",
              "content_index": 0,
              "error": {
                  "type": "transcription_error",
                  "code": "audio_unintelligible",
                  "message": "The audio could not be transcribed.",
                  "param": null
              }
          }
    RealtimeServerEventConversationItemRetrieved:
      type: object
      description: |
        Returned when a conversation item is retrieved with `conversation.item.retrieve`.
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - conversation.item.retrieved
          description: The event type, must be `conversation.item.retrieved`.
          x-stainless-const: true
        item:
          $ref: '#/components/schemas/RealtimeConversationItem'
      required:
        - event_id
        - type
        - item
      x-oaiMeta:
        name: conversation.item.retrieved
        group: realtime
        example: |
          {
              "event_id": "event_1920",
              "type": "conversation.item.created",
              "previous_item_id": "msg_002",
              "item": {
                  "id": "msg_003",
                  "object": "realtime.item",
                  "type": "message",
                  "status": "completed",
                  "role": "user",
                  "content": [
                      {
                          "type": "input_audio",
                          "transcript": "hello how are you",
                          "audio": "base64encodedaudio=="
                      }
                  ]
              }
          }
    RealtimeServerEventConversationItemTruncated:
      type: object
      description: |
        Returned when an earlier assistant audio message item is truncated by the 
        client with a `conversation.item.truncate` event. This event is used to 
        synchronize the server's understanding of the audio with the client's playback.

        This action will truncate the audio and remove the server-side text transcript 
        to ensure there is no text in the context that hasn't been heard by the user.
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - conversation.item.truncated
          description: The event type, must be `conversation.item.truncated`.
          x-stainless-const: true
        item_id:
          type: string
          description: The ID of the assistant message item that was truncated.
        content_index:
          type: integer
          description: The index of the content part that was truncated.
        audio_end_ms:
          type: integer
          description: |
            The duration up to which the audio was truncated, in milliseconds.
      required:
        - event_id
        - type
        - item_id
        - content_index
        - audio_end_ms
      x-oaiMeta:
        name: conversation.item.truncated
        group: realtime
        example: |
          {
              "event_id": "event_2526",
              "type": "conversation.item.truncated",
              "item_id": "msg_004",
              "content_index": 0,
              "audio_end_ms": 1500
          }
    RealtimeServerEventError:
      type: object
      description: |
        Returned when an error occurs, which could be a client problem or a server 
        problem. Most errors are recoverable and the session will stay open, we 
        recommend to implementors to monitor and log error messages by default.
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - error
          description: The event type, must be `error`.
          x-stainless-const: true
        error:
          type: object
          description: Details of the error.
          required:
            - type
            - message
          properties:
            type:
              type: string
              description: |
                The type of error (e.g., "invalid_request_error", "server_error").
            code:
              type: string
              description: Error code, if any.
              nullable: true
            message:
              type: string
              description: A human-readable error message.
            param:
              type: string
              description: Parameter related to the error, if any.
              nullable: true
            event_id:
              type: string
              description: |
                The event_id of the client event that caused the error, if applicable.
              nullable: true
      required:
        - event_id
        - type
        - error
      x-oaiMeta:
        name: error
        group: realtime
        example: |
          {
              "event_id": "event_890",
              "type": "error",
              "error": {
                  "type": "invalid_request_error",
                  "code": "invalid_event",
                  "message": "The 'type' field is missing.",
                  "param": null,
                  "event_id": "event_567"
              }
          }
    RealtimeServerEventInputAudioBufferCleared:
      type: object
      description: |
        Returned when the input audio buffer is cleared by the client with a 
        `input_audio_buffer.clear` event.
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - input_audio_buffer.cleared
          description: The event type, must be `input_audio_buffer.cleared`.
          x-stainless-const: true
      required:
        - event_id
        - type
      x-oaiMeta:
        name: input_audio_buffer.cleared
        group: realtime
        example: |
          {
              "event_id": "event_1314",
              "type": "input_audio_buffer.cleared"
          }
    RealtimeServerEventInputAudioBufferCommitted:
      type: object
      description: |
        Returned when an input audio buffer is committed, either by the client or 
        automatically in server VAD mode. The `item_id` property is the ID of the user
        message item that will be created, thus a `conversation.item.created` event 
        will also be sent to the client.
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - input_audio_buffer.committed
          description: The event type, must be `input_audio_buffer.committed`.
          x-stainless-const: true
        previous_item_id:
          type: string
          description: |
            The ID of the preceding item after which the new item will be inserted.
        item_id:
          type: string
          description: The ID of the user message item that will be created.
      required:
        - event_id
        - type
        - previous_item_id
        - item_id
      x-oaiMeta:
        name: input_audio_buffer.committed
        group: realtime
        example: |
          {
              "event_id": "event_1121",
              "type": "input_audio_buffer.committed",
              "previous_item_id": "msg_001",
              "item_id": "msg_002"
          }
    RealtimeServerEventInputAudioBufferSpeechStarted:
      type: object
      description: |
        Sent by the server when in `server_vad` mode to indicate that speech has been 
        detected in the audio buffer. This can happen any time audio is added to the 
        buffer (unless speech is already detected). The client may want to use this 
        event to interrupt audio playback or provide visual feedback to the user. 

        The client should expect to receive a `input_audio_buffer.speech_stopped` event 
        when speech stops. The `item_id` property is the ID of the user message item 
        that will be created when speech stops and will also be included in the 
        `input_audio_buffer.speech_stopped` event (unless the client manually commits 
        the audio buffer during VAD activation).
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - input_audio_buffer.speech_started
          description: The event type, must be `input_audio_buffer.speech_started`.
          x-stainless-const: true
        audio_start_ms:
          type: integer
          description: |
            Milliseconds from the start of all audio written to the buffer during the 
            session when speech was first detected. This will correspond to the 
            beginning of audio sent to the model, and thus includes the 
            `prefix_padding_ms` configured in the Session.
        item_id:
          type: string
          description: |
            The ID of the user message item that will be created when speech stops.
      required:
        - event_id
        - type
        - audio_start_ms
        - item_id
      x-oaiMeta:
        name: input_audio_buffer.speech_started
        group: realtime
        example: |
          {
              "event_id": "event_1516",
              "type": "input_audio_buffer.speech_started",
              "audio_start_ms": 1000,
              "item_id": "msg_003"
          }
    RealtimeServerEventInputAudioBufferSpeechStopped:
      type: object
      description: |
        Returned in `server_vad` mode when the server detects the end of speech in 
        the audio buffer. The server will also send an `conversation.item.created` 
        event with the user message item that is created from the audio buffer.
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - input_audio_buffer.speech_stopped
          description: The event type, must be `input_audio_buffer.speech_stopped`.
          x-stainless-const: true
        audio_end_ms:
          type: integer
          description: |
            Milliseconds since the session started when speech stopped. This will 
            correspond to the end of audio sent to the model, and thus includes the 
            `min_silence_duration_ms` configured in the Session.
        item_id:
          type: string
          description: The ID of the user message item that will be created.
      required:
        - event_id
        - type
        - audio_end_ms
        - item_id
      x-oaiMeta:
        name: input_audio_buffer.speech_stopped
        group: realtime
        example: |
          {
              "event_id": "event_1718",
              "type": "input_audio_buffer.speech_stopped",
              "audio_end_ms": 2000,
              "item_id": "msg_003"
          }
    RealtimeServerEventOutputAudioBufferCleared:
      type: object
      description: |
        **WebRTC Only:** Emitted when the output audio buffer is cleared. This happens either in VAD
        mode when the user has interrupted (`input_audio_buffer.speech_started`),
        or when the client has emitted the `output_audio_buffer.clear` event to manually
        cut off the current audio response.
        [Learn more](/docs/guides/realtime-conversations#client-and-server-events-for-audio-in-webrtc).
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - output_audio_buffer.cleared
          description: The event type, must be `output_audio_buffer.cleared`.
          x-stainless-const: true
        response_id:
          type: string
          description: The unique ID of the response that produced the audio.
      required:
        - event_id
        - type
        - response_id
      x-oaiMeta:
        name: output_audio_buffer.cleared
        group: realtime
        example: |
          {
              "event_id": "event_abc123",
              "type": "output_audio_buffer.cleared",
              "response_id": "resp_abc123"
          }
    RealtimeServerEventOutputAudioBufferStarted:
      type: object
      description: |
        **WebRTC Only:** Emitted when the server begins streaming audio to the client. This event is
        emitted after an audio content part has been added (`response.content_part.added`)
        to the response.
        [Learn more](/docs/guides/realtime-conversations#client-and-server-events-for-audio-in-webrtc).
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - output_audio_buffer.started
          description: The event type, must be `output_audio_buffer.started`.
          x-stainless-const: true
        response_id:
          type: string
          description: The unique ID of the response that produced the audio.
      required:
        - event_id
        - type
        - response_id
      x-oaiMeta:
        name: output_audio_buffer.started
        group: realtime
        example: |
          {
              "event_id": "event_abc123",
              "type": "output_audio_buffer.started",
              "response_id": "resp_abc123"
          }
    RealtimeServerEventOutputAudioBufferStopped:
      type: object
      description: |
        **WebRTC Only:** Emitted when the output audio buffer has been completely drained on the server,
        and no more audio is forthcoming. This event is emitted after the full response
        data has been sent to the client (`response.done`).
        [Learn more](/docs/guides/realtime-conversations#client-and-server-events-for-audio-in-webrtc).
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - output_audio_buffer.stopped
          description: The event type, must be `output_audio_buffer.stopped`.
          x-stainless-const: true
        response_id:
          type: string
          description: The unique ID of the response that produced the audio.
      required:
        - event_id
        - type
        - response_id
      x-oaiMeta:
        name: output_audio_buffer.stopped
        group: realtime
        example: |
          {
              "event_id": "event_abc123",
              "type": "output_audio_buffer.stopped",
              "response_id": "resp_abc123"
          }
    RealtimeServerEventRateLimitsUpdated:
      type: object
      description: |
        Emitted at the beginning of a Response to indicate the updated rate limits. 
        When a Response is created some tokens will be "reserved" for the output 
        tokens, the rate limits shown here reflect that reservation, which is then 
        adjusted accordingly once the Response is completed.
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - rate_limits.updated
          description: The event type, must be `rate_limits.updated`.
          x-stainless-const: true
        rate_limits:
          type: array
          description: List of rate limit information.
          items:
            type: object
            properties:
              name:
                type: string
                enum:
                  - requests
                  - tokens
                description: |
                  The name of the rate limit (`requests`, `tokens`).
              limit:
                type: integer
                description: The maximum allowed value for the rate limit.
              remaining:
                type: integer
                description: The remaining value before the limit is reached.
              reset_seconds:
                type: number
                description: Seconds until the rate limit resets.
      required:
        - event_id
        - type
        - rate_limits
      x-oaiMeta:
        name: rate_limits.updated
        group: realtime
        example: |
          {
              "event_id": "event_5758",
              "type": "rate_limits.updated",
              "rate_limits": [
                  {
                      "name": "requests",
                      "limit": 1000,
                      "remaining": 999,
                      "reset_seconds": 60
                  },
                  {
                      "name": "tokens",
                      "limit": 50000,
                      "remaining": 49950,
                      "reset_seconds": 60
                  }
              ]
          }
    RealtimeServerEventResponseAudioDelta:
      type: object
      description: Returned when the model-generated audio is updated.
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - response.audio.delta
          description: The event type, must be `response.audio.delta`.
          x-stainless-const: true
        response_id:
          type: string
          description: The ID of the response.
        item_id:
          type: string
          description: The ID of the item.
        output_index:
          type: integer
          description: The index of the output item in the response.
        content_index:
          type: integer
          description: The index of the content part in the item's content array.
        delta:
          type: string
          description: Base64-encoded audio data delta.
      required:
        - event_id
        - type
        - response_id
        - item_id
        - output_index
        - content_index
        - delta
      x-oaiMeta:
        name: response.audio.delta
        group: realtime
        example: |
          {
              "event_id": "event_4950",
              "type": "response.audio.delta",
              "response_id": "resp_001",
              "item_id": "msg_008",
              "output_index": 0,
              "content_index": 0,
              "delta": "Base64EncodedAudioDelta"
          }
    RealtimeServerEventResponseAudioDone:
      type: object
      description: |
        Returned when the model-generated audio is done. Also emitted when a Response
        is interrupted, incomplete, or cancelled.
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - response.audio.done
          description: The event type, must be `response.audio.done`.
          x-stainless-const: true
        response_id:
          type: string
          description: The ID of the response.
        item_id:
          type: string
          description: The ID of the item.
        output_index:
          type: integer
          description: The index of the output item in the response.
        content_index:
          type: integer
          description: The index of the content part in the item's content array.
      required:
        - event_id
        - type
        - response_id
        - item_id
        - output_index
        - content_index
      x-oaiMeta:
        name: response.audio.done
        group: realtime
        example: |
          {
              "event_id": "event_5152",
              "type": "response.audio.done",
              "response_id": "resp_001",
              "item_id": "msg_008",
              "output_index": 0,
              "content_index": 0
          }
    RealtimeServerEventResponseAudioTranscriptDelta:
      type: object
      description: |
        Returned when the model-generated transcription of audio output is updated.
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - response.audio_transcript.delta
          description: The event type, must be `response.audio_transcript.delta`.
          x-stainless-const: true
        response_id:
          type: string
          description: The ID of the response.
        item_id:
          type: string
          description: The ID of the item.
        output_index:
          type: integer
          description: The index of the output item in the response.
        content_index:
          type: integer
          description: The index of the content part in the item's content array.
        delta:
          type: string
          description: The transcript delta.
      required:
        - event_id
        - type
        - response_id
        - item_id
        - output_index
        - content_index
        - delta
      x-oaiMeta:
        name: response.audio_transcript.delta
        group: realtime
        example: |
          {
              "event_id": "event_4546",
              "type": "response.audio_transcript.delta",
              "response_id": "resp_001",
              "item_id": "msg_008",
              "output_index": 0,
              "content_index": 0,
              "delta": "Hello, how can I a"
          }
    RealtimeServerEventResponseAudioTranscriptDone:
      type: object
      description: |
        Returned when the model-generated transcription of audio output is done
        streaming. Also emitted when a Response is interrupted, incomplete, or
        cancelled.
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - response.audio_transcript.done
          description: The event type, must be `response.audio_transcript.done`.
          x-stainless-const: true
        response_id:
          type: string
          description: The ID of the response.
        item_id:
          type: string
          description: The ID of the item.
        output_index:
          type: integer
          description: The index of the output item in the response.
        content_index:
          type: integer
          description: The index of the content part in the item's content array.
        transcript:
          type: string
          description: The final transcript of the audio.
      required:
        - event_id
        - type
        - response_id
        - item_id
        - output_index
        - content_index
        - transcript
      x-oaiMeta:
        name: response.audio_transcript.done
        group: realtime
        example: |
          {
              "event_id": "event_4748",
              "type": "response.audio_transcript.done",
              "response_id": "resp_001",
              "item_id": "msg_008",
              "output_index": 0,
              "content_index": 0,
              "transcript": "Hello, how can I assist you today?"
          }
    RealtimeServerEventResponseContentPartAdded:
      type: object
      description: |
        Returned when a new content part is added to an assistant message item during
        response generation.
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - response.content_part.added
          description: The event type, must be `response.content_part.added`.
          x-stainless-const: true
        response_id:
          type: string
          description: The ID of the response.
        item_id:
          type: string
          description: The ID of the item to which the content part was added.
        output_index:
          type: integer
          description: The index of the output item in the response.
        content_index:
          type: integer
          description: The index of the content part in the item's content array.
        part:
          type: object
          description: The content part that was added.
          properties:
            type:
              type: string
              enum:
                - audio
                - text
              description: The content type ("text", "audio").
            text:
              type: string
              description: The text content (if type is "text").
            audio:
              type: string
              description: Base64-encoded audio data (if type is "audio").
            transcript:
              type: string
              description: The transcript of the audio (if type is "audio").
      required:
        - event_id
        - type
        - response_id
        - item_id
        - output_index
        - content_index
        - part
      x-oaiMeta:
        name: response.content_part.added
        group: realtime
        example: |
          {
              "event_id": "event_3738",
              "type": "response.content_part.added",
              "response_id": "resp_001",
              "item_id": "msg_007",
              "output_index": 0,
              "content_index": 0,
              "part": {
                  "type": "text",
                  "text": ""
              }
          }
    RealtimeServerEventResponseContentPartDone:
      type: object
      description: |
        Returned when a content part is done streaming in an assistant message item.
        Also emitted when a Response is interrupted, incomplete, or cancelled.
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - response.content_part.done
          description: The event type, must be `response.content_part.done`.
          x-stainless-const: true
        response_id:
          type: string
          description: The ID of the response.
        item_id:
          type: string
          description: The ID of the item.
        output_index:
          type: integer
          description: The index of the output item in the response.
        content_index:
          type: integer
          description: The index of the content part in the item's content array.
        part:
          type: object
          description: The content part that is done.
          properties:
            type:
              type: string
              enum:
                - audio
                - text
              description: The content type ("text", "audio").
            text:
              type: string
              description: The text content (if type is "text").
            audio:
              type: string
              description: Base64-encoded audio data (if type is "audio").
            transcript:
              type: string
              description: The transcript of the audio (if type is "audio").
      required:
        - event_id
        - type
        - response_id
        - item_id
        - output_index
        - content_index
        - part
      x-oaiMeta:
        name: response.content_part.done
        group: realtime
        example: |
          {
              "event_id": "event_3940",
              "type": "response.content_part.done",
              "response_id": "resp_001",
              "item_id": "msg_007",
              "output_index": 0,
              "content_index": 0,
              "part": {
                  "type": "text",
                  "text": "Sure, I can help with that."
              }
          }
    RealtimeServerEventResponseCreated:
      type: object
      description: |
        Returned when a new Response is created. The first event of response creation,
        where the response is in an initial state of `in_progress`.
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - response.created
          description: The event type, must be `response.created`.
          x-stainless-const: true
        response:
          $ref: '#/components/schemas/RealtimeResponse'
      required:
        - event_id
        - type
        - response
      x-oaiMeta:
        name: response.created
        group: realtime
        example: |
          {
              "event_id": "event_2930",
              "type": "response.created",
              "response": {
                  "id": "resp_001",
                  "object": "realtime.response",
                  "status": "in_progress",
                  "status_details": null,
                  "output": [],
                  "usage": null
              }
          }
    RealtimeServerEventResponseDone:
      type: object
      description: |
        Returned when a Response is done streaming. Always emitted, no matter the 
        final state. The Response object included in the `response.done` event will 
        include all output Items in the Response but will omit the raw audio data.
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - response.done
          description: The event type, must be `response.done`.
          x-stainless-const: true
        response:
          $ref: '#/components/schemas/RealtimeResponse'
      required:
        - event_id
        - type
        - response
      x-oaiMeta:
        name: response.done
        group: realtime
        example: |
          {
              "event_id": "event_3132",
              "type": "response.done",
              "response": {
                  "id": "resp_001",
                  "object": "realtime.response",
                  "status": "completed",
                  "status_details": null,
                  "output": [
                      {
                          "id": "msg_006",
                          "object": "realtime.item",
                          "type": "message",
                          "status": "completed",
                          "role": "assistant",
                          "content": [
                              {
                                  "type": "text",
                                  "text": "Sure, how can I assist you today?"
                              }
                          ]
                      }
                  ],
                  "usage": {
                      "total_tokens":275,
                      "input_tokens":127,
                      "output_tokens":148,
                      "input_token_details": {
                          "cached_tokens":384,
                          "text_tokens":119,
                          "audio_tokens":8,
                          "cached_tokens_details": {
                              "text_tokens": 128,
                              "audio_tokens": 256
                          }
                      },
                      "output_token_details": {
                        "text_tokens":36,
                        "audio_tokens":112
                      }
                  }
              }
          }
    RealtimeServerEventResponseFunctionCallArgumentsDelta:
      type: object
      description: |
        Returned when the model-generated function call arguments are updated.
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - response.function_call_arguments.delta
          description: |
            The event type, must be `response.function_call_arguments.delta`.
          x-stainless-const: true
        response_id:
          type: string
          description: The ID of the response.
        item_id:
          type: string
          description: The ID of the function call item.
        output_index:
          type: integer
          description: The index of the output item in the response.
        call_id:
          type: string
          description: The ID of the function call.
        delta:
          type: string
          description: The arguments delta as a JSON string.
      required:
        - event_id
        - type
        - response_id
        - item_id
        - output_index
        - call_id
        - delta
      x-oaiMeta:
        name: response.function_call_arguments.delta
        group: realtime
        example: |
          {
              "event_id": "event_5354",
              "type": "response.function_call_arguments.delta",
              "response_id": "resp_002",
              "item_id": "fc_001",
              "output_index": 0,
              "call_id": "call_001",
              "delta": "{\"location\": \"San\""
          }
    RealtimeServerEventResponseFunctionCallArgumentsDone:
      type: object
      description: |
        Returned when the model-generated function call arguments are done streaming.
        Also emitted when a Response is interrupted, incomplete, or cancelled.
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - response.function_call_arguments.done
          description: |
            The event type, must be `response.function_call_arguments.done`.
          x-stainless-const: true
        response_id:
          type: string
          description: The ID of the response.
        item_id:
          type: string
          description: The ID of the function call item.
        output_index:
          type: integer
          description: The index of the output item in the response.
        call_id:
          type: string
          description: The ID of the function call.
        arguments:
          type: string
          description: The final arguments as a JSON string.
      required:
        - event_id
        - type
        - response_id
        - item_id
        - output_index
        - call_id
        - arguments
      x-oaiMeta:
        name: response.function_call_arguments.done
        group: realtime
        example: |
          {
              "event_id": "event_5556",
              "type": "response.function_call_arguments.done",
              "response_id": "resp_002",
              "item_id": "fc_001",
              "output_index": 0,
              "call_id": "call_001",
              "arguments": "{\"location\": \"San Francisco\"}"
          }
    RealtimeServerEventResponseOutputItemAdded:
      type: object
      description: Returned when a new Item is created during Response generation.
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - response.output_item.added
          description: The event type, must be `response.output_item.added`.
          x-stainless-const: true
        response_id:
          type: string
          description: The ID of the Response to which the item belongs.
        output_index:
          type: integer
          description: The index of the output item in the Response.
        item:
          $ref: '#/components/schemas/RealtimeConversationItem'
      required:
        - event_id
        - type
        - response_id
        - output_index
        - item
      x-oaiMeta:
        name: response.output_item.added
        group: realtime
        example: |
          {
              "event_id": "event_3334",
              "type": "response.output_item.added",
              "response_id": "resp_001",
              "output_index": 0,
              "item": {
                  "id": "msg_007",
                  "object": "realtime.item",
                  "type": "message",
                  "status": "in_progress",
                  "role": "assistant",
                  "content": []
              }
          }
    RealtimeServerEventResponseOutputItemDone:
      type: object
      description: |
        Returned when an Item is done streaming. Also emitted when a Response is 
        interrupted, incomplete, or cancelled.
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - response.output_item.done
          description: The event type, must be `response.output_item.done`.
          x-stainless-const: true
        response_id:
          type: string
          description: The ID of the Response to which the item belongs.
        output_index:
          type: integer
          description: The index of the output item in the Response.
        item:
          $ref: '#/components/schemas/RealtimeConversationItem'
      required:
        - event_id
        - type
        - response_id
        - output_index
        - item
      x-oaiMeta:
        name: response.output_item.done
        group: realtime
        example: |
          {
              "event_id": "event_3536",
              "type": "response.output_item.done",
              "response_id": "resp_001",
              "output_index": 0,
              "item": {
                  "id": "msg_007",
                  "object": "realtime.item",
                  "type": "message",
                  "status": "completed",
                  "role": "assistant",
                  "content": [
                      {
                          "type": "text",
                          "text": "Sure, I can help with that."
                      }
                  ]
              }
          }
    RealtimeServerEventResponseTextDelta:
      type: object
      description: Returned when the text value of a "text" content part is updated.
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - response.text.delta
          description: The event type, must be `response.text.delta`.
          x-stainless-const: true
        response_id:
          type: string
          description: The ID of the response.
        item_id:
          type: string
          description: The ID of the item.
        output_index:
          type: integer
          description: The index of the output item in the response.
        content_index:
          type: integer
          description: The index of the content part in the item's content array.
        delta:
          type: string
          description: The text delta.
      required:
        - event_id
        - type
        - response_id
        - item_id
        - output_index
        - content_index
        - delta
      x-oaiMeta:
        name: response.text.delta
        group: realtime
        example: |
          {
              "event_id": "event_4142",
              "type": "response.text.delta",
              "response_id": "resp_001",
              "item_id": "msg_007",
              "output_index": 0,
              "content_index": 0,
              "delta": "Sure, I can h"
          }
    RealtimeServerEventResponseTextDone:
      type: object
      description: |
        Returned when the text value of a "text" content part is done streaming. Also
        emitted when a Response is interrupted, incomplete, or cancelled.
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - response.text.done
          description: The event type, must be `response.text.done`.
          x-stainless-const: true
        response_id:
          type: string
          description: The ID of the response.
        item_id:
          type: string
          description: The ID of the item.
        output_index:
          type: integer
          description: The index of the output item in the response.
        content_index:
          type: integer
          description: The index of the content part in the item's content array.
        text:
          type: string
          description: The final text content.
      required:
        - event_id
        - type
        - response_id
        - item_id
        - output_index
        - content_index
        - text
      x-oaiMeta:
        name: response.text.done
        group: realtime
        example: |
          {
              "event_id": "event_4344",
              "type": "response.text.done",
              "response_id": "resp_001",
              "item_id": "msg_007",
              "output_index": 0,
              "content_index": 0,
              "text": "Sure, I can help with that."
          }
    RealtimeServerEventSessionCreated:
      type: object
      description: |
        Returned when a Session is created. Emitted automatically when a new 
        connection is established as the first server event. This event will contain 
        the default Session configuration.
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - session.created
          description: The event type, must be `session.created`.
          x-stainless-const: true
        session:
          $ref: '#/components/schemas/RealtimeSession'
      required:
        - event_id
        - type
        - session
      x-oaiMeta:
        name: session.created
        group: realtime
        example: |
          {
              "event_id": "event_1234",
              "type": "session.created",
              "session": {
                  "id": "sess_001",
                  "object": "realtime.session",
                  "model": "gpt-4o-realtime-preview",
                  "modalities": ["text", "audio"],
                  "instructions": "...model instructions here...",
                  "voice": "sage",
                  "input_audio_format": "pcm16",
                  "output_audio_format": "pcm16",
                  "input_audio_transcription": null,
                  "turn_detection": {
                      "type": "server_vad",
                      "threshold": 0.5,
                      "prefix_padding_ms": 300,
                      "silence_duration_ms": 200
                  },
                  "tools": [],
                  "tool_choice": "auto",
                  "temperature": 0.8,
                  "max_response_output_tokens": "inf",
                  "speed": 1.1,
                  "tracing": "auto"
              }
          }
    RealtimeServerEventSessionUpdated:
      type: object
      description: |
        Returned when a session is updated with a `session.update` event, unless 
        there is an error.
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - session.updated
          description: The event type, must be `session.updated`.
          x-stainless-const: true
        session:
          $ref: '#/components/schemas/RealtimeSession'
      required:
        - event_id
        - type
        - session
      x-oaiMeta:
        name: session.updated
        group: realtime
        example: |
          {
              "event_id": "event_5678",
              "type": "session.updated",
              "session": {
                  "id": "sess_001",
                  "object": "realtime.session",
                  "model": "gpt-4o-realtime-preview",
                  "modalities": ["text"],
                  "instructions": "New instructions",
                  "voice": "sage",
                  "input_audio_format": "pcm16",
                  "output_audio_format": "pcm16",
                  "input_audio_transcription": {
                      "model": "whisper-1"
                  },
                  "turn_detection": null,
                  "tools": [],
                  "tool_choice": "none",
                  "temperature": 0.7,
                  "max_response_output_tokens": 200,
                  "speed": 1.1,
                  "tracing": "auto"
              }
          }
    RealtimeServerEventTranscriptionSessionUpdated:
      type: object
      description: |
        Returned when a transcription session is updated with a `transcription_session.update` event, unless 
        there is an error.
      properties:
        event_id:
          type: string
          description: The unique ID of the server event.
        type:
          type: string
          enum:
            - transcription_session.updated
          description: The event type, must be `transcription_session.updated`.
          x-stainless-const: true
        session:
          $ref: '#/components/schemas/RealtimeTranscriptionSessionCreateResponse'
      required:
        - event_id
        - type
        - session
      x-oaiMeta:
        name: transcription_session.updated
        group: realtime
        example: |
          {
            "event_id": "event_5678",
            "type": "transcription_session.updated",
            "session": {
              "id": "sess_001",
              "object": "realtime.transcription_session",
              "input_audio_format": "pcm16",
              "input_audio_transcription": {
                "model": "gpt-4o-transcribe",
                "prompt": "",
                "language": ""
              },
              "turn_detection": {
                "type": "server_vad",
                "threshold": 0.5,
                "prefix_padding_ms": 300,
                "silence_duration_ms": 500,
                "create_response": true,
                // "interrupt_response": false  -- this will NOT be returned
              },
              "input_audio_noise_reduction": {
                "type": "near_field"
              },
              "include": [
                "item.input_audio_transcription.avg_logprob",
              ],
            }
          }
    RealtimeSession:
      type: object
      description: Realtime session object configuration.
      properties:
        id:
          type: string
          description: |
            Unique identifier for the session that looks like `sess_1234567890abcdef`.
        modalities:
          description: |
            The set of modalities the model can respond with. To disable audio,
            set this to ["text"].
          items:
            type: string
            default:
              - text
              - audio
            enum:
              - text
              - audio
        model:
          type: string
          description: |
            The Realtime model used for this session.
          enum:
            - gpt-4o-realtime-preview
            - gpt-4o-realtime-preview-2024-10-01
            - gpt-4o-realtime-preview-2024-12-17
            - gpt-4o-realtime-preview-2025-06-03
            - gpt-4o-mini-realtime-preview
            - gpt-4o-mini-realtime-preview-2024-12-17
        instructions:
          type: string
          description: |
            The default system instructions (i.e. system message) prepended to model 
            calls. This field allows the client to guide the model on desired 
            responses. The model can be instructed on response content and format, 
            (e.g. "be extremely succinct", "act friendly", "here are examples of good 
            responses") and on audio behavior (e.g. "talk quickly", "inject emotion 
            into your voice", "laugh frequently"). The instructions are not
            guaranteed to be followed by the model, but they provide guidance to the 
            model on the desired behavior.


            Note that the server sets default instructions which will be used if this
            field is not set and are visible in the `session.created` event at the
            start of the session.
        voice:
          $ref: '#/components/schemas/VoiceIdsShared'
          description: |
            The voice the model uses to respond. Voice cannot be changed during the
            session once the model has responded with audio at least once. Current
            voice options are `alloy`, `ash`, `ballad`, `coral`, `echo`, `fable`,
            `onyx`, `nova`, `sage`, `shimmer`, and `verse`.
        input_audio_format:
          type: string
          default: pcm16
          enum:
            - pcm16
            - g711_ulaw
            - g711_alaw
          description: |
            The format of input audio. Options are `pcm16`, `g711_ulaw`, or `g711_alaw`.
            For `pcm16`, input audio must be 16-bit PCM at a 24kHz sample rate, 
            single channel (mono), and little-endian byte order.
        output_audio_format:
          type: string
          default: pcm16
          enum:
            - pcm16
            - g711_ulaw
            - g711_alaw
          description: |
            The format of output audio. Options are `pcm16`, `g711_ulaw`, or `g711_alaw`.
            For `pcm16`, output audio is sampled at a rate of 24kHz.
        input_audio_transcription:
          type: object
          description: >
            Configuration for input audio transcription, defaults to off and can be  set to `null` to turn off
            once on. Input audio transcription is not native to the model, since the model consumes audio
            directly. Transcription runs  asynchronously through [the /audio/transcriptions
            endpoint](https://platform.openai.com/docs/api-reference/audio/createTranscription) and should be
            treated as guidance of input audio content rather than precisely what the model heard. The client
            can optionally set the language and prompt for transcription, these offer additional guidance to
            the transcription service.
          properties:
            model:
              type: string
              description: >
                The model to use for transcription, current options are `gpt-4o-transcribe`,
                `gpt-4o-mini-transcribe`, and `whisper-1`.
            language:
              type: string
              description: |
                The language of the input audio. Supplying the input language in
                [ISO-639-1](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes) (e.g. `en`) format
                will improve accuracy and latency.
            prompt:
              type: string
              description: >
                An optional text to guide the model's style or continue a previous audio

                segment.

                For `whisper-1`, the [prompt is a list of keywords](/docs/guides/speech-to-text#prompting).

                For `gpt-4o-transcribe` models, the prompt is a free text string, for example "expect words
                related to technology".
        turn_detection:
          type: object
          description: >
            Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to `null` to
            turn off, in which case the client must manually trigger model response.

            Server VAD means that the model will detect the start and end of speech based on audio volume and
            respond at the end of user speech.

            Semantic VAD is more advanced and uses a turn detection model (in conjuction with VAD) to
            semantically estimate whether the user has finished speaking, then dynamically sets a timeout
            based on this probability. For example, if user audio trails off with "uhhm", the model will score
            a low probability of turn end and wait longer for the user to continue speaking. This can be
            useful for more natural conversations, but may have a higher latency.
          properties:
            type:
              type: string
              default: server_vad
              enum:
                - server_vad
                - semantic_vad
              description: |
                Type of turn detection.
            eagerness:
              type: string
              default: auto
              enum:
                - low
                - medium
                - high
                - auto
              description: >
                Used only for `semantic_vad` mode. The eagerness of the model to respond. `low` will wait
                longer for the user to continue speaking, `high` will respond more quickly. `auto` is the
                default and is equivalent to `medium`.
            threshold:
              type: number
              description: >
                Used only for `server_vad` mode. Activation threshold for VAD (0.0 to 1.0), this defaults to
                0.5. A 

                higher threshold will require louder audio to activate the model, and 

                thus might perform better in noisy environments.
            prefix_padding_ms:
              type: integer
              description: >
                Used only for `server_vad` mode. Amount of audio to include before the VAD detected speech
                (in 

                milliseconds). Defaults to 300ms.
            silence_duration_ms:
              type: integer
              description: >
                Used only for `server_vad` mode. Duration of silence to detect speech stop (in milliseconds).
                Defaults 

                to 500ms. With shorter values the model will respond more quickly, 

                but may jump in on short pauses from the user.
            create_response:
              type: boolean
              default: true
              description: |
                Whether or not to automatically generate a response when a VAD stop event occurs.
            interrupt_response:
              type: boolean
              default: true
              description: |
                Whether or not to automatically interrupt any ongoing response with output to the default
                conversation (i.e. `conversation` of `auto`) when a VAD start event occurs.
        input_audio_noise_reduction:
          type: object
          default: null
          description: >
            Configuration for input audio noise reduction. This can be set to `null` to turn off.

            Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the
            model.

            Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and
            model performance by improving perception of the input audio.
          properties:
            type:
              type: string
              enum:
                - near_field
                - far_field
              description: >
                Type of noise reduction. `near_field` is for close-talking microphones such as headphones,
                `far_field` is for far-field microphones such as laptop or conference room microphones.
        speed:
          type: number
          default: 1
          maximum: 1.5
          minimum: 0.25
          description: |
            The speed of the model's spoken response. 1.0 is the default speed. 0.25 is
            the minimum speed. 1.5 is the maximum speed. This value can only be changed
            in between model turns, not while a response is in progress.
        tracing:
          title: Tracing Configuration
          description: |
            Configuration options for tracing. Set to null to disable tracing. Once 
            tracing is enabled for a session, the configuration cannot be modified.

            `auto` will create a trace for the session with default values for the 
            workflow name, group id, and metadata.
          oneOf:
            - type: string
              default: auto
              description: |
                Default tracing mode for the session.
              enum:
                - auto
              x-stainless-const: true
            - type: object
              title: Tracing Configuration
              description: |
                Granular configuration for tracing.
              properties:
                workflow_name:
                  type: string
                  description: |
                    The name of the workflow to attach to this trace. This is used to 
                    name the trace in the traces dashboard.
                group_id:
                  type: string
                  description: |
                    The group id to attach to this trace to enable filtering and 
                    grouping in the traces dashboard.
                metadata:
                  type: object
                  description: |
                    The arbitrary metadata to attach to this trace to enable 
                    filtering in the traces dashboard.
        tools:
          type: array
          description: Tools (functions) available to the model.
          items:
            type: object
            properties:
              type:
                type: string
                enum:
                  - function
                description: The type of the tool, i.e. `function`.
                x-stainless-const: true
              name:
                type: string
                description: The name of the function.
              description:
                type: string
                description: |
                  The description of the function, including guidance on when and how 
                  to call it, and guidance about what to tell the user when calling 
                  (if anything).
              parameters:
                type: object
                description: Parameters of the function in JSON Schema.
        tool_choice:
          type: string
          default: auto
          description: |
            How the model chooses tools. Options are `auto`, `none`, `required`, or 
            specify a function.
        temperature:
          type: number
          default: 0.8
          description: >
            Sampling temperature for the model, limited to [0.6, 1.2]. For audio models a temperature of 0.8
            is highly recommended for best performance.
        max_response_output_tokens:
          oneOf:
            - type: integer
            - type: string
              enum:
                - inf
              x-stainless-const: true
          description: |
            Maximum number of output tokens for a single assistant response,
            inclusive of tool calls. Provide an integer between 1 and 4096 to
            limit output tokens, or `inf` for the maximum available tokens for a
            given model. Defaults to `inf`.
    RealtimeSessionCreateRequest:
      type: object
      description: Realtime session object configuration.
      properties:
        modalities:
          description: |
            The set of modalities the model can respond with. To disable audio,
            set this to ["text"].
          items:
            type: string
            default:
              - text
              - audio
            enum:
              - text
              - audio
        model:
          type: string
          description: |
            The Realtime model used for this session.
          enum:
            - gpt-4o-realtime-preview
            - gpt-4o-realtime-preview-2024-10-01
            - gpt-4o-realtime-preview-2024-12-17
            - gpt-4o-realtime-preview-2025-06-03
            - gpt-4o-mini-realtime-preview
            - gpt-4o-mini-realtime-preview-2024-12-17
        instructions:
          type: string
          description: >
            The default system instructions (i.e. system message) prepended to model calls. This field allows
            the client to guide the model on desired responses. The model can be instructed on response
            content and format, (e.g. "be extremely succinct", "act friendly", "here are examples of good
            responses") and on audio behavior (e.g. "talk quickly", "inject emotion into your voice", "laugh
            frequently"). The instructions are not guaranteed to be followed by the model, but they provide
            guidance to the model on the desired behavior.


            Note that the server sets default instructions which will be used if this field is not set and are
            visible in the `session.created` event at the start of the session.
        voice:
          $ref: '#/components/schemas/VoiceIdsShared'
          description: |
            The voice the model uses to respond. Voice cannot be changed during the
            session once the model has responded with audio at least once. Current
            voice options are `alloy`, `ash`, `ballad`, `coral`, `echo`, `fable`,
            `onyx`, `nova`, `sage`, `shimmer`, and `verse`.
        input_audio_format:
          type: string
          default: pcm16
          enum:
            - pcm16
            - g711_ulaw
            - g711_alaw
          description: |
            The format of input audio. Options are `pcm16`, `g711_ulaw`, or `g711_alaw`.
            For `pcm16`, input audio must be 16-bit PCM at a 24kHz sample rate,
            single channel (mono), and little-endian byte order.
        output_audio_format:
          type: string
          default: pcm16
          enum:
            - pcm16
            - g711_ulaw
            - g711_alaw
          description: |
            The format of output audio. Options are `pcm16`, `g711_ulaw`, or `g711_alaw`.
            For `pcm16`, output audio is sampled at a rate of 24kHz.
        input_audio_transcription:
          type: object
          description: >
            Configuration for input audio transcription, defaults to off and can be set to `null` to turn off
            once on. Input audio transcription is not native to the model, since the model consumes audio
            directly. Transcription runs asynchronously through [the /audio/transcriptions
            endpoint](https://platform.openai.com/docs/api-reference/audio/createTranscription) and should be
            treated as guidance of input audio content rather than precisely what the model heard. The client
            can optionally set the language and prompt for transcription, these offer additional guidance to
            the transcription service.
          properties:
            model:
              type: string
              description: >
                The model to use for transcription, current options are `gpt-4o-transcribe`,
                `gpt-4o-mini-transcribe`, and `whisper-1`.
            language:
              type: string
              description: |
                The language of the input audio. Supplying the input language in
                [ISO-639-1](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes) (e.g. `en`) format
                will improve accuracy and latency.
            prompt:
              type: string
              description: >
                An optional text to guide the model's style or continue a previous audio

                segment.

                For `whisper-1`, the [prompt is a list of keywords](/docs/guides/speech-to-text#prompting).

                For `gpt-4o-transcribe` models, the prompt is a free text string, for example "expect words
                related to technology".
        turn_detection:
          type: object
          description: >
            Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to `null` to
            turn off, in which case the client must manually trigger model response.

            Server VAD means that the model will detect the start and end of speech based on audio volume and
            respond at the end of user speech.

            Semantic VAD is more advanced and uses a turn detection model (in conjuction with VAD) to
            semantically estimate whether the user has finished speaking, then dynamically sets a timeout
            based on this probability. For example, if user audio trails off with "uhhm", the model will score
            a low probability of turn end and wait longer for the user to continue speaking. This can be
            useful for more natural conversations, but may have a higher latency.
          properties:
            type:
              type: string
              default: server_vad
              enum:
                - server_vad
                - semantic_vad
              description: |
                Type of turn detection.
            eagerness:
              type: string
              default: auto
              enum:
                - low
                - medium
                - high
                - auto
              description: >
                Used only for `semantic_vad` mode. The eagerness of the model to respond. `low` will wait
                longer for the user to continue speaking, `high` will respond more quickly. `auto` is the
                default and is equivalent to `medium`.
            threshold:
              type: number
              description: >
                Used only for `server_vad` mode. Activation threshold for VAD (0.0 to 1.0), this defaults to
                0.5. A

                higher threshold will require louder audio to activate the model, and

                thus might perform better in noisy environments.
            prefix_padding_ms:
              type: integer
              description: |
                Used only for `server_vad` mode. Amount of audio to include before the VAD detected speech (in
                milliseconds). Defaults to 300ms.
            silence_duration_ms:
              type: integer
              description: >
                Used only for `server_vad` mode. Duration of silence to detect speech stop (in milliseconds).
                Defaults

                to 500ms. With shorter values the model will respond more quickly,

                but may jump in on short pauses from the user.
            create_response:
              type: boolean
              default: true
              description: |
                Whether or not to automatically generate a response when a VAD stop event occurs.
            interrupt_response:
              type: boolean
              default: true
              description: |
                Whether or not to automatically interrupt any ongoing response with output to the default
                conversation (i.e. `conversation` of `auto`) when a VAD start event occurs.
        input_audio_noise_reduction:
          type: object
          default: null
          description: >
            Configuration for input audio noise reduction. This can be set to `null` to turn off.

            Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the
            model.

            Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and
            model performance by improving perception of the input audio.
          properties:
            type:
              type: string
              enum:
                - near_field
                - far_field
              description: >
                Type of noise reduction. `near_field` is for close-talking microphones such as headphones,
                `far_field` is for far-field microphones such as laptop or conference room microphones.
        speed:
          type: number
          default: 1
          maximum: 1.5
          minimum: 0.25
          description: |
            The speed of the model's spoken response. 1.0 is the default speed. 0.25 is
            the minimum speed. 1.5 is the maximum speed. This value can only be changed
            in between model turns, not while a response is in progress.
        tracing:
          title: Tracing Configuration
          description: |
            Configuration options for tracing. Set to null to disable tracing. Once 
            tracing is enabled for a session, the configuration cannot be modified.

            `auto` will create a trace for the session with default values for the 
            workflow name, group id, and metadata.
          oneOf:
            - type: string
              default: auto
              description: |
                Default tracing mode for the session.
              enum:
                - auto
              x-stainless-const: true
            - type: object
              title: Tracing Configuration
              description: |
                Granular configuration for tracing.
              properties:
                workflow_name:
                  type: string
                  description: |
                    The name of the workflow to attach to this trace. This is used to 
                    name the trace in the traces dashboard.
                group_id:
                  type: string
                  description: |
                    The group id to attach to this trace to enable filtering and 
                    grouping in the traces dashboard.
                metadata:
                  type: object
                  description: |
                    The arbitrary metadata to attach to this trace to enable 
                    filtering in the traces dashboard.
        tools:
          type: array
          description: Tools (functions) available to the model.
          items:
            type: object
            properties:
              type:
                type: string
                enum:
                  - function
                description: The type of the tool, i.e. `function`.
                x-stainless-const: true
              name:
                type: string
                description: The name of the function.
              description:
                type: string
                description: |
                  The description of the function, including guidance on when and how
                  to call it, and guidance about what to tell the user when calling
                  (if anything).
              parameters:
                type: object
                description: Parameters of the function in JSON Schema.
        tool_choice:
          type: string
          default: auto
          description: |
            How the model chooses tools. Options are `auto`, `none`, `required`, or
            specify a function.
        temperature:
          type: number
          default: 0.8
          description: >
            Sampling temperature for the model, limited to [0.6, 1.2]. For audio models a temperature of 0.8
            is highly recommended for best performance.
        max_response_output_tokens:
          oneOf:
            - type: integer
            - type: string
              enum:
                - inf
              x-stainless-const: true
          description: |
            Maximum number of output tokens for a single assistant response,
            inclusive of tool calls. Provide an integer between 1 and 4096 to
            limit output tokens, or `inf` for the maximum available tokens for a
            given model. Defaults to `inf`.
        client_secret:
          type: object
          description: |
            Configuration options for the generated client secret.
          properties:
            expires_at:
              type: object
              description: |
                Configuration for the ephemeral token expiration.
              properties:
                anchor:
                  default: created_at
                  type: string
                  enum:
                    - created_at
                  description: >
                    The anchor point for the ephemeral token expiration. Only `created_at` is currently
                    supported.
                seconds:
                  default: 600
                  type: integer
                  description: >
                    The number of seconds from the anchor point to the expiration. Select a value between `10`
                    and `7200`.
    RealtimeSessionCreateResponse:
      type: object
      description: |
        A new Realtime session configuration, with an ephermeral key. Default TTL
        for keys is one minute.
      properties:
        client_secret:
          type: object
          description: Ephemeral key returned by the API.
          properties:
            value:
              type: string
              description: |
                Ephemeral key usable in client environments to authenticate connections
                to the Realtime API. Use this in client-side environments rather than
                a standard API token, which should only be used server-side.
            expires_at:
              type: integer
              description: |
                Timestamp for when the token expires. Currently, all tokens expire
                after one minute.
          required:
            - value
            - expires_at
        modalities:
          description: |
            The set of modalities the model can respond with. To disable audio,
            set this to ["text"].
          items:
            type: string
            enum:
              - text
              - audio
        instructions:
          type: string
          description: |
            The default system instructions (i.e. system message) prepended to model 
            calls. This field allows the client to guide the model on desired 
            responses. The model can be instructed on response content and format, 
            (e.g. "be extremely succinct", "act friendly", "here are examples of good 
            responses") and on audio behavior (e.g. "talk quickly", "inject emotion 
            into your voice", "laugh frequently"). The instructions are not guaranteed 
            to be followed by the model, but they provide guidance to the model on the 
            desired behavior.

            Note that the server sets default instructions which will be used if this 
            field is not set and are visible in the `session.created` event at the 
            start of the session.
        voice:
          $ref: '#/components/schemas/VoiceIdsShared'
          description: |
            The voice the model uses to respond. Voice cannot be changed during the 
            session once the model has responded with audio at least once. Current 
            voice options are `alloy`, `ash`, `ballad`, `coral`, `echo` `sage`, 
            `shimmer` and `verse`.
        input_audio_format:
          type: string
          description: |
            The format of input audio. Options are `pcm16`, `g711_ulaw`, or `g711_alaw`.
        output_audio_format:
          type: string
          description: |
            The format of output audio. Options are `pcm16`, `g711_ulaw`, or `g711_alaw`.
        input_audio_transcription:
          type: object
          description: |
            Configuration for input audio transcription, defaults to off and can be 
            set to `null` to turn off once on. Input audio transcription is not native 
            to the model, since the model consumes audio directly. Transcription runs 
            asynchronously through Whisper and should be treated as rough guidance 
            rather than the representation understood by the model.
          properties:
            model:
              type: string
              description: |
                The model to use for transcription, `whisper-1` is the only currently 
                supported model.
        speed:
          type: number
          default: 1
          maximum: 1.5
          minimum: 0.25
          description: |
            The speed of the model's spoken response. 1.0 is the default speed. 0.25 is
            the minimum speed. 1.5 is the maximum speed. This value can only be changed
            in between model turns, not while a response is in progress.
        tracing:
          title: Tracing Configuration
          description: |
            Configuration options for tracing. Set to null to disable tracing. Once 
            tracing is enabled for a session, the configuration cannot be modified.

            `auto` will create a trace for the session with default values for the 
            workflow name, group id, and metadata.
          oneOf:
            - type: string
              default: auto
              description: |
                Default tracing mode for the session.
              enum:
                - auto
              x-stainless-const: true
            - type: object
              title: Tracing Configuration
              description: |
                Granular configuration for tracing.
              properties:
                workflow_name:
                  type: string
                  description: |
                    The name of the workflow to attach to this trace. This is used to 
                    name the trace in the traces dashboard.
                group_id:
                  type: string
                  description: |
                    The group id to attach to this trace to enable filtering and 
                    grouping in the traces dashboard.
                metadata:
                  type: object
                  description: |
                    The arbitrary metadata to attach to this trace to enable 
                    filtering in the traces dashboard.
        turn_detection:
          type: object
          description: |
            Configuration for turn detection. Can be set to `null` to turn off. Server 
            VAD means that the model will detect the start and end of speech based on 
            audio volume and respond at the end of user speech.
          properties:
            type:
              type: string
              description: |
                Type of turn detection, only `server_vad` is currently supported.
            threshold:
              type: number
              description: |
                Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A 
                higher threshold will require louder audio to activate the model, and 
                thus might perform better in noisy environments.
            prefix_padding_ms:
              type: integer
              description: |
                Amount of audio to include before the VAD detected speech (in 
                milliseconds). Defaults to 300ms.
            silence_duration_ms:
              type: integer
              description: |
                Duration of silence to detect speech stop (in milliseconds). Defaults 
                to 500ms. With shorter values the model will respond more quickly, 
                but may jump in on short pauses from the user.
        tools:
          type: array
          description: Tools (functions) available to the model.
          items:
            type: object
            properties:
              type:
                type: string
                enum:
                  - function
                description: The type of the tool, i.e. `function`.
                x-stainless-const: true
              name:
                type: string
                description: The name of the function.
              description:
                type: string
                description: |
                  The description of the function, including guidance on when and how 
                  to call it, and guidance about what to tell the user when calling 
                  (if anything).
              parameters:
                type: object
                description: Parameters of the function in JSON Schema.
        tool_choice:
          type: string
          description: |
            How the model chooses tools. Options are `auto`, `none`, `required`, or 
            specify a function.
        temperature:
          type: number
          description: |
            Sampling temperature for the model, limited to [0.6, 1.2]. Defaults to 0.8.
        max_response_output_tokens:
          oneOf:
            - type: integer
            - type: string
              enum:
                - inf
              x-stainless-const: true
          description: |
            Maximum number of output tokens for a single assistant response,
            inclusive of tool calls. Provide an integer between 1 and 4096 to
            limit output tokens, or `inf` for the maximum available tokens for a
            given model. Defaults to `inf`.
      required:
        - client_secret
      x-oaiMeta:
        name: The session object
        group: realtime
        example: |
          {
            "id": "sess_001",
            "object": "realtime.session",
            "model": "gpt-4o-realtime-preview",
            "modalities": ["audio", "text"],
            "instructions": "You are a friendly assistant.",
            "voice": "alloy",
            "input_audio_format": "pcm16",
            "output_audio_format": "pcm16",
            "input_audio_transcription": {
                "model": "whisper-1"
            },
            "turn_detection": null,
            "tools": [],
            "tool_choice": "none",
            "temperature": 0.7,
            "speed": 1.1,
            "tracing": "auto",
            "max_response_output_tokens": 200,
            "client_secret": {
              "value": "ek_abc123", 
              "expires_at": 1234567890
            }
          }
    RealtimeTranscriptionSessionCreateRequest:
      type: object
      description: Realtime transcription session object configuration.
      properties:
        modalities:
          description: |
            The set of modalities the model can respond with. To disable audio,
            set this to ["text"].
          items:
            type: string
            default:
              - text
              - audio
            enum:
              - text
              - audio
        input_audio_format:
          type: string
          default: pcm16
          enum:
            - pcm16
            - g711_ulaw
            - g711_alaw
          description: |
            The format of input audio. Options are `pcm16`, `g711_ulaw`, or `g711_alaw`.
            For `pcm16`, input audio must be 16-bit PCM at a 24kHz sample rate,
            single channel (mono), and little-endian byte order.
        input_audio_transcription:
          type: object
          description: >
            Configuration for input audio transcription. The client can optionally set the language and prompt
            for transcription, these offer additional guidance to the transcription service.
          properties:
            model:
              type: string
              description: >
                The model to use for transcription, current options are `gpt-4o-transcribe`,
                `gpt-4o-mini-transcribe`, and `whisper-1`.
              enum:
                - gpt-4o-transcribe
                - gpt-4o-mini-transcribe
                - whisper-1
            language:
              type: string
              description: |
                The language of the input audio. Supplying the input language in
                [ISO-639-1](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes) (e.g. `en`) format
                will improve accuracy and latency.
            prompt:
              type: string
              description: >
                An optional text to guide the model's style or continue a previous audio

                segment.

                For `whisper-1`, the [prompt is a list of keywords](/docs/guides/speech-to-text#prompting).

                For `gpt-4o-transcribe` models, the prompt is a free text string, for example "expect words
                related to technology".
        turn_detection:
          type: object
          description: >
            Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to `null` to
            turn off, in which case the client must manually trigger model response.

            Server VAD means that the model will detect the start and end of speech based on audio volume and
            respond at the end of user speech.

            Semantic VAD is more advanced and uses a turn detection model (in conjuction with VAD) to
            semantically estimate whether the user has finished speaking, then dynamically sets a timeout
            based on this probability. For example, if user audio trails off with "uhhm", the model will score
            a low probability of turn end and wait longer for the user to continue speaking. This can be
            useful for more natural conversations, but may have a higher latency.
          properties:
            type:
              type: string
              default: server_vad
              enum:
                - server_vad
                - semantic_vad
              description: |
                Type of turn detection.
            eagerness:
              type: string
              default: auto
              enum:
                - low
                - medium
                - high
                - auto
              description: >
                Used only for `semantic_vad` mode. The eagerness of the model to respond. `low` will wait
                longer for the user to continue speaking, `high` will respond more quickly. `auto` is the
                default and is equivalent to `medium`.
            threshold:
              type: number
              description: >
                Used only for `server_vad` mode. Activation threshold for VAD (0.0 to 1.0), this defaults to
                0.5. A

                higher threshold will require louder audio to activate the model, and

                thus might perform better in noisy environments.
            prefix_padding_ms:
              type: integer
              description: |
                Used only for `server_vad` mode. Amount of audio to include before the VAD detected speech (in
                milliseconds). Defaults to 300ms.
            silence_duration_ms:
              type: integer
              description: >
                Used only for `server_vad` mode. Duration of silence to detect speech stop (in milliseconds).
                Defaults

                to 500ms. With shorter values the model will respond more quickly,

                but may jump in on short pauses from the user.
            create_response:
              type: boolean
              default: true
              description: >
                Whether or not to automatically generate a response when a VAD stop event occurs. Not
                available for transcription sessions.
            interrupt_response:
              type: boolean
              default: true
              description: >
                Whether or not to automatically interrupt any ongoing response with output to the default

                conversation (i.e. `conversation` of `auto`) when a VAD start event occurs. Not available for
                transcription sessions.
        input_audio_noise_reduction:
          type: object
          default: null
          description: >
            Configuration for input audio noise reduction. This can be set to `null` to turn off.

            Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the
            model.

            Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and
            model performance by improving perception of the input audio.
          properties:
            type:
              type: string
              enum:
                - near_field
                - far_field
              description: >
                Type of noise reduction. `near_field` is for close-talking microphones such as headphones,
                `far_field` is for far-field microphones such as laptop or conference room microphones.
        include:
          type: array
          items:
            type: string
          description: |
            The set of items to include in the transcription. Current available items are:
            - `item.input_audio_transcription.logprobs`
        client_secret:
          type: object
          description: |
            Configuration options for the generated client secret.
          properties:
            expires_at:
              type: object
              description: |
                Configuration for the ephemeral token expiration.
              properties:
                anchor:
                  default: created_at
                  type: string
                  enum:
                    - created_at
                  description: >
                    The anchor point for the ephemeral token expiration. Only `created_at` is currently
                    supported.
                seconds:
                  default: 600
                  type: integer
                  description: >
                    The number of seconds from the anchor point to the expiration. Select a value between `10`
                    and `7200`.
    RealtimeTranscriptionSessionCreateResponse:
      type: object
      description: |
        A new Realtime transcription session configuration.

        When a session is created on the server via REST API, the session object
        also contains an ephemeral key. Default TTL for keys is 10 minutes. This 
        property is not present when a session is updated via the WebSocket API.
      properties:
        client_secret:
          type: object
          description: |
            Ephemeral key returned by the API. Only present when the session is
            created on the server via REST API.
          properties:
            value:
              type: string
              description: |
                Ephemeral key usable in client environments to authenticate connections
                to the Realtime API. Use this in client-side environments rather than
                a standard API token, which should only be used server-side.
            expires_at:
              type: integer
              description: |
                Timestamp for when the token expires. Currently, all tokens expire
                after one minute.
          required:
            - value
            - expires_at
        modalities:
          description: |
            The set of modalities the model can respond with. To disable audio,
            set this to ["text"].
          items:
            type: string
            enum:
              - text
              - audio
        input_audio_format:
          type: string
          description: |
            The format of input audio. Options are `pcm16`, `g711_ulaw`, or `g711_alaw`.
        input_audio_transcription:
          type: object
          description: |
            Configuration of the transcription model.
          properties:
            model:
              type: string
              description: >
                The model to use for transcription. Can be `gpt-4o-transcribe`, `gpt-4o-mini-transcribe`, or
                `whisper-1`.
              enum:
                - gpt-4o-transcribe
                - gpt-4o-mini-transcribe
                - whisper-1
            language:
              type: string
              description: |
                The language of the input audio. Supplying the input language in
                [ISO-639-1](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes) (e.g. `en`) format
                will improve accuracy and latency.
            prompt:
              type: string
              description: |
                An optional text to guide the model's style or continue a previous audio
                segment. The [prompt](/docs/guides/speech-to-text#prompting) should match
                the audio language.
        turn_detection:
          type: object
          description: |
            Configuration for turn detection. Can be set to `null` to turn off. Server 
            VAD means that the model will detect the start and end of speech based on 
            audio volume and respond at the end of user speech.
          properties:
            type:
              type: string
              description: |
                Type of turn detection, only `server_vad` is currently supported.
            threshold:
              type: number
              description: |
                Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A 
                higher threshold will require louder audio to activate the model, and 
                thus might perform better in noisy environments.
            prefix_padding_ms:
              type: integer
              description: |
                Amount of audio to include before the VAD detected speech (in 
                milliseconds). Defaults to 300ms.
            silence_duration_ms:
              type: integer
              description: |
                Duration of silence to detect speech stop (in milliseconds). Defaults 
                to 500ms. With shorter values the model will respond more quickly, 
                but may jump in on short pauses from the user.
      required:
        - client_secret
      x-oaiMeta:
        name: The transcription session object
        group: realtime
        example: |
          {
            "id": "sess_BBwZc7cFV3XizEyKGDCGL",
            "object": "realtime.transcription_session",
            "expires_at": 1742188264,
            "modalities": ["audio", "text"],
            "turn_detection": {
              "type": "server_vad",
              "threshold": 0.5,
              "prefix_padding_ms": 300,
              "silence_duration_ms": 200
            },
            "input_audio_format": "pcm16",
            "input_audio_transcription": {
              "model": "gpt-4o-transcribe",
              "language": null,
              "prompt": ""
            },
            "client_secret": null
          }
    Reasoning:
      type: object
      description: |
        **o-series models only**

        Configuration options for 
        [reasoning models](https://platform.openai.com/docs/guides/reasoning).
      title: Reasoning
      properties:
        effort:
          $ref: '#/components/schemas/ReasoningEffort'
        summary:
          type: string
          description: |
            A summary of the reasoning performed by the model. This can be
            useful for debugging and understanding the model's reasoning process.
            One of `auto`, `concise`, or `detailed`.
          enum:
            - auto
            - concise
            - detailed
          nullable: true
        generate_summary:
          type: string
          deprecated: true
          description: |
            **Deprecated:** use `summary` instead.

            A summary of the reasoning performed by the model. This can be
            useful for debugging and understanding the model's reasoning process.
            One of `auto`, `concise`, or `detailed`.
          enum:
            - auto
            - concise
            - detailed
          nullable: true
    ReasoningEffort:
      type: string
      enum:
        - low
        - medium
        - high
      default: medium
      nullable: true
      description: |
        **o-series models only** 

        Constrains effort on reasoning for 
        [reasoning models](https://platform.openai.com/docs/guides/reasoning).
        Currently supported values are `low`, `medium`, and `high`. Reducing
        reasoning effort can result in faster responses and fewer tokens used
        on reasoning in a response.
    ReasoningItem:
      type: object
      description: |
        A description of the chain of thought used by a reasoning model while generating
        a response. Be sure to include these items in your `input` to the Responses API
        for subsequent turns of a conversation if you are manually 
        [managing context](/docs/guides/conversation-state).
      title: Reasoning
      properties:
        type:
          type: string
          description: |
            The type of the object. Always `reasoning`.
          enum:
            - reasoning
          x-stainless-const: true
        id:
          type: string
          description: |
            The unique identifier of the reasoning content.
        encrypted_content:
          type: string
          description: |
            The encrypted content of the reasoning item - populated when a response is
            generated with `reasoning.encrypted_content` in the `include` parameter.
          nullable: true
        summary:
          type: array
          description: |
            Reasoning text contents.
          items:
            type: object
            properties:
              type:
                type: string
                description: |
                  The type of the object. Always `summary_text`.
                enum:
                  - summary_text
                x-stainless-const: true
              text:
                type: string
                description: |
                  A short summary of the reasoning used by the model when generating
                  the response.
            required:
              - type
              - text
        status:
          type: string
          description: |
            The status of the item. One of `in_progress`, `completed`, or
            `incomplete`. Populated when items are returned via API.
          enum:
            - in_progress
            - completed
            - incomplete
      required:
        - id
        - summary
        - type
    Response:
      title: The response object
      allOf:
        - $ref: '#/components/schemas/ModelResponseProperties'
        - $ref: '#/components/schemas/ResponseProperties'
        - type: object
          properties:
            id:
              type: string
              description: |
                Unique identifier for this Response.
            object:
              type: string
              description: |
                The object type of this resource - always set to `response`.
              enum:
                - response
              x-stainless-const: true
            status:
              type: string
              description: |
                The status of the response generation. One of `completed`, `failed`, 
                `in_progress`, `cancelled`, `queued`, or `incomplete`.
              enum:
                - completed
                - failed
                - in_progress
                - cancelled
                - queued
                - incomplete
            created_at:
              type: number
              description: |
                Unix timestamp (in seconds) of when this Response was created.
            error:
              $ref: '#/components/schemas/ResponseError'
            incomplete_details:
              type: object
              nullable: true
              description: |
                Details about why the response is incomplete.
              properties:
                reason:
                  type: string
                  description: The reason why the response is incomplete.
                  enum:
                    - max_output_tokens
                    - content_filter
            output:
              type: array
              description: |
                An array of content items generated by the model.

                - The length and order of items in the `output` array is dependent
                  on the model's response.
                - Rather than accessing the first item in the `output` array and 
                  assuming it's an `assistant` message with the content generated by
                  the model, you might consider using the `output_text` property where
                  supported in SDKs.
              items:
                $ref: '#/components/schemas/OutputItem'
            instructions:
              nullable: true
              description: |
                A system (or developer) message inserted into the model's context.

                When using along with `previous_response_id`, the instructions from a previous
                response will not be carried over to the next response. This makes it simple
                to swap out system (or developer) messages in new responses.
              oneOf:
                - type: string
                  description: |
                    A text input to the model, equivalent to a text input with the 
                    `developer` role.
                - type: array
                  title: Input item list
                  description: |
                    A list of one or many input items to the model, containing 
                    different content types.
                  items:
                    $ref: '#/components/schemas/InputItem'
            output_text:
              type: string
              nullable: true
              description: |
                SDK-only convenience property that contains the aggregated text output 
                from all `output_text` items in the `output` array, if any are present. 
                Supported in the Python and JavaScript SDKs.
              x-oaiSupportedSDKs:
                - python
                - javascript
            usage:
              $ref: '#/components/schemas/ResponseUsage'
            parallel_tool_calls:
              type: boolean
              description: |
                Whether to allow the model to run tool calls in parallel.
              default: true
          required:
            - id
            - object
            - created_at
            - error
            - incomplete_details
            - instructions
            - model
            - tools
            - output
            - parallel_tool_calls
            - metadata
            - tool_choice
            - temperature
            - top_p
      example:
        id: resp_67ccd3a9da748190baa7f1570fe91ac604becb25c45c1d41
        object: response
        created_at: 1741476777
        status: completed
        error: null
        incomplete_details: null
        instructions: null
        max_output_tokens: null
        model: gpt-4o-2024-08-06
        output:
          - type: message
            id: msg_67ccd3acc8d48190a77525dc6de64b4104becb25c45c1d41
            status: completed
            role: assistant
            content:
              - type: output_text
                text: >-
                  The image depicts a scenic landscape with a wooden boardwalk or pathway leading through
                  lush, green grass under a blue sky with some clouds. The setting suggests a peaceful natural
                  area, possibly a park or nature reserve. There are trees and shrubs in the background.
                annotations: []
        parallel_tool_calls: true
        previous_response_id: null
        reasoning:
          effort: null
          summary: null
        store: true
        temperature: 1
        text:
          format:
            type: text
        tool_choice: auto
        tools: []
        top_p: 1
        truncation: disabled
        usage:
          input_tokens: 328
          input_tokens_details:
            cached_tokens: 0
          output_tokens: 52
          output_tokens_details:
            reasoning_tokens: 0
          total_tokens: 380
        user: null
        metadata: {}
    ResponseAudioDeltaEvent:
      type: object
      description: Emitted when there is a partial audio response.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.audio.delta`.
          enum:
            - response.audio.delta
          x-stainless-const: true
        sequence_number:
          type: integer
          description: |
            A sequence number for this chunk of the stream response.
        delta:
          type: string
          description: |
            A chunk of Base64 encoded response audio bytes.
      required:
        - type
        - delta
        - sequence_number
      x-oaiMeta:
        name: response.audio.delta
        group: responses
        example: |
          {
            "type": "response.audio.delta",
            "response_id": "resp_123",
            "delta": "base64encoded...",
            "sequence_number": 1
          }
    ResponseAudioDoneEvent:
      type: object
      description: Emitted when the audio response is complete.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.audio.done`.
          enum:
            - response.audio.done
          x-stainless-const: true
        sequence_number:
          type: integer
          description: |
            The sequence number of the delta.
      required:
        - type
        - sequence_number
        - response_id
      x-oaiMeta:
        name: response.audio.done
        group: responses
        example: |
          {
            "type": "response.audio.done",
            "response_id": "resp-123",
            "sequence_number": 1
          }
    ResponseAudioTranscriptDeltaEvent:
      type: object
      description: Emitted when there is a partial transcript of audio.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.audio.transcript.delta`.
          enum:
            - response.audio.transcript.delta
          x-stainless-const: true
        delta:
          type: string
          description: |
            The partial transcript of the audio response.
        sequence_number:
          type: integer
          description: The sequence number of this event.
      required:
        - type
        - response_id
        - delta
        - sequence_number
      x-oaiMeta:
        name: response.audio.transcript.delta
        group: responses
        example: |
          {
            "type": "response.audio.transcript.delta",
            "response_id": "resp_123",
            "delta": " ... partial transcript ... ",
            "sequence_number": 1
          }
    ResponseAudioTranscriptDoneEvent:
      type: object
      description: Emitted when the full audio transcript is completed.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.audio.transcript.done`.
          enum:
            - response.audio.transcript.done
          x-stainless-const: true
        sequence_number:
          type: integer
          description: The sequence number of this event.
      required:
        - type
        - response_id
        - sequence_number
      x-oaiMeta:
        name: response.audio.transcript.done
        group: responses
        example: |
          {
            "type": "response.audio.transcript.done",
            "response_id": "resp_123",
            "sequence_number": 1
          }
    ResponseCodeInterpreterCallCodeDeltaEvent:
      type: object
      description: Emitted when a partial code snippet is added by the code interpreter.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.code_interpreter_call_code.delta`.
          enum:
            - response.code_interpreter_call_code.delta
          x-stainless-const: true
        output_index:
          type: integer
          description: |
            The index of the output item that the code interpreter call is in progress.
        delta:
          type: string
          description: |
            The partial code snippet added by the code interpreter.
        sequence_number:
          type: integer
          description: The sequence number of this event.
      required:
        - type
        - response_id
        - output_index
        - delta
        - sequence_number
      x-oaiMeta:
        name: response.code_interpreter_call_code.delta
        group: responses
        example: |
          {
            "type": "response.code_interpreter_call_code.delta",
            "response_id": "resp-123",
            "output_index": 0,
            "delta": "partial code",
            "sequence_number": 1
          }
    ResponseCodeInterpreterCallCodeDoneEvent:
      type: object
      description: Emitted when code snippet output is finalized by the code interpreter.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.code_interpreter_call_code.done`.
          enum:
            - response.code_interpreter_call_code.done
          x-stainless-const: true
        output_index:
          type: integer
          description: |
            The index of the output item that the code interpreter call is in progress.
        code:
          type: string
          description: |
            The final code snippet output by the code interpreter.
        sequence_number:
          type: integer
          description: The sequence number of this event.
      required:
        - type
        - response_id
        - output_index
        - code
        - sequence_number
      x-oaiMeta:
        name: response.code_interpreter_call_code.done
        group: responses
        example: |
          {
            "type": "response.code_interpreter_call_code.done",
            "response_id": "resp-123",
            "output_index": 3,
            "code": "console.log('done');",
            "sequence_number": 1
          }
    ResponseCodeInterpreterCallCompletedEvent:
      type: object
      description: Emitted when the code interpreter call is completed.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.code_interpreter_call.completed`.
          enum:
            - response.code_interpreter_call.completed
          x-stainless-const: true
        output_index:
          type: integer
          description: |
            The index of the output item that the code interpreter call is in progress.
        code_interpreter_call:
          $ref: '#/components/schemas/CodeInterpreterToolCall'
        sequence_number:
          type: integer
          description: The sequence number of this event.
      required:
        - type
        - response_id
        - output_index
        - code_interpreter_call
        - sequence_number
      x-oaiMeta:
        name: response.code_interpreter_call.completed
        group: responses
        example: |
          {
            "type": "response.code_interpreter_call.completed",
            "response_id": "resp-123",
            "output_index": 5,
            "code_interpreter_call": {},
            "sequence_number": 1
          }
    ResponseCodeInterpreterCallInProgressEvent:
      type: object
      description: Emitted when a code interpreter call is in progress.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.code_interpreter_call.in_progress`.
          enum:
            - response.code_interpreter_call.in_progress
          x-stainless-const: true
        output_index:
          type: integer
          description: |
            The index of the output item that the code interpreter call is in progress.
        code_interpreter_call:
          $ref: '#/components/schemas/CodeInterpreterToolCall'
        sequence_number:
          type: integer
          description: The sequence number of this event.
      required:
        - type
        - response_id
        - output_index
        - code_interpreter_call
        - sequence_number
      x-oaiMeta:
        name: response.code_interpreter_call.in_progress
        group: responses
        example: |
          {
            "type": "response.code_interpreter_call.in.progress",
            "response_id": "resp-123",
            "output_index": 0,
            "code_interpreter_call": {},
            "sequence_number": 1
          }
    ResponseCodeInterpreterCallInterpretingEvent:
      type: object
      description: Emitted when the code interpreter is actively interpreting the code snippet.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.code_interpreter_call.interpreting`.
          enum:
            - response.code_interpreter_call.interpreting
          x-stainless-const: true
        sequence_number:
          type: integer
          description: The sequence number of this event.
        output_index:
          type: integer
          description: |
            The index of the output item that the code interpreter call is in progress.
        code_interpreter_call:
          $ref: '#/components/schemas/CodeInterpreterToolCall'
      required:
        - type
        - response_id
        - output_index
        - code_interpreter_call
        - sequence_number
      x-oaiMeta:
        name: response.code_interpreter_call.interpreting
        group: responses
        example: |
          {
            "type": "response.code_interpreter_call.interpreting",
            "response_id": "resp-123",
            "output_index": 4,
            "code_interpreter_call": {},
            "sequence_number": 1
          }
    ResponseCompletedEvent:
      type: object
      description: Emitted when the model response is complete.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.completed`.
          enum:
            - response.completed
          x-stainless-const: true
        response:
          $ref: '#/components/schemas/Response'
          description: |
            Properties of the completed response.
        sequence_number:
          type: integer
          description: The sequence number for this event.
      required:
        - type
        - response
        - sequence_number
      x-oaiMeta:
        name: response.completed
        group: responses
        example: |
          {
            "type": "response.completed",
            "response": {
              "id": "resp_123",
              "object": "response",
              "created_at": 1740855869,
              "status": "completed",
              "error": null,
              "incomplete_details": null,
              "input": [],
              "instructions": null,
              "max_output_tokens": null,
              "model": "gpt-4o-mini-2024-07-18",
              "output": [
                {
                  "id": "msg_123",
                  "type": "message",
                  "role": "assistant",
                  "content": [
                    {
                      "type": "output_text",
                      "text": "In a shimmering forest under a sky full of stars, a lonely unicorn named Lila discovered a hidden pond that glowed with moonlight. Every night, she would leave sparkling, magical flowers by the water's edge, hoping to share her beauty with others. One enchanting evening, she woke to find a group of friendly animals gathered around, eager to be friends and share in her magic.",
                      "annotations": []
                    }
                  ]
                }
              ],
              "previous_response_id": null,
              "reasoning_effort": null,
              "store": false,
              "temperature": 1,
              "text": {
                "format": {
                  "type": "text"
                }
              },
              "tool_choice": "auto",
              "tools": [],
              "top_p": 1,
              "truncation": "disabled",
              "usage": {
                "input_tokens": 0,
                "output_tokens": 0,
                "output_tokens_details": {
                  "reasoning_tokens": 0
                },
                "total_tokens": 0
              },
              "user": null,
              "metadata": {}
            },
            "sequence_number": 1
          }
    ResponseContentPartAddedEvent:
      type: object
      description: Emitted when a new content part is added.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.content_part.added`.
          enum:
            - response.content_part.added
          x-stainless-const: true
        item_id:
          type: string
          description: |
            The ID of the output item that the content part was added to.
        output_index:
          type: integer
          description: |
            The index of the output item that the content part was added to.
        content_index:
          type: integer
          description: |
            The index of the content part that was added.
        part:
          $ref: '#/components/schemas/OutputContent'
          description: |
            The content part that was added.
        sequence_number:
          type: integer
          description: The sequence number of this event.
      required:
        - type
        - item_id
        - output_index
        - content_index
        - part
        - sequence_number
      x-oaiMeta:
        name: response.content_part.added
        group: responses
        example: |
          {
            "type": "response.content_part.added",
            "item_id": "msg_123",
            "output_index": 0,
            "content_index": 0,
            "part": {
              "type": "output_text",
              "text": "",
              "annotations": []
            },
            "sequence_number": 1
          }
    ResponseContentPartDoneEvent:
      type: object
      description: Emitted when a content part is done.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.content_part.done`.
          enum:
            - response.content_part.done
          x-stainless-const: true
        item_id:
          type: string
          description: |
            The ID of the output item that the content part was added to.
        output_index:
          type: integer
          description: |
            The index of the output item that the content part was added to.
        content_index:
          type: integer
          description: |
            The index of the content part that is done.
        sequence_number:
          type: integer
          description: The sequence number of this event.
        part:
          $ref: '#/components/schemas/OutputContent'
          description: |
            The content part that is done.
      required:
        - type
        - item_id
        - output_index
        - content_index
        - part
        - sequence_number
      x-oaiMeta:
        name: response.content_part.done
        group: responses
        example: |
          {
            "type": "response.content_part.done",
            "item_id": "msg_123",
            "output_index": 0,
            "content_index": 0,
            "sequence_number": 1,
            "part": {
              "type": "output_text",
              "text": "In a shimmering forest under a sky full of stars, a lonely unicorn named Lila discovered a hidden pond that glowed with moonlight. Every night, she would leave sparkling, magical flowers by the water's edge, hoping to share her beauty with others. One enchanting evening, she woke to find a group of friendly animals gathered around, eager to be friends and share in her magic.",
              "annotations": []
            }
          }
    ResponseCreatedEvent:
      type: object
      description: |
        An event that is emitted when a response is created.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.created`.
          enum:
            - response.created
          x-stainless-const: true
        response:
          $ref: '#/components/schemas/Response'
          description: |
            The response that was created.
        sequence_number:
          type: integer
          description: The sequence number for this event.
      required:
        - type
        - response
        - sequence_number
      x-oaiMeta:
        name: response.created
        group: responses
        example: |
          {
            "type": "response.created",
            "response": {
              "id": "resp_67ccfcdd16748190a91872c75d38539e09e4d4aac714747c",
              "object": "response",
              "created_at": 1741487325,
              "status": "in_progress",
              "error": null,
              "incomplete_details": null,
              "instructions": null,
              "max_output_tokens": null,
              "model": "gpt-4o-2024-08-06",
              "output": [],
              "parallel_tool_calls": true,
              "previous_response_id": null,
              "reasoning": {
                "effort": null,
                "summary": null
              },
              "store": true,
              "temperature": 1,
              "text": {
                "format": {
                  "type": "text"
                }
              },
              "tool_choice": "auto",
              "tools": [],
              "top_p": 1,
              "truncation": "disabled",
              "usage": null,
              "user": null,
              "metadata": {}
            },
            "sequence_number": 1
          }
    ResponseError:
      type: object
      description: |
        An error object returned when the model fails to generate a Response.
      nullable: true
      properties:
        code:
          $ref: '#/components/schemas/ResponseErrorCode'
        message:
          type: string
          description: |
            A human-readable description of the error.
      required:
        - code
        - message
    ResponseErrorCode:
      type: string
      description: |
        The error code for the response.
      enum:
        - server_error
        - rate_limit_exceeded
        - invalid_prompt
        - vector_store_timeout
        - invalid_image
        - invalid_image_format
        - invalid_base64_image
        - invalid_image_url
        - image_too_large
        - image_too_small
        - image_parse_error
        - image_content_policy_violation
        - invalid_image_mode
        - image_file_too_large
        - unsupported_image_media_type
        - empty_image_file
        - failed_to_download_image
        - image_file_not_found
    ResponseErrorEvent:
      type: object
      description: Emitted when an error occurs.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `error`.
          enum:
            - error
          x-stainless-const: true
        code:
          type: string
          description: |
            The error code.
          nullable: true
        message:
          type: string
          description: |
            The error message.
        param:
          type: string
          description: |
            The error parameter.
          nullable: true
        sequence_number:
          type: integer
          description: The sequence number of this event.
      required:
        - type
        - code
        - message
        - param
        - sequence_number
      x-oaiMeta:
        name: error
        group: responses
        example: |
          {
            "type": "error",
            "code": "ERR_SOMETHING",
            "message": "Something went wrong",
            "param": null,
            "sequence_number": 1
          }
    ResponseFailedEvent:
      type: object
      description: |
        An event that is emitted when a response fails.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.failed`.
          enum:
            - response.failed
          x-stainless-const: true
        sequence_number:
          type: integer
          description: The sequence number of this event.
        response:
          $ref: '#/components/schemas/Response'
          description: |
            The response that failed.
      required:
        - type
        - response
        - sequence_number
      x-oaiMeta:
        name: response.failed
        group: responses
        example: |
          {
            "type": "response.failed",
            "response": {
              "id": "resp_123",
              "object": "response",
              "created_at": 1740855869,
              "status": "failed",
              "error": {
                "code": "server_error",
                "message": "The model failed to generate a response."
              },
              "incomplete_details": null,
              "instructions": null,
              "max_output_tokens": null,
              "model": "gpt-4o-mini-2024-07-18",
              "output": [],
              "previous_response_id": null,
              "reasoning_effort": null,
              "store": false,
              "temperature": 1,
              "text": {
                "format": {
                  "type": "text"
                }
              },
              "tool_choice": "auto",
              "tools": [],
              "top_p": 1,
              "truncation": "disabled",
              "usage": null,
              "user": null,
              "metadata": {}
            }
          }
    ResponseFileSearchCallCompletedEvent:
      type: object
      description: Emitted when a file search call is completed (results found).
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.file_search_call.completed`.
          enum:
            - response.file_search_call.completed
          x-stainless-const: true
        output_index:
          type: integer
          description: |
            The index of the output item that the file search call is initiated.
        item_id:
          type: string
          description: |
            The ID of the output item that the file search call is initiated.
        sequence_number:
          type: integer
          description: The sequence number of this event.
      required:
        - type
        - output_index
        - item_id
        - sequence_number
      x-oaiMeta:
        name: response.file_search_call.completed
        group: responses
        example: |
          {
            "type": "response.file_search_call.completed",
            "output_index": 0,
            "item_id": "fs_123",
            "sequence_number": 1
          }
    ResponseFileSearchCallInProgressEvent:
      type: object
      description: Emitted when a file search call is initiated.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.file_search_call.in_progress`.
          enum:
            - response.file_search_call.in_progress
          x-stainless-const: true
        output_index:
          type: integer
          description: |
            The index of the output item that the file search call is initiated.
        item_id:
          type: string
          description: |
            The ID of the output item that the file search call is initiated.
        sequence_number:
          type: integer
          description: The sequence number of this event.
      required:
        - type
        - output_index
        - item_id
        - sequence_number
      x-oaiMeta:
        name: response.file_search_call.in_progress
        group: responses
        example: |
          {
            "type": "response.file_search_call.in_progress",
            "output_index": 0,
            "item_id": "fs_123",
            "sequence_number": 1
          }
    ResponseFileSearchCallSearchingEvent:
      type: object
      description: Emitted when a file search is currently searching.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.file_search_call.searching`.
          enum:
            - response.file_search_call.searching
          x-stainless-const: true
        output_index:
          type: integer
          description: |
            The index of the output item that the file search call is searching.
        item_id:
          type: string
          description: |
            The ID of the output item that the file search call is initiated.
        sequence_number:
          type: integer
          description: The sequence number of this event.
      required:
        - type
        - output_index
        - item_id
        - sequence_number
      x-oaiMeta:
        name: response.file_search_call.searching
        group: responses
        example: |
          {
            "type": "response.file_search_call.searching",
            "output_index": 0,
            "item_id": "fs_123",
            "sequence_number": 1
          }
    ResponseFormatJsonObject:
      type: object
      title: JSON object
      description: |
        JSON object response format. An older method of generating JSON responses.
        Using `json_schema` is recommended for models that support it. Note that the
        model will not generate JSON without a system or user message instructing it
        to do so.
      properties:
        type:
          type: string
          description: The type of response format being defined. Always `json_object`.
          enum:
            - json_object
          x-stainless-const: true
      required:
        - type
    ResponseFormatJsonSchema:
      type: object
      title: JSON schema
      description: |
        JSON Schema response format. Used to generate structured JSON responses.
        Learn more about [Structured Outputs](/docs/guides/structured-outputs).
      properties:
        type:
          type: string
          description: The type of response format being defined. Always `json_schema`.
          enum:
            - json_schema
          x-stainless-const: true
        json_schema:
          type: object
          title: JSON schema
          description: |
            Structured Outputs configuration options, including a JSON Schema.
          properties:
            description:
              type: string
              description: |
                A description of what the response format is for, used by the model to
                determine how to respond in the format.
            name:
              type: string
              description: |
                The name of the response format. Must be a-z, A-Z, 0-9, or contain
                underscores and dashes, with a maximum length of 64.
            schema:
              $ref: '#/components/schemas/ResponseFormatJsonSchemaSchema'
            strict:
              type: boolean
              nullable: true
              default: false
              description: |
                Whether to enable strict schema adherence when generating the output.
                If set to true, the model will always follow the exact schema defined
                in the `schema` field. Only a subset of JSON Schema is supported when
                `strict` is `true`. To learn more, read the [Structured Outputs
                guide](/docs/guides/structured-outputs).
          required:
            - name
      required:
        - type
        - json_schema
    ResponseFormatJsonSchemaSchema:
      type: object
      title: JSON schema
      description: |
        The schema for the response format, described as a JSON Schema object.
        Learn how to build JSON schemas [here](https://json-schema.org/).
      additionalProperties: true
    ResponseFormatText:
      type: object
      title: Text
      description: |
        Default response format. Used to generate text responses.
      properties:
        type:
          type: string
          description: The type of response format being defined. Always `text`.
          enum:
            - text
          x-stainless-const: true
      required:
        - type
    ResponseFunctionCallArgumentsDeltaEvent:
      type: object
      description: Emitted when there is a partial function-call arguments delta.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.function_call_arguments.delta`.
          enum:
            - response.function_call_arguments.delta
          x-stainless-const: true
        item_id:
          type: string
          description: |
            The ID of the output item that the function-call arguments delta is added to.
        output_index:
          type: integer
          description: |
            The index of the output item that the function-call arguments delta is added to.
        sequence_number:
          type: integer
          description: The sequence number of this event.
        delta:
          type: string
          description: |
            The function-call arguments delta that is added.
      required:
        - type
        - item_id
        - output_index
        - delta
        - sequence_number
      x-oaiMeta:
        name: response.function_call_arguments.delta
        group: responses
        example: |
          {
            "type": "response.function_call_arguments.delta",
            "item_id": "item-abc",
            "output_index": 0,
            "delta": "{ \"arg\":"
            "sequence_number": 1
          }
    ResponseFunctionCallArgumentsDoneEvent:
      type: object
      description: Emitted when function-call arguments are finalized.
      properties:
        type:
          type: string
          enum:
            - response.function_call_arguments.done
          x-stainless-const: true
        item_id:
          type: string
          description: The ID of the item.
        output_index:
          type: integer
          description: The index of the output item.
        sequence_number:
          type: integer
          description: The sequence number of this event.
        arguments:
          type: string
          description: The function-call arguments.
      required:
        - type
        - item_id
        - output_index
        - arguments
        - sequence_number
      x-oaiMeta:
        name: response.function_call_arguments.done
        group: responses
        example: |
          {
            "type": "response.function_call_arguments.done",
            "item_id": "item-abc",
            "output_index": 1,
            "arguments": "{ \"arg\": 123 }",
            "sequence_number": 1
          }
    ResponseImageGenCallCompletedEvent:
      type: object
      title: ResponseImageGenCallCompletedEvent
      description: |
        Emitted when an image generation tool call has completed and the final image is available.
      properties:
        type:
          type: string
          enum:
            - response.image_generation_call.completed
          description: The type of the event. Always 'response.image_generation_call.completed'.
          x-stainless-const: true
        output_index:
          type: integer
          description: The index of the output item in the response's output array.
        sequence_number:
          type: integer
          description: The sequence number of this event.
        item_id:
          type: string
          description: The unique identifier of the image generation item being processed.
      required:
        - type
        - output_index
        - item_id
        - sequence_number
      x-oaiMeta:
        name: response.image_generation_call.completed
        group: responses
        example: |
          {
            "type": "response.image_generation_call.completed",
            "output_index": 0,
            "item_id": "item-123",
            "sequence_number": 1
          }
    ResponseImageGenCallGeneratingEvent:
      type: object
      title: ResponseImageGenCallGeneratingEvent
      description: |
        Emitted when an image generation tool call is actively generating an image (intermediate state).
      properties:
        type:
          type: string
          enum:
            - response.image_generation_call.generating
          description: The type of the event. Always 'response.image_generation_call.generating'.
          x-stainless-const: true
        output_index:
          type: integer
          description: The index of the output item in the response's output array.
        item_id:
          type: string
          description: The unique identifier of the image generation item being processed.
        sequence_number:
          type: integer
          description: The sequence number of the image generation item being processed.
      required:
        - type
        - output_index
        - item_id
        - sequence_number
      x-oaiMeta:
        name: response.image_generation_call.generating
        group: responses
        example: |
          {
            "type": "response.image_generation_call.generating",
            "output_index": 0,
            "item_id": "item-123",
            "sequence_number": 0
          }
    ResponseImageGenCallInProgressEvent:
      type: object
      title: ResponseImageGenCallInProgressEvent
      description: |
        Emitted when an image generation tool call is in progress.
      properties:
        type:
          type: string
          enum:
            - response.image_generation_call.in_progress
          description: The type of the event. Always 'response.image_generation_call.in_progress'.
          x-stainless-const: true
        output_index:
          type: integer
          description: The index of the output item in the response's output array.
        item_id:
          type: string
          description: The unique identifier of the image generation item being processed.
        sequence_number:
          type: integer
          description: The sequence number of the image generation item being processed.
      required:
        - type
        - output_index
        - item_id
        - sequence_number
      x-oaiMeta:
        name: response.image_generation_call.in_progress
        group: responses
        example: |
          {
            "type": "response.image_generation_call.in_progress",
            "output_index": 0,
            "item_id": "item-123",
            "sequence_number": 0
          }
    ResponseImageGenCallPartialImageEvent:
      type: object
      title: ResponseImageGenCallPartialImageEvent
      description: |
        Emitted when a partial image is available during image generation streaming.
      properties:
        type:
          type: string
          enum:
            - response.image_generation_call.partial_image
          description: The type of the event. Always 'response.image_generation_call.partial_image'.
          x-stainless-const: true
        output_index:
          type: integer
          description: The index of the output item in the response's output array.
        item_id:
          type: string
          description: The unique identifier of the image generation item being processed.
        sequence_number:
          type: integer
          description: The sequence number of the image generation item being processed.
        partial_image_index:
          type: integer
          description: 0-based index for the partial image (backend is 1-based, but this is 0-based for the user).
        partial_image_b64:
          type: string
          description: Base64-encoded partial image data, suitable for rendering as an image.
      required:
        - type
        - output_index
        - item_id
        - sequence_number
        - partial_image_index
        - partial_image_b64
      x-oaiMeta:
        name: response.image_generation_call.partial_image
        group: responses
        example: |
          {
            "type": "response.image_generation_call.partial_image",
            "output_index": 0,
            "item_id": "item-123",
            "sequence_number": 0,
            "partial_image_index": 0,
            "partial_image_b64": "..."
          }
    ResponseInProgressEvent:
      type: object
      description: Emitted when the response is in progress.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.in_progress`.
          enum:
            - response.in_progress
          x-stainless-const: true
        response:
          $ref: '#/components/schemas/Response'
          description: |
            The response that is in progress.
        sequence_number:
          type: integer
          description: The sequence number of this event.
      required:
        - type
        - response
        - sequence_number
      x-oaiMeta:
        name: response.in_progress
        group: responses
        example: |
          {
            "type": "response.in_progress",
            "response": {
              "id": "resp_67ccfcdd16748190a91872c75d38539e09e4d4aac714747c",
              "object": "response",
              "created_at": 1741487325,
              "status": "in_progress",
              "error": null,
              "incomplete_details": null,
              "instructions": null,
              "max_output_tokens": null,
              "model": "gpt-4o-2024-08-06",
              "output": [],
              "parallel_tool_calls": true,
              "previous_response_id": null,
              "reasoning": {
                "effort": null,
                "summary": null
              },
              "store": true,
              "temperature": 1,
              "text": {
                "format": {
                  "type": "text"
                }
              },
              "tool_choice": "auto",
              "tools": [],
              "top_p": 1,
              "truncation": "disabled",
              "usage": null,
              "user": null,
              "metadata": {}
            },
            "sequence_number": 1
          }
    ResponseIncompleteEvent:
      type: object
      description: |
        An event that is emitted when a response finishes as incomplete.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.incomplete`.
          enum:
            - response.incomplete
          x-stainless-const: true
        response:
          $ref: '#/components/schemas/Response'
          description: |
            The response that was incomplete.
        sequence_number:
          type: integer
          description: The sequence number of this event.
      required:
        - type
        - response
        - sequence_number
      x-oaiMeta:
        name: response.incomplete
        group: responses
        example: |
          {
            "type": "response.incomplete",
            "response": {
              "id": "resp_123",
              "object": "response",
              "created_at": 1740855869,
              "status": "incomplete",
              "error": null, 
              "incomplete_details": {
                "reason": "max_tokens"
              },
              "instructions": null,
              "max_output_tokens": null,
              "model": "gpt-4o-mini-2024-07-18",
              "output": [],
              "previous_response_id": null,
              "reasoning_effort": null,
              "store": false,
              "temperature": 1,
              "text": {
                "format": {
                  "type": "text"
                }
              },
              "tool_choice": "auto",
              "tools": [],
              "top_p": 1,
              "truncation": "disabled",
              "usage": null,
              "user": null,
              "metadata": {}
            },
            "sequence_number": 1
          }
    ResponseItemList:
      type: object
      description: A list of Response items.
      properties:
        object:
          type: string
          description: The type of object returned, must be `list`.
          enum:
            - list
          x-stainless-const: true
        data:
          type: array
          description: A list of items used to generate this response.
          items:
            $ref: '#/components/schemas/ItemResource'
        has_more:
          type: boolean
          description: Whether there are more items available.
        first_id:
          type: string
          description: The ID of the first item in the list.
        last_id:
          type: string
          description: The ID of the last item in the list.
      required:
        - object
        - data
        - has_more
        - first_id
        - last_id
      x-oaiMeta:
        name: The input item list
        group: responses
        example: |
          {
            "object": "list",
            "data": [
              {
                "id": "msg_abc123",
                "type": "message",
                "role": "user",
                "content": [
                  {
                    "type": "input_text",
                    "text": "Tell me a three sentence bedtime story about a unicorn."
                  }
                ]
              }
            ],
            "first_id": "msg_abc123",
            "last_id": "msg_abc123",
            "has_more": false
          }
    ResponseMCPCallArgumentsDeltaEvent:
      type: object
      title: ResponseMCPCallArgumentsDeltaEvent
      description: |
        Emitted when there is a delta (partial update) to the arguments of an MCP tool call.
      properties:
        type:
          type: string
          enum:
            - response.mcp_call.arguments_delta
          description: The type of the event. Always 'response.mcp_call.arguments_delta'.
          x-stainless-const: true
        output_index:
          type: integer
          description: The index of the output item in the response's output array.
        item_id:
          type: string
          description: The unique identifier of the MCP tool call item being processed.
        delta:
          type: object
          description: The partial update to the arguments for the MCP tool call.
        sequence_number:
          type: integer
          description: The sequence number of this event.
      required:
        - type
        - output_index
        - item_id
        - delta
        - sequence_number
      x-oaiMeta:
        name: response.mcp_call.arguments.delta
        group: responses
        example: |
          {
            "type": "response.mcp_call.arguments.delta",
            "output_index": 0,
            "item_id": "item-abc",
            "delta": {
              "arg1": "new_value1",
              "arg2": "new_value2"
            },
            "sequence_number": 1
          }
    ResponseMCPCallArgumentsDoneEvent:
      type: object
      title: ResponseMCPCallArgumentsDoneEvent
      description: |
        Emitted when the arguments for an MCP tool call are finalized.
      properties:
        type:
          type: string
          enum:
            - response.mcp_call.arguments_done
          description: The type of the event. Always 'response.mcp_call.arguments_done'.
          x-stainless-const: true
        output_index:
          type: integer
          description: The index of the output item in the response's output array.
        item_id:
          type: string
          description: The unique identifier of the MCP tool call item being processed.
        arguments:
          type: object
          description: The finalized arguments for the MCP tool call.
        sequence_number:
          type: integer
          description: The sequence number of this event.
      required:
        - type
        - output_index
        - item_id
        - arguments
        - sequence_number
      x-oaiMeta:
        name: response.mcp_call.arguments.done
        group: responses
        example: |
          {
            "type": "response.mcp_call.arguments.done",
            "output_index": 0,
            "item_id": "item-abc",
            "arguments": {
              "arg1": "value1",
              "arg2": "value2"
            },
            "sequence_number": 1
          }
    ResponseMCPCallCompletedEvent:
      type: object
      title: ResponseMCPCallCompletedEvent
      description: |
        Emitted when an MCP  tool call has completed successfully.
      properties:
        type:
          type: string
          enum:
            - response.mcp_call.completed
          description: The type of the event. Always 'response.mcp_call.completed'.
          x-stainless-const: true
        sequence_number:
          type: integer
          description: The sequence number of this event.
      required:
        - type
        - sequence_number
      x-oaiMeta:
        name: response.mcp_call.completed
        group: responses
        example: |
          {
            "type": "response.mcp_call.completed",
            "sequence_number": 1
          }
    ResponseMCPCallFailedEvent:
      type: object
      title: ResponseMCPCallFailedEvent
      description: |
        Emitted when an MCP  tool call has failed.
      properties:
        type:
          type: string
          enum:
            - response.mcp_call.failed
          description: The type of the event. Always 'response.mcp_call.failed'.
          x-stainless-const: true
        sequence_number:
          type: integer
          description: The sequence number of this event.
      required:
        - type
        - sequence_number
      x-oaiMeta:
        name: response.mcp_call.failed
        group: responses
        example: |
          {
            "type": "response.mcp_call.failed",
            "sequence_number": 1
          }
    ResponseMCPCallInProgressEvent:
      type: object
      title: ResponseMCPCallInProgressEvent
      description: |
        Emitted when an MCP  tool call is in progress.
      properties:
        type:
          type: string
          enum:
            - response.mcp_call.in_progress
          description: The type of the event. Always 'response.mcp_call.in_progress'.
          x-stainless-const: true
        sequence_number:
          type: integer
          description: The sequence number of this event.
        output_index:
          type: integer
          description: The index of the output item in the response's output array.
        item_id:
          type: string
          description: The unique identifier of the MCP tool call item being processed.
      required:
        - type
        - output_index
        - item_id
        - sequence_number
      x-oaiMeta:
        name: response.mcp_call.in_progress
        group: responses
        example: |
          {
            "type": "response.mcp_call.in_progress",
            "output_index": 0,
            "item_id": "item-abc",
            "sequence_number": 1
          }
    ResponseMCPListToolsCompletedEvent:
      type: object
      title: ResponseMCPListToolsCompletedEvent
      description: |
        Emitted when the list of available MCP tools has been successfully retrieved.
      properties:
        type:
          type: string
          enum:
            - response.mcp_list_tools.completed
          description: The type of the event. Always 'response.mcp_list_tools.completed'.
          x-stainless-const: true
        sequence_number:
          type: integer
          description: The sequence number of this event.
      required:
        - type
        - sequence_number
      x-oaiMeta:
        name: response.mcp_list_tools.completed
        group: responses
        example: |
          {
            "type": "response.mcp_list_tools.completed",
            "sequence_number": 1
          }
    ResponseMCPListToolsFailedEvent:
      type: object
      title: ResponseMCPListToolsFailedEvent
      description: |
        Emitted when the attempt to list available MCP tools has failed.
      properties:
        type:
          type: string
          enum:
            - response.mcp_list_tools.failed
          description: The type of the event. Always 'response.mcp_list_tools.failed'.
          x-stainless-const: true
        sequence_number:
          type: integer
          description: The sequence number of this event.
      required:
        - type
        - sequence_number
      x-oaiMeta:
        name: response.mcp_list_tools.failed
        group: responses
        example: |
          {
            "type": "response.mcp_list_tools.failed",
            "sequence_number": 1
          }
    ResponseMCPListToolsInProgressEvent:
      type: object
      title: ResponseMCPListToolsInProgressEvent
      description: |
        Emitted when the system is in the process of retrieving the list of available MCP tools.
      properties:
        type:
          type: string
          enum:
            - response.mcp_list_tools.in_progress
          description: The type of the event. Always 'response.mcp_list_tools.in_progress'.
          x-stainless-const: true
        sequence_number:
          type: integer
          description: The sequence number of this event.
      required:
        - type
        - sequence_number
      x-oaiMeta:
        name: response.mcp_list_tools.in_progress
        group: responses
        example: |
          {
            "type": "response.mcp_list_tools.in_progress",
            "sequence_number": 1
          }
    ResponseModalities:
      type: array
      nullable: true
      description: |
        Output types that you would like the model to generate.
        Most models are capable of generating text, which is the default:

        `["text"]`

        The `gpt-4o-audio-preview` model can also be used to 
        [generate audio](/docs/guides/audio). To request that this model generate 
        both text and audio responses, you can use:

        `["text", "audio"]`
      items:
        type: string
        enum:
          - text
          - audio
    ResponseOutputItemAddedEvent:
      type: object
      description: Emitted when a new output item is added.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.output_item.added`.
          enum:
            - response.output_item.added
          x-stainless-const: true
        output_index:
          type: integer
          description: |
            The index of the output item that was added.
        sequence_number:
          type: integer
          description: |
            The sequence number of this event.
        item:
          $ref: '#/components/schemas/OutputItem'
          description: |
            The output item that was added.
      required:
        - type
        - output_index
        - item
        - sequence_number
      x-oaiMeta:
        name: response.output_item.added
        group: responses
        example: |
          {
            "type": "response.output_item.added",
            "output_index": 0,
            "item": {
              "id": "msg_123",
              "status": "in_progress",
              "type": "message",
              "role": "assistant",
              "content": []
            },
            "sequence_number": 1
          }
    ResponseOutputItemDoneEvent:
      type: object
      description: Emitted when an output item is marked done.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.output_item.done`.
          enum:
            - response.output_item.done
          x-stainless-const: true
        output_index:
          type: integer
          description: |
            The index of the output item that was marked done.
        sequence_number:
          type: integer
          description: |
            The sequence number of this event.
        item:
          $ref: '#/components/schemas/OutputItem'
          description: |
            The output item that was marked done.
      required:
        - type
        - output_index
        - item
        - sequence_number
      x-oaiMeta:
        name: response.output_item.done
        group: responses
        example: |
          {
            "type": "response.output_item.done",
            "output_index": 0,
            "item": {
              "id": "msg_123",
              "status": "completed",
              "type": "message",
              "role": "assistant",
              "content": [
                {
                  "type": "output_text",
                  "text": "In a shimmering forest under a sky full of stars, a lonely unicorn named Lila discovered a hidden pond that glowed with moonlight. Every night, she would leave sparkling, magical flowers by the water's edge, hoping to share her beauty with others. One enchanting evening, she woke to find a group of friendly animals gathered around, eager to be friends and share in her magic.",
                  "annotations": []
                }
              ]
            },
            "sequence_number": 1
          }
    ResponseOutputTextAnnotationAddedEvent:
      type: object
      title: ResponseOutputTextAnnotationAddedEvent
      description: |
        Emitted when an annotation is added to output text content.
      properties:
        type:
          type: string
          enum:
            - response.output_text_annotation.added
          description: The type of the event. Always 'response.output_text_annotation.added'.
          x-stainless-const: true
        item_id:
          type: string
          description: The unique identifier of the item to which the annotation is being added.
        output_index:
          type: integer
          description: The index of the output item in the response's output array.
        content_index:
          type: integer
          description: The index of the content part within the output item.
        annotation_index:
          type: integer
          description: The index of the annotation within the content part.
        sequence_number:
          type: integer
          description: The sequence number of this event.
        annotation:
          type: object
          description: The annotation object being added. (See annotation schema for details.)
      required:
        - type
        - item_id
        - output_index
        - content_index
        - annotation_index
        - annotation
        - sequence_number
      x-oaiMeta:
        name: response.output_text_annotation.added
        group: responses
        example: |
          {
            "type": "response.output_text_annotation.added",
            "item_id": "item-abc",
            "output_index": 0,
            "content_index": 0,
            "annotation_index": 0,
            "annotation": {
              "type": "text_annotation",
              "text": "This is a test annotation",
              "start": 0,
              "end": 10
            },
            "sequence_number": 1
          }
    ResponsePromptVariables:
      type: object
      title: Prompt Variables
      description: |
        Optional map of values to substitute in for variables in your
        prompt. The substitution values can either be strings, or other
        Response input types like images or files.
      x-oaiExpandable: true
      x-oaiTypeLabel: map
      nullable: true
      additionalProperties:
        x-oaiExpandable: true
        x-oaiTypeLabel: map
        oneOf:
          - type: string
          - $ref: '#/components/schemas/InputTextContent'
          - $ref: '#/components/schemas/InputImageContent'
          - $ref: '#/components/schemas/InputFileContent'
    ResponseProperties:
      type: object
      properties:
        previous_response_id:
          type: string
          description: |
            The unique ID of the previous response to the model. Use this to
            create multi-turn conversations. Learn more about 
            [conversation state](/docs/guides/conversation-state).
          nullable: true
        model:
          description: |
            Model ID used to generate the response, like `gpt-4o` or `o3`. OpenAI
            offers a wide range of models with different capabilities, performance
            characteristics, and price points. Refer to the [model guide](/docs/models)
            to browse and compare available models.
          $ref: '#/components/schemas/ModelIdsResponses'
        reasoning:
          $ref: '#/components/schemas/Reasoning'
          nullable: true
        background:
          type: boolean
          description: |
            Whether to run the model response in the background. 
            [Learn more](/docs/guides/background).
          default: false
          nullable: true
        max_output_tokens:
          description: >
            An upper bound for the number of tokens that can be generated for a response, including visible
            output tokens and [reasoning tokens](/docs/guides/reasoning).
          type: integer
          nullable: true
        text:
          type: object
          description: |
            Configuration options for a text response from the model. Can be plain
            text or structured JSON data. Learn more:
            - [Text inputs and outputs](/docs/guides/text)
            - [Structured Outputs](/docs/guides/structured-outputs)
          properties:
            format:
              $ref: '#/components/schemas/TextResponseFormatConfiguration'
        tools:
          type: array
          description: |
            An array of tools the model may call while generating a response. You 
            can specify which tool to use by setting the `tool_choice` parameter.

            The two categories of tools you can provide the model are:

            - **Built-in tools**: Tools that are provided by OpenAI that extend the
              model's capabilities, like [web search](/docs/guides/tools-web-search)
              or [file search](/docs/guides/tools-file-search). Learn more about
              [built-in tools](/docs/guides/tools).
            - **Function calls (custom tools)**: Functions that are defined by you,
              enabling the model to call your own code. Learn more about
              [function calling](/docs/guides/function-calling).
          items:
            $ref: '#/components/schemas/Tool'
        tool_choice:
          description: |
            How the model should select which tool (or tools) to use when generating
            a response. See the `tools` parameter to see how to specify which tools
            the model can call.
          oneOf:
            - $ref: '#/components/schemas/ToolChoiceOptions'
            - $ref: '#/components/schemas/ToolChoiceTypes'
            - $ref: '#/components/schemas/ToolChoiceFunction'
        prompt:
          $ref: '#/components/schemas/Prompt'
        truncation:
          type: string
          description: |
            The truncation strategy to use for the model response.
            - `auto`: If the context of this response and previous ones exceeds
              the model's context window size, the model will truncate the 
              response to fit the context window by dropping input items in the
              middle of the conversation. 
            - `disabled` (default): If a model response will exceed the context window 
              size for a model, the request will fail with a 400 error.
          enum:
            - auto
            - disabled
          nullable: true
          default: disabled
    ResponseQueuedEvent:
      type: object
      title: ResponseQueuedEvent
      description: |
        Emitted when a response is queued and waiting to be processed.
      properties:
        type:
          type: string
          enum:
            - response.queued
          description: The type of the event. Always 'response.queued'.
          x-stainless-const: true
        response:
          $ref: '#/components/schemas/Response'
          description: The full response object that is queued.
        sequence_number:
          type: integer
          description: The sequence number for this event.
      required:
        - type
        - response
        - sequence_number
      x-oaiMeta:
        name: response.queued
        group: responses
        example: |
          {
            "type": "response.queued",
            "response": {
              "id": "res_123",
              "status": "queued",
              "created_at": "2021-01-01T00:00:00Z",
              "updated_at": "2021-01-01T00:00:00Z"
            },
            "sequence_number": 1
          }
    ResponseReasoningDeltaEvent:
      type: object
      title: ResponseReasoningDeltaEvent
      description: |
        Emitted when there is a delta (partial update) to the reasoning content.
      properties:
        type:
          type: string
          enum:
            - response.reasoning.delta
          description: The type of the event. Always 'response.reasoning.delta'.
          x-stainless-const: true
        item_id:
          type: string
          description: The unique identifier of the item for which reasoning is being updated.
        output_index:
          type: integer
          description: The index of the output item in the response's output array.
        content_index:
          type: integer
          description: The index of the reasoning content part within the output item.
        delta:
          type: object
          description: The partial update to the reasoning content.
        sequence_number:
          type: integer
          description: The sequence number of this event.
      required:
        - type
        - item_id
        - output_index
        - content_index
        - delta
        - sequence_number
      x-oaiMeta:
        name: response.reasoning.delta
        group: responses
        example: |
          {
            "type": "response.reasoning.delta",
            "item_id": "item-abc",
            "output_index": 0,
            "content_index": 0,
            "delta": {
              "text": "This is a test delta"
            },
            "sequence_number": 1
          }
    ResponseReasoningDoneEvent:
      type: object
      title: ResponseReasoningDoneEvent
      description: |
        Emitted when the reasoning content is finalized for an item.
      properties:
        type:
          type: string
          enum:
            - response.reasoning.done
          description: The type of the event. Always 'response.reasoning.done'.
          x-stainless-const: true
        item_id:
          type: string
          description: The unique identifier of the item for which reasoning is finalized.
        output_index:
          type: integer
          description: The index of the output item in the response's output array.
        content_index:
          type: integer
          description: The index of the reasoning content part within the output item.
        text:
          type: string
          description: The finalized reasoning text.
        sequence_number:
          type: integer
          description: The sequence number of this event.
      required:
        - type
        - item_id
        - output_index
        - content_index
        - text
        - sequence_number
      x-oaiMeta:
        name: response.reasoning.done
        group: responses
        example: |
          {
            "type": "response.reasoning.done",
            "item_id": "item-abc",
            "output_index": 0,
            "content_index": 0,
            "text": "This is a test reasoning",
            "sequence_number": 1
          }
    ResponseReasoningSummaryDeltaEvent:
      type: object
      title: ResponseReasoningSummaryDeltaEvent
      description: |
        Emitted when there is a delta (partial update) to the reasoning summary content.
      properties:
        type:
          type: string
          enum:
            - response.reasoning_summary.delta
          description: The type of the event. Always 'response.reasoning_summary.delta'.
          x-stainless-const: true
        item_id:
          type: string
          description: The unique identifier of the item for which the reasoning summary is being updated.
        output_index:
          type: integer
          description: The index of the output item in the response's output array.
        summary_index:
          type: integer
          description: The index of the summary part within the output item.
        sequence_number:
          type: integer
          description: The sequence number of this event.
        delta:
          type: object
          description: The partial update to the reasoning summary content.
      required:
        - type
        - item_id
        - output_index
        - summary_index
        - delta
        - sequence_number
      x-oaiMeta:
        name: response.reasoning_summary.delta
        group: responses
        example: |
          {
            "type": "response.reasoning_summary.delta",
            "item_id": "item-abc",
            "output_index": 0,
            "summary_index": 0,
            "delta": {
              "text": "delta text"
            },
            "sequence_number": 1
          }
    ResponseReasoningSummaryDoneEvent:
      type: object
      title: ResponseReasoningSummaryDoneEvent
      description: |
        Emitted when the reasoning summary content is finalized for an item.
      properties:
        type:
          type: string
          enum:
            - response.reasoning_summary.done
          description: The type of the event. Always 'response.reasoning_summary.done'.
          x-stainless-const: true
        item_id:
          type: string
          description: The unique identifier of the item for which the reasoning summary is finalized.
        output_index:
          type: integer
          description: The index of the output item in the response's output array.
        summary_index:
          type: integer
          description: The index of the summary part within the output item.
        text:
          type: string
          description: The finalized reasoning summary text.
        sequence_number:
          type: integer
          description: The sequence number of this event.
      required:
        - type
        - item_id
        - output_index
        - summary_index
        - text
        - sequence_number
      x-oaiMeta:
        name: response.reasoning_summary.done
        group: responses
        example: |
          {
            "type": "response.reasoning_summary.done",
            "item_id": "item-abc",
            "output_index": 0,
            "summary_index": 0,
            "text": "This is a test reasoning summary",
            "sequence_number": 1
          }
    ResponseReasoningSummaryPartAddedEvent:
      type: object
      description: Emitted when a new reasoning summary part is added.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.reasoning_summary_part.added`.
          enum:
            - response.reasoning_summary_part.added
          x-stainless-const: true
        item_id:
          type: string
          description: |
            The ID of the item this summary part is associated with.
        output_index:
          type: integer
          description: |
            The index of the output item this summary part is associated with.
        summary_index:
          type: integer
          description: |
            The index of the summary part within the reasoning summary.
        sequence_number:
          type: integer
          description: |
            The sequence number of this event.
        part:
          type: object
          description: |
            The summary part that was added.
          properties:
            type:
              type: string
              description: The type of the summary part. Always `summary_text`.
              enum:
                - summary_text
              x-stainless-const: true
            text:
              type: string
              description: The text of the summary part.
          required:
            - type
            - text
      required:
        - type
        - item_id
        - output_index
        - summary_index
        - part
        - sequence_number
      x-oaiMeta:
        name: response.reasoning_summary_part.added
        group: responses
        example: |
          {
            "type": "response.reasoning_summary_part.added",
            "item_id": "rs_6806bfca0b2481918a5748308061a2600d3ce51bdffd5476",
            "output_index": 0,
            "summary_index": 0,
            "part": {
              "type": "summary_text",
              "text": ""
            },
            "sequence_number": 1
          }
    ResponseReasoningSummaryPartDoneEvent:
      type: object
      description: Emitted when a reasoning summary part is completed.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.reasoning_summary_part.done`.
          enum:
            - response.reasoning_summary_part.done
          x-stainless-const: true
        item_id:
          type: string
          description: |
            The ID of the item this summary part is associated with.
        output_index:
          type: integer
          description: |
            The index of the output item this summary part is associated with.
        summary_index:
          type: integer
          description: |
            The index of the summary part within the reasoning summary.
        sequence_number:
          type: integer
          description: |
            The sequence number of this event.
        part:
          type: object
          description: |
            The completed summary part.
          properties:
            type:
              type: string
              description: The type of the summary part. Always `summary_text`.
              enum:
                - summary_text
              x-stainless-const: true
            text:
              type: string
              description: The text of the summary part.
          required:
            - type
            - text
      required:
        - type
        - item_id
        - output_index
        - summary_index
        - part
        - sequence_number
      x-oaiMeta:
        name: response.reasoning_summary_part.done
        group: responses
        example: |
          {
            "type": "response.reasoning_summary_part.done",
            "item_id": "rs_6806bfca0b2481918a5748308061a2600d3ce51bdffd5476",
            "output_index": 0,
            "summary_index": 0,
            "part": {
              "type": "summary_text",
              "text": "**Responding to a greeting**\n\nThe user just said, \"Hello!\" So, it seems I need to engage. I'll greet them back and offer help since they're looking to chat. I could say something like, \"Hello! How can I assist you today?\" That feels friendly and open. They didn't ask a specific question, so this approach will work well for starting a conversation. Let's see where it goes from there!"
            },
            "sequence_number": 1
          }
    ResponseReasoningSummaryTextDeltaEvent:
      type: object
      description: Emitted when a delta is added to a reasoning summary text.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.reasoning_summary_text.delta`.
          enum:
            - response.reasoning_summary_text.delta
          x-stainless-const: true
        item_id:
          type: string
          description: |
            The ID of the item this summary text delta is associated with.
        output_index:
          type: integer
          description: |
            The index of the output item this summary text delta is associated with.
        summary_index:
          type: integer
          description: |
            The index of the summary part within the reasoning summary.
        delta:
          type: string
          description: |
            The text delta that was added to the summary.
        sequence_number:
          type: integer
          description: |
            The sequence number of this event.
      required:
        - type
        - item_id
        - output_index
        - summary_index
        - delta
        - sequence_number
      x-oaiMeta:
        name: response.reasoning_summary_text.delta
        group: responses
        example: |
          {
            "type": "response.reasoning_summary_text.delta",
            "item_id": "rs_6806bfca0b2481918a5748308061a2600d3ce51bdffd5476",
            "output_index": 0,
            "summary_index": 0,
            "delta": "**Responding to a greeting**\n\nThe user just said, \"Hello!\" So, it seems I need to engage. I'll greet them back and offer help since they're looking to chat. I could say something like, \"Hello! How can I assist you today?\" That feels friendly and open. They didn't ask a specific question, so this approach will work well for starting a conversation. Let's see where it goes from there!",
            "sequence_number": 1
          }
    ResponseReasoningSummaryTextDoneEvent:
      type: object
      description: Emitted when a reasoning summary text is completed.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.reasoning_summary_text.done`.
          enum:
            - response.reasoning_summary_text.done
          x-stainless-const: true
        item_id:
          type: string
          description: |
            The ID of the item this summary text is associated with.
        output_index:
          type: integer
          description: |
            The index of the output item this summary text is associated with.
        summary_index:
          type: integer
          description: |
            The index of the summary part within the reasoning summary.
        text:
          type: string
          description: |
            The full text of the completed reasoning summary.
        sequence_number:
          type: integer
          description: |
            The sequence number of this event.
      required:
        - type
        - item_id
        - output_index
        - summary_index
        - text
        - sequence_number
      x-oaiMeta:
        name: response.reasoning_summary_text.done
        group: responses
        example: |
          {
            "type": "response.reasoning_summary_text.done",
            "item_id": "rs_6806bfca0b2481918a5748308061a2600d3ce51bdffd5476",
            "output_index": 0,
            "summary_index": 0,
            "text": "**Responding to a greeting**\n\nThe user just said, \"Hello!\" So, it seems I need to engage. I'll greet them back and offer help since they're looking to chat. I could say something like, \"Hello! How can I assist you today?\" That feels friendly and open. They didn't ask a specific question, so this approach will work well for starting a conversation. Let's see where it goes from there!",
            "sequence_number": 1
          }
    ResponseRefusalDeltaEvent:
      type: object
      description: Emitted when there is a partial refusal text.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.refusal.delta`.
          enum:
            - response.refusal.delta
          x-stainless-const: true
        item_id:
          type: string
          description: |
            The ID of the output item that the refusal text is added to.
        output_index:
          type: integer
          description: |
            The index of the output item that the refusal text is added to.
        content_index:
          type: integer
          description: |
            The index of the content part that the refusal text is added to.
        delta:
          type: string
          description: |
            The refusal text that is added.
        sequence_number:
          type: integer
          description: |
            The sequence number of this event.
      required:
        - type
        - item_id
        - output_index
        - content_index
        - delta
        - sequence_number
      x-oaiMeta:
        name: response.refusal.delta
        group: responses
        example: |
          {
            "type": "response.refusal.delta",
            "item_id": "msg_123",
            "output_index": 0,
            "content_index": 0,
            "delta": "refusal text so far",
            "sequence_number": 1
          }
    ResponseRefusalDoneEvent:
      type: object
      description: Emitted when refusal text is finalized.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.refusal.done`.
          enum:
            - response.refusal.done
          x-stainless-const: true
        item_id:
          type: string
          description: |
            The ID of the output item that the refusal text is finalized.
        output_index:
          type: integer
          description: |
            The index of the output item that the refusal text is finalized.
        content_index:
          type: integer
          description: |
            The index of the content part that the refusal text is finalized.
        refusal:
          type: string
          description: |
            The refusal text that is finalized.
        sequence_number:
          type: integer
          description: |
            The sequence number of this event.
      required:
        - type
        - item_id
        - output_index
        - content_index
        - refusal
        - sequence_number
      x-oaiMeta:
        name: response.refusal.done
        group: responses
        example: |
          {
            "type": "response.refusal.done",
            "item_id": "item-abc",
            "output_index": 1,
            "content_index": 2,
            "refusal": "final refusal text",
            "sequence_number": 1
          }
    ResponseStreamEvent:
      anyOf:
        - $ref: '#/components/schemas/ResponseAudioDeltaEvent'
        - $ref: '#/components/schemas/ResponseAudioDoneEvent'
        - $ref: '#/components/schemas/ResponseAudioTranscriptDeltaEvent'
        - $ref: '#/components/schemas/ResponseAudioTranscriptDoneEvent'
        - $ref: '#/components/schemas/ResponseCodeInterpreterCallCodeDeltaEvent'
        - $ref: '#/components/schemas/ResponseCodeInterpreterCallCodeDoneEvent'
        - $ref: '#/components/schemas/ResponseCodeInterpreterCallCompletedEvent'
        - $ref: '#/components/schemas/ResponseCodeInterpreterCallInProgressEvent'
        - $ref: '#/components/schemas/ResponseCodeInterpreterCallInterpretingEvent'
        - $ref: '#/components/schemas/ResponseCompletedEvent'
        - $ref: '#/components/schemas/ResponseContentPartAddedEvent'
        - $ref: '#/components/schemas/ResponseContentPartDoneEvent'
        - $ref: '#/components/schemas/ResponseCreatedEvent'
        - $ref: '#/components/schemas/ResponseErrorEvent'
        - $ref: '#/components/schemas/ResponseFileSearchCallCompletedEvent'
        - $ref: '#/components/schemas/ResponseFileSearchCallInProgressEvent'
        - $ref: '#/components/schemas/ResponseFileSearchCallSearchingEvent'
        - $ref: '#/components/schemas/ResponseFunctionCallArgumentsDeltaEvent'
        - $ref: '#/components/schemas/ResponseFunctionCallArgumentsDoneEvent'
        - $ref: '#/components/schemas/ResponseInProgressEvent'
        - $ref: '#/components/schemas/ResponseFailedEvent'
        - $ref: '#/components/schemas/ResponseIncompleteEvent'
        - $ref: '#/components/schemas/ResponseOutputItemAddedEvent'
        - $ref: '#/components/schemas/ResponseOutputItemDoneEvent'
        - $ref: '#/components/schemas/ResponseReasoningSummaryPartAddedEvent'
        - $ref: '#/components/schemas/ResponseReasoningSummaryPartDoneEvent'
        - $ref: '#/components/schemas/ResponseReasoningSummaryTextDeltaEvent'
        - $ref: '#/components/schemas/ResponseReasoningSummaryTextDoneEvent'
        - $ref: '#/components/schemas/ResponseRefusalDeltaEvent'
        - $ref: '#/components/schemas/ResponseRefusalDoneEvent'
        - $ref: '#/components/schemas/ResponseTextDeltaEvent'
        - $ref: '#/components/schemas/ResponseTextDoneEvent'
        - $ref: '#/components/schemas/ResponseWebSearchCallCompletedEvent'
        - $ref: '#/components/schemas/ResponseWebSearchCallInProgressEvent'
        - $ref: '#/components/schemas/ResponseWebSearchCallSearchingEvent'
        - $ref: '#/components/schemas/ResponseImageGenCallCompletedEvent'
        - $ref: '#/components/schemas/ResponseImageGenCallGeneratingEvent'
        - $ref: '#/components/schemas/ResponseImageGenCallInProgressEvent'
        - $ref: '#/components/schemas/ResponseImageGenCallPartialImageEvent'
        - $ref: '#/components/schemas/ResponseMCPCallArgumentsDeltaEvent'
        - $ref: '#/components/schemas/ResponseMCPCallArgumentsDoneEvent'
        - $ref: '#/components/schemas/ResponseMCPCallCompletedEvent'
        - $ref: '#/components/schemas/ResponseMCPCallFailedEvent'
        - $ref: '#/components/schemas/ResponseMCPCallInProgressEvent'
        - $ref: '#/components/schemas/ResponseMCPListToolsCompletedEvent'
        - $ref: '#/components/schemas/ResponseMCPListToolsFailedEvent'
        - $ref: '#/components/schemas/ResponseMCPListToolsInProgressEvent'
        - $ref: '#/components/schemas/ResponseOutputTextAnnotationAddedEvent'
        - $ref: '#/components/schemas/ResponseQueuedEvent'
        - $ref: '#/components/schemas/ResponseReasoningDeltaEvent'
        - $ref: '#/components/schemas/ResponseReasoningDoneEvent'
        - $ref: '#/components/schemas/ResponseReasoningSummaryDeltaEvent'
        - $ref: '#/components/schemas/ResponseReasoningSummaryDoneEvent'
      discriminator:
        propertyName: type
    ResponseTextDeltaEvent:
      type: object
      description: Emitted when there is an additional text delta.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.output_text.delta`.
          enum:
            - response.output_text.delta
          x-stainless-const: true
        item_id:
          type: string
          description: |
            The ID of the output item that the text delta was added to.
        output_index:
          type: integer
          description: |
            The index of the output item that the text delta was added to.
        content_index:
          type: integer
          description: |
            The index of the content part that the text delta was added to.
        delta:
          type: string
          description: |
            The text delta that was added.
        sequence_number:
          type: integer
          description: The sequence number for this event.
      required:
        - type
        - item_id
        - output_index
        - content_index
        - delta
        - sequence_number
      x-oaiMeta:
        name: response.output_text.delta
        group: responses
        example: |
          {
            "type": "response.output_text.delta",
            "item_id": "msg_123",
            "output_index": 0,
            "content_index": 0,
            "delta": "In",
            "sequence_number": 1
          }
    ResponseTextDoneEvent:
      type: object
      description: Emitted when text content is finalized.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.output_text.done`.
          enum:
            - response.output_text.done
          x-stainless-const: true
        item_id:
          type: string
          description: |
            The ID of the output item that the text content is finalized.
        output_index:
          type: integer
          description: |
            The index of the output item that the text content is finalized.
        content_index:
          type: integer
          description: |
            The index of the content part that the text content is finalized.
        text:
          type: string
          description: |
            The text content that is finalized.
        sequence_number:
          type: integer
          description: The sequence number for this event.
      required:
        - type
        - item_id
        - output_index
        - content_index
        - text
        - sequence_number
      x-oaiMeta:
        name: response.output_text.done
        group: responses
        example: |
          {
            "type": "response.output_text.done",
            "item_id": "msg_123",
            "output_index": 0,
            "content_index": 0,
            "text": "In a shimmering forest under a sky full of stars, a lonely unicorn named Lila discovered a hidden pond that glowed with moonlight. Every night, she would leave sparkling, magical flowers by the water's edge, hoping to share her beauty with others. One enchanting evening, she woke to find a group of friendly animals gathered around, eager to be friends and share in her magic.",
            "sequence_number": 1
          }
    ResponseUsage:
      type: object
      description: |
        Represents token usage details including input tokens, output tokens,
        a breakdown of output tokens, and the total tokens used.
      properties:
        input_tokens:
          type: integer
          description: The number of input tokens.
        input_tokens_details:
          type: object
          description: A detailed breakdown of the input tokens.
          properties:
            cached_tokens:
              type: integer
              description: |
                The number of tokens that were retrieved from the cache. 
                [More on prompt caching](/docs/guides/prompt-caching).
          required:
            - cached_tokens
        output_tokens:
          type: integer
          description: The number of output tokens.
        output_tokens_details:
          type: object
          description: A detailed breakdown of the output tokens.
          properties:
            reasoning_tokens:
              type: integer
              description: The number of reasoning tokens.
          required:
            - reasoning_tokens
        total_tokens:
          type: integer
          description: The total number of tokens used.
      required:
        - input_tokens
        - input_tokens_details
        - output_tokens
        - output_tokens_details
        - total_tokens
    ResponseWebSearchCallCompletedEvent:
      type: object
      description: Emitted when a web search call is completed.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.web_search_call.completed`.
          enum:
            - response.web_search_call.completed
          x-stainless-const: true
        output_index:
          type: integer
          description: |
            The index of the output item that the web search call is associated with.
        item_id:
          type: string
          description: |
            Unique ID for the output item associated with the web search call.
        sequence_number:
          type: integer
          description: The sequence number of the web search call being processed.
      required:
        - type
        - output_index
        - item_id
        - sequence_number
      x-oaiMeta:
        name: response.web_search_call.completed
        group: responses
        example: |
          {
            "type": "response.web_search_call.completed",
            "output_index": 0,
            "item_id": "ws_123",
            "sequence_number": 0
          }
    ResponseWebSearchCallInProgressEvent:
      type: object
      description: Emitted when a web search call is initiated.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.web_search_call.in_progress`.
          enum:
            - response.web_search_call.in_progress
          x-stainless-const: true
        output_index:
          type: integer
          description: |
            The index of the output item that the web search call is associated with.
        item_id:
          type: string
          description: |
            Unique ID for the output item associated with the web search call.
        sequence_number:
          type: integer
          description: The sequence number of the web search call being processed.
      required:
        - type
        - output_index
        - item_id
        - sequence_number
      x-oaiMeta:
        name: response.web_search_call.in_progress
        group: responses
        example: |
          {
            "type": "response.web_search_call.in_progress",
            "output_index": 0,
            "item_id": "ws_123",
            "sequence_number": 0
          }
    ResponseWebSearchCallSearchingEvent:
      type: object
      description: Emitted when a web search call is executing.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `response.web_search_call.searching`.
          enum:
            - response.web_search_call.searching
          x-stainless-const: true
        output_index:
          type: integer
          description: |
            The index of the output item that the web search call is associated with.
        item_id:
          type: string
          description: |
            Unique ID for the output item associated with the web search call.
        sequence_number:
          type: integer
          description: The sequence number of the web search call being processed.
      required:
        - type
        - output_index
        - item_id
        - sequence_number
      x-oaiMeta:
        name: response.web_search_call.searching
        group: responses
        example: |
          {
            "type": "response.web_search_call.searching",
            "output_index": 0,
            "item_id": "ws_123",
            "sequence_number": 0
          }
    RunCompletionUsage:
      type: object
      description: >-
        Usage statistics related to the run. This value will be `null` if the run is not in a terminal state
        (i.e. `in_progress`, `queued`, etc.).
      properties:
        completion_tokens:
          type: integer
          description: Number of completion tokens used over the course of the run.
        prompt_tokens:
          type: integer
          description: Number of prompt tokens used over the course of the run.
        total_tokens:
          type: integer
          description: Total number of tokens used (prompt + completion).
      required:
        - prompt_tokens
        - completion_tokens
        - total_tokens
      nullable: true
    RunGraderRequest:
      type: object
      title: RunGraderRequest
      properties:
        grader:
          type: object
          description: The grader used for the fine-tuning job.
          oneOf:
            - $ref: '#/components/schemas/GraderStringCheck'
            - $ref: '#/components/schemas/GraderTextSimilarity'
            - $ref: '#/components/schemas/GraderPython'
            - $ref: '#/components/schemas/GraderScoreModel'
            - $ref: '#/components/schemas/GraderMulti'
        item:
          type: object
          description: |
            The dataset item provided to the grader. This will be used to populate 
            the `item` namespace. See [the guide](/docs/guides/graders) for more details. 
        model_sample:
          type: string
          description: |
            The model sample to be evaluated. This value will be used to populate 
            the `sample` namespace. See [the guide](/docs/guides/graders) for more details.
            The `output_json` variable will be populated if the model sample is a 
            valid JSON string.
             
      required:
        - grader
        - model_sample
    RunGraderResponse:
      type: object
      properties:
        reward:
          type: number
        metadata:
          type: object
          properties:
            name:
              type: string
            type:
              type: string
            errors:
              type: object
              properties:
                formula_parse_error:
                  type: boolean
                sample_parse_error:
                  type: boolean
                truncated_observation_error:
                  type: boolean
                unresponsive_reward_error:
                  type: boolean
                invalid_variable_error:
                  type: boolean
                other_error:
                  type: boolean
                python_grader_server_error:
                  type: boolean
                python_grader_server_error_type:
                  type: string
                  nullable: true
                python_grader_runtime_error:
                  type: boolean
                python_grader_runtime_error_details:
                  type: string
                  nullable: true
                model_grader_server_error:
                  type: boolean
                model_grader_refusal_error:
                  type: boolean
                model_grader_parse_error:
                  type: boolean
                model_grader_server_error_details:
                  type: string
                  nullable: true
              required:
                - formula_parse_error
                - sample_parse_error
                - truncated_observation_error
                - unresponsive_reward_error
                - invalid_variable_error
                - other_error
                - python_grader_server_error
                - python_grader_server_error_type
                - python_grader_runtime_error
                - python_grader_runtime_error_details
                - model_grader_server_error
                - model_grader_refusal_error
                - model_grader_parse_error
                - model_grader_server_error_details
            execution_time:
              type: number
            scores:
              type: object
              additionalProperties: {}
            token_usage:
              type: integer
              nullable: true
            sampled_model_name:
              type: string
              nullable: true
          required:
            - name
            - type
            - errors
            - execution_time
            - scores
            - token_usage
            - sampled_model_name
        sub_rewards:
          type: object
          additionalProperties: {}
        model_grader_token_usage_per_model:
          type: object
          additionalProperties: {}
      required:
        - reward
        - metadata
        - sub_rewards
        - model_grader_token_usage_per_model
    RunObject:
      type: object
      title: A run on a thread
      description: Represents an execution run on a [thread](/docs/api-reference/threads).
      properties:
        id:
          description: The identifier, which can be referenced in API endpoints.
          type: string
        object:
          description: The object type, which is always `thread.run`.
          type: string
          enum:
            - thread.run
          x-stainless-const: true
        created_at:
          description: The Unix timestamp (in seconds) for when the run was created.
          type: integer
        thread_id:
          description: The ID of the [thread](/docs/api-reference/threads) that was executed on as a part of this run.
          type: string
        assistant_id:
          description: The ID of the [assistant](/docs/api-reference/assistants) used for execution of this run.
          type: string
        status:
          description: >-
            The status of the run, which can be either `queued`, `in_progress`, `requires_action`,
            `cancelling`, `cancelled`, `failed`, `completed`, `incomplete`, or `expired`.
          type: string
          enum:
            - queued
            - in_progress
            - requires_action
            - cancelling
            - cancelled
            - failed
            - completed
            - incomplete
            - expired
        required_action:
          type: object
          description: Details on the action required to continue the run. Will be `null` if no action is required.
          nullable: true
          properties:
            type:
              description: For now, this is always `submit_tool_outputs`.
              type: string
              enum:
                - submit_tool_outputs
              x-stainless-const: true
            submit_tool_outputs:
              type: object
              description: Details on the tool outputs needed for this run to continue.
              properties:
                tool_calls:
                  type: array
                  description: A list of the relevant tool calls.
                  items:
                    $ref: '#/components/schemas/RunToolCallObject'
              required:
                - tool_calls
          required:
            - type
            - submit_tool_outputs
        last_error:
          type: object
          description: The last error associated with this run. Will be `null` if there are no errors.
          nullable: true
          properties:
            code:
              type: string
              description: One of `server_error`, `rate_limit_exceeded`, or `invalid_prompt`.
              enum:
                - server_error
                - rate_limit_exceeded
                - invalid_prompt
            message:
              type: string
              description: A human-readable description of the error.
          required:
            - code
            - message
        expires_at:
          description: The Unix timestamp (in seconds) for when the run will expire.
          type: integer
          nullable: true
        started_at:
          description: The Unix timestamp (in seconds) for when the run was started.
          type: integer
          nullable: true
        cancelled_at:
          description: The Unix timestamp (in seconds) for when the run was cancelled.
          type: integer
          nullable: true
        failed_at:
          description: The Unix timestamp (in seconds) for when the run failed.
          type: integer
          nullable: true
        completed_at:
          description: The Unix timestamp (in seconds) for when the run was completed.
          type: integer
          nullable: true
        incomplete_details:
          description: Details on why the run is incomplete. Will be `null` if the run is not incomplete.
          type: object
          nullable: true
          properties:
            reason:
              description: >-
                The reason why the run is incomplete. This will point to which specific token limit was
                reached over the course of the run.
              type: string
              enum:
                - max_completion_tokens
                - max_prompt_tokens
        model:
          description: The model that the [assistant](/docs/api-reference/assistants) used for this run.
          type: string
        instructions:
          description: The instructions that the [assistant](/docs/api-reference/assistants) used for this run.
          type: string
        tools:
          description: The list of tools that the [assistant](/docs/api-reference/assistants) used for this run.
          default: []
          type: array
          maxItems: 20
          items:
            oneOf:
              - $ref: '#/components/schemas/AssistantToolsCode'
              - $ref: '#/components/schemas/AssistantToolsFileSearch'
              - $ref: '#/components/schemas/AssistantToolsFunction'
        metadata:
          $ref: '#/components/schemas/Metadata'
        usage:
          $ref: '#/components/schemas/RunCompletionUsage'
        temperature:
          description: The sampling temperature used for this run. If not set, defaults to 1.
          type: number
          nullable: true
        top_p:
          description: The nucleus sampling value used for this run. If not set, defaults to 1.
          type: number
          nullable: true
        max_prompt_tokens:
          type: integer
          nullable: true
          description: |
            The maximum number of prompt tokens specified to have been used over the course of the run.
          minimum: 256
        max_completion_tokens:
          type: integer
          nullable: true
          description: |
            The maximum number of completion tokens specified to have been used over the course of the run.
          minimum: 256
        truncation_strategy:
          allOf:
            - $ref: '#/components/schemas/TruncationObject'
            - nullable: true
        tool_choice:
          allOf:
            - $ref: '#/components/schemas/AssistantsApiToolChoiceOption'
            - nullable: true
        parallel_tool_calls:
          $ref: '#/components/schemas/ParallelToolCalls'
        response_format:
          $ref: '#/components/schemas/AssistantsApiResponseFormatOption'
          nullable: true
      required:
        - id
        - object
        - created_at
        - thread_id
        - assistant_id
        - status
        - required_action
        - last_error
        - expires_at
        - started_at
        - cancelled_at
        - failed_at
        - completed_at
        - model
        - instructions
        - tools
        - metadata
        - usage
        - incomplete_details
        - max_prompt_tokens
        - max_completion_tokens
        - truncation_strategy
        - tool_choice
        - parallel_tool_calls
        - response_format
      x-oaiMeta:
        name: The run object
        beta: true
        example: |
          {
            "id": "run_abc123",
            "object": "thread.run",
            "created_at": 1698107661,
            "assistant_id": "asst_abc123",
            "thread_id": "thread_abc123",
            "status": "completed",
            "started_at": 1699073476,
            "expires_at": null,
            "cancelled_at": null,
            "failed_at": null,
            "completed_at": 1699073498,
            "last_error": null,
            "model": "gpt-4o",
            "instructions": null,
            "tools": [{"type": "file_search"}, {"type": "code_interpreter"}],
            "metadata": {},
            "incomplete_details": null,
            "usage": {
              "prompt_tokens": 123,
              "completion_tokens": 456,
              "total_tokens": 579
            },
            "temperature": 1.0,
            "top_p": 1.0,
            "max_prompt_tokens": 1000,
            "max_completion_tokens": 1000,
            "truncation_strategy": {
              "type": "auto",
              "last_messages": null
            },
            "response_format": "auto",
            "tool_choice": "auto",
            "parallel_tool_calls": true
          }
    RunStepCompletionUsage:
      type: object
      description: >-
        Usage statistics related to the run step. This value will be `null` while the run step's status is
        `in_progress`.
      properties:
        completion_tokens:
          type: integer
          description: Number of completion tokens used over the course of the run step.
        prompt_tokens:
          type: integer
          description: Number of prompt tokens used over the course of the run step.
        total_tokens:
          type: integer
          description: Total number of tokens used (prompt + completion).
      required:
        - prompt_tokens
        - completion_tokens
        - total_tokens
      nullable: true
    RunStepDeltaObject:
      type: object
      title: Run step delta object
      description: |
        Represents a run step delta i.e. any changed fields on a run step during streaming.
      properties:
        id:
          description: The identifier of the run step, which can be referenced in API endpoints.
          type: string
        object:
          description: The object type, which is always `thread.run.step.delta`.
          type: string
          enum:
            - thread.run.step.delta
          x-stainless-const: true
        delta:
          description: The delta containing the fields that have changed on the run step.
          type: object
          properties:
            step_details:
              type: object
              description: The details of the run step.
              oneOf:
                - $ref: '#/components/schemas/RunStepDeltaStepDetailsMessageCreationObject'
                - $ref: '#/components/schemas/RunStepDeltaStepDetailsToolCallsObject'
      required:
        - id
        - object
        - delta
      x-oaiMeta:
        name: The run step delta object
        beta: true
        example: |
          {
            "id": "step_123",
            "object": "thread.run.step.delta",
            "delta": {
              "step_details": {
                "type": "tool_calls",
                "tool_calls": [
                  {
                    "index": 0,
                    "id": "call_123",
                    "type": "code_interpreter",
                    "code_interpreter": { "input": "", "outputs": [] }
                  }
                ]
              }
            }
          }
    RunStepDeltaStepDetailsMessageCreationObject:
      title: Message creation
      type: object
      description: Details of the message creation by the run step.
      properties:
        type:
          description: Always `message_creation`.
          type: string
          enum:
            - message_creation
          x-stainless-const: true
        message_creation:
          type: object
          properties:
            message_id:
              type: string
              description: The ID of the message that was created by this run step.
      required:
        - type
    RunStepDeltaStepDetailsToolCallsCodeObject:
      title: Code interpreter tool call
      type: object
      description: Details of the Code Interpreter tool call the run step was involved in.
      properties:
        index:
          type: integer
          description: The index of the tool call in the tool calls array.
        id:
          type: string
          description: The ID of the tool call.
        type:
          type: string
          description: The type of tool call. This is always going to be `code_interpreter` for this type of tool call.
          enum:
            - code_interpreter
          x-stainless-const: true
        code_interpreter:
          type: object
          description: The Code Interpreter tool call definition.
          properties:
            input:
              type: string
              description: The input to the Code Interpreter tool call.
            outputs:
              type: array
              description: >-
                The outputs from the Code Interpreter tool call. Code Interpreter can output one or more
                items, including text (`logs`) or images (`image`). Each of these are represented by a
                different object type.
              items:
                type: object
                oneOf:
                  - $ref: '#/components/schemas/RunStepDeltaStepDetailsToolCallsCodeOutputLogsObject'
                  - $ref: '#/components/schemas/RunStepDeltaStepDetailsToolCallsCodeOutputImageObject'
      required:
        - index
        - type
    RunStepDeltaStepDetailsToolCallsCodeOutputImageObject:
      title: Code interpreter image output
      type: object
      properties:
        index:
          type: integer
          description: The index of the output in the outputs array.
        type:
          description: Always `image`.
          type: string
          enum:
            - image
          x-stainless-const: true
        image:
          type: object
          properties:
            file_id:
              description: The [file](/docs/api-reference/files) ID of the image.
              type: string
      required:
        - index
        - type
    RunStepDeltaStepDetailsToolCallsCodeOutputLogsObject:
      title: Code interpreter log output
      type: object
      description: Text output from the Code Interpreter tool call as part of a run step.
      properties:
        index:
          type: integer
          description: The index of the output in the outputs array.
        type:
          description: Always `logs`.
          type: string
          enum:
            - logs
          x-stainless-const: true
        logs:
          type: string
          description: The text output from the Code Interpreter tool call.
      required:
        - index
        - type
    RunStepDeltaStepDetailsToolCallsFileSearchObject:
      title: File search tool call
      type: object
      properties:
        index:
          type: integer
          description: The index of the tool call in the tool calls array.
        id:
          type: string
          description: The ID of the tool call object.
        type:
          type: string
          description: The type of tool call. This is always going to be `file_search` for this type of tool call.
          enum:
            - file_search
          x-stainless-const: true
        file_search:
          type: object
          description: For now, this is always going to be an empty object.
          x-oaiTypeLabel: map
      required:
        - index
        - type
        - file_search
    RunStepDeltaStepDetailsToolCallsFunctionObject:
      type: object
      title: Function tool call
      properties:
        index:
          type: integer
          description: The index of the tool call in the tool calls array.
        id:
          type: string
          description: The ID of the tool call object.
        type:
          type: string
          description: The type of tool call. This is always going to be `function` for this type of tool call.
          enum:
            - function
          x-stainless-const: true
        function:
          type: object
          description: The definition of the function that was called.
          properties:
            name:
              type: string
              description: The name of the function.
            arguments:
              type: string
              description: The arguments passed to the function.
            output:
              type: string
              description: >-
                The output of the function. This will be `null` if the outputs have not been
                [submitted](/docs/api-reference/runs/submitToolOutputs) yet.
              nullable: true
      required:
        - index
        - type
    RunStepDeltaStepDetailsToolCallsObject:
      title: Tool calls
      type: object
      description: Details of the tool call.
      properties:
        type:
          description: Always `tool_calls`.
          type: string
          enum:
            - tool_calls
          x-stainless-const: true
        tool_calls:
          type: array
          description: >
            An array of tool calls the run step was involved in. These can be associated with one of three
            types of tools: `code_interpreter`, `file_search`, or `function`.
          items:
            oneOf:
              - $ref: '#/components/schemas/RunStepDeltaStepDetailsToolCallsCodeObject'
              - $ref: '#/components/schemas/RunStepDeltaStepDetailsToolCallsFileSearchObject'
              - $ref: '#/components/schemas/RunStepDeltaStepDetailsToolCallsFunctionObject'
      required:
        - type
    RunStepDetailsMessageCreationObject:
      title: Message creation
      type: object
      description: Details of the message creation by the run step.
      properties:
        type:
          description: Always `message_creation`.
          type: string
          enum:
            - message_creation
          x-stainless-const: true
        message_creation:
          type: object
          properties:
            message_id:
              type: string
              description: The ID of the message that was created by this run step.
          required:
            - message_id
      required:
        - type
        - message_creation
    RunStepDetailsToolCallsCodeObject:
      title: Code Interpreter tool call
      type: object
      description: Details of the Code Interpreter tool call the run step was involved in.
      properties:
        id:
          type: string
          description: The ID of the tool call.
        type:
          type: string
          description: The type of tool call. This is always going to be `code_interpreter` for this type of tool call.
          enum:
            - code_interpreter
          x-stainless-const: true
        code_interpreter:
          type: object
          description: The Code Interpreter tool call definition.
          required:
            - input
            - outputs
          properties:
            input:
              type: string
              description: The input to the Code Interpreter tool call.
            outputs:
              type: array
              description: >-
                The outputs from the Code Interpreter tool call. Code Interpreter can output one or more
                items, including text (`logs`) or images (`image`). Each of these are represented by a
                different object type.
              items:
                type: object
                oneOf:
                  - $ref: '#/components/schemas/RunStepDetailsToolCallsCodeOutputLogsObject'
                  - $ref: '#/components/schemas/RunStepDetailsToolCallsCodeOutputImageObject'
      required:
        - id
        - type
        - code_interpreter
    RunStepDetailsToolCallsCodeOutputImageObject:
      title: Code Interpreter image output
      type: object
      properties:
        type:
          description: Always `image`.
          type: string
          enum:
            - image
          x-stainless-const: true
        image:
          type: object
          properties:
            file_id:
              description: The [file](/docs/api-reference/files) ID of the image.
              type: string
          required:
            - file_id
      required:
        - type
        - image
    RunStepDetailsToolCallsCodeOutputLogsObject:
      title: Code Interpreter log output
      type: object
      description: Text output from the Code Interpreter tool call as part of a run step.
      properties:
        type:
          description: Always `logs`.
          type: string
          enum:
            - logs
          x-stainless-const: true
        logs:
          type: string
          description: The text output from the Code Interpreter tool call.
      required:
        - type
        - logs
    RunStepDetailsToolCallsFileSearchObject:
      title: File search tool call
      type: object
      properties:
        id:
          type: string
          description: The ID of the tool call object.
        type:
          type: string
          description: The type of tool call. This is always going to be `file_search` for this type of tool call.
          enum:
            - file_search
          x-stainless-const: true
        file_search:
          type: object
          description: For now, this is always going to be an empty object.
          x-oaiTypeLabel: map
          properties:
            ranking_options:
              $ref: '#/components/schemas/RunStepDetailsToolCallsFileSearchRankingOptionsObject'
            results:
              type: array
              description: The results of the file search.
              items:
                $ref: '#/components/schemas/RunStepDetailsToolCallsFileSearchResultObject'
      required:
        - id
        - type
        - file_search
    RunStepDetailsToolCallsFileSearchRankingOptionsObject:
      title: File search tool call ranking options
      type: object
      description: The ranking options for the file search.
      properties:
        ranker:
          $ref: '#/components/schemas/FileSearchRanker'
        score_threshold:
          type: number
          description: >-
            The score threshold for the file search. All values must be a floating point number between 0 and
            1.
          minimum: 0
          maximum: 1
      required:
        - ranker
        - score_threshold
    RunStepDetailsToolCallsFileSearchResultObject:
      title: File search tool call result
      type: object
      description: A result instance of the file search.
      x-oaiTypeLabel: map
      properties:
        file_id:
          type: string
          description: The ID of the file that result was found in.
        file_name:
          type: string
          description: The name of the file that result was found in.
        score:
          type: number
          description: The score of the result. All values must be a floating point number between 0 and 1.
          minimum: 0
          maximum: 1
        content:
          type: array
          description: >-
            The content of the result that was found. The content is only included if requested via the
            include query parameter.
          items:
            type: object
            properties:
              type:
                type: string
                description: The type of the content.
                enum:
                  - text
                x-stainless-const: true
              text:
                type: string
                description: The text content of the file.
      required:
        - file_id
        - file_name
        - score
    RunStepDetailsToolCallsFunctionObject:
      type: object
      title: Function tool call
      properties:
        id:
          type: string
          description: The ID of the tool call object.
        type:
          type: string
          description: The type of tool call. This is always going to be `function` for this type of tool call.
          enum:
            - function
          x-stainless-const: true
        function:
          type: object
          description: The definition of the function that was called.
          properties:
            name:
              type: string
              description: The name of the function.
            arguments:
              type: string
              description: The arguments passed to the function.
            output:
              type: string
              description: >-
                The output of the function. This will be `null` if the outputs have not been
                [submitted](/docs/api-reference/runs/submitToolOutputs) yet.
              nullable: true
          required:
            - name
            - arguments
            - output
      required:
        - id
        - type
        - function
    RunStepDetailsToolCallsObject:
      title: Tool calls
      type: object
      description: Details of the tool call.
      properties:
        type:
          description: Always `tool_calls`.
          type: string
          enum:
            - tool_calls
          x-stainless-const: true
        tool_calls:
          type: array
          description: >
            An array of tool calls the run step was involved in. These can be associated with one of three
            types of tools: `code_interpreter`, `file_search`, or `function`.
          items:
            oneOf:
              - $ref: '#/components/schemas/RunStepDetailsToolCallsCodeObject'
              - $ref: '#/components/schemas/RunStepDetailsToolCallsFileSearchObject'
              - $ref: '#/components/schemas/RunStepDetailsToolCallsFunctionObject'
      required:
        - type
        - tool_calls
    RunStepObject:
      type: object
      title: Run steps
      description: |
        Represents a step in execution of a run.
      properties:
        id:
          description: The identifier of the run step, which can be referenced in API endpoints.
          type: string
        object:
          description: The object type, which is always `thread.run.step`.
          type: string
          enum:
            - thread.run.step
          x-stainless-const: true
        created_at:
          description: The Unix timestamp (in seconds) for when the run step was created.
          type: integer
        assistant_id:
          description: The ID of the [assistant](/docs/api-reference/assistants) associated with the run step.
          type: string
        thread_id:
          description: The ID of the [thread](/docs/api-reference/threads) that was run.
          type: string
        run_id:
          description: The ID of the [run](/docs/api-reference/runs) that this run step is a part of.
          type: string
        type:
          description: The type of run step, which can be either `message_creation` or `tool_calls`.
          type: string
          enum:
            - message_creation
            - tool_calls
        status:
          description: >-
            The status of the run step, which can be either `in_progress`, `cancelled`, `failed`, `completed`,
            or `expired`.
          type: string
          enum:
            - in_progress
            - cancelled
            - failed
            - completed
            - expired
        step_details:
          type: object
          description: The details of the run step.
          oneOf:
            - $ref: '#/components/schemas/RunStepDetailsMessageCreationObject'
            - $ref: '#/components/schemas/RunStepDetailsToolCallsObject'
        last_error:
          type: object
          description: The last error associated with this run step. Will be `null` if there are no errors.
          nullable: true
          properties:
            code:
              type: string
              description: One of `server_error` or `rate_limit_exceeded`.
              enum:
                - server_error
                - rate_limit_exceeded
            message:
              type: string
              description: A human-readable description of the error.
          required:
            - code
            - message
        expired_at:
          description: >-
            The Unix timestamp (in seconds) for when the run step expired. A step is considered expired if the
            parent run is expired.
          type: integer
          nullable: true
        cancelled_at:
          description: The Unix timestamp (in seconds) for when the run step was cancelled.
          type: integer
          nullable: true
        failed_at:
          description: The Unix timestamp (in seconds) for when the run step failed.
          type: integer
          nullable: true
        completed_at:
          description: The Unix timestamp (in seconds) for when the run step completed.
          type: integer
          nullable: true
        metadata:
          $ref: '#/components/schemas/Metadata'
        usage:
          $ref: '#/components/schemas/RunStepCompletionUsage'
      required:
        - id
        - object
        - created_at
        - assistant_id
        - thread_id
        - run_id
        - type
        - status
        - step_details
        - last_error
        - expired_at
        - cancelled_at
        - failed_at
        - completed_at
        - metadata
        - usage
      x-oaiMeta:
        name: The run step object
        beta: true
        example: |
          {
            "id": "step_abc123",
            "object": "thread.run.step",
            "created_at": 1699063291,
            "run_id": "run_abc123",
            "assistant_id": "asst_abc123",
            "thread_id": "thread_abc123",
            "type": "message_creation",
            "status": "completed",
            "cancelled_at": null,
            "completed_at": 1699063291,
            "expired_at": null,
            "failed_at": null,
            "last_error": null,
            "step_details": {
              "type": "message_creation",
              "message_creation": {
                "message_id": "msg_abc123"
              }
            },
            "usage": {
              "prompt_tokens": 123,
              "completion_tokens": 456,
              "total_tokens": 579
            }
          }
    RunStepStreamEvent:
      oneOf:
        - type: object
          properties:
            event:
              type: string
              enum:
                - thread.run.step.created
              x-stainless-const: true
            data:
              $ref: '#/components/schemas/RunStepObject'
          required:
            - event
            - data
          description: Occurs when a [run step](/docs/api-reference/run-steps/step-object) is created.
          x-oaiMeta:
            dataDescription: '`data` is a [run step](/docs/api-reference/run-steps/step-object)'
        - type: object
          properties:
            event:
              type: string
              enum:
                - thread.run.step.in_progress
              x-stainless-const: true
            data:
              $ref: '#/components/schemas/RunStepObject'
          required:
            - event
            - data
          description: >-
            Occurs when a [run step](/docs/api-reference/run-steps/step-object) moves to an `in_progress`
            state.
          x-oaiMeta:
            dataDescription: '`data` is a [run step](/docs/api-reference/run-steps/step-object)'
        - type: object
          properties:
            event:
              type: string
              enum:
                - thread.run.step.delta
              x-stainless-const: true
            data:
              $ref: '#/components/schemas/RunStepDeltaObject'
          required:
            - event
            - data
          description: Occurs when parts of a [run step](/docs/api-reference/run-steps/step-object) are being streamed.
          x-oaiMeta:
            dataDescription: '`data` is a [run step delta](/docs/api-reference/assistants-streaming/run-step-delta-object)'
        - type: object
          properties:
            event:
              type: string
              enum:
                - thread.run.step.completed
              x-stainless-const: true
            data:
              $ref: '#/components/schemas/RunStepObject'
          required:
            - event
            - data
          description: Occurs when a [run step](/docs/api-reference/run-steps/step-object) is completed.
          x-oaiMeta:
            dataDescription: '`data` is a [run step](/docs/api-reference/run-steps/step-object)'
        - type: object
          properties:
            event:
              type: string
              enum:
                - thread.run.step.failed
              x-stainless-const: true
            data:
              $ref: '#/components/schemas/RunStepObject'
          required:
            - event
            - data
          description: Occurs when a [run step](/docs/api-reference/run-steps/step-object) fails.
          x-oaiMeta:
            dataDescription: '`data` is a [run step](/docs/api-reference/run-steps/step-object)'
        - type: object
          properties:
            event:
              type: string
              enum:
                - thread.run.step.cancelled
              x-stainless-const: true
            data:
              $ref: '#/components/schemas/RunStepObject'
          required:
            - event
            - data
          description: Occurs when a [run step](/docs/api-reference/run-steps/step-object) is cancelled.
          x-oaiMeta:
            dataDescription: '`data` is a [run step](/docs/api-reference/run-steps/step-object)'
        - type: object
          properties:
            event:
              type: string
              enum:
                - thread.run.step.expired
              x-stainless-const: true
            data:
              $ref: '#/components/schemas/RunStepObject'
          required:
            - event
            - data
          description: Occurs when a [run step](/docs/api-reference/run-steps/step-object) expires.
          x-oaiMeta:
            dataDescription: '`data` is a [run step](/docs/api-reference/run-steps/step-object)'
    RunStreamEvent:
      oneOf:
        - type: object
          properties:
            event:
              type: string
              enum:
                - thread.run.created
              x-stainless-const: true
            data:
              $ref: '#/components/schemas/RunObject'
          required:
            - event
            - data
          description: Occurs when a new [run](/docs/api-reference/runs/object) is created.
          x-oaiMeta:
            dataDescription: '`data` is a [run](/docs/api-reference/runs/object)'
        - type: object
          properties:
            event:
              type: string
              enum:
                - thread.run.queued
              x-stainless-const: true
            data:
              $ref: '#/components/schemas/RunObject'
          required:
            - event
            - data
          description: Occurs when a [run](/docs/api-reference/runs/object) moves to a `queued` status.
          x-oaiMeta:
            dataDescription: '`data` is a [run](/docs/api-reference/runs/object)'
        - type: object
          properties:
            event:
              type: string
              enum:
                - thread.run.in_progress
              x-stainless-const: true
            data:
              $ref: '#/components/schemas/RunObject'
          required:
            - event
            - data
          description: Occurs when a [run](/docs/api-reference/runs/object) moves to an `in_progress` status.
          x-oaiMeta:
            dataDescription: '`data` is a [run](/docs/api-reference/runs/object)'
        - type: object
          properties:
            event:
              type: string
              enum:
                - thread.run.requires_action
              x-stainless-const: true
            data:
              $ref: '#/components/schemas/RunObject'
          required:
            - event
            - data
          description: Occurs when a [run](/docs/api-reference/runs/object) moves to a `requires_action` status.
          x-oaiMeta:
            dataDescription: '`data` is a [run](/docs/api-reference/runs/object)'
        - type: object
          properties:
            event:
              type: string
              enum:
                - thread.run.completed
              x-stainless-const: true
            data:
              $ref: '#/components/schemas/RunObject'
          required:
            - event
            - data
          description: Occurs when a [run](/docs/api-reference/runs/object) is completed.
          x-oaiMeta:
            dataDescription: '`data` is a [run](/docs/api-reference/runs/object)'
        - type: object
          properties:
            event:
              type: string
              enum:
                - thread.run.incomplete
              x-stainless-const: true
            data:
              $ref: '#/components/schemas/RunObject'
          required:
            - event
            - data
          description: Occurs when a [run](/docs/api-reference/runs/object) ends with status `incomplete`.
          x-oaiMeta:
            dataDescription: '`data` is a [run](/docs/api-reference/runs/object)'
        - type: object
          properties:
            event:
              type: string
              enum:
                - thread.run.failed
              x-stainless-const: true
            data:
              $ref: '#/components/schemas/RunObject'
          required:
            - event
            - data
          description: Occurs when a [run](/docs/api-reference/runs/object) fails.
          x-oaiMeta:
            dataDescription: '`data` is a [run](/docs/api-reference/runs/object)'
        - type: object
          properties:
            event:
              type: string
              enum:
                - thread.run.cancelling
              x-stainless-const: true
            data:
              $ref: '#/components/schemas/RunObject'
          required:
            - event
            - data
          description: Occurs when a [run](/docs/api-reference/runs/object) moves to a `cancelling` status.
          x-oaiMeta:
            dataDescription: '`data` is a [run](/docs/api-reference/runs/object)'
        - type: object
          properties:
            event:
              type: string
              enum:
                - thread.run.cancelled
              x-stainless-const: true
            data:
              $ref: '#/components/schemas/RunObject'
          required:
            - event
            - data
          description: Occurs when a [run](/docs/api-reference/runs/object) is cancelled.
          x-oaiMeta:
            dataDescription: '`data` is a [run](/docs/api-reference/runs/object)'
        - type: object
          properties:
            event:
              type: string
              enum:
                - thread.run.expired
              x-stainless-const: true
            data:
              $ref: '#/components/schemas/RunObject'
          required:
            - event
            - data
          description: Occurs when a [run](/docs/api-reference/runs/object) expires.
          x-oaiMeta:
            dataDescription: '`data` is a [run](/docs/api-reference/runs/object)'
    RunToolCallObject:
      type: object
      description: Tool call objects
      properties:
        id:
          type: string
          description: >-
            The ID of the tool call. This ID must be referenced when you submit the tool outputs in using the
            [Submit tool outputs to run](/docs/api-reference/runs/submitToolOutputs) endpoint.
        type:
          type: string
          description: The type of tool call the output is required for. For now, this is always `function`.
          enum:
            - function
          x-stainless-const: true
        function:
          type: object
          description: The function definition.
          properties:
            name:
              type: string
              description: The name of the function.
            arguments:
              type: string
              description: The arguments that the model expects you to pass to the function.
          required:
            - name
            - arguments
      required:
        - id
        - type
        - function
    Screenshot:
      type: object
      title: Screenshot
      description: |
        A screenshot action.
      properties:
        type:
          type: string
          enum:
            - screenshot
          default: screenshot
          description: |
            Specifies the event type. For a screenshot action, this property is 
            always set to `screenshot`.
          x-stainless-const: true
      required:
        - type
    Scroll:
      type: object
      title: Scroll
      description: |
        A scroll action.
      properties:
        type:
          type: string
          enum:
            - scroll
          default: scroll
          description: |
            Specifies the event type. For a scroll action, this property is 
            always set to `scroll`.
          x-stainless-const: true
        x:
          type: integer
          description: |
            The x-coordinate where the scroll occurred.
        'y':
          type: integer
          description: |
            The y-coordinate where the scroll occurred.
        scroll_x:
          type: integer
          description: |
            The horizontal scroll distance.
        scroll_y:
          type: integer
          description: |
            The vertical scroll distance.
      required:
        - type
        - x
        - 'y'
        - scroll_x
        - scroll_y
    ServiceTier:
      type: string
      description: >
        Specifies the latency tier to use for processing the request. This parameter is relevant for customers
        subscribed to the scale tier service:
          - If set to 'auto', and the Project is Scale tier enabled, the system
            will utilize scale tier credits until they are exhausted.
          - If set to 'auto', and the Project is not Scale tier enabled, the request will be processed using the default service tier with a lower uptime SLA and no latency guarantee.
          - If set to 'default', the request will be processed using the default service tier with a lower uptime SLA and no latency guarantee.
          - If set to 'flex', the request will be processed with the Flex Processing service tier. [Learn more](/docs/guides/flex-processing).
          - When not set, the default behavior is 'auto'.

          When this parameter is set, the response body will include the `service_tier` utilized.
      enum:
        - auto
        - default
        - flex
        - scale
      nullable: true
      default: auto
    StaticChunkingStrategy:
      type: object
      additionalProperties: false
      properties:
        max_chunk_size_tokens:
          type: integer
          minimum: 100
          maximum: 4096
          description: >-
            The maximum number of tokens in each chunk. The default value is `800`. The minimum value is `100`
            and the maximum value is `4096`.
        chunk_overlap_tokens:
          type: integer
          description: |
            The number of tokens that overlap between chunks. The default value is `400`.

            Note that the overlap must not exceed half of `max_chunk_size_tokens`.
      required:
        - max_chunk_size_tokens
        - chunk_overlap_tokens
    StaticChunkingStrategyRequestParam:
      type: object
      title: Static Chunking Strategy
      description: Customize your own chunking strategy by setting chunk size and chunk overlap.
      additionalProperties: false
      properties:
        type:
          type: string
          description: Always `static`.
          enum:
            - static
          x-stainless-const: true
        static:
          $ref: '#/components/schemas/StaticChunkingStrategy'
      required:
        - type
        - static
    StaticChunkingStrategyResponseParam:
      type: object
      title: Static Chunking Strategy
      additionalProperties: false
      properties:
        type:
          type: string
          description: Always `static`.
          enum:
            - static
          x-stainless-const: true
        static:
          $ref: '#/components/schemas/StaticChunkingStrategy'
      required:
        - type
        - static
    StopConfiguration:
      description: |
        Not supported with latest reasoning models `o3` and `o4-mini`.

        Up to 4 sequences where the API will stop generating further tokens. The
        returned text will not contain the stop sequence.
      default: null
      nullable: true
      oneOf:
        - type: string
          default: <|endoftext|>
          example: |+

          nullable: true
        - type: array
          minItems: 1
          maxItems: 4
          items:
            type: string
            example: '["\n"]'
    SubmitToolOutputsRunRequest:
      type: object
      additionalProperties: false
      properties:
        tool_outputs:
          description: A list of tools for which the outputs are being submitted.
          type: array
          items:
            type: object
            properties:
              tool_call_id:
                type: string
                description: >-
                  The ID of the tool call in the `required_action` object within the run object the output is
                  being submitted for.
              output:
                type: string
                description: The output of the tool call to be submitted to continue the run.
        stream:
          type: boolean
          nullable: true
          description: >
            If `true`, returns a stream of events that happen during the Run as server-sent events,
            terminating when the Run enters a terminal state with a `data: [DONE]` message.
      required:
        - tool_outputs
    TextResponseFormatConfiguration:
      description: |
        An object specifying the format that the model must output.

        Configuring `{ "type": "json_schema" }` enables Structured Outputs, 
        which ensures the model will match your supplied JSON schema. Learn more in the 
        [Structured Outputs guide](/docs/guides/structured-outputs).

        The default format is `{ "type": "text" }` with no additional options.

        **Not recommended for gpt-4o and newer models:**

        Setting to `{ "type": "json_object" }` enables the older JSON mode, which
        ensures the message the model generates is valid JSON. Using `json_schema`
        is preferred for models that support it.
      oneOf:
        - $ref: '#/components/schemas/ResponseFormatText'
        - $ref: '#/components/schemas/TextResponseFormatJsonSchema'
        - $ref: '#/components/schemas/ResponseFormatJsonObject'
    TextResponseFormatJsonSchema:
      type: object
      title: JSON schema
      description: |
        JSON Schema response format. Used to generate structured JSON responses.
        Learn more about [Structured Outputs](/docs/guides/structured-outputs).
      properties:
        type:
          type: string
          description: The type of response format being defined. Always `json_schema`.
          enum:
            - json_schema
          x-stainless-const: true
        description:
          type: string
          description: |
            A description of what the response format is for, used by the model to
            determine how to respond in the format.
        name:
          type: string
          description: |
            The name of the response format. Must be a-z, A-Z, 0-9, or contain
            underscores and dashes, with a maximum length of 64.
        schema:
          $ref: '#/components/schemas/ResponseFormatJsonSchemaSchema'
        strict:
          type: boolean
          nullable: true
          default: false
          description: |
            Whether to enable strict schema adherence when generating the output.
            If set to true, the model will always follow the exact schema defined
            in the `schema` field. Only a subset of JSON Schema is supported when
            `strict` is `true`. To learn more, read the [Structured Outputs
            guide](/docs/guides/structured-outputs).
      required:
        - type
        - schema
        - name
    ThreadObject:
      type: object
      title: Thread
      description: Represents a thread that contains [messages](/docs/api-reference/messages).
      properties:
        id:
          description: The identifier, which can be referenced in API endpoints.
          type: string
        object:
          description: The object type, which is always `thread`.
          type: string
          enum:
            - thread
          x-stainless-const: true
        created_at:
          description: The Unix timestamp (in seconds) for when the thread was created.
          type: integer
        tool_resources:
          type: object
          description: >
            A set of resources that are made available to the assistant's tools in this thread. The resources
            are specific to the type of tool. For example, the `code_interpreter` tool requires a list of file
            IDs, while the `file_search` tool requires a list of vector store IDs.
          properties:
            code_interpreter:
              type: object
              properties:
                file_ids:
                  type: array
                  description: >
                    A list of [file](/docs/api-reference/files) IDs made available to the `code_interpreter`
                    tool. There can be a maximum of 20 files associated with the tool.
                  default: []
                  maxItems: 20
                  items:
                    type: string
            file_search:
              type: object
              properties:
                vector_store_ids:
                  type: array
                  description: >
                    The [vector store](/docs/api-reference/vector-stores/object) attached to this thread.
                    There can be a maximum of 1 vector store attached to the thread.
                  maxItems: 1
                  items:
                    type: string
          nullable: true
        metadata:
          $ref: '#/components/schemas/Metadata'
      required:
        - id
        - object
        - created_at
        - tool_resources
        - metadata
      x-oaiMeta:
        name: The thread object
        beta: true
        example: |
          {
            "id": "thread_abc123",
            "object": "thread",
            "created_at": 1698107661,
            "metadata": {}
          }
    ThreadStreamEvent:
      oneOf:
        - type: object
          properties:
            enabled:
              type: boolean
              description: Whether to enable input audio transcription.
            event:
              type: string
              enum:
                - thread.created
              x-stainless-const: true
            data:
              $ref: '#/components/schemas/ThreadObject'
          required:
            - event
            - data
          description: Occurs when a new [thread](/docs/api-reference/threads/object) is created.
          x-oaiMeta:
            dataDescription: '`data` is a [thread](/docs/api-reference/threads/object)'
    ToggleCertificatesRequest:
      type: object
      properties:
        certificate_ids:
          type: array
          items:
            type: string
            example: cert_abc
          minItems: 1
          maxItems: 10
      required:
        - certificate_ids
    Tool:
      description: |
        A tool that can be used to generate a response.
      discriminator:
        propertyName: type
      oneOf:
        - $ref: '#/components/schemas/FunctionTool'
        - $ref: '#/components/schemas/FileSearchTool'
        - $ref: '#/components/schemas/WebSearchPreviewTool'
        - $ref: '#/components/schemas/ComputerUsePreviewTool'
        - $ref: '#/components/schemas/MCPTool'
        - $ref: '#/components/schemas/CodeInterpreterTool'
        - $ref: '#/components/schemas/ImageGenTool'
        - $ref: '#/components/schemas/LocalShellTool'
    ToolChoiceFunction:
      type: object
      title: Function tool
      description: |
        Use this option to force the model to call a specific function.
      properties:
        type:
          type: string
          enum:
            - function
          description: For function calling, the type is always `function`.
          x-stainless-const: true
        name:
          type: string
          description: The name of the function to call.
      required:
        - type
        - name
    ToolChoiceOptions:
      type: string
      title: Tool choice mode
      description: |
        Controls which (if any) tool is called by the model.

        `none` means the model will not call any tool and instead generates a message.

        `auto` means the model can pick between generating a message or calling one or
        more tools.

        `required` means the model must call one or more tools.
      enum:
        - none
        - auto
        - required
    ToolChoiceTypes:
      type: object
      title: Hosted tool
      description: |
        Indicates that the model should use a built-in tool to generate a response.
        [Learn more about built-in tools](/docs/guides/tools).
      properties:
        type:
          type: string
          description: |
            The type of hosted tool the model should to use. Learn more about
            [built-in tools](/docs/guides/tools).

            Allowed values are:
            - `file_search`
            - `web_search_preview`
            - `computer_use_preview`
            - `code_interpreter`
            - `mcp`
            - `image_generation`
          enum:
            - file_search
            - web_search_preview
            - computer_use_preview
            - web_search_preview_2025_03_11
            - image_generation
            - code_interpreter
            - mcp
      required:
        - type
    TranscriptTextDeltaEvent:
      type: object
      description: >-
        Emitted when there is an additional text delta. This is also the first event emitted when the
        transcription starts. Only emitted when you [create a
        transcription](/docs/api-reference/audio/create-transcription) with the `Stream` parameter set to
        `true`.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `transcript.text.delta`.
          enum:
            - transcript.text.delta
          x-stainless-const: true
        delta:
          type: string
          description: |
            The text delta that was additionally transcribed.
        logprobs:
          type: array
          description: >
            The log probabilities of the delta. Only included if you [create a
            transcription](/docs/api-reference/audio/create-transcription) with the `include[]` parameter set
            to `logprobs`.
          items:
            type: object
            properties:
              token:
                type: string
                description: |
                  The token that was used to generate the log probability.
              logprob:
                type: number
                description: |
                  The log probability of the token.
              bytes:
                type: array
                items:
                  type: integer
                description: |
                  The bytes that were used to generate the log probability.
      required:
        - type
        - delta
      x-oaiMeta:
        name: Stream Event (transcript.text.delta)
        group: transcript
        example: |
          {
            "type": "transcript.text.delta",
            "delta": " wonderful"
          }
    TranscriptTextDoneEvent:
      type: object
      description: >-
        Emitted when the transcription is complete. Contains the complete transcription text. Only emitted
        when you [create a transcription](/docs/api-reference/audio/create-transcription) with the `Stream`
        parameter set to `true`.
      properties:
        type:
          type: string
          description: |
            The type of the event. Always `transcript.text.done`.
          enum:
            - transcript.text.done
          x-stainless-const: true
        text:
          type: string
          description: |
            The text that was transcribed.
        logprobs:
          type: array
          description: >
            The log probabilities of the individual tokens in the transcription. Only included if you [create
            a transcription](/docs/api-reference/audio/create-transcription) with the `include[]` parameter
            set to `logprobs`.
          items:
            type: object
            properties:
              token:
                type: string
                description: |
                  The token that was used to generate the log probability.
              logprob:
                type: number
                description: |
                  The log probability of the token.
              bytes:
                type: array
                items:
                  type: integer
                description: |
                  The bytes that were used to generate the log probability.
      required:
        - type
        - text
      x-oaiMeta:
        name: Stream Event (transcript.text.done)
        group: transcript
        example: |
          {
            "type": "transcript.text.done",
            "text": "I see skies of blue and clouds of white, the bright blessed days, the dark sacred nights, and I think to myself, what a wonderful world."
          }
    TranscriptionChunkingStrategy:
      type: object
      description: |-
        Controls how the audio is cut into chunks. When set to `"auto"`, the
        server first normalizes loudness and then uses voice activity detection (VAD) to
        choose boundaries. `server_vad` object can be provided to tweak VAD detection
        parameters manually. If unset, the audio is transcribed as a single block. 
      oneOf:
        - type: string
          enum:
            - auto
          default:
            - auto
          description: |
            Automatically set chunking parameters based on the audio. Must be set to `"auto"`.
          x-stainless-const: true
        - $ref: '#/components/schemas/VadConfig'
    TranscriptionInclude:
      type: string
      enum:
        - logprobs
      default: []
    TranscriptionSegment:
      type: object
      properties:
        id:
          type: integer
          description: Unique identifier of the segment.
        seek:
          type: integer
          description: Seek offset of the segment.
        start:
          type: number
          format: float
          description: Start time of the segment in seconds.
        end:
          type: number
          format: float
          description: End time of the segment in seconds.
        text:
          type: string
          description: Text content of the segment.
        tokens:
          type: array
          items:
            type: integer
          description: Array of token IDs for the text content.
        temperature:
          type: number
          format: float
          description: Temperature parameter used for generating the segment.
        avg_logprob:
          type: number
          format: float
          description: Average logprob of the segment. If the value is lower than -1, consider the logprobs failed.
        compression_ratio:
          type: number
          format: float
          description: >-
            Compression ratio of the segment. If the value is greater than 2.4, consider the compression
            failed.
        no_speech_prob:
          type: number
          format: float
          description: >-
            Probability of no speech in the segment. If the value is higher than 1.0 and the `avg_logprob` is
            below -1, consider this segment silent.
      required:
        - id
        - seek
        - start
        - end
        - text
        - tokens
        - temperature
        - avg_logprob
        - compression_ratio
        - no_speech_prob
    TranscriptionWord:
      type: object
      properties:
        word:
          type: string
          description: The text content of the word.
        start:
          type: number
          format: float
          description: Start time of the word in seconds.
        end:
          type: number
          format: float
          description: End time of the word in seconds.
      required:
        - word
        - start
        - end
    TruncationObject:
      type: object
      title: Thread Truncation Controls
      description: >-
        Controls for how a thread will be truncated prior to the run. Use this to control the intial context
        window of the run.
      properties:
        type:
          type: string
          description: >-
            The truncation strategy to use for the thread. The default is `auto`. If set to `last_messages`,
            the thread will be truncated to the n most recent messages in the thread. When set to `auto`,
            messages in the middle of the thread will be dropped to fit the context length of the model,
            `max_prompt_tokens`.
          enum:
            - auto
            - last_messages
        last_messages:
          type: integer
          description: The number of most recent messages from the thread when constructing the context for the run.
          minimum: 1
          nullable: true
      required:
        - type
    Type:
      type: object
      title: Type
      description: |
        An action to type in text.
      properties:
        type:
          type: string
          enum:
            - type
          default: type
          description: |
            Specifies the event type. For a type action, this property is 
            always set to `type`.
          x-stainless-const: true
        text:
          type: string
          description: |
            The text to type.
      required:
        - type
        - text
    UpdateVectorStoreFileAttributesRequest:
      type: object
      additionalProperties: false
      properties:
        attributes:
          $ref: '#/components/schemas/VectorStoreFileAttributes'
      required:
        - attributes
      x-oaiMeta:
        name: Update vector store file attributes request
    UpdateVectorStoreRequest:
      type: object
      additionalProperties: false
      properties:
        name:
          description: The name of the vector store.
          type: string
          nullable: true
        expires_after:
          allOf:
            - $ref: '#/components/schemas/VectorStoreExpirationAfter'
            - nullable: true
        metadata:
          $ref: '#/components/schemas/Metadata'
    Upload:
      type: object
      title: Upload
      description: |
        The Upload object can accept byte chunks in the form of Parts.
      properties:
        id:
          type: string
          description: The Upload unique identifier, which can be referenced in API endpoints.
        created_at:
          type: integer
          description: The Unix timestamp (in seconds) for when the Upload was created.
        filename:
          type: string
          description: The name of the file to be uploaded.
        bytes:
          type: integer
          description: The intended number of bytes to be uploaded.
        purpose:
          type: string
          description: >-
            The intended purpose of the file. [Please refer
            here](/docs/api-reference/files/object#files/object-purpose) for acceptable values.
        status:
          type: string
          description: The status of the Upload.
          enum:
            - pending
            - completed
            - cancelled
            - expired
        expires_at:
          type: integer
          description: The Unix timestamp (in seconds) for when the Upload will expire.
        object:
          type: string
          description: The object type, which is always "upload".
          enum:
            - upload
          x-stainless-const: true
        file:
          allOf:
            - $ref: '#/components/schemas/OpenAIFile'
            - nullable: true
              description: The ready File object after the Upload is completed.
      required:
        - bytes
        - created_at
        - expires_at
        - filename
        - id
        - purpose
        - status
      x-oaiMeta:
        name: The upload object
        example: |
          {
            "id": "upload_abc123",
            "object": "upload",
            "bytes": 2147483648,
            "created_at": 1719184911,
            "filename": "training_examples.jsonl",
            "purpose": "fine-tune",
            "status": "completed",
            "expires_at": 1719127296,
            "file": {
              "id": "file-xyz321",
              "object": "file",
              "bytes": 2147483648,
              "created_at": 1719186911,
              "filename": "training_examples.jsonl",
              "purpose": "fine-tune",
            }
          }
    UploadCertificateRequest:
      type: object
      properties:
        name:
          type: string
          description: An optional name for the certificate
        content:
          type: string
          description: The certificate content in PEM format
      required:
        - content
    UploadPart:
      type: object
      title: UploadPart
      description: |
        The upload Part represents a chunk of bytes we can add to an Upload object.
      properties:
        id:
          type: string
          description: The upload Part unique identifier, which can be referenced in API endpoints.
        created_at:
          type: integer
          description: The Unix timestamp (in seconds) for when the Part was created.
        upload_id:
          type: string
          description: The ID of the Upload object that this Part was added to.
        object:
          type: string
          description: The object type, which is always `upload.part`.
          enum:
            - upload.part
          x-stainless-const: true
      required:
        - created_at
        - id
        - object
        - upload_id
      x-oaiMeta:
        name: The upload part object
        example: |
          {
              "id": "part_def456",
              "object": "upload.part",
              "created_at": 1719186911,
              "upload_id": "upload_abc123"
          }
    UsageAudioSpeechesResult:
      type: object
      description: The aggregated audio speeches usage details of the specific time bucket.
      properties:
        object:
          type: string
          enum:
            - organization.usage.audio_speeches.result
          x-stainless-const: true
        characters:
          type: integer
          description: The number of characters processed.
        num_model_requests:
          type: integer
          description: The count of requests made to the model.
        project_id:
          type: string
          nullable: true
          description: When `group_by=project_id`, this field provides the project ID of the grouped usage result.
        user_id:
          type: string
          nullable: true
          description: When `group_by=user_id`, this field provides the user ID of the grouped usage result.
        api_key_id:
          type: string
          nullable: true
          description: When `group_by=api_key_id`, this field provides the API key ID of the grouped usage result.
        model:
          type: string
          nullable: true
          description: When `group_by=model`, this field provides the model name of the grouped usage result.
      required:
        - object
        - characters
        - num_model_requests
      x-oaiMeta:
        name: Audio speeches usage object
        example: |
          {
              "object": "organization.usage.audio_speeches.result",
              "characters": 45,
              "num_model_requests": 1,
              "project_id": "proj_abc",
              "user_id": "user-abc",
              "api_key_id": "key_abc",
              "model": "tts-1"
          }
    UsageAudioTranscriptionsResult:
      type: object
      description: The aggregated audio transcriptions usage details of the specific time bucket.
      properties:
        object:
          type: string
          enum:
            - organization.usage.audio_transcriptions.result
          x-stainless-const: true
        seconds:
          type: integer
          description: The number of seconds processed.
        num_model_requests:
          type: integer
          description: The count of requests made to the model.
        project_id:
          type: string
          nullable: true
          description: When `group_by=project_id`, this field provides the project ID of the grouped usage result.
        user_id:
          type: string
          nullable: true
          description: When `group_by=user_id`, this field provides the user ID of the grouped usage result.
        api_key_id:
          type: string
          nullable: true
          description: When `group_by=api_key_id`, this field provides the API key ID of the grouped usage result.
        model:
          type: string
          nullable: true
          description: When `group_by=model`, this field provides the model name of the grouped usage result.
      required:
        - object
        - seconds
        - num_model_requests
      x-oaiMeta:
        name: Audio transcriptions usage object
        example: |
          {
              "object": "organization.usage.audio_transcriptions.result",
              "seconds": 10,
              "num_model_requests": 1,
              "project_id": "proj_abc",
              "user_id": "user-abc",
              "api_key_id": "key_abc",
              "model": "tts-1"
          }
    UsageCodeInterpreterSessionsResult:
      type: object
      description: The aggregated code interpreter sessions usage details of the specific time bucket.
      properties:
        object:
          type: string
          enum:
            - organization.usage.code_interpreter_sessions.result
          x-stainless-const: true
        num_sessions:
          type: integer
          description: The number of code interpreter sessions.
        project_id:
          type: string
          nullable: true
          description: When `group_by=project_id`, this field provides the project ID of the grouped usage result.
      required:
        - object
        - sessions
      x-oaiMeta:
        name: Code interpreter sessions usage object
        example: |
          {
              "object": "organization.usage.code_interpreter_sessions.result",
              "num_sessions": 1,
              "project_id": "proj_abc"
          }
    UsageCompletionsResult:
      type: object
      description: The aggregated completions usage details of the specific time bucket.
      properties:
        object:
          type: string
          enum:
            - organization.usage.completions.result
          x-stainless-const: true
        input_tokens:
          type: integer
          description: >-
            The aggregated number of text input tokens used, including cached tokens. For customers subscribe
            to scale tier, this includes scale tier tokens.
        input_cached_tokens:
          type: integer
          description: >-
            The aggregated number of text input tokens that has been cached from previous requests. For
            customers subscribe to scale tier, this includes scale tier tokens.
        output_tokens:
          type: integer
          description: >-
            The aggregated number of text output tokens used. For customers subscribe to scale tier, this
            includes scale tier tokens.
        input_audio_tokens:
          type: integer
          description: The aggregated number of audio input tokens used, including cached tokens.
        output_audio_tokens:
          type: integer
          description: The aggregated number of audio output tokens used.
        num_model_requests:
          type: integer
          description: The count of requests made to the model.
        project_id:
          type: string
          nullable: true
          description: When `group_by=project_id`, this field provides the project ID of the grouped usage result.
        user_id:
          type: string
          nullable: true
          description: When `group_by=user_id`, this field provides the user ID of the grouped usage result.
        api_key_id:
          type: string
          nullable: true
          description: When `group_by=api_key_id`, this field provides the API key ID of the grouped usage result.
        model:
          type: string
          nullable: true
          description: When `group_by=model`, this field provides the model name of the grouped usage result.
        batch:
          type: boolean
          nullable: true
          description: When `group_by=batch`, this field tells whether the grouped usage result is batch or not.
      required:
        - object
        - input_tokens
        - output_tokens
        - num_model_requests
      x-oaiMeta:
        name: Completions usage object
        example: |
          {
              "object": "organization.usage.completions.result",
              "input_tokens": 5000,
              "output_tokens": 1000,
              "input_cached_tokens": 4000,
              "input_audio_tokens": 300,
              "output_audio_tokens": 200,
              "num_model_requests": 5,
              "project_id": "proj_abc",
              "user_id": "user-abc",
              "api_key_id": "key_abc",
              "model": "gpt-4o-mini-2024-07-18",
              "batch": false
          }
    UsageEmbeddingsResult:
      type: object
      description: The aggregated embeddings usage details of the specific time bucket.
      properties:
        object:
          type: string
          enum:
            - organization.usage.embeddings.result
          x-stainless-const: true
        input_tokens:
          type: integer
          description: The aggregated number of input tokens used.
        num_model_requests:
          type: integer
          description: The count of requests made to the model.
        project_id:
          type: string
          nullable: true
          description: When `group_by=project_id`, this field provides the project ID of the grouped usage result.
        user_id:
          type: string
          nullable: true
          description: When `group_by=user_id`, this field provides the user ID of the grouped usage result.
        api_key_id:
          type: string
          nullable: true
          description: When `group_by=api_key_id`, this field provides the API key ID of the grouped usage result.
        model:
          type: string
          nullable: true
          description: When `group_by=model`, this field provides the model name of the grouped usage result.
      required:
        - object
        - input_tokens
        - num_model_requests
      x-oaiMeta:
        name: Embeddings usage object
        example: |
          {
              "object": "organization.usage.embeddings.result",
              "input_tokens": 20,
              "num_model_requests": 2,
              "project_id": "proj_abc",
              "user_id": "user-abc",
              "api_key_id": "key_abc",
              "model": "text-embedding-ada-002-v2"
          }
    UsageImagesResult:
      type: object
      description: The aggregated images usage details of the specific time bucket.
      properties:
        object:
          type: string
          enum:
            - organization.usage.images.result
          x-stainless-const: true
        images:
          type: integer
          description: The number of images processed.
        num_model_requests:
          type: integer
          description: The count of requests made to the model.
        source:
          type: string
          nullable: true
          description: >-
            When `group_by=source`, this field provides the source of the grouped usage result, possible
            values are `image.generation`, `image.edit`, `image.variation`.
        size:
          type: string
          nullable: true
          description: When `group_by=size`, this field provides the image size of the grouped usage result.
        project_id:
          type: string
          nullable: true
          description: When `group_by=project_id`, this field provides the project ID of the grouped usage result.
        user_id:
          type: string
          nullable: true
          description: When `group_by=user_id`, this field provides the user ID of the grouped usage result.
        api_key_id:
          type: string
          nullable: true
          description: When `group_by=api_key_id`, this field provides the API key ID of the grouped usage result.
        model:
          type: string
          nullable: true
          description: When `group_by=model`, this field provides the model name of the grouped usage result.
      required:
        - object
        - images
        - num_model_requests
      x-oaiMeta:
        name: Images usage object
        example: |
          {
              "object": "organization.usage.images.result",
              "images": 2,
              "num_model_requests": 2,
              "size": "1024x1024",
              "source": "image.generation",
              "project_id": "proj_abc",
              "user_id": "user-abc",
              "api_key_id": "key_abc",
              "model": "dall-e-3"
          }
    UsageModerationsResult:
      type: object
      description: The aggregated moderations usage details of the specific time bucket.
      properties:
        object:
          type: string
          enum:
            - organization.usage.moderations.result
          x-stainless-const: true
        input_tokens:
          type: integer
          description: The aggregated number of input tokens used.
        num_model_requests:
          type: integer
          description: The count of requests made to the model.
        project_id:
          type: string
          nullable: true
          description: When `group_by=project_id`, this field provides the project ID of the grouped usage result.
        user_id:
          type: string
          nullable: true
          description: When `group_by=user_id`, this field provides the user ID of the grouped usage result.
        api_key_id:
          type: string
          nullable: true
          description: When `group_by=api_key_id`, this field provides the API key ID of the grouped usage result.
        model:
          type: string
          nullable: true
          description: When `group_by=model`, this field provides the model name of the grouped usage result.
      required:
        - object
        - input_tokens
        - num_model_requests
      x-oaiMeta:
        name: Moderations usage object
        example: |
          {
              "object": "organization.usage.moderations.result",
              "input_tokens": 20,
              "num_model_requests": 2,
              "project_id": "proj_abc",
              "user_id": "user-abc",
              "api_key_id": "key_abc",
              "model": "text-moderation"
          }
    UsageResponse:
      type: object
      properties:
        object:
          type: string
          enum:
            - page
          x-stainless-const: true
        data:
          type: array
          items:
            $ref: '#/components/schemas/UsageTimeBucket'
        has_more:
          type: boolean
        next_page:
          type: string
      required:
        - object
        - data
        - has_more
        - next_page
    UsageTimeBucket:
      type: object
      properties:
        object:
          type: string
          enum:
            - bucket
          x-stainless-const: true
        start_time:
          type: integer
        end_time:
          type: integer
        result:
          type: array
          items:
            oneOf:
              - $ref: '#/components/schemas/UsageCompletionsResult'
              - $ref: '#/components/schemas/UsageEmbeddingsResult'
              - $ref: '#/components/schemas/UsageModerationsResult'
              - $ref: '#/components/schemas/UsageImagesResult'
              - $ref: '#/components/schemas/UsageAudioSpeechesResult'
              - $ref: '#/components/schemas/UsageAudioTranscriptionsResult'
              - $ref: '#/components/schemas/UsageVectorStoresResult'
              - $ref: '#/components/schemas/UsageCodeInterpreterSessionsResult'
              - $ref: '#/components/schemas/CostsResult'
      required:
        - object
        - start_time
        - end_time
        - result
    UsageVectorStoresResult:
      type: object
      description: The aggregated vector stores usage details of the specific time bucket.
      properties:
        object:
          type: string
          enum:
            - organization.usage.vector_stores.result
          x-stainless-const: true
        usage_bytes:
          type: integer
          description: The vector stores usage in bytes.
        project_id:
          type: string
          nullable: true
          description: When `group_by=project_id`, this field provides the project ID of the grouped usage result.
      required:
        - object
        - usage_bytes
      x-oaiMeta:
        name: Vector stores usage object
        example: |
          {
              "object": "organization.usage.vector_stores.result",
              "usage_bytes": 1024,
              "project_id": "proj_abc"
          }
    User:
      type: object
      description: Represents an individual `user` within an organization.
      properties:
        object:
          type: string
          enum:
            - organization.user
          description: The object type, which is always `organization.user`
          x-stainless-const: true
        id:
          type: string
          description: The identifier, which can be referenced in API endpoints
        name:
          type: string
          description: The name of the user
        email:
          type: string
          description: The email address of the user
        role:
          type: string
          enum:
            - owner
            - reader
          description: '`owner` or `reader`'
        added_at:
          type: integer
          description: The Unix timestamp (in seconds) of when the user was added.
      required:
        - object
        - id
        - name
        - email
        - role
        - added_at
      x-oaiMeta:
        name: The user object
        example: |
          {
              "object": "organization.user",
              "id": "user_abc",
              "name": "First Last",
              "email": "user@example.com",
              "role": "owner",
              "added_at": 1711471533
          }
    UserDeleteResponse:
      type: object
      properties:
        object:
          type: string
          enum:
            - organization.user.deleted
          x-stainless-const: true
        id:
          type: string
        deleted:
          type: boolean
      required:
        - object
        - id
        - deleted
    UserListResponse:
      type: object
      properties:
        object:
          type: string
          enum:
            - list
          x-stainless-const: true
        data:
          type: array
          items:
            $ref: '#/components/schemas/User'
        first_id:
          type: string
        last_id:
          type: string
        has_more:
          type: boolean
      required:
        - object
        - data
        - first_id
        - last_id
        - has_more
    UserRoleUpdateRequest:
      type: object
      properties:
        role:
          type: string
          enum:
            - owner
            - reader
          description: '`owner` or `reader`'
      required:
        - role
    VadConfig:
      type: object
      additionalProperties: false
      required:
        - type
      properties:
        type:
          type: string
          enum:
            - server_vad
          description: Must be set to `server_vad` to enable manual chunking using server side VAD.
        prefix_padding_ms:
          type: integer
          default: 300
          description: |
            Amount of audio to include before the VAD detected speech (in 
            milliseconds).
        silence_duration_ms:
          type: integer
          default: 200
          description: |
            Duration of silence to detect speech stop (in milliseconds).
            With shorter values the model will respond more quickly, 
            but may jump in on short pauses from the user.
        threshold:
          type: number
          default: 0.5
          description: |
            Sensitivity threshold (0.0 to 1.0) for voice activity detection. A 
            higher threshold will require louder audio to activate the model, and 
            thus might perform better in noisy environments.
    ValidateGraderRequest:
      type: object
      title: ValidateGraderRequest
      properties:
        grader:
          type: object
          description: The grader used for the fine-tuning job.
          oneOf:
            - $ref: '#/components/schemas/GraderStringCheck'
            - $ref: '#/components/schemas/GraderTextSimilarity'
            - $ref: '#/components/schemas/GraderPython'
            - $ref: '#/components/schemas/GraderScoreModel'
            - $ref: '#/components/schemas/GraderMulti'
      required:
        - grader
    ValidateGraderResponse:
      type: object
      title: ValidateGraderResponse
      properties:
        grader:
          type: object
          description: The grader used for the fine-tuning job.
          oneOf:
            - $ref: '#/components/schemas/GraderStringCheck'
            - $ref: '#/components/schemas/GraderTextSimilarity'
            - $ref: '#/components/schemas/GraderPython'
            - $ref: '#/components/schemas/GraderScoreModel'
            - $ref: '#/components/schemas/GraderMulti'
    VectorStoreExpirationAfter:
      type: object
      title: Vector store expiration policy
      description: The expiration policy for a vector store.
      properties:
        anchor:
          description: 'Anchor timestamp after which the expiration policy applies. Supported anchors: `last_active_at`.'
          type: string
          enum:
            - last_active_at
          x-stainless-const: true
        days:
          description: The number of days after the anchor time that the vector store will expire.
          type: integer
          minimum: 1
          maximum: 365
      required:
        - anchor
        - days
    VectorStoreFileAttributes:
      type: object
      description: |
        Set of 16 key-value pairs that can be attached to an object. This can be 
        useful for storing additional information about the object in a structured 
        format, and querying for objects via API or the dashboard. Keys are strings 
        with a maximum length of 64 characters. Values are strings with a maximum 
        length of 512 characters, booleans, or numbers.
      maxProperties: 16
      propertyNames:
        type: string
        maxLength: 64
      additionalProperties:
        oneOf:
          - type: string
            maxLength: 512
          - type: number
          - type: boolean
      x-oaiTypeLabel: map
      nullable: true
    VectorStoreFileBatchObject:
      type: object
      title: Vector store file batch
      description: A batch of files attached to a vector store.
      properties:
        id:
          description: The identifier, which can be referenced in API endpoints.
          type: string
        object:
          description: The object type, which is always `vector_store.file_batch`.
          type: string
          enum:
            - vector_store.files_batch
          x-stainless-const: true
        created_at:
          description: The Unix timestamp (in seconds) for when the vector store files batch was created.
          type: integer
        vector_store_id:
          description: >-
            The ID of the [vector store](/docs/api-reference/vector-stores/object) that the
            [File](/docs/api-reference/files) is attached to.
          type: string
        status:
          description: >-
            The status of the vector store files batch, which can be either `in_progress`, `completed`,
            `cancelled` or `failed`.
          type: string
          enum:
            - in_progress
            - completed
            - cancelled
            - failed
        file_counts:
          type: object
          properties:
            in_progress:
              description: The number of files that are currently being processed.
              type: integer
            completed:
              description: The number of files that have been processed.
              type: integer
            failed:
              description: The number of files that have failed to process.
              type: integer
            cancelled:
              description: The number of files that where cancelled.
              type: integer
            total:
              description: The total number of files.
              type: integer
          required:
            - in_progress
            - completed
            - cancelled
            - failed
            - total
      required:
        - id
        - object
        - created_at
        - vector_store_id
        - status
        - file_counts
      x-oaiMeta:
        name: The vector store files batch object
        beta: true
        example: |
          {
            "id": "vsfb_123",
            "object": "vector_store.files_batch",
            "created_at": 1698107661,
            "vector_store_id": "vs_abc123",
            "status": "completed",
            "file_counts": {
              "in_progress": 0,
              "completed": 100,
              "failed": 0,
              "cancelled": 0,
              "total": 100
            }
          }
    VectorStoreFileContentResponse:
      type: object
      description: Represents the parsed content of a vector store file.
      properties:
        object:
          type: string
          enum:
            - vector_store.file_content.page
          description: The object type, which is always `vector_store.file_content.page`
          x-stainless-const: true
        data:
          type: array
          description: Parsed content of the file.
          items:
            type: object
            properties:
              type:
                type: string
                description: The content type (currently only `"text"`)
              text:
                type: string
                description: The text content
        has_more:
          type: boolean
          description: Indicates if there are more content pages to fetch.
        next_page:
          type: string
          description: The token for the next page, if any.
          nullable: true
      required:
        - object
        - data
        - has_more
        - next_page
    VectorStoreFileObject:
      type: object
      title: Vector store files
      description: A list of files attached to a vector store.
      properties:
        id:
          description: The identifier, which can be referenced in API endpoints.
          type: string
        object:
          description: The object type, which is always `vector_store.file`.
          type: string
          enum:
            - vector_store.file
          x-stainless-const: true
        usage_bytes:
          description: >-
            The total vector store usage in bytes. Note that this may be different from the original file
            size.
          type: integer
        created_at:
          description: The Unix timestamp (in seconds) for when the vector store file was created.
          type: integer
        vector_store_id:
          description: >-
            The ID of the [vector store](/docs/api-reference/vector-stores/object) that the
            [File](/docs/api-reference/files) is attached to.
          type: string
        status:
          description: >-
            The status of the vector store file, which can be either `in_progress`, `completed`, `cancelled`,
            or `failed`. The status `completed` indicates that the vector store file is ready for use.
          type: string
          enum:
            - in_progress
            - completed
            - cancelled
            - failed
        last_error:
          type: object
          description: The last error associated with this vector store file. Will be `null` if there are no errors.
          nullable: true
          properties:
            code:
              type: string
              description: One of `server_error` or `rate_limit_exceeded`.
              enum:
                - server_error
                - unsupported_file
                - invalid_file
            message:
              type: string
              description: A human-readable description of the error.
          required:
            - code
            - message
        chunking_strategy:
          type: object
          description: The strategy used to chunk the file.
          oneOf:
            - $ref: '#/components/schemas/StaticChunkingStrategyResponseParam'
            - $ref: '#/components/schemas/OtherChunkingStrategyResponseParam'
        attributes:
          $ref: '#/components/schemas/VectorStoreFileAttributes'
      required:
        - id
        - object
        - usage_bytes
        - created_at
        - vector_store_id
        - status
        - last_error
      x-oaiMeta:
        name: The vector store file object
        beta: true
        example: |
          {
            "id": "file-abc123",
            "object": "vector_store.file",
            "usage_bytes": 1234,
            "created_at": 1698107661,
            "vector_store_id": "vs_abc123",
            "status": "completed",
            "last_error": null,
            "chunking_strategy": {
              "type": "static",
              "static": {
                "max_chunk_size_tokens": 800,
                "chunk_overlap_tokens": 400
              }
            }
          }
    VectorStoreObject:
      type: object
      title: Vector store
      description: A vector store is a collection of processed files can be used by the `file_search` tool.
      properties:
        id:
          description: The identifier, which can be referenced in API endpoints.
          type: string
        object:
          description: The object type, which is always `vector_store`.
          type: string
          enum:
            - vector_store
          x-stainless-const: true
        created_at:
          description: The Unix timestamp (in seconds) for when the vector store was created.
          type: integer
        name:
          description: The name of the vector store.
          type: string
        usage_bytes:
          description: The total number of bytes used by the files in the vector store.
          type: integer
        file_counts:
          type: object
          properties:
            in_progress:
              description: The number of files that are currently being processed.
              type: integer
            completed:
              description: The number of files that have been successfully processed.
              type: integer
            failed:
              description: The number of files that have failed to process.
              type: integer
            cancelled:
              description: The number of files that were cancelled.
              type: integer
            total:
              description: The total number of files.
              type: integer
          required:
            - in_progress
            - completed
            - failed
            - cancelled
            - total
        status:
          description: >-
            The status of the vector store, which can be either `expired`, `in_progress`, or `completed`. A
            status of `completed` indicates that the vector store is ready for use.
          type: string
          enum:
            - expired
            - in_progress
            - completed
        expires_after:
          $ref: '#/components/schemas/VectorStoreExpirationAfter'
        expires_at:
          description: The Unix timestamp (in seconds) for when the vector store will expire.
          type: integer
          nullable: true
        last_active_at:
          description: The Unix timestamp (in seconds) for when the vector store was last active.
          type: integer
          nullable: true
        metadata:
          $ref: '#/components/schemas/Metadata'
      required:
        - id
        - object
        - usage_bytes
        - created_at
        - status
        - last_active_at
        - name
        - file_counts
        - metadata
      x-oaiMeta:
        name: The vector store object
        example: |
          {
            "id": "vs_123",
            "object": "vector_store",
            "created_at": 1698107661,
            "usage_bytes": 123456,
            "last_active_at": 1698107661,
            "name": "my_vector_store",
            "status": "completed",
            "file_counts": {
              "in_progress": 0,
              "completed": 100,
              "cancelled": 0,
              "failed": 0,
              "total": 100
            },
            "last_used_at": 1698107661
          }
    VectorStoreSearchRequest:
      type: object
      additionalProperties: false
      properties:
        query:
          description: A query string for a search
          oneOf:
            - type: string
            - type: array
              items:
                type: string
                description: A list of queries to search for.
                minItems: 1
        rewrite_query:
          description: Whether to rewrite the natural language query for vector search.
          type: boolean
          default: false
        max_num_results:
          description: The maximum number of results to return. This number should be between 1 and 50 inclusive.
          type: integer
          default: 10
          minimum: 1
          maximum: 50
        filters:
          description: A filter to apply based on file attributes.
          oneOf:
            - $ref: '#/components/schemas/ComparisonFilter'
            - $ref: '#/components/schemas/CompoundFilter'
        ranking_options:
          description: Ranking options for search.
          type: object
          additionalProperties: false
          properties:
            ranker:
              type: string
              enum:
                - auto
                - default-2024-11-15
              default: auto
            score_threshold:
              type: number
              minimum: 0
              maximum: 1
              default: 0
      required:
        - query
      x-oaiMeta:
        name: Vector store search request
    VectorStoreSearchResultContentObject:
      type: object
      additionalProperties: false
      properties:
        type:
          description: The type of content.
          type: string
          enum:
            - text
        text:
          description: The text content returned from search.
          type: string
      required:
        - type
        - text
      x-oaiMeta:
        name: Vector store search result content object
    VectorStoreSearchResultItem:
      type: object
      additionalProperties: false
      properties:
        file_id:
          type: string
          description: The ID of the vector store file.
        filename:
          type: string
          description: The name of the vector store file.
        score:
          type: number
          description: The similarity score for the result.
          minimum: 0
          maximum: 1
        attributes:
          $ref: '#/components/schemas/VectorStoreFileAttributes'
        content:
          type: array
          description: Content chunks from the file.
          items:
            $ref: '#/components/schemas/VectorStoreSearchResultContentObject'
      required:
        - file_id
        - filename
        - score
        - attributes
        - content
      x-oaiMeta:
        name: Vector store search result item
    VectorStoreSearchResultsPage:
      type: object
      additionalProperties: false
      properties:
        object:
          type: string
          enum:
            - vector_store.search_results.page
          description: The object type, which is always `vector_store.search_results.page`
          x-stainless-const: true
        search_query:
          type: array
          items:
            type: string
            description: The query used for this search.
            minItems: 1
        data:
          type: array
          description: The list of search result items.
          items:
            $ref: '#/components/schemas/VectorStoreSearchResultItem'
        has_more:
          type: boolean
          description: Indicates if there are more results to fetch.
        next_page:
          type: string
          description: The token for the next page, if any.
          nullable: true
      required:
        - object
        - search_query
        - data
        - has_more
        - next_page
      x-oaiMeta:
        name: Vector store search results page
    VoiceIdsShared:
      example: ash
      anyOf:
        - type: string
        - type: string
          enum:
            - alloy
            - ash
            - ballad
            - coral
            - echo
            - fable
            - onyx
            - nova
            - sage
            - shimmer
            - verse
    Wait:
      type: object
      title: Wait
      description: |
        A wait action.
      properties:
        type:
          type: string
          enum:
            - wait
          default: wait
          description: |
            Specifies the event type. For a wait action, this property is 
            always set to `wait`.
          x-stainless-const: true
      required:
        - type
    WebSearchContextSize:
      type: string
      description: |
        High level guidance for the amount of context window space to use for the 
        search. One of `low`, `medium`, or `high`. `medium` is the default.
      enum:
        - low
        - medium
        - high
      default: medium
    WebSearchLocation:
      type: object
      title: Web search location
      description: Approximate location parameters for the search.
      properties:
        country:
          type: string
          description: |
            The two-letter 
            [ISO country code](https://en.wikipedia.org/wiki/ISO_3166-1) of the user,
            e.g. `US`.
        region:
          type: string
          description: |
            Free text input for the region of the user, e.g. `California`.
        city:
          type: string
          description: |
            Free text input for the city of the user, e.g. `San Francisco`.
        timezone:
          type: string
          description: |
            The [IANA timezone](https://timeapi.io/documentation/iana-timezones) 
            of the user, e.g. `America/Los_Angeles`.
    WebSearchToolCall:
      type: object
      title: Web search tool call
      description: |
        The results of a web search tool call. See the 
        [web search guide](/docs/guides/tools-web-search) for more information.
      properties:
        id:
          type: string
          description: |
            The unique ID of the web search tool call.
        type:
          type: string
          enum:
            - web_search_call
          description: |
            The type of the web search tool call. Always `web_search_call`.
          x-stainless-const: true
        status:
          type: string
          description: |
            The status of the web search tool call.
          enum:
            - in_progress
            - searching
            - completed
            - failed
      required:
        - id
        - type
        - status
    InputTextContent:
      properties:
        type:
          type: string
          enum:
            - input_text
          description: The type of the input item. Always `input_text`.
          default: input_text
          x-stainless-const: true
        text:
          type: string
          description: The text input to the model.
      type: object
      required:
        - type
        - text
      title: Input text
      description: A text input to the model.
    InputImageContent:
      properties:
        type:
          type: string
          enum:
            - input_image
          description: The type of the input item. Always `input_image`.
          default: input_image
          x-stainless-const: true
        image_url:
          anyOf:
            - type: string
              description: >-
                The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in
                a data URL.
            - type: 'null'
        file_id:
          anyOf:
            - type: string
              description: The ID of the file to be sent to the model.
            - type: 'null'
        detail:
          type: string
          enum:
            - low
            - high
            - auto
          description: >-
            The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults
            to `auto`.
      type: object
      required:
        - type
        - detail
      title: Input image
      description: An image input to the model. Learn about [image inputs](/docs/guides/vision).
    InputFileContent:
      properties:
        type:
          type: string
          enum:
            - input_file
          description: The type of the input item. Always `input_file`.
          default: input_file
          x-stainless-const: true
        file_id:
          anyOf:
            - type: string
              description: The ID of the file to be sent to the model.
            - type: 'null'
        filename:
          type: string
          description: The name of the file to be sent to the model.
        file_data:
          type: string
          description: |
            The content of the file to be sent to the model.
      type: object
      required:
        - type
      title: Input file
      description: A file input to the model.
    FunctionTool:
      properties:
        type:
          type: string
          enum:
            - function
          description: The type of the function tool. Always `function`.
          default: function
          x-stainless-const: true
        name:
          type: string
          description: The name of the function to call.
        description:
          anyOf:
            - type: string
              description: >-
                A description of the function. Used by the model to determine whether or not to call the
                function.
            - type: 'null'
        parameters:
          anyOf:
            - additionalProperties: {}
              type: object
              description: A JSON schema object describing the parameters of the function.
            - type: 'null'
        strict:
          anyOf:
            - type: boolean
              description: Whether to enforce strict parameter validation. Default `true`.
            - type: 'null'
      type: object
      required:
        - type
        - name
        - strict
        - parameters
      title: Function
      description: >-
        Defines a function in your own code the model can choose to call. Learn more about [function
        calling](https://platform.openai.com/docs/guides/function-calling).
    RankingOptions:
      properties:
        ranker:
          type: string
          enum:
            - auto
            - default-2024-11-15
          description: The ranker to use for the file search.
        score_threshold:
          type: number
          description: >-
            The score threshold for the file search, a number between 0 and 1. Numbers closer to 1 will
            attempt to return only the most relevant results, but may return fewer results.
      type: object
      required: []
    Filters:
      anyOf:
        - $ref: '#/components/schemas/ComparisonFilter'
        - $ref: '#/components/schemas/CompoundFilter'
    FileSearchTool:
      properties:
        type:
          type: string
          enum:
            - file_search
          description: The type of the file search tool. Always `file_search`.
          default: file_search
          x-stainless-const: true
        vector_store_ids:
          items:
            type: string
          type: array
          description: The IDs of the vector stores to search.
        max_num_results:
          type: integer
          description: The maximum number of results to return. This number should be between 1 and 50 inclusive.
        ranking_options:
          $ref: '#/components/schemas/RankingOptions'
          description: Ranking options for search.
        filters:
          anyOf:
            - $ref: '#/components/schemas/Filters'
              description: A filter to apply.
            - type: 'null'
      type: object
      required:
        - type
        - vector_store_ids
      title: File search
      description: >-
        A tool that searches for relevant content from uploaded files. Learn more about the [file search
        tool](https://platform.openai.com/docs/guides/tools-file-search).
    ApproximateLocation:
      properties:
        type:
          type: string
          enum:
            - approximate
          description: The type of location approximation. Always `approximate`.
          default: approximate
          x-stainless-const: true
        country:
          anyOf:
            - type: string
              description: >-
                The two-letter [ISO country code](https://en.wikipedia.org/wiki/ISO_3166-1) of the user, e.g.
                `US`.
            - type: 'null'
        region:
          anyOf:
            - type: string
              description: Free text input for the region of the user, e.g. `California`.
            - type: 'null'
        city:
          anyOf:
            - type: string
              description: Free text input for the city of the user, e.g. `San Francisco`.
            - type: 'null'
        timezone:
          anyOf:
            - type: string
              description: >-
                The [IANA timezone](https://timeapi.io/documentation/iana-timezones) of the user, e.g.
                `America/Los_Angeles`.
            - type: 'null'
      type: object
      required:
        - type
    WebSearchPreviewTool:
      properties:
        type:
          type: string
          enum:
            - web_search_preview
            - web_search_preview_2025_03_11
          description: The type of the web search tool. One of `web_search_preview` or `web_search_preview_2025_03_11`.
          default: web_search_preview
          x-stainless-const: true
        user_location:
          anyOf:
            - $ref: '#/components/schemas/ApproximateLocation'
              description: The user's location.
            - type: 'null'
        search_context_size:
          type: string
          enum:
            - low
            - medium
            - high
          description: >-
            High level guidance for the amount of context window space to use for the search. One of `low`,
            `medium`, or `high`. `medium` is the default.
      type: object
      required:
        - type
      title: Web search preview
      description: >-
        This tool searches the web for relevant results to use in a response. Learn more about the [web search
        tool](https://platform.openai.com/docs/guides/tools-web-search).
    ComputerUsePreviewTool:
      properties:
        type:
          type: string
          enum:
            - computer_use_preview
          description: The type of the computer use tool. Always `computer_use_preview`.
          default: computer_use_preview
          x-stainless-const: true
        environment:
          type: string
          enum:
            - windows
            - mac
            - linux
            - ubuntu
            - browser
          description: The type of computer environment to control.
        display_width:
          type: integer
          description: The width of the computer display.
        display_height:
          type: integer
          description: The height of the computer display.
      type: object
      required:
        - type
        - environment
        - display_width
        - display_height
      title: Computer use preview
      description: >-
        A tool that controls a virtual computer. Learn more about the [computer
        tool](https://platform.openai.com/docs/guides/tools-computer-use).
    FileCitationBody:
      properties:
        type:
          type: string
          enum:
            - file_citation
          description: The type of the file citation. Always `file_citation`.
          default: file_citation
          x-stainless-const: true
        file_id:
          type: string
          description: The ID of the file.
        index:
          type: integer
          description: The index of the file in the list of files.
      type: object
      required:
        - type
        - file_id
        - index
      title: File citation
      description: A citation to a file.
    UrlCitationBody:
      properties:
        type:
          type: string
          enum:
            - url_citation
          description: The type of the URL citation. Always `url_citation`.
          default: url_citation
          x-stainless-const: true
        url:
          type: string
          description: The URL of the web resource.
        start_index:
          type: integer
          description: The index of the first character of the URL citation in the message.
        end_index:
          type: integer
          description: The index of the last character of the URL citation in the message.
        title:
          type: string
          description: The title of the web resource.
      type: object
      required:
        - type
        - url
        - start_index
        - end_index
        - title
      title: URL citation
      description: A citation for a web resource used to generate a model response.
    ContainerFileCitationBody:
      properties:
        type:
          type: string
          enum:
            - container_file_citation
          description: The type of the container file citation. Always `container_file_citation`.
          default: container_file_citation
          x-stainless-const: true
        container_id:
          type: string
          description: The ID of the container file.
        file_id:
          type: string
          description: The ID of the file.
        start_index:
          type: integer
          description: The index of the first character of the container file citation in the message.
        end_index:
          type: integer
          description: The index of the last character of the container file citation in the message.
      type: object
      required:
        - type
        - container_id
        - file_id
        - start_index
        - end_index
      title: Container file citation
      description: A citation for a container file used to generate a model response.
    Annotation:
      oneOf:
        - $ref: '#/components/schemas/FileCitationBody'
        - $ref: '#/components/schemas/UrlCitationBody'
        - $ref: '#/components/schemas/ContainerFileCitationBody'
        - $ref: '#/components/schemas/FilePath'
      discriminator:
        propertyName: type
    TopLogProb:
      properties:
        token:
          type: string
        logprob:
          type: number
        bytes:
          items:
            type: integer
          type: array
      type: object
      required:
        - token
        - logprob
        - bytes
      title: Top log probability
      description: The top log probability of a token.
    LogProb:
      properties:
        token:
          type: string
        logprob:
          type: number
        bytes:
          items:
            type: integer
          type: array
        top_logprobs:
          items:
            $ref: '#/components/schemas/TopLogProb'
          type: array
      type: object
      required:
        - token
        - logprob
        - bytes
        - top_logprobs
      title: Log probability
      description: The log probability of a token.
    OutputTextContent:
      properties:
        type:
          type: string
          enum:
            - output_text
          description: The type of the output text. Always `output_text`.
          default: output_text
          x-stainless-const: true
        text:
          type: string
          description: The text output from the model.
        annotations:
          items:
            $ref: '#/components/schemas/Annotation'
          type: array
          description: The annotations of the text output.
        logprobs:
          items:
            $ref: '#/components/schemas/LogProb'
          type: array
      type: object
      required:
        - type
        - text
        - annotations
      title: Output text
      description: A text output from the model.
    RefusalContent:
      properties:
        type:
          type: string
          enum:
            - refusal
          description: The type of the refusal. Always `refusal`.
          default: refusal
          x-stainless-const: true
        refusal:
          type: string
          description: The refusal explanationfrom the model.
      type: object
      required:
        - type
        - refusal
      title: Refusal
      description: A refusal from the model.
    ComputerCallSafetyCheckParam:
      properties:
        id:
          type: string
          description: The ID of the pending safety check.
        code:
          anyOf:
            - type: string
              description: The type of the pending safety check.
            - type: 'null'
        message:
          anyOf:
            - type: string
              description: Details about the pending safety check.
            - type: 'null'
      type: object
      required:
        - id
      description: A pending safety check for the computer call.
    ComputerCallOutputItemParam:
      properties:
        id:
          anyOf:
            - type: string
              description: The ID of the computer tool call output.
            - type: 'null'
        call_id:
          type: string
          maxLength: 64
          minLength: 1
          description: The ID of the computer tool call that produced the output.
        type:
          type: string
          enum:
            - computer_call_output
          description: The type of the computer tool call output. Always `computer_call_output`.
          default: computer_call_output
          x-stainless-const: true
        output:
          $ref: '#/components/schemas/ComputerScreenshotImage'
        acknowledged_safety_checks:
          anyOf:
            - items:
                $ref: '#/components/schemas/ComputerCallSafetyCheckParam'
              type: array
              description: The safety checks reported by the API that have been acknowledged by the developer.
            - type: 'null'
        status:
          anyOf:
            - type: string
              enum:
                - in_progress
                - completed
                - incomplete
              description: >-
                The status of the message input. One of `in_progress`, `completed`, or `incomplete`. Populated
                when input items are returned via API.
            - type: 'null'
      type: object
      required:
        - call_id
        - type
        - output
      title: Computer tool call output
      description: The output of a computer tool call.
    FunctionCallOutputItemParam:
      properties:
        id:
          anyOf:
            - type: string
              description: The unique ID of the function tool call output. Populated when this item is returned via API.
            - type: 'null'
        call_id:
          type: string
          maxLength: 64
          minLength: 1
          description: The unique ID of the function tool call generated by the model.
        type:
          type: string
          enum:
            - function_call_output
          description: The type of the function tool call output. Always `function_call_output`.
          default: function_call_output
          x-stainless-const: true
        output:
          type: string
          maxLength: 10485760
          description: A JSON string of the output of the function tool call.
        status:
          anyOf:
            - type: string
              enum:
                - in_progress
                - completed
                - incomplete
              description: >-
                The status of the item. One of `in_progress`, `completed`, or `incomplete`. Populated when
                items are returned via API.
            - type: 'null'
      type: object
      required:
        - call_id
        - type
        - output
      title: Function tool call output
      description: The output of a function tool call.
    ItemReferenceParam:
      properties:
        type:
          anyOf:
            - type: string
              enum:
                - item_reference
              description: The type of item to reference. Always `item_reference`.
              default: item_reference
              x-stainless-const: true
            - type: 'null'
        id:
          type: string
          description: The ID of the item to reference.
      type: object
      required:
        - id
      title: Item reference
      description: An internal identifier for an item to reference.
  securitySchemes:
    ApiKeyAuth:
      type: http
      scheme: bearer
x-oaiMeta:
  navigationGroups:
    - id: responses
      title: Responses
    - id: chat
      title: Chat Completions
    - id: realtime
      title: Realtime
      beta: true
    - id: endpoints
      title: Platform APIs
    - id: vector_stores
      title: Vector stores
    - id: containers
      title: Containers
    - id: assistants
      title: Assistants
      beta: true
    - id: administration
      title: Administration
    - id: legacy
      title: Legacy
  groups:
    - id: responses
      title: Responses
      description: |
        OpenAI's most advanced interface for generating model responses. Supports
        text and image inputs, and text outputs. Create stateful interactions
        with the model, using the output of previous responses as input. Extend
        the model's capabilities with built-in tools for file search, web search,
        computer use, and more. Allow the model access to external systems and data
        using function calling.

        Related guides:
        - [Quickstart](/docs/quickstart?api-mode=responses)
        - [Text inputs and outputs](/docs/guides/text?api-mode=responses)
        - [Image inputs](/docs/guides/images?api-mode=responses)
        - [Structured Outputs](/docs/guides/structured-outputs?api-mode=responses)
        - [Function calling](/docs/guides/function-calling?api-mode=responses)
        - [Conversation state](/docs/guides/conversation-state?api-mode=responses)
        - [Extend the models with tools](/docs/guides/tools?api-mode=responses)
      navigationGroup: responses
      sections:
        - type: endpoint
          key: createResponse
          path: create
        - type: endpoint
          key: getResponse
          path: get
        - type: endpoint
          key: deleteResponse
          path: delete
        - type: endpoint
          key: cancelResponse
          path: cancel
        - type: endpoint
          key: listInputItems
          path: input-items
        - type: object
          key: Response
          path: object
        - type: object
          key: ResponseItemList
          path: list
    - id: responses-streaming
      title: Streaming
      description: |
        When you [create a Response](/docs/api-reference/responses/create) with
        `stream` set to `true`, the server will emit server-sent events to the
        client as the Response is generated. This section contains the events that
        are emitted by the server.

        [Learn more about streaming responses](/docs/guides/streaming-responses?api-mode=responses).
      navigationGroup: responses
      sections:
        - type: object
          key: ResponseCreatedEvent
          path: <auto>
        - type: object
          key: ResponseInProgressEvent
          path: <auto>
        - type: object
          key: ResponseCompletedEvent
          path: <auto>
        - type: object
          key: ResponseFailedEvent
          path: <auto>
        - type: object
          key: ResponseIncompleteEvent
          path: <auto>
        - type: object
          key: ResponseOutputItemAddedEvent
          path: <auto>
        - type: object
          key: ResponseOutputItemDoneEvent
          path: <auto>
        - type: object
          key: ResponseContentPartAddedEvent
          path: <auto>
        - type: object
          key: ResponseContentPartDoneEvent
          path: <auto>
        - type: object
          key: ResponseTextDeltaEvent
          path: <auto>
        - type: object
          key: ResponseTextDoneEvent
          path: <auto>
        - type: object
          key: ResponseRefusalDeltaEvent
          path: <auto>
        - type: object
          key: ResponseRefusalDoneEvent
          path: <auto>
        - type: object
          key: ResponseFunctionCallArgumentsDeltaEvent
          path: <auto>
        - type: object
          key: ResponseFunctionCallArgumentsDoneEvent
          path: <auto>
        - type: object
          key: ResponseFileSearchCallInProgressEvent
          path: <auto>
        - type: object
          key: ResponseFileSearchCallSearchingEvent
          path: <auto>
        - type: object
          key: ResponseFileSearchCallCompletedEvent
          path: <auto>
        - type: object
          key: ResponseWebSearchCallInProgressEvent
          path: <auto>
        - type: object
          key: ResponseWebSearchCallSearchingEvent
          path: <auto>
        - type: object
          key: ResponseWebSearchCallCompletedEvent
          path: <auto>
        - type: object
          key: ResponseReasoningSummaryPartAddedEvent
          path: <auto>
        - type: object
          key: ResponseReasoningSummaryPartDoneEvent
          path: <auto>
        - type: object
          key: ResponseReasoningSummaryTextDeltaEvent
          path: <auto>
        - type: object
          key: ResponseReasoningSummaryTextDoneEvent
          path: <auto>
        - type: object
          key: ResponseImageGenCallCompletedEvent
          path: <auto>
        - type: object
          key: ResponseImageGenCallGeneratingEvent
          path: <auto>
        - type: object
          key: ResponseImageGenCallInProgressEvent
          path: <auto>
        - type: object
          key: ResponseImageGenCallPartialImageEvent
          path: <auto>
        - type: object
          key: ResponseMCPCallArgumentsDeltaEvent
          path: <auto>
        - type: object
          key: ResponseMCPCallArgumentsDoneEvent
          path: <auto>
        - type: object
          key: ResponseMCPCallCompletedEvent
          path: <auto>
        - type: object
          key: ResponseMCPCallFailedEvent
          path: <auto>
        - type: object
          key: ResponseMCPCallInProgressEvent
          path: <auto>
        - type: object
          key: ResponseMCPListToolsCompletedEvent
          path: <auto>
        - type: object
          key: ResponseMCPListToolsFailedEvent
          path: <auto>
        - type: object
          key: ResponseMCPListToolsInProgressEvent
          path: <auto>
        - type: object
          key: ResponseOutputTextAnnotationAddedEvent
          path: <auto>
        - type: object
          key: ResponseQueuedEvent
          path: <auto>
        - type: object
          key: ResponseReasoningDeltaEvent
          path: <auto>
        - type: object
          key: ResponseReasoningDoneEvent
          path: <auto>
        - type: object
          key: ResponseReasoningSummaryDeltaEvent
          path: <auto>
        - type: object
          key: ResponseReasoningSummaryDoneEvent
          path: <auto>
        - type: object
          key: ResponseErrorEvent
          path: <auto>
    - id: chat
      title: Chat Completions
      description: |
        The Chat Completions API endpoint will generate a model response from a
        list of messages comprising a conversation.

        Related guides:
        - [Quickstart](/docs/quickstart?api-mode=chat)
        - [Text inputs and outputs](/docs/guides/text?api-mode=chat)
        - [Image inputs](/docs/guides/images?api-mode=chat)
        - [Audio inputs and outputs](/docs/guides/audio?api-mode=chat)
        - [Structured Outputs](/docs/guides/structured-outputs?api-mode=chat)
        - [Function calling](/docs/guides/function-calling?api-mode=chat)
        - [Conversation state](/docs/guides/conversation-state?api-mode=chat)

        **Starting a new project?** We recommend trying [Responses](/docs/api-reference/responses)
        to take advantage of the latest OpenAI platform features. Compare
        [Chat Completions with Responses](/docs/guides/responses-vs-chat-completions?api-mode=responses).
      navigationGroup: chat
      sections:
        - type: endpoint
          key: createChatCompletion
          path: create
        - type: endpoint
          key: getChatCompletion
          path: get
        - type: endpoint
          key: getChatCompletionMessages
          path: getMessages
        - type: endpoint
          key: listChatCompletions
          path: list
        - type: endpoint
          key: updateChatCompletion
          path: update
        - type: endpoint
          key: deleteChatCompletion
          path: delete
        - type: object
          key: CreateChatCompletionResponse
          path: object
        - type: object
          key: ChatCompletionList
          path: list-object
        - type: object
          key: ChatCompletionMessageList
          path: message-list
    - id: chat-streaming
      title: Streaming
      description: |
        Stream Chat Completions in real time. Receive chunks of completions
        returned from the model using server-sent events.
        [Learn more](/docs/guides/streaming-responses?api-mode=chat).
      navigationGroup: chat
      sections:
        - type: object
          key: CreateChatCompletionStreamResponse
          path: streaming
    - id: realtime
      title: Realtime
      beta: true
      description: |
        Communicate with a GPT-4o class model in real time using WebRTC or
        WebSockets. Supports text and audio inputs and ouputs, along with audio
        transcriptions.
        [Learn more about the Realtime API](/docs/guides/realtime).
      navigationGroup: realtime
    - id: realtime-sessions
      title: Session tokens
      description: |
        REST API endpoint to generate ephemeral session tokens for use in client-side
        applications.
      navigationGroup: realtime
      sections:
        - type: endpoint
          key: create-realtime-session
          path: create
        - type: endpoint
          key: create-realtime-transcription-session
          path: create-transcription
        - type: object
          key: RealtimeSessionCreateResponse
          path: session_object
        - type: object
          key: RealtimeTranscriptionSessionCreateResponse
          path: transcription_session_object
    - id: realtime-client-events
      title: Client events
      description: |
        These are events that the OpenAI Realtime WebSocket server will accept from the client.
      navigationGroup: realtime
      sections:
        - type: object
          key: RealtimeClientEventSessionUpdate
          path: <auto>
        - type: object
          key: RealtimeClientEventInputAudioBufferAppend
          path: <auto>
        - type: object
          key: RealtimeClientEventInputAudioBufferCommit
          path: <auto>
        - type: object
          key: RealtimeClientEventInputAudioBufferClear
          path: <auto>
        - type: object
          key: RealtimeClientEventConversationItemCreate
          path: <auto>
        - type: object
          key: RealtimeClientEventConversationItemRetrieve
          path: <auto>
        - type: object
          key: RealtimeClientEventConversationItemTruncate
          path: <auto>
        - type: object
          key: RealtimeClientEventConversationItemDelete
          path: <auto>
        - type: object
          key: RealtimeClientEventResponseCreate
          path: <auto>
        - type: object
          key: RealtimeClientEventResponseCancel
          path: <auto>
        - type: object
          key: RealtimeClientEventTranscriptionSessionUpdate
          path: <auto>
        - type: object
          key: RealtimeClientEventOutputAudioBufferClear
          path: <auto>
    - id: realtime-server-events
      title: Server events
      description: |
        These are events emitted from the OpenAI Realtime WebSocket server to the client.
      navigationGroup: realtime
      sections:
        - type: object
          key: RealtimeServerEventError
          path: <auto>
        - type: object
          key: RealtimeServerEventSessionCreated
          path: <auto>
        - type: object
          key: RealtimeServerEventSessionUpdated
          path: <auto>
        - type: object
          key: RealtimeServerEventConversationCreated
          path: <auto>
        - type: object
          key: RealtimeServerEventConversationItemCreated
          path: <auto>
        - type: object
          key: RealtimeServerEventConversationItemRetrieved
          path: <auto>
        - type: object
          key: RealtimeServerEventConversationItemInputAudioTranscriptionCompleted
          path: <auto>
        - type: object
          key: RealtimeServerEventConversationItemInputAudioTranscriptionDelta
          path: <auto>
        - type: object
          key: RealtimeServerEventConversationItemInputAudioTranscriptionFailed
          path: <auto>
        - type: object
          key: RealtimeServerEventConversationItemTruncated
          path: <auto>
        - type: object
          key: RealtimeServerEventConversationItemDeleted
          path: <auto>
        - type: object
          key: RealtimeServerEventInputAudioBufferCommitted
          path: <auto>
        - type: object
          key: RealtimeServerEventInputAudioBufferCleared
          path: <auto>
        - type: object
          key: RealtimeServerEventInputAudioBufferSpeechStarted
          path: <auto>
        - type: object
          key: RealtimeServerEventInputAudioBufferSpeechStopped
          path: <auto>
        - type: object
          key: RealtimeServerEventResponseCreated
          path: <auto>
        - type: object
          key: RealtimeServerEventResponseDone
          path: <auto>
        - type: object
          key: RealtimeServerEventResponseOutputItemAdded
          path: <auto>
        - type: object
          key: RealtimeServerEventResponseOutputItemDone
          path: <auto>
        - type: object
          key: RealtimeServerEventResponseContentPartAdded
          path: <auto>
        - type: object
          key: RealtimeServerEventResponseContentPartDone
          path: <auto>
        - type: object
          key: RealtimeServerEventResponseTextDelta
          path: <auto>
        - type: object
          key: RealtimeServerEventResponseTextDone
          path: <auto>
        - type: object
          key: RealtimeServerEventResponseAudioTranscriptDelta
          path: <auto>
        - type: object
          key: RealtimeServerEventResponseAudioTranscriptDone
          path: <auto>
        - type: object
          key: RealtimeServerEventResponseAudioDelta
          path: <auto>
        - type: object
          key: RealtimeServerEventResponseAudioDone
          path: <auto>
        - type: object
          key: RealtimeServerEventResponseFunctionCallArgumentsDelta
          path: <auto>
        - type: object
          key: RealtimeServerEventResponseFunctionCallArgumentsDone
          path: <auto>
        - type: object
          key: RealtimeServerEventTranscriptionSessionUpdated
          path: <auto>
        - type: object
          key: RealtimeServerEventRateLimitsUpdated
          path: <auto>
        - type: object
          key: RealtimeServerEventOutputAudioBufferStarted
          path: <auto>
        - type: object
          key: RealtimeServerEventOutputAudioBufferStopped
          path: <auto>
        - type: object
          key: RealtimeServerEventOutputAudioBufferCleared
          path: <auto>
    - id: audio
      title: Audio
      description: |
        Learn how to turn audio into text or text into audio.

        Related guide: [Speech to text](/docs/guides/speech-to-text)
      navigationGroup: endpoints
      sections:
        - type: endpoint
          key: createSpeech
          path: createSpeech
        - type: endpoint
          key: createTranscription
          path: createTranscription
        - type: endpoint
          key: createTranslation
          path: createTranslation
        - type: object
          key: CreateTranscriptionResponseJson
          path: json-object
        - type: object
          key: CreateTranscriptionResponseVerboseJson
          path: verbose-json-object
        - type: object
          key: TranscriptTextDeltaEvent
          path: transcript-text-delta-event
        - type: object
          key: TranscriptTextDoneEvent
          path: transcript-text-done-event
    - id: images
      title: Images
      description: |
        Given a prompt and/or an input image, the model will generate a new image.
        Related guide: [Image generation](/docs/guides/images)
      navigationGroup: endpoints
      sections:
        - type: endpoint
          key: createImage
          path: create
        - type: endpoint
          key: createImageEdit
          path: createEdit
        - type: endpoint
          key: createImageVariation
          path: createVariation
        - type: object
          key: ImagesResponse
          path: object
    - id: embeddings
      title: Embeddings
      description: >
        Get a vector representation of a given input that can be easily consumed by machine learning models
        and algorithms.

        Related guide: [Embeddings](/docs/guides/embeddings)
      navigationGroup: endpoints
      sections:
        - type: endpoint
          key: createEmbedding
          path: create
        - type: object
          key: Embedding
          path: object
    - id: evals
      title: Evals
      description: |
        Create, manage, and run evals in the OpenAI platform.
        Related guide: [Evals](/docs/guides/evals)
      navigationGroup: endpoints
      sections:
        - type: endpoint
          key: createEval
          path: create
        - type: endpoint
          key: getEval
          path: get
        - type: endpoint
          key: updateEval
          path: update
        - type: endpoint
          key: deleteEval
          path: delete
        - type: endpoint
          key: listEvals
          path: list
        - type: endpoint
          key: getEvalRuns
          path: getRuns
        - type: endpoint
          key: getEvalRun
          path: getRun
        - type: endpoint
          key: createEvalRun
          path: createRun
        - type: endpoint
          key: cancelEvalRun
          path: cancelRun
        - type: endpoint
          key: deleteEvalRun
          path: deleteRun
        - type: endpoint
          key: getEvalRunOutputItem
          path: getRunOutputItem
        - type: endpoint
          key: getEvalRunOutputItems
          path: getRunOutputItems
        - type: object
          key: Eval
          path: object
        - type: object
          key: EvalRun
          path: run-object
        - type: object
          key: EvalRunOutputItem
          path: run-output-item-object
    - id: fine-tuning
      title: Fine-tuning
      description: |
        Manage fine-tuning jobs to tailor a model to your specific training data.
        Related guide: [Fine-tune models](/docs/guides/fine-tuning)
      navigationGroup: endpoints
      sections:
        - type: endpoint
          key: createFineTuningJob
          path: create
        - type: endpoint
          key: listPaginatedFineTuningJobs
          path: list
        - type: endpoint
          key: listFineTuningEvents
          path: list-events
        - type: endpoint
          key: listFineTuningJobCheckpoints
          path: list-checkpoints
        - type: endpoint
          key: listFineTuningCheckpointPermissions
          path: list-permissions
        - type: endpoint
          key: createFineTuningCheckpointPermission
          path: create-permission
        - type: endpoint
          key: deleteFineTuningCheckpointPermission
          path: delete-permission
        - type: endpoint
          key: retrieveFineTuningJob
          path: retrieve
        - type: endpoint
          key: cancelFineTuningJob
          path: cancel
        - type: endpoint
          key: resumeFineTuningJob
          path: resume
        - type: endpoint
          key: pauseFineTuningJob
          path: pause
        - type: object
          key: FineTuneChatRequestInput
          path: chat-input
        - type: object
          key: FineTunePreferenceRequestInput
          path: preference-input
        - type: object
          key: FineTuneReinforcementRequestInput
          path: reinforcement-input
        - type: object
          key: FineTuningJob
          path: object
        - type: object
          key: FineTuningJobEvent
          path: event-object
        - type: object
          key: FineTuningJobCheckpoint
          path: checkpoint-object
        - type: object
          key: FineTuningCheckpointPermission
          path: permission-object
    - id: graders
      title: Graders
      description: |
        Manage and run graders in the OpenAI platform.
        Related guide: [Graders](/docs/guides/graders)
      navigationGroup: endpoints
      sections:
        - type: object
          key: GraderStringCheck
          path: string-check
        - type: object
          key: GraderTextSimilarity
          path: text-similarity
        - type: object
          key: GraderScoreModel
          path: score-model
        - type: object
          key: GraderLabelModel
          path: label-model
        - type: object
          key: GraderPython
          path: python
        - type: object
          key: GraderMulti
          path: multi
        - type: endpoint
          key: runGrader
          path: run
        - type: endpoint
          key: validateGrader
          path: validate
          beta: true
    - id: batch
      title: Batch
      description: >
        Create large batches of API requests for asynchronous processing. The Batch API returns completions
        within 24 hours for a 50% discount.

        Related guide: [Batch](/docs/guides/batch)
      navigationGroup: endpoints
      sections:
        - type: endpoint
          key: createBatch
          path: create
        - type: endpoint
          key: retrieveBatch
          path: retrieve
        - type: endpoint
          key: cancelBatch
          path: cancel
        - type: endpoint
          key: listBatches
          path: list
        - type: object
          key: Batch
          path: object
        - type: object
          key: BatchRequestInput
          path: request-input
        - type: object
          key: BatchRequestOutput
          path: request-output
    - id: files
      title: Files
      description: >
        Files are used to upload documents that can be used with features like
        [Assistants](/docs/api-reference/assistants), [Fine-tuning](/docs/api-reference/fine-tuning), and
        [Batch API](/docs/guides/batch).
      navigationGroup: endpoints
      sections:
        - type: endpoint
          key: createFile
          path: create
        - type: endpoint
          key: listFiles
          path: list
        - type: endpoint
          key: retrieveFile
          path: retrieve
        - type: endpoint
          key: deleteFile
          path: delete
        - type: endpoint
          key: downloadFile
          path: retrieve-contents
        - type: object
          key: OpenAIFile
          path: object
    - id: uploads
      title: Uploads
      description: |
        Allows you to upload large files in multiple parts.
      navigationGroup: endpoints
      sections:
        - type: endpoint
          key: createUpload
          path: create
        - type: endpoint
          key: addUploadPart
          path: add-part
        - type: endpoint
          key: completeUpload
          path: complete
        - type: endpoint
          key: cancelUpload
          path: cancel
        - type: object
          key: Upload
          path: object
        - type: object
          key: UploadPart
          path: part-object
    - id: models
      title: Models
      description: >
        List and describe the various models available in the API. You can refer to the [Models](/docs/models)
        documentation to understand what models are available and the differences between them.
      navigationGroup: endpoints
      sections:
        - type: endpoint
          key: listModels
          path: list
        - type: endpoint
          key: retrieveModel
          path: retrieve
        - type: endpoint
          key: deleteModel
          path: delete
        - type: object
          key: Model
          path: object
    - id: moderations
      title: Moderations
      description: >
        Given text and/or image inputs, classifies if those inputs are potentially harmful across several
        categories.

        Related guide: [Moderations](/docs/guides/moderation)
      navigationGroup: endpoints
      sections:
        - type: endpoint
          key: createModeration
          path: create
        - type: object
          key: CreateModerationResponse
          path: object
    - id: vector-stores
      title: Vector stores
      description: >
        Vector stores power semantic search for the Retrieval API and the `file_search` tool in the Responses
        and Assistants APIs.


        Related guide: [File Search](/docs/assistants/tools/file-search)
      navigationGroup: vector_stores
      sections:
        - type: endpoint
          key: createVectorStore
          path: create
        - type: endpoint
          key: listVectorStores
          path: list
        - type: endpoint
          key: getVectorStore
          path: retrieve
        - type: endpoint
          key: modifyVectorStore
          path: modify
        - type: endpoint
          key: deleteVectorStore
          path: delete
        - type: endpoint
          key: searchVectorStore
          path: search
        - type: object
          key: VectorStoreObject
          path: object
    - id: vector-stores-files
      title: Vector store files
      description: |
        Vector store files represent files inside a vector store.

        Related guide: [File Search](/docs/assistants/tools/file-search)
      navigationGroup: vector_stores
      sections:
        - type: endpoint
          key: createVectorStoreFile
          path: createFile
        - type: endpoint
          key: listVectorStoreFiles
          path: listFiles
        - type: endpoint
          key: getVectorStoreFile
          path: getFile
        - type: endpoint
          key: retrieveVectorStoreFileContent
          path: getContent
        - type: endpoint
          key: updateVectorStoreFileAttributes
          path: updateAttributes
        - type: endpoint
          key: deleteVectorStoreFile
          path: deleteFile
        - type: object
          key: VectorStoreFileObject
          path: file-object
    - id: vector-stores-file-batches
      title: Vector store file batches
      description: |
        Vector store file batches represent operations to add multiple files to a vector store.
        Related guide: [File Search](/docs/assistants/tools/file-search)
      navigationGroup: vector_stores
      sections:
        - type: endpoint
          key: createVectorStoreFileBatch
          path: createBatch
        - type: endpoint
          key: getVectorStoreFileBatch
          path: getBatch
        - type: endpoint
          key: cancelVectorStoreFileBatch
          path: cancelBatch
        - type: endpoint
          key: listFilesInVectorStoreBatch
          path: listBatchFiles
        - type: object
          key: VectorStoreFileBatchObject
          path: batch-object
    - id: containers
      title: Containers
      description: |
        Create and manage containers for use with the Code Interpreter tool.
      navigationGroup: containers
      sections:
        - type: endpoint
          key: CreateContainer
          path: createContainers
        - type: endpoint
          key: ListContainers
          path: listContainers
        - type: endpoint
          key: RetrieveContainer
          path: retrieveContainer
        - type: endpoint
          key: DeleteContainer
          path: deleteContainer
        - type: object
          key: ContainerResource
          path: object
    - id: container-files
      title: Container Files
      description: |
        Create and manage container files for use with the Code Interpreter tool.
      navigationGroup: containers
      sections:
        - type: endpoint
          key: CreateContainerFile
          path: createContainerFile
        - type: endpoint
          key: ListContainerFiles
          path: listContainerFiles
        - type: endpoint
          key: RetrieveContainerFile
          path: retrieveContainerFile
        - type: endpoint
          key: RetrieveContainerFileContent
          path: retrieveContainerFileContent
        - type: endpoint
          key: DeleteContainerFile
          path: deleteContainerFile
        - type: object
          key: ContainerFileResource
          path: object
    - id: assistants
      title: Assistants
      beta: true
      description: |
        Build assistants that can call models and use tools to perform tasks.

        [Get started with the Assistants API](/docs/assistants)
      navigationGroup: assistants
      sections:
        - type: endpoint
          key: createAssistant
          path: createAssistant
        - type: endpoint
          key: listAssistants
          path: listAssistants
        - type: endpoint
          key: getAssistant
          path: getAssistant
        - type: endpoint
          key: modifyAssistant
          path: modifyAssistant
        - type: endpoint
          key: deleteAssistant
          path: deleteAssistant
        - type: object
          key: AssistantObject
          path: object
    - id: threads
      title: Threads
      beta: true
      description: |
        Create threads that assistants can interact with.

        Related guide: [Assistants](/docs/assistants/overview)
      navigationGroup: assistants
      sections:
        - type: endpoint
          key: createThread
          path: createThread
        - type: endpoint
          key: getThread
          path: getThread
        - type: endpoint
          key: modifyThread
          path: modifyThread
        - type: endpoint
          key: deleteThread
          path: deleteThread
        - type: object
          key: ThreadObject
          path: object
    - id: messages
      title: Messages
      beta: true
      description: |
        Create messages within threads

        Related guide: [Assistants](/docs/assistants/overview)
      navigationGroup: assistants
      sections:
        - type: endpoint
          key: createMessage
          path: createMessage
        - type: endpoint
          key: listMessages
          path: listMessages
        - type: endpoint
          key: getMessage
          path: getMessage
        - type: endpoint
          key: modifyMessage
          path: modifyMessage
        - type: endpoint
          key: deleteMessage
          path: deleteMessage
        - type: object
          key: MessageObject
          path: object
    - id: runs
      title: Runs
      beta: true
      description: |
        Represents an execution run on a thread.

        Related guide: [Assistants](/docs/assistants/overview)
      navigationGroup: assistants
      sections:
        - type: endpoint
          key: createRun
          path: createRun
        - type: endpoint
          key: createThreadAndRun
          path: createThreadAndRun
        - type: endpoint
          key: listRuns
          path: listRuns
        - type: endpoint
          key: getRun
          path: getRun
        - type: endpoint
          key: modifyRun
          path: modifyRun
        - type: endpoint
          key: submitToolOuputsToRun
          path: submitToolOutputs
        - type: endpoint
          key: cancelRun
          path: cancelRun
        - type: object
          key: RunObject
          path: object
    - id: run-steps
      title: Run steps
      beta: true
      description: |
        Represents the steps (model and tool calls) taken during the run.

        Related guide: [Assistants](/docs/assistants/overview)
      navigationGroup: assistants
      sections:
        - type: endpoint
          key: listRunSteps
          path: listRunSteps
        - type: endpoint
          key: getRunStep
          path: getRunStep
        - type: object
          key: RunStepObject
          path: step-object
    - id: assistants-streaming
      title: Streaming
      beta: true
      description: >
        Stream the result of executing a Run or resuming a Run after submitting tool outputs.

        You can stream events from the [Create Thread and Run](/docs/api-reference/runs/createThreadAndRun),

        [Create Run](/docs/api-reference/runs/createRun), and [Submit Tool
        Outputs](/docs/api-reference/runs/submitToolOutputs)

        endpoints by passing `"stream": true`. The response will be a [Server-Sent
        events](https://html.spec.whatwg.org/multipage/server-sent-events.html#server-sent-events) stream.

        Our Node and Python SDKs provide helpful utilities to make streaming easy. Reference the

        [Assistants API quickstart](/docs/assistants/overview) to learn more.
      navigationGroup: assistants
      sections:
        - type: object
          key: MessageDeltaObject
          path: message-delta-object
        - type: object
          key: RunStepDeltaObject
          path: run-step-delta-object
        - type: object
          key: AssistantStreamEvent
          path: events
    - id: administration
      title: Administration
      description: >
        Programmatically manage your organization.

        The Audit Logs endpoint provides a log of all actions taken in the organization for security and
        monitoring purposes.

        To access these endpoints please generate an Admin API Key through the [API Platform Organization
        overview](/organization/admin-keys). Admin API keys cannot be used for non-administration endpoints.

        For best practices on setting up your organization, please refer to this
        [guide](/docs/guides/production-best-practices#setting-up-your-organization)
      navigationGroup: administration
    - id: admin-api-keys
      title: Admin API Keys
      description: >
        Admin API keys enable Organization Owners to programmatically manage various aspects of their
        organization, including users, projects, and API keys. These keys provide administrative capabilities,
        such as creating, updating, and deleting users; managing projects; and overseeing API key lifecycles.


        Key Features of Admin API Keys:


        - User Management: Invite new users, update roles, and remove users from the organization.


        - Project Management: Create, update, archive projects, and manage user assignments within projects.


        - API Key Oversight: List, retrieve, and delete API keys associated with projects.


        Only Organization Owners have the authority to create and utilize Admin API keys. To manage these
        keys, Organization Owners can navigate to the Admin Keys section of their API Platform dashboard.


        For direct access to the Admin Keys management page, Organization Owners can use the following link:


        [https://platform.openai.com/settings/organization/admin-keys](https://platform.openai.com/settings/organization/admin-keys)


        It's crucial to handle Admin API keys with care due to their elevated permissions. Adhering to best
        practices, such as regular key rotation and assigning appropriate permissions, enhances security and
        ensures proper governance within the organization.
      navigationGroup: administration
      sections:
        - type: endpoint
          key: admin-api-keys-list
          path: list
        - type: endpoint
          key: admin-api-keys-create
          path: create
        - type: endpoint
          key: admin-api-keys-get
          path: listget
        - type: endpoint
          key: admin-api-keys-delete
          path: delete
        - type: object
          key: AdminApiKey
          path: object
    - id: invite
      title: Invites
      description: Invite and manage invitations for an organization.
      navigationGroup: administration
      sections:
        - type: endpoint
          key: list-invites
          path: list
        - type: endpoint
          key: inviteUser
          path: create
        - type: endpoint
          key: retrieve-invite
          path: retrieve
        - type: endpoint
          key: delete-invite
          path: delete
        - type: object
          key: Invite
          path: object
    - id: users
      title: Users
      description: |
        Manage users and their role in an organization.
      navigationGroup: administration
      sections:
        - type: endpoint
          key: list-users
          path: list
        - type: endpoint
          key: modify-user
          path: modify
        - type: endpoint
          key: retrieve-user
          path: retrieve
        - type: endpoint
          key: delete-user
          path: delete
        - type: object
          key: User
          path: object
    - id: projects
      title: Projects
      description: |
        Manage the projects within an orgnanization includes creation, updating, and archiving or projects.
        The Default project cannot be archived.
      navigationGroup: administration
      sections:
        - type: endpoint
          key: list-projects
          path: list
        - type: endpoint
          key: create-project
          path: create
        - type: endpoint
          key: retrieve-project
          path: retrieve
        - type: endpoint
          key: modify-project
          path: modify
        - type: endpoint
          key: archive-project
          path: archive
        - type: object
          key: Project
          path: object
    - id: project-users
      title: Project users
      description: |
        Manage users within a project, including adding, updating roles, and removing users.
      navigationGroup: administration
      sections:
        - type: endpoint
          key: list-project-users
          path: list
        - type: endpoint
          key: create-project-user
          path: creeate
        - type: endpoint
          key: retrieve-project-user
          path: retrieve
        - type: endpoint
          key: modify-project-user
          path: modify
        - type: endpoint
          key: delete-project-user
          path: delete
        - type: object
          key: ProjectUser
          path: object
    - id: project-service-accounts
      title: Project service accounts
      description: >
        Manage service accounts within a project. A service account is a bot user that is not associated with
        a user.

        If a user leaves an organization, their keys and membership in projects will no longer work. Service
        accounts

        do not have this limitation. However, service accounts can also be deleted from a project.
      navigationGroup: administration
      sections:
        - type: endpoint
          key: list-project-service-accounts
          path: list
        - type: endpoint
          key: create-project-service-account
          path: create
        - type: endpoint
          key: retrieve-project-service-account
          path: retrieve
        - type: endpoint
          key: delete-project-service-account
          path: delete
        - type: object
          key: ProjectServiceAccount
          path: object
    - id: project-api-keys
      title: Project API keys
      description: >
        Manage API keys for a given project. Supports listing and deleting keys for users.

        This API does not allow issuing keys for users, as users need to authorize themselves to generate
        keys.
      navigationGroup: administration
      sections:
        - type: endpoint
          key: list-project-api-keys
          path: list
        - type: endpoint
          key: retrieve-project-api-key
          path: retrieve
        - type: endpoint
          key: delete-project-api-key
          path: delete
        - type: object
          key: ProjectApiKey
          path: object
    - id: project-rate-limits
      title: Project rate limits
      description: >
        Manage rate limits per model for projects. Rate limits may be configured to be equal to or lower than
        the organization's rate limits.
      navigationGroup: administration
      sections:
        - type: endpoint
          key: list-project-rate-limits
          path: list
        - type: endpoint
          key: update-project-rate-limits
          path: update
        - type: object
          key: ProjectRateLimit
          path: object
    - id: audit-logs
      title: Audit logs
      description: >
        Logs of user actions and configuration changes within this organization.

        To log events, an Organization Owner must activate logging in the [Data Controls
        Settings](/settings/organization/data-controls/data-retention).

        Once activated, for security reasons, logging cannot be deactivated.
      navigationGroup: administration
      sections:
        - type: endpoint
          key: list-audit-logs
          path: list
        - type: object
          key: AuditLog
          path: object
    - id: usage
      title: Usage
      description: >
        The **Usage API** provides detailed insights into your activity across the OpenAI API. It also
        includes a separate [Costs endpoint](/docs/api-reference/usage/costs), which offers visibility into
        your spend, breaking down consumption by invoice line items and project IDs.


        While the Usage API delivers granular usage data, it may not always reconcile perfectly with the Costs
        due to minor differences in how usage and spend are recorded. For financial purposes, we recommend
        using the [Costs endpoint](/docs/api-reference/usage/costs) or the [Costs
        tab](/settings/organization/usage) in the Usage Dashboard, which will reconcile back to your billing
        invoice.
      navigationGroup: administration
      sections:
        - type: endpoint
          key: usage-completions
          path: completions
        - type: object
          key: UsageCompletionsResult
          path: completions_object
        - type: endpoint
          key: usage-embeddings
          path: embeddings
        - type: object
          key: UsageEmbeddingsResult
          path: embeddings_object
        - type: endpoint
          key: usage-moderations
          path: moderations
        - type: object
          key: UsageModerationsResult
          path: moderations_object
        - type: endpoint
          key: usage-images
          path: images
        - type: object
          key: UsageImagesResult
          path: images_object
        - type: endpoint
          key: usage-audio-speeches
          path: audio_speeches
        - type: object
          key: UsageAudioSpeechesResult
          path: audio_speeches_object
        - type: endpoint
          key: usage-audio-transcriptions
          path: audio_transcriptions
        - type: object
          key: UsageAudioTranscriptionsResult
          path: audio_transcriptions_object
        - type: endpoint
          key: usage-vector-stores
          path: vector_stores
        - type: object
          key: UsageVectorStoresResult
          path: vector_stores_object
        - type: endpoint
          key: usage-code-interpreter-sessions
          path: code_interpreter_sessions
        - type: object
          key: UsageCodeInterpreterSessionsResult
          path: code_interpreter_sessions_object
        - type: endpoint
          key: usage-costs
          path: costs
        - type: object
          key: CostsResult
          path: costs_object
    - id: certificates
      beta: true
      title: Certificates
      description: >
        Manage Mutual TLS certificates across your organization and projects.


        [Learn more about Mutual
        TLS.](https://help.openai.com/en/articles/10876024-openai-mutual-tls-beta-program)
      navigationGroup: administration
      sections:
        - type: endpoint
          key: uploadCertificate
          path: uploadCertificate
        - type: endpoint
          key: getCertificate
          path: getCertificate
        - type: endpoint
          key: modifyCertificate
          path: modifyCertificate
        - type: endpoint
          key: deleteCertificate
          path: deleteCertificate
        - type: endpoint
          key: listOrganizationCertificates
          path: listOrganizationCertificates
        - type: endpoint
          key: listProjectCertificates
          path: listProjectCertificates
        - type: endpoint
          key: activateOrganizationCertificates
          path: activateOrganizationCertificates
        - type: endpoint
          key: deactivateOrganizationCertificates
          path: deactivateOrganizationCertificates
        - type: endpoint
          key: activateProjectCertificates
          path: activateProjectCertificates
        - type: endpoint
          key: deactivateProjectCertificates
          path: deactivateProjectCertificates
        - type: object
          key: Certificate
          path: object
    - id: completions
      title: Completions
      legacy: true
      navigationGroup: legacy
      description: >
        Given a prompt, the model will return one or more predicted completions along with the probabilities
        of alternative tokens at each position. Most developer should use our [Chat Completions
        API](/docs/guides/text-generation#text-generation-models) to leverage our best and newest models.
      sections:
        - type: endpoint
          key: createCompletion
          path: create
        - type: object
          key: CreateCompletionResponse
          path: object
