openai.yaml

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: "2.0.0"
  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
tags:
  - name: Assistants
    description: Build Assistants that can call models and use tools.
  - name: Audio
    description: Learn how to 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: Fine-tuning
    description: Manage fine-tuning jobs to tailor a model to your specific training data.
  - 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: 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 a input text, outputs if the model classifies it as potentially harmful.
paths:
  # Note: When adding an endpoint, make sure you also add it in the `groups` section, in the end of this file,
  # under the appropriate group
  /chat/completions:
    post:
      operationId: createChatCompletion
      tags:
        - Chat
      summary: Creates a model response for the given chat conversation.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/CreateChatCompletionRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/CreateChatCompletionResponse"

      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_model_id",
                    "messages": [
                      {
                        "role": "system",
                        "content": "You are a helpful assistant."
                      },
                      {
                        "role": "user",
                        "content": "Hello!"
                      }
                    ]
                  }'
              python: |
                from openai import OpenAI
                client = OpenAI()

                completion = client.chat.completions.create(
                  model="VAR_model_id",
                  messages=[
                    {"role": "system", "content": "You are a helpful assistant."},
                    {"role": "user", "content": "Hello!"}
                  ]
                )

                print(completion.choices[0].message)
              node.js: |-
                import OpenAI from "openai";

                const openai = new OpenAI();

                async function main() {
                  const completion = await openai.chat.completions.create({
                    messages: [{ role: "system", content: "You are a helpful assistant." }],
                    model: "VAR_model_id",
                  });

                  console.log(completion.choices[0]);
                }

                main();
            response: &chat_completion_example |
              {
                "id": "chatcmpl-123",
                "object": "chat.completion",
                "created": 1677652288,
                "model": "gpt-3.5-turbo-0125",
                "system_fingerprint": "fp_44709d6fcb",
                "choices": [{
                  "index": 0,
                  "message": {
                    "role": "assistant",
                    "content": "\n\nHello there, how may I assist you today?",
                  },
                  "logprobs": null,
                  "finish_reason": "stop"
                }],
                "usage": {
                  "prompt_tokens": 9,
                  "completion_tokens": 12,
                  "total_tokens": 21
                }
              }
          - 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-turbo",
                    "messages": [
                      {
                        "role": "user",
                        "content": [
                          {
                            "type": "text",
                            "text": "What'\''s 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: |
                from openai import OpenAI

                client = OpenAI()

                response = client.chat.completions.create(
                    model="gpt-4-turbo",
                    messages=[
                        {
                            "role": "user",
                            "content": [
                                {"type": "text", "text": "What's in this image?"},
                                {
                                    "type": "image_url",
                                    "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",
                                },
                            ],
                        }
                    ],
                    max_tokens=300,
                )

                print(response.choices[0])
              node.js: |-
                import OpenAI from "openai";

                const openai = new OpenAI();

                async function main() {
                  const response = await openai.chat.completions.create({
                    model: "gpt-4-turbo",
                    messages: [
                      {
                        role: "user",
                        content: [
                          { type: "text", text: "What's in this image?" },
                          {
                            type: "image_url",
                            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.choices[0]);
                }
                main();
            response: &chat_completion_image_example |
              {
                "id": "chatcmpl-123",
                "object": "chat.completion",
                "created": 1677652288,
                "model": "gpt-3.5-turbo-0125",
                "system_fingerprint": "fp_44709d6fcb",
                "choices": [{
                  "index": 0,
                  "message": {
                    "role": "assistant",
                    "content": "\n\nThis image shows a wooden boardwalk extending through a lush green marshland.",
                  },
                  "logprobs": null,
                  "finish_reason": "stop"
                }],
                "usage": {
                  "prompt_tokens": 9,
                  "completion_tokens": 12,
                  "total_tokens": 21
                }
              }
          - 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_model_id",
                    "messages": [
                      {
                        "role": "system",
                        "content": "You are a helpful assistant."
                      },
                      {
                        "role": "user",
                        "content": "Hello!"
                      }
                    ],
                    "stream": true
                  }'
              python: |
                from openai import OpenAI
                client = OpenAI()

                completion = client.chat.completions.create(
                  model="VAR_model_id",
                  messages=[
                    {"role": "system", "content": "You are a helpful assistant."},
                    {"role": "user", "content": "Hello!"}
                  ],
                  stream=True
                )

                for chunk in completion:
                  print(chunk.choices[0].delta)

              node.js: |-
                import OpenAI from "openai";

                const openai = new OpenAI();

                async function main() {
                  const completion = await openai.chat.completions.create({
                    model: "VAR_model_id",
                    messages: [
                      {"role": "system", "content": "You are a helpful assistant."},
                      {"role": "user", "content": "Hello!"}
                    ],
                    stream: true,
                  });

                  for await (const chunk of completion) {
                    console.log(chunk.choices[0].delta.content);
                  }
                }

                main();
            response: &chat_completion_chunk_example |
              {"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"gpt-3.5-turbo-0125", "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-3.5-turbo-0125", "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-3.5-turbo-0125", "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-turbo",
                  "messages": [
                    {
                      "role": "user",
                      "content": "What'\''s 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: |
                from openai import OpenAI
                client = OpenAI()

                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"],
                      },
                    }
                  }
                ]
                messages = [{"role": "user", "content": "What's the weather like in Boston today?"}]
                completion = client.chat.completions.create(
                  model="VAR_model_id",
                  messages=messages,
                  tools=tools,
                  tool_choice="auto"
                )

                print(completion)
              node.js: |-
                import OpenAI from "openai";

                const openai = new OpenAI();

                async function main() {
                  const messages = [{"role": "user", "content": "What's the weather like in Boston today?"}];
                  const 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"],
                          },
                        }
                      }
                  ];

                  const response = await openai.chat.completions.create({
                    model: "gpt-4-turbo",
                    messages: messages,
                    tools: tools,
                    tool_choice: "auto",
                  });

                  console.log(response);
                }

                main();
            response: &chat_completion_function_example |
              {
                "id": "chatcmpl-abc123",
                "object": "chat.completion",
                "created": 1699896916,
                "model": "gpt-3.5-turbo-0125",
                "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
                }
              }
          - 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_model_id",
                    "messages": [
                      {
                        "role": "user",
                        "content": "Hello!"
                      }
                    ],
                    "logprobs": true,
                    "top_logprobs": 2
                  }'
              python: |
                from openai import OpenAI
                client = OpenAI()

                completion = client.chat.completions.create(
                  model="VAR_model_id",
                  messages=[
                    {"role": "user", "content": "Hello!"}
                  ],
                  logprobs=True,
                  top_logprobs=2
                )

                print(completion.choices[0].message)
                print(completion.choices[0].logprobs)
              node.js: |-
                import OpenAI from "openai";

                const openai = new OpenAI();

                async function main() {
                  const completion = await openai.chat.completions.create({
                    messages: [{ role: "user", content: "Hello!" }],
                    model: "VAR_model_id",
                    logprobs: true,
                    top_logprobs: 2,
                  });

                  console.log(completion.choices[0]);
                }

                main();
            response: |
              {
                "id": "chatcmpl-123",
                "object": "chat.completion",
                "created": 1702685778,
                "model": "gpt-3.5-turbo-0125",
                "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
                },
                "system_fingerprint": null
              }

  /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_model_id",
                    "prompt": "Say this is a test",
                    "max_tokens": 7,
                    "temperature": 0
                  }'
              python: |
                from openai import OpenAI
                client = OpenAI()

                client.completions.create(
                  model="VAR_model_id",
                  prompt="Say this is a test",
                  max_tokens=7,
                  temperature=0
                )
              node.js: |-
                import OpenAI from "openai";

                const openai = new OpenAI();

                async function main() {
                  const completion = await openai.completions.create({
                    model: "VAR_model_id",
                    prompt: "Say this is a test.",
                    max_tokens: 7,
                    temperature: 0,
                  });

                  console.log(completion);
                }
                main();
            response: |
              {
                "id": "cmpl-uqkvlQyYK7bGYrRHQ0eXlWi7",
                "object": "text_completion",
                "created": 1589478378,
                "model": "VAR_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_model_id",
                    "prompt": "Say this is a test",
                    "max_tokens": 7,
                    "temperature": 0,
                    "stream": true
                  }'
              python: |
                from openai import OpenAI
                client = OpenAI()

                for chunk in client.completions.create(
                  model="VAR_model_id",
                  prompt="Say this is a test",
                  max_tokens=7,
                  temperature=0,
                  stream=True
                ):
                  print(chunk.choices[0].text)
              node.js: |-
                import OpenAI from "openai";

                const openai = new OpenAI();

                async function main() {
                  const stream = await openai.completions.create({
                    model: "VAR_model_id",
                    prompt: "Say this is a test.",
                    stream: true,
                  });

                  for await (const chunk of stream) {
                    console.log(chunk.choices[0].text)
                  }
                }
                main();
            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",
              }

  /images/generations:
    post:
      operationId: createImage
      tags:
        - Images
      summary: Creates an image given a prompt.
      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:
          request:
            curl: |
              curl https://api.openai.com/v1/images/generations \
                -H "Content-Type: application/json" \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -d '{
                  "model": "dall-e-3",
                  "prompt": "A cute baby sea otter",
                  "n": 1,
                  "size": "1024x1024"
                }'
            python: |
              from openai import OpenAI
              client = OpenAI()

              client.images.generate(
                model="dall-e-3",
                prompt="A cute baby sea otter",
                n=1,
                size="1024x1024"
              )
            node.js: |-
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const image = await openai.images.generate({ model: "dall-e-3", prompt: "A cute baby sea otter" });

                console.log(image.data);
              }
              main();
          response: |
            {
              "created": 1589478378,
              "data": [
                {
                  "url": "https://..."
                },
                {
                  "url": "https://..."
                }
              ]
            }
  /images/edits:
    post:
      operationId: createImageEdit
      tags:
        - Images
      summary: Creates an edited or extended image given an original image and a prompt.
      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:
          request:
            curl: |
              curl https://api.openai.com/v1/images/edits \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -F image="@otter.png" \
                -F mask="@mask.png" \
                -F prompt="A cute baby sea otter wearing a beret" \
                -F n=2 \
                -F size="1024x1024"
            python: |
              from openai import OpenAI
              client = OpenAI()

              client.images.edit(
                image=open("otter.png", "rb"),
                mask=open("mask.png", "rb"),
                prompt="A cute baby sea otter wearing a beret",
                n=2,
                size="1024x1024"
              )
            node.js: |-
              import fs from "fs";
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const image = await openai.images.edit({
                  image: fs.createReadStream("otter.png"),
                  mask: fs.createReadStream("mask.png"),
                  prompt: "A cute baby sea otter wearing a beret",
                });

                console.log(image.data);
              }
              main();
          response: |
            {
              "created": 1589478378,
              "data": [
                {
                  "url": "https://..."
                },
                {
                  "url": "https://..."
                }
              ]
            }
  /images/variations:
    post:
      operationId: createImageVariation
      tags:
        - Images
      summary: Creates a variation of a given image.
      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:
          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: |
              from openai import OpenAI
              client = OpenAI()

              response = client.images.create_variation(
                image=open("image_edit_original.png", "rb"),
                n=2,
                size="1024x1024"
              )
            node.js: |-
              import fs from "fs";
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const image = await openai.images.createVariation({
                  image: fs.createReadStream("otter.png"),
                });

                console.log(image.data);
              }
              main();
          response: |
            {
              "created": 1589478378,
              "data": [
                {
                  "url": "https://..."
                },
                {
                  "url": "https://..."
                }
              ]
            }

  /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:
          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: |
              from openai import OpenAI
              client = OpenAI()

              client.embeddings.create(
                model="text-embedding-ada-002",
                input="The food was delicious and the waiter...",
                encoding_format="float"
              )
            node.js: |-
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const embedding = await openai.embeddings.create({
                  model: "text-embedding-ada-002",
                  input: "The quick brown fox jumped over the lazy dog",
                  encoding_format: "float",
                });

                console.log(embedding);
              }

              main();
          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
              }
            }

  /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:
          request:
            curl: |
              curl https://api.openai.com/v1/audio/speech \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
                -d '{
                  "model": "tts-1",
                  "input": "The quick brown fox jumped over the lazy dog.",
                  "voice": "alloy"
                }' \
                --output speech.mp3
            python: |
              from pathlib import Path
              import openai

              speech_file_path = Path(__file__).parent / "speech.mp3"
              response = openai.audio.speech.create(
                model="tts-1",
                voice="alloy",
                input="The quick brown fox jumped over the lazy dog."
              )
              response.stream_to_file(speech_file_path)
            node: |
              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: "tts-1",
                  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();
  /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"
      x-oaiMeta:
        name: Create transcription
        group: audio
        returns: The [transcription object](/docs/api-reference/audio/json-object) or a [verbose transcription object](/docs/api-reference/audio/verbose-json-object).
        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="whisper-1"
              python: |
                from openai import OpenAI
                client = OpenAI()

                audio_file = open("speech.mp3", "rb")
                transcript = client.audio.transcriptions.create(
                  model="whisper-1",
                  file=audio_file
                )
              node: |
                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",
                  });

                  console.log(transcription.text);
                }
                main();
            response: &basic_transcription_response_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."
              }
          - 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: |
                from openai import OpenAI
                client = OpenAI()

                audio_file = open("speech.mp3", "rb")
                transcript = client.audio.transcriptions.create(
                  file=audio_file,
                  model="whisper-1",
                  response_format="verbose_json",
                  timestamp_granularities=["word"]
                )

                print(transcript.words)
              node: |
                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();
            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: |
                from openai import OpenAI
                client = OpenAI()

                audio_file = open("speech.mp3", "rb")
                transcript = client.audio.transcriptions.create(
                  file=audio_file,
                  model="whisper-1",
                  response_format="verbose_json",
                  timestamp_granularities=["segment"]
                )

                print(transcript.words)
              node: |
                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();
            response: &verbose_transcription_response_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
                  },
                  ...
                ]
              }
  /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:
          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: |
              from openai import OpenAI
              client = OpenAI()

              audio_file = open("speech.mp3", "rb")
              transcript = client.audio.translations.create(
                model="whisper-1",
                file=audio_file
              )
            node: |
              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();
          response: |
            {
              "text": "Hello, my name is Wolfgang and I come from Germany. Where are you heading today?"
            }

  /files:
    get:
      operationId: listFiles
      tags:
        - Files
      summary: Returns a list of files that belong to the user's organization.
      parameters:
        - in: query
          name: purpose
          required: false
          schema:
            type: string
          description: Only return files with the given purpose.
      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:
          request:
            curl: |
              curl https://api.openai.com/v1/files \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            python: |
              from openai import OpenAI
              client = OpenAI()

              client.files.list()
            node.js: |-
              import OpenAI from "openai";

              const openai = new OpenAI();

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

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

              main();
          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"
            }
    post:
      operationId: createFile
      tags:
        - Files
      summary: |
        Upload a file that can be used across various endpoints. The size of all the files uploaded by one organization can be up to 100 GB.

        The size of individual files can be a maximum of 512 MB or 2 million tokens for Assistants. See the [Assistants Tools guide](/docs/assistants/tools) to learn more about the types of files supported. The Fine-tuning API only supports `.jsonl` files.

        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:
          request:
            curl: |
              curl https://api.openai.com/v1/files \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -F purpose="fine-tune" \
                -F file="@mydata.jsonl"
            python: |
              from openai import OpenAI
              client = OpenAI()

              client.files.create(
                file=open("mydata.jsonl", "rb"),
                purpose="fine-tune"
              )
            node.js: |-
              import fs from "fs";
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const file = await openai.files.create({
                  file: fs.createReadStream("mydata.jsonl"),
                  purpose: "fine-tune",
                });

                console.log(file);
              }

              main();
          response: |
            {
              "id": "file-abc123",
              "object": "file",
              "bytes": 120000,
              "created_at": 1677610602,
              "filename": "mydata.jsonl",
              "purpose": "fine-tune",
            }
  /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:
          request:
            curl: |
              curl https://api.openai.com/v1/files/file-abc123 \
                -X DELETE \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            python: |
              from openai import OpenAI
              client = OpenAI()

              client.files.delete("file-abc123")
            node.js: |-
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const file = await openai.files.del("file-abc123");

                console.log(file);
              }

              main();
          response: |
            {
              "id": "file-abc123",
              "object": "file",
              "deleted": true
            }
    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:
          request:
            curl: |
              curl https://api.openai.com/v1/files/file-abc123 \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            python: |
              from openai import OpenAI
              client = OpenAI()

              client.files.retrieve("file-abc123")
            node.js: |-
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const file = await openai.files.retrieve("file-abc123");

                console.log(file);
              }

              main();
          response: |
            {
              "id": "file-abc123",
              "object": "file",
              "bytes": 120000,
              "created_at": 1677610602,
              "filename": "mydata.jsonl",
              "purpose": "fine-tune",
            }
  /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:
          request:
            curl: |
              curl https://api.openai.com/v1/files/file-abc123/content \
                -H "Authorization: Bearer $OPENAI_API_KEY" > file.jsonl
            python: |
              from openai import OpenAI
              client = OpenAI()

              content = client.files.content("file-abc123")
            node.js: |
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const file = await openai.files.content("file-abc123");

                console.log(file);
              }

              main();

  /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/fine-tuning)
      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-3.5-turbo"
                  }'
              python: |
                from openai import OpenAI
                client = OpenAI()

                client.fine_tuning.jobs.create(
                  training_file="file-abc123",
                  model="gpt-3.5-turbo"
                )
              node.js: |
                import OpenAI from "openai";

                const openai = new OpenAI();

                async function main() {
                  const fineTune = await openai.fineTuning.jobs.create({
                    training_file: "file-abc123"
                  });

                  console.log(fineTune);
                }

                main();
            response: |
              {
                "object": "fine_tuning.job",
                "id": "ftjob-abc123",
                "model": "gpt-3.5-turbo-0125",
                "created_at": 1614807352,
                "fine_tuned_model": null,
                "organization_id": "org-123",
                "result_files": [],
                "status": "queued",
                "validation_file": null,
                "training_file": "file-abc123",
              }
          - 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-3.5-turbo",
                    "hyperparameters": {
                      "n_epochs": 2
                    }
                  }'
              python: |
                from openai import OpenAI
                client = OpenAI()

                client.fine_tuning.jobs.create(
                  training_file="file-abc123",
                  model="gpt-3.5-turbo",
                  hyperparameters={
                    "n_epochs":2
                  }
                )
              node.js: |
                import OpenAI from "openai";

                const openai = new OpenAI();

                async function main() {
                  const fineTune = await openai.fineTuning.jobs.create({
                    training_file: "file-abc123",
                    model: "gpt-3.5-turbo",
                    hyperparameters: { n_epochs: 2 }
                  });

                  console.log(fineTune);
                }

                main();
            response: |
              {
                "object": "fine_tuning.job",
                "id": "ftjob-abc123",
                "model": "gpt-3.5-turbo-0125",
                "created_at": 1614807352,
                "fine_tuned_model": null,
                "organization_id": "org-123",
                "result_files": [],
                "status": "queued",
                "validation_file": null,
                "training_file": "file-abc123",
                "hyperparameters": {"n_epochs": 2},
              }
          - 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-3.5-turbo"
                  }'
              python: |
                from openai import OpenAI
                client = OpenAI()

                client.fine_tuning.jobs.create(
                  training_file="file-abc123",
                  validation_file="file-def456",
                  model="gpt-3.5-turbo"
                )
              node.js: |
                import OpenAI from "openai";

                const openai = new OpenAI();

                async function main() {
                  const fineTune = await openai.fineTuning.jobs.create({
                    training_file: "file-abc123",
                    validation_file: "file-abc123"
                  });

                  console.log(fineTune);
                }

                main();
            response: |
              {
                "object": "fine_tuning.job",
                "id": "ftjob-abc123",
                "model": "gpt-3.5-turbo-0125",
                "created_at": 1614807352,
                "fine_tuned_model": null,
                "organization_id": "org-123",
                "result_files": [],
                "status": "queued",
                "validation_file": "file-abc123",
                "training_file": "file-abc123",
              }
          - 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-3.5-turbo",
                    "integrations": [
                      {
                        "type": "wandb",
                        "wandb": {
                          "project": "my-wandb-project",
                          "name": "ft-run-display-name"
                          "tags": [
                            "first-experiment", "v2"
                          ]
                        }
                      }
                    ]
                  }'
            response: |
              {
                "object": "fine_tuning.job",
                "id": "ftjob-abc123",
                "model": "gpt-3.5-turbo-0125",
                "created_at": 1614807352,
                "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"
                    }
                  }
                ]
              }
    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
      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:
          request:
            curl: |
              curl https://api.openai.com/v1/fine_tuning/jobs?limit=2 \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            python: |
              from openai import OpenAI
              client = OpenAI()

              client.fine_tuning.jobs.list()
            node.js: |-
              import OpenAI from "openai";

              const openai = new OpenAI();

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

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

              main();
          response: |
            {
              "object": "list",
              "data": [
                {
                  "object": "fine_tuning.job.event",
                  "id": "ft-event-TjX0lMfOniCZX64t9PUQT5hn",
                  "created_at": 1689813489,
                  "level": "warn",
                  "message": "Fine tuning process stopping due to job cancellation",
                  "data": null,
                  "type": "message"
                },
                { ... },
                { ... }
              ], "has_more": true
            }
  /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/fine-tuning)
      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:
          request:
            curl: |
              curl https://api.openai.com/v1/fine_tuning/jobs/ft-AF1WoRqd3aJAHsqc9NY7iL8F \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            python: |
              from openai import OpenAI
              client = OpenAI()

              client.fine_tuning.jobs.retrieve("ftjob-abc123")
            node.js: |
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const fineTune = await openai.fineTuning.jobs.retrieve("ftjob-abc123");

                console.log(fineTune);
              }

              main();
          response: &fine_tuning_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
            }
  /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:
          request:
            curl: |
              curl https://api.openai.com/v1/fine_tuning/jobs/ftjob-abc123/events \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            python: |
              from openai import OpenAI
              client = OpenAI()

              client.fine_tuning.jobs.list_events(
                fine_tuning_job_id="ftjob-abc123",
                limit=2
              )
            node.js: |-
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const list = await openai.fineTuning.list_events(id="ftjob-abc123", limit=2);

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

              main();
          response: |
            {
              "object": "list",
              "data": [
                {
                  "object": "fine_tuning.job.event",
                  "id": "ft-event-ddTJfwuMVpfLXseO0Am0Gqjm",
                  "created_at": 1692407401,
                  "level": "info",
                  "message": "Fine tuning job successfully completed",
                  "data": null,
                  "type": "message"
                },
                {
                  "object": "fine_tuning.job.event",
                  "id": "ft-event-tyiGuB72evQncpH87xe505Sv",
                  "created_at": 1692407400,
                  "level": "info",
                  "message": "New fine-tuned model created: ft:gpt-3.5-turbo:openai::7p4lURel",
                  "data": null,
                  "type": "message"
                }
              ],
              "has_more": true
            }
  /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:
          request:
            curl: |
              curl -X POST https://api.openai.com/v1/fine_tuning/jobs/ftjob-abc123/cancel \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            python: |
              from openai import OpenAI
              client = OpenAI()

              client.fine_tuning.jobs.cancel("ftjob-abc123")
            node.js: |-
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const fineTune = await openai.fineTuning.jobs.cancel("ftjob-abc123");

                console.log(fineTune);
              }
              main();
          response: |
            {
              "object": "fine_tuning.job",
              "id": "ftjob-abc123",
              "model": "gpt-3.5-turbo-0125",
              "created_at": 1689376978,
              "fine_tuned_model": null,
              "organization_id": "org-123",
              "result_files": [],
              "hyperparameters": {
                "n_epochs":  "auto"
              },
              "status": "cancelled",
              "validation_file": "file-abc123",
              "training_file": "file-abc123"
            }
  /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:
          request:
            curl: |
              curl https://api.openai.com/v1/fine_tuning/jobs/ftjob-abc123/checkpoints \
                -H "Authorization: Bearer $OPENAI_API_KEY"
          response: |
            {
              "object": "list"
              "data": [
                {
                  "object": "fine_tuning.job.checkpoint",
                  "id": "ftckpt_zc4Q7MP6XxulcVzj4MZdwsAB",
                  "created_at": 1519129973,
                  "fine_tuned_model_checkpoint": "ft:gpt-3.5-turbo-0125: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": 1519129833,
                  "fine_tuned_model_checkpoint": "ft:gpt-3.5-turbo-0125: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
            }

  /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:
          request:
            curl: |
              curl https://api.openai.com/v1/models \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            python: |
              from openai import OpenAI
              client = OpenAI()

              client.models.list()
            node.js: |-
              import OpenAI from "openai";

              const openai = new OpenAI();

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

                for await (const model of list) {
                  console.log(model);
                }
              }
              main();
          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"
            }
  /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
            # ideally this will be an actual ID, so this will always work from browser
            example: gpt-3.5-turbo
          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:
          request:
            curl: |
              curl https://api.openai.com/v1/models/VAR_model_id \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            python: |
              from openai import OpenAI
              client = OpenAI()

              client.models.retrieve("VAR_model_id")
            node.js: |-
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const model = await openai.models.retrieve("VAR_model_id");

                console.log(model);
              }

              main();
          response: &retrieve_model_response |
            {
              "id": "VAR_model_id",
              "object": "model",
              "created": 1686935002,
              "owned_by": "openai"
            }
    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-3.5-turbo: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:
          request:
            curl: |
              curl https://api.openai.com/v1/models/ft:gpt-3.5-turbo:acemeco:suffix:abc123 \
                -X DELETE \
                -H "Authorization: Bearer $OPENAI_API_KEY"
            python: |
              from openai import OpenAI
              client = OpenAI()

              client.models.delete("ft:gpt-3.5-turbo:acemeco:suffix:abc123")
            node.js: |-
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const model = await openai.models.del("ft:gpt-3.5-turbo:acemeco:suffix:abc123");

                console.log(model);
              }
              main();
          response: |
            {
              "id": "ft:gpt-3.5-turbo:acemeco:suffix:abc123",
              "object": "model",
              "deleted": true
            }

  /moderations:
    post:
      operationId: createModeration
      tags:
        - Moderations
      summary: Classifies if text is potentially harmful.
      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:
          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: |
              from openai import OpenAI
              client = OpenAI()

              moderation = client.moderations.create(input="I want to kill them.")
              print(moderation)
            node.js: |
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const moderation = await openai.moderations.create({ input: "I want to kill them." });

                console.log(moderation);
              }
              main();
          response: &moderation_example |
            {
              "id": "modr-XXXXX",
              "model": "text-moderation-005",
              "results": [
                {
                  "flagged": true,
                  "categories": {
                    "sexual": false,
                    "hate": false,
                    "harassment": false,
                    "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": 1.2282071e-06,
                    "hate": 0.010696256,
                    "harassment": 0.29842457,
                    "self-harm": 1.5236925e-08,
                    "sexual/minors": 5.7246268e-08,
                    "hate/threatening": 0.0060676364,
                    "violence/graphic": 4.435014e-06,
                    "self-harm/intent": 8.098441e-10,
                    "self-harm/instructions": 2.8498655e-11,
                    "harassment/threatening": 0.63055265,
                    "violence": 0.99011886,
                  }
                }
              ]
            }

  /assistants:
    get:
      operationId: listAssistants
      tags:
        - Assistants
      summary: Returns a list of assistants.
      parameters:
        - name: limit
          in: query
          description: &pagination_limit_param_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: &pagination_order_param_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: &pagination_after_param_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: &pagination_before_param_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, ending 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:
          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: |
              from openai import OpenAI
              client = OpenAI()

              my_assistants = client.beta.assistants.list(
                  order="desc",
                  limit="20",
              )
              print(my_assistants.data)
            node.js: |-
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const myAssistants = await openai.beta.assistants.list({
                  order: "desc",
                  limit: "20",
                });

                console.log(myAssistants.data);
              }

              main();
          response: &list_assistants_example |
            {
              "object": "list",
              "data": [
                {
                  "id": "asst_abc123",
                  "object": "assistant",
                  "created_at": 1698982736,
                  "name": "Coding Tutor",
                  "description": null,
                  "model": "gpt-4-turbo",
                  "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-4-turbo",
                  "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-4-turbo",
                  "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
            }
    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-4-turbo"
                  }'

              python: |
                from openai import OpenAI
                client = OpenAI()

                my_assistant = client.beta.assistants.create(
                    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-4-turbo",
                )
                print(my_assistant)
              node.js: |-
                import OpenAI from "openai";

                const openai = new OpenAI();

                async function main() {
                  const myAssistant = await openai.beta.assistants.create({
                    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-4-turbo",
                  });

                  console.log(myAssistant);
                }

                main();
            response: &create_assistants_example |
              {
                "id": "asst_abc123",
                "object": "assistant",
                "created_at": 1698984975,
                "name": "Math Tutor",
                "description": null,
                "model": "gpt-4-turbo",
                "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-4-turbo"
                  }'
              python: |
                from openai import OpenAI
                client = OpenAI()

                my_assistant = client.beta.assistants.create(
                    instructions="You are an HR bot, and you have access to files to answer employee questions about company policies.",
                    name="HR Helper",
                    tools=[{"type": "file_search"}],
                    tool_resources={"file_search": {"vector_store_ids": ["vs_123"]}},
                    model="gpt-4-turbo"
                )
                print(my_assistant)
              node.js: |-
                import OpenAI from "openai";

                const openai = new OpenAI();

                async function main() {
                  const myAssistant = await openai.beta.assistants.create({
                    instructions:
                      "You are an HR bot, and you have access to files to answer employee questions about company policies.",
                    name: "HR Helper",
                    tools: [{ type: "file_search" }],
                    tool_resources: {
                      file_search: {
                        vector_store_ids: ["vs_123"]
                      }
                    },
                    model: "gpt-4-turbo"
                  });

                  console.log(myAssistant);
                }

                main();
            response: |
              {
                "id": "asst_abc123",
                "object": "assistant",
                "created_at": 1699009403,
                "name": "HR Helper",
                "description": null,
                "model": "gpt-4-turbo",
                "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:
          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: |
              from openai import OpenAI
              client = OpenAI()

              my_assistant = client.beta.assistants.retrieve("asst_abc123")
              print(my_assistant)
            node.js: |-
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const myAssistant = await openai.beta.assistants.retrieve(
                  "asst_abc123"
                );

                console.log(myAssistant);
              }

              main();
          response: |
            {
              "id": "asst_abc123",
              "object": "assistant",
              "created_at": 1699009709,
              "name": "HR Helper",
              "description": null,
              "model": "gpt-4-turbo",
              "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"
            }
    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:
          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-4-turbo"
                  }'
            python: |
              from openai import OpenAI
              client = OpenAI()

              my_updated_assistant = client.beta.assistants.update(
                "asst_abc123",
                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.",
                name="HR Helper",
                tools=[{"type": "file_search"}],
                model="gpt-4-turbo"
              )

              print(my_updated_assistant)
            node.js: |-
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const myUpdatedAssistant = await openai.beta.assistants.update(
                  "asst_abc123",
                  {
                    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.",
                    name: "HR Helper",
                    tools: [{ type: "file_search" }],
                    model: "gpt-4-turbo"
                  }
                );

                console.log(myUpdatedAssistant);
              }

              main();
          response: |
            {
              "id": "asst_123",
              "object": "assistant",
              "created_at": 1699009709,
              "name": "HR Helper",
              "description": null,
              "model": "gpt-4-turbo",
              "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"
            }
    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:
          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: |
              from openai import OpenAI
              client = OpenAI()

              response = client.beta.assistants.delete("asst_abc123")
              print(response)
            node.js: |-
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const response = await openai.beta.assistants.del("asst_abc123");

                console.log(response);
              }
              main();
          response: |
            {
              "id": "asst_abc123",
              "object": "assistant.deleted",
              "deleted": true
            }

  /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: |
                from openai import OpenAI
                client = OpenAI()

                empty_thread = client.beta.threads.create()
                print(empty_thread)
              node.js: |-
                import OpenAI from "openai";

                const openai = new OpenAI();

                async function main() {
                  const emptyThread = await openai.beta.threads.create();

                  console.log(emptyThread);
                }

                main();
            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: |
                from openai import OpenAI
                client = OpenAI()

                message_thread = client.beta.threads.create(
                  messages=[
                    {
                      "role": "user",
                      "content": "Hello, what is AI?"
                    },
                    {
                      "role": "user",
                      "content": "How does AI work? Explain it in simple terms."
                    },
                  ]
                )

                print(message_thread)
              node.js: |-
                import OpenAI from "openai";

                const openai = new OpenAI();

                async function main() {
                  const messageThread = await openai.beta.threads.create({
                    messages: [
                      {
                        role: "user",
                        content: "Hello, what is AI?"
                      },
                      {
                        role: "user",
                        content: "How does AI work? Explain it in simple terms.",
                      },
                    ],
                  });

                  console.log(messageThread);
                }

                main();
            response: |
              {
                "id": "thread_abc123",
                "object": "thread",
                "created_at": 1699014083,
                "metadata": {},
                "tool_resources": {}
              }

  /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:
          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: |
              from openai import OpenAI
              client = OpenAI()

              my_thread = client.beta.threads.retrieve("thread_abc123")
              print(my_thread)
            node.js: |-
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const myThread = await openai.beta.threads.retrieve(
                  "thread_abc123"
                );

                console.log(myThread);
              }

              main();
          response: |
            {
              "id": "thread_abc123",
              "object": "thread",
              "created_at": 1699014083,
              "metadata": {},
              "tool_resources": {
                "code_interpreter": {
                  "file_ids": []
                }
              }
            }
    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:
          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: |
              from openai import OpenAI
              client = OpenAI()

              my_updated_thread = client.beta.threads.update(
                "thread_abc123",
                metadata={
                  "modified": "true",
                  "user": "abc123"
                }
              )
              print(my_updated_thread)
            node.js: |-
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const updatedThread = await openai.beta.threads.update(
                  "thread_abc123",
                  {
                    metadata: { modified: "true", user: "abc123" },
                  }
                );

                console.log(updatedThread);
              }

              main();
          response: |
            {
              "id": "thread_abc123",
              "object": "thread",
              "created_at": 1699014083,
              "metadata": {
                "modified": "true",
                "user": "abc123"
              },
              "tool_resources": {}
            }
    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:
          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: |
              from openai import OpenAI
              client = OpenAI()

              response = client.beta.threads.delete("thread_abc123")
              print(response)
            node.js: |-
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const response = await openai.beta.threads.del("thread_abc123");

                console.log(response);
              }
              main();
          response: |
            {
              "id": "thread_abc123",
              "object": "thread.deleted",
              "deleted": true
            }

  /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: *pagination_limit_param_description
          required: false
          schema:
            type: integer
            default: 20
        - name: order
          in: query
          description: *pagination_order_param_description
          schema:
            type: string
            default: desc
            enum: ["asc", "desc"]
        - name: after
          in: query
          description: *pagination_after_param_description
          schema:
            type: string
        - name: before
          in: query
          description: *pagination_before_param_description
          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:
          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: |
              from openai import OpenAI
              client = OpenAI()

              thread_messages = client.beta.threads.messages.list("thread_abc123")
              print(thread_messages.data)
            node.js: |-
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const threadMessages = await openai.beta.threads.messages.list(
                  "thread_abc123"
                );

                console.log(threadMessages.data);
              }

              main();
          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
            }
    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:
          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: |
              from openai import OpenAI
              client = OpenAI()

              thread_message = client.beta.threads.messages.create(
                "thread_abc123",
                role="user",
                content="How does AI work? Explain it in simple terms.",
              )
              print(thread_message)
            node.js: |-
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const threadMessages = await openai.beta.threads.messages.create(
                  "thread_abc123",
                  { role: "user", content: "How does AI work? Explain it in simple terms." }
                );

                console.log(threadMessages);
              }

              main();
          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": {}
            }

  /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/threads/messages/object) object matching the specified ID.
        examples:
          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: |
              from openai import OpenAI
              client = OpenAI()

              message = client.beta.threads.messages.retrieve(
                message_id="msg_abc123",
                thread_id="thread_abc123",
              )
              print(message)
            node.js: |-
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const message = await openai.beta.threads.messages.retrieve(
                  "thread_abc123",
                  "msg_abc123"
                );

                console.log(message);
              }

              main();
          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": {}
            }
    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/threads/messages/object) object.
        examples:
          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: |
              from openai import OpenAI
              client = OpenAI()

              message = client.beta.threads.messages.update(
                message_id="msg_abc12",
                thread_id="thread_abc123",
                metadata={
                  "modified": "true",
                  "user": "abc123",
                },
              )
              print(message)
            node.js: |-
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const message = await openai.beta.threads.messages.update(
                  "thread_abc123",
                  "msg_abc123",
                  {
                    metadata: {
                      modified: "true",
                      user: "abc123",
                    },
                  }
                }'
          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"
              }
            }
    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:
          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: |
              from openai import OpenAI
              client = OpenAI()

              deleted_message = client.beta.threads.messages.delete(
                message_id="msg_abc12",
                thread_id="thread_abc123",
              )
              print(deleted_message)
            node.js: |-
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const deletedMessage = await openai.beta.threads.messages.del(
                  "thread_abc123",
                  "msg_abc123"
                );

                console.log(deletedMessage);
              }
          response: |
            {
              "id": "msg_abc123",
              "object": "thread.message.deleted",
              "deleted": true
            }

  /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: |
                from openai import OpenAI
                client = OpenAI()

                run = client.beta.threads.create_and_run(
                  assistant_id="asst_abc123",
                  thread={
                    "messages": [
                      {"role": "user", "content": "Explain deep learning to a 5 year old."}
                    ]
                  }
                )

                print(run)
              node.js: |
                import OpenAI from "openai";

                const openai = new OpenAI();

                async function main() {
                  const run = await openai.beta.threads.createAndRun({
                    assistant_id: "asst_abc123",
                    thread: {
                      messages: [
                        { role: "user", content: "Explain deep learning to a 5 year old." },
                      ],
                    },
                  });

                  console.log(run);
                }

                main();
            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-4-turbo",
                "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"
              }

          - 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: |
                from openai import OpenAI
                client = OpenAI()

                stream = client.beta.threads.create_and_run(
                  assistant_id="asst_123",
                  thread={
                    "messages": [
                      {"role": "user", "content": "Hello"}
                    ]
                  },
                  stream=True
                )

                for event in stream:
                  print(event)
              node.js: |
                import OpenAI from "openai";

                const openai = new OpenAI();

                async function main() {
                  const stream = await openai.beta.threads.createAndRun({
                      assistant_id: "asst_123",
                      thread: {
                        messages: [
                          { role: "user", content: "Hello" },
                        ],
                      },
                      stream: true
                  });

                  for await (const event of stream) {
                    console.log(event);
                  }
                }

                main();
            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-4-turbo","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"}

              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-4-turbo","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"}

              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-4-turbo","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"}

              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-4-turbo","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"}

              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: |
                from openai import OpenAI
                client = OpenAI()

                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 = client.beta.threads.create_and_run(
                  thread={
                      "messages": [
                        {"role": "user", "content": "What is the weather like in San Francisco?"}
                      ]
                  },
                  assistant_id="asst_abc123",
                  tools=tools,
                  stream=True
                )

                for event in stream:
                  print(event)
              node.js: |
                import OpenAI from "openai";

                const openai = new OpenAI();

                const 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"],
                        },
                      }
                    }
                ];

                async function main() {
                  const stream = await openai.beta.threads.createAndRun({
                    assistant_id: "asst_123",
                    thread: {
                      messages: [
                        { role: "user", content: "What is the weather like in San Francisco?" },
                      ],
                    },
                    tools: tools,
                    stream: true
                  });

                  for await (const event of stream) {
                    console.log(event);
                  }
                }

                main();
            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-4-turbo","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"}}

              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-4-turbo","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"}}

              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-4-turbo","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"}}

              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-4-turbo","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"}}

              event: done
              data: [DONE]

  /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: *pagination_limit_param_description
          required: false
          schema:
            type: integer
            default: 20
        - name: order
          in: query
          description: *pagination_order_param_description
          schema:
            type: string
            default: desc
            enum: ["asc", "desc"]
        - name: after
          in: query
          description: *pagination_after_param_description
          schema:
            type: string
        - name: before
          in: query
          description: *pagination_before_param_description
          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:
          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: |
              from openai import OpenAI
              client = OpenAI()

              runs = client.beta.threads.runs.list(
                "thread_abc123"
              )

              print(runs)
            node.js: |
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const runs = await openai.beta.threads.runs.list(
                  "thread_abc123"
                );

                console.log(runs);
              }

              main();
          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-4-turbo",
                  "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"
                },
                {
                  "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-4-turbo",
                  "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"
                }
              ],
              "first_id": "run_abc123",
              "last_id": "run_abc456",
              "has_more": false
            }
    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.
      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: |
                from openai import OpenAI
                client = OpenAI()

                run = client.beta.threads.runs.create(
                  thread_id="thread_abc123",
                  assistant_id="asst_abc123"
                )

                print(run)
              node.js: |
                import OpenAI from "openai";

                const openai = new OpenAI();

                async function main() {
                  const run = await openai.beta.threads.runs.create(
                    "thread_abc123",
                    { assistant_id: "asst_abc123" }
                  );

                  console.log(run);
                }

                main();
            response: &run_object_example |
              {
                "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-4-turbo",
                "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"
              }
          - 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: |
                from openai import OpenAI
                client = OpenAI()

                stream = client.beta.threads.runs.create(
                  thread_id="thread_123",
                  assistant_id="asst_123",
                  stream=True
                )

                for event in stream:
                  print(event)
              node.js: |
                import OpenAI from "openai";

                const openai = new OpenAI();

                async function main() {
                  const stream = await openai.beta.threads.runs.create(
                    "thread_123",
                    { assistant_id: "asst_123", stream: true }
                  );

                  for await (const event of stream) {
                    console.log(event);
                  }
                }

                main();
            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-4-turbo","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"}}

              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-4-turbo","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"}}

              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-4-turbo","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"}}

              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-4-turbo","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"}}

              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: |
                from openai import OpenAI
                client = OpenAI()

                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 = client.beta.threads.runs.create(
                  thread_id="thread_abc123",
                  assistant_id="asst_abc123",
                  tools=tools,
                  stream=True
                )

                for event in stream:
                  print(event)
              node.js: |
                import OpenAI from "openai";

                const openai = new OpenAI();

                const 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"],
                        },
                      }
                    }
                ];

                async function main() {
                  const stream = await openai.beta.threads.runs.create(
                    "thread_abc123",
                    {
                      assistant_id: "asst_abc123",
                      tools: tools,
                      stream: true
                    }
                  );

                  for await (const event of stream) {
                    console.log(event);
                  }
                }

                main();
            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-4-turbo","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"}}

              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-4-turbo","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"}}

              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-4-turbo","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"}}

              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-4-turbo","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"}}

              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:
          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: |
              from openai import OpenAI
              client = OpenAI()

              run = client.beta.threads.runs.retrieve(
                thread_id="thread_abc123",
                run_id="run_abc123"
              )

              print(run)
            node.js: |
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const run = await openai.beta.threads.runs.retrieve(
                  "thread_abc123",
                  "run_abc123"
                );

                console.log(run);
              }

              main();
          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-4-turbo",
              "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"
            }
    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:
          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: |
              from openai import OpenAI
              client = OpenAI()

              run = client.beta.threads.runs.update(
                thread_id="thread_abc123",
                run_id="run_abc123",
                metadata={"user_id": "user_abc123"},
              )

              print(run)
            node.js: |
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const run = await openai.beta.threads.runs.update(
                  "thread_abc123",
                  "run_abc123",
                  {
                    metadata: {
                      user_id: "user_abc123",
                    },
                  }
                );

                console.log(run);
              }

              main();
          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-4-turbo",
              "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"
            }

  /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: |
                from openai import OpenAI
                client = OpenAI()

                run = client.beta.threads.runs.submit_tool_outputs(
                  thread_id="thread_123",
                  run_id="run_123",
                  tool_outputs=[
                    {
                      "tool_call_id": "call_001",
                      "output": "70 degrees and sunny."
                    }
                  ]
                )

                print(run)
              node.js: |
                import OpenAI from "openai";

                const openai = new OpenAI();

                async function main() {
                  const run = await openai.beta.threads.runs.submitToolOutputs(
                    "thread_123",
                    "run_123",
                    {
                      tool_outputs: [
                        {
                          tool_call_id: "call_001",
                          output: "70 degrees and sunny.",
                        },
                      ],
                    }
                  );

                  console.log(run);
                }

                main();
            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-4-turbo",
                "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"
              }

          - 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: |
                from openai import OpenAI
                client = OpenAI()

                stream = client.beta.threads.runs.submit_tool_outputs(
                  thread_id="thread_123",
                  run_id="run_123",
                  tool_outputs=[
                    {
                      "tool_call_id": "call_001",
                      "output": "70 degrees and sunny."
                    }
                  ],
                  stream=True
                )

                for event in stream:
                  print(event)
              node.js: |
                import OpenAI from "openai";

                const openai = new OpenAI();

                async function main() {
                  const stream = await openai.beta.threads.runs.submitToolOutputs(
                    "thread_123",
                    "run_123",
                    {
                      tool_outputs: [
                        {
                          tool_call_id: "call_001",
                          output: "70 degrees and sunny.",
                        },
                      ],
                    }
                  );

                  for await (const event of stream) {
                    console.log(event);
                  }
                }

                main();
            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-4-turbo","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"}}

              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-4-turbo","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"}}

              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-4-turbo","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"}}

              event: done
              data: [DONE]

  /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:
          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: |
              from openai import OpenAI
              client = OpenAI()

              run = client.beta.threads.runs.cancel(
                thread_id="thread_abc123",
                run_id="run_abc123"
              )

              print(run)
            node.js: |
              import OpenAI from "openai";

              const openai = new OpenAI();

              async function main() {
                const run = await openai.beta.threads.runs.cancel(
                  "thread_abc123",
                  "run_abc123"
                );

                console.log(run);
              }

              main();
          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-4-turbo",
              "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"
            }

  /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: *pagination_limit_param_description
          required: false
          schema:
            type: integer
            default: 20
        - name: order
          in: query
          description: *pagination_order_param_description
          schema:
            type: string
            default: desc
            enum: ["asc", "desc"]
        - name: after
          in: query
          description: *pagination_after_param_description
          schema:
            type: string
        - name: before
          in: query
          description: *pagination_before_param_description
          schema:
            type: string
      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/runs/step-object) objects.
        examples:
          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: |
              from openai import OpenAI
              client = OpenAI()

              run_steps = client.beta.threads.runs.steps.list(
                  thread_id="thread_abc123",
                  run_id="run_abc123"
              )

              print(run_steps)
            node.js: |
              import OpenAI from "openai";
              const openai = new OpenAI();

              async function main() {
                const runStep = await openai.beta.threads.runs.steps.list(
                  "thread_abc123",
                  "run_abc123"
                );
                console.log(runStep);
              }

              main();
          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
            }

  /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.
      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/runs/step-object) object matching the specified ID.
        examples:
          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: |
              from openai import OpenAI
              client = OpenAI()

              run_step = client.beta.threads.runs.steps.retrieve(
                  thread_id="thread_abc123",
                  run_id="run_abc123",
                  step_id="step_abc123"
              )

              print(run_step)
            node.js: |
              import OpenAI from "openai";
              const openai = new OpenAI();

              async function main() {
                const runStep = await openai.beta.threads.runs.steps.retrieve(
                  "thread_abc123",
                  "run_abc123",
                  "step_abc123"
                );
                console.log(runStep);
              }

              main();
          response: &run_step_object_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
              }
            }

  /vector_stores:
    get:
      operationId: listVectorStores
      tags:
        - Vector Stores
      summary: Returns a list of vector stores.
      parameters:
        - name: limit
          in: query
          description: *pagination_limit_param_description
          required: false
          schema:
            type: integer
            default: 20
        - name: order
          in: query
          description: *pagination_order_param_description
          schema:
            type: string
            default: desc
            enum: ["asc", "desc"]
        - name: after
          in: query
          description: *pagination_after_param_description
          schema:
            type: string
        - name: before
          in: query
          description: *pagination_before_param_description
          schema:
            type: string
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ListVectorStoresResponse"
      x-oaiMeta:
        name: List vector stores
        group: vector_stores
        beta: true
        returns: A list of [vector store](/docs/api-reference/vector-stores/object) objects.
        examples:
          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: |
              from openai import OpenAI
              client = OpenAI()

              vector_stores = client.beta.vector_stores.list()
              print(vector_stores)
            node.js: |
              import OpenAI from "openai";
              const openai = new OpenAI();

              async function main() {
                const vectorStores = await openai.beta.vectorStores.list();
                console.log(vectorStores);
              }

              main();
          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
            }
    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
        beta: true
        returns: A [vector store](/docs/api-reference/vector-stores/object) object.
        examples:
          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: |
              from openai import OpenAI
              client = OpenAI()

              vector_store = client.beta.vector_stores.create(
                name="Support FAQ"
              )
              print(vector_store)
            node.js: |
              import OpenAI from "openai";
              const openai = new OpenAI();

              async function main() {
                const vectorStore = await openai.beta.vectorStores.create({
                  name: "Support FAQ"
                });
                console.log(vectorStore);
              }

              main();
          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
              }
            }

  /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
        beta: true
        returns: The [vector store](/docs/api-reference/vector-stores/object) object matching the specified ID.
        examples:
          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: |
              from openai import OpenAI
              client = OpenAI()

              vector_store = client.beta.vector_stores.retrieve(
                vector_store_id="vs_abc123"
              )
              print(vector_store)
            node.js: |
              import OpenAI from "openai";
              const openai = new OpenAI();

              async function main() {
                const vectorStore = await openai.beta.vectorStores.retrieve(
                  "vs_abc123"
                );
                console.log(vectorStore);
              }

              main();
          response: |
            {
              "id": "vs_abc123",
              "object": "vector_store",
              "created_at": 1699061776
            }
    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
        beta: true
        returns: The modified [vector store](/docs/api-reference/vector-stores/object) object.
        examples:
          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: |
              from openai import OpenAI
              client = OpenAI()

              vector_store = client.beta.vector_stores.update(
                vector_store_id="vs_abc123",
                name="Support FAQ"
              )
              print(vector_store)
            node.js: |
              import OpenAI from "openai";
              const openai = new OpenAI();

              async function main() {
                const vectorStore = await openai.beta.vectorStores.update(
                  "vs_abc123",
                  {
                    name: "Support FAQ"
                  }
                );
                console.log(vectorStore);
              }

              main();
          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
              }
            }

    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
        beta: true
        returns: Deletion status
        examples:
          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: |
              from openai import OpenAI
              client = OpenAI()

              deleted_vector_store = client.beta.vector_stores.delete(
                vector_store_id="vs_abc123"
              )
              print(deleted_vector_store)
            node.js: |
              import OpenAI from "openai";
              const openai = new OpenAI();

              async function main() {
                const deletedVectorStore = await openai.beta.vectorStores.del(
                  "vs_abc123"
                );
                console.log(deletedVectorStore);
              }

              main();
          response: |
            {
              id: "vs_abc123",
              object: "vector_store.deleted",
              deleted: true
            }

  /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: *pagination_limit_param_description
          required: false
          schema:
            type: integer
            default: 20
        - name: order
          in: query
          description: *pagination_order_param_description
          schema:
            type: string
            default: desc
            enum: ["asc", "desc"]
        - name: after
          in: query
          description: *pagination_after_param_description
          schema:
            type: string
        - name: before
          in: query
          description: *pagination_before_param_description
          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
        beta: true
        returns: A list of [vector store file](/docs/api-reference/vector-stores-files/file-object) objects.
        examples:
          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: |
              from openai import OpenAI
              client = OpenAI()

              vector_store_files = client.beta.vector_stores.files.list(
                vector_store_id="vs_abc123"
              )
              print(vector_store_files)
            node.js: |
              import OpenAI from "openai";
              const openai = new OpenAI();

              async function main() {
                const vectorStoreFiles = await openai.beta.vectorStores.files.list(
                  "vs_abc123"
                );
                console.log(vectorStoreFiles);
              }

              main();
          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
            }
    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
        beta: true
        returns: A [vector store file](/docs/api-reference/vector-stores-files/file-object) object.
        examples:
          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: |
              from openai import OpenAI
              client = OpenAI()

              vector_store_file = client.beta.vector_stores.files.create(
                vector_store_id="vs_abc123",
                file_id="file-abc123"
              )
              print(vector_store_file)
            node.js: |
              import OpenAI from "openai";
              const openai = new OpenAI();

              async function main() {
                const myVectorStoreFile = await openai.beta.vectorStores.files.create(
                  "vs_abc123",
                  {
                    file_id: "file-abc123"
                  }
                );
                console.log(myVectorStoreFile);
              }

              main();
          response: |
            {
              "id": "file-abc123",
              "object": "vector_store.file",
              "created_at": 1699061776,
              "usage_bytes": 1234,
              "vector_store_id": "vs_abcd",
              "status": "completed",
              "last_error": null
            }

  /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
        beta: true
        returns: The [vector store file](/docs/api-reference/vector-stores-files/file-object) object.
        examples:
          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: |
              from openai import OpenAI
              client = OpenAI()

              vector_store_file = client.beta.vector_stores.files.retrieve(
                vector_store_id="vs_abc123",
                file_id="file-abc123"
              )
              print(vector_store_file)
            node.js: |
              import OpenAI from "openai";
              const openai = new OpenAI();

              async function main() {
                const vectorStoreFile = await openai.beta.vectorStores.files.retrieve(
                  "vs_abc123",
                  "file-abc123"
                );
                console.log(vectorStoreFile);
              }

              main();
          response: |
            {
              "id": "file-abc123",
              "object": "vector_store.file",
              "created_at": 1699061776,
              "vector_store_id": "vs_abcd",
              "status": "completed",
              "last_error": null
            }
    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
        beta: true
        returns: Deletion status
        examples:
          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: |
              from openai import OpenAI
              client = OpenAI()

              deleted_vector_store_file = client.beta.vector_stores.files.delete(
                  vector_store_id="vs_abc123",
                  file_id="file-abc123"
              )
              print(deleted_vector_store_file)
            node.js: |
              import OpenAI from "openai";
              const openai = new OpenAI();

              async function main() {
                const deletedVectorStoreFile = await openai.beta.vectorStores.files.del(
                  "vs_abc123",
                  "file-abc123"
                );
                console.log(deletedVectorStoreFile);
              }

              main();
          response: |
            {
              id: "file-abc123",
              object: "vector_store.file.deleted",
              deleted: true
            }

  /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
        beta: true
        returns: A [vector store file batch](/docs/api-reference/vector-stores-file-batches/batch-object) object.
        examples:
          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: |
              from openai import OpenAI
              client = OpenAI()

              vector_store_file_batch = client.beta.vector_stores.file_batches.create(
                vector_store_id="vs_abc123",
                file_ids=["file-abc123", "file-abc456"]
              )
              print(vector_store_file_batch)
            node.js: |
              import OpenAI from "openai";
              const openai = new OpenAI();

              async function main() {
                const myVectorStoreFileBatch = await openai.beta.vectorStores.fileBatches.create(
                  "vs_abc123",
                  {
                    file_ids: ["file-abc123", "file-abc456"]
                  }
                );
                console.log(myVectorStoreFileBatch);
              }

              main();
          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,
              }
            }

  /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
        beta: true
        returns: The [vector store file batch](/docs/api-reference/vector-stores-file-batches/batch-object) object.
        examples:
          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: |
              from openai import OpenAI
              client = OpenAI()

              vector_store_file_batch = client.beta.vector_stores.file_batches.retrieve(
                vector_store_id="vs_abc123",
                batch_id="vsfb_abc123"
              )
              print(vector_store_file_batch)
            node.js: |
              import OpenAI from "openai";
              const openai = new OpenAI();

              async function main() {
                const vectorStoreFileBatch = await openai.beta.vectorStores.fileBatches.retrieve(
                  "vs_abc123",
                  "vsfb_abc123"
                );
                console.log(vectorStoreFileBatch);
              }

              main();
          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,
              }
            }

  /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
        beta: true
        returns: The modified vector store file batch object.
        examples:
          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: |
              from openai import OpenAI
              client = OpenAI()

              deleted_vector_store_file_batch = client.beta.vector_stores.file_batches.cancel(
                  vector_store_id="vs_abc123",
                  file_batch_id="vsfb_abc123"
              )
              print(deleted_vector_store_file_batch)
            node.js: |
              import OpenAI from "openai";
              const openai = new OpenAI();

              async function main() {
                const deletedVectorStoreFileBatch = await openai.vector_stores.fileBatches.cancel(
                  "vs_abc123",
                  "vsfb_abc123"
                );
                console.log(deletedVectorStoreFileBatch);
              }

              main();
          response: |
            {
              "id": "vsfb_abc123",
              "object": "vector_store.file_batch",
              "created_at": 1699061776,
              "vector_store_id": "vs_abc123",
              "status": "cancelling",
              "file_counts": {
                "in_progress": 12,
                "completed": 3,
                "failed": 0,
                "cancelled": 0,
                "total": 15,
              }
            }

  /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: *pagination_limit_param_description
          required: false
          schema:
            type: integer
            default: 20
        - name: order
          in: query
          description: *pagination_order_param_description
          schema:
            type: string
            default: desc
            enum: ["asc", "desc"]
        - name: after
          in: query
          description: *pagination_after_param_description
          schema:
            type: string
        - name: before
          in: query
          description: *pagination_before_param_description
          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
        beta: true
        returns: A list of [vector store file](/docs/api-reference/vector-stores-files/file-object) objects.
        examples:
          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: |
              from openai import OpenAI
              client = OpenAI()

              vector_store_files = client.beta.vector_stores.file_batches.list_files(
                vector_store_id="vs_abc123",
                batch_id="vsfb_abc123"
              )
              print(vector_store_files)
            node.js: |
              import OpenAI from "openai";
              const openai = new OpenAI();

              async function main() {
                const vectorStoreFiles = await openai.beta.vectorStores.fileBatches.listFiles(
                  "vs_abc123",
                  "vsfb_abc123"
                );
                console.log(vectorStoreFiles);
              }

              main();
          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
            }

  /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/requestInput), and must be uploaded with the purpose `batch`.
                endpoint:
                  type: string
                  enum: ["/v1/chat/completions", "/v1/embeddings"]
                  description: The endpoint to be used for all requests in the batch. Currently `/v1/chat/completions` and `/v1/embeddings` are supported.
                completion_window:
                  type: string
                  enum: ["24h"]
                  description: The time frame within which the batch should be processed. Currently only `24h` is supported.
                metadata:
                  type: object
                  additionalProperties:
                    type: string
                  description: Optional custom metadata for the batch.
                  nullable: true
      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:
          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: |
              from openai import OpenAI
              client = OpenAI()

              client.batches.create(
                input_file_id="file-abc123",
                endpoint="/v1/chat/completions",
                completion_window="24h"
              )
            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();
          response: |
            {
              "id": "batch_abc123",
              "object": "batch",
              "endpoint": "/v1/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",
              }
            }
    get:
      operationId: listBatches
      tags:
        - Batch
      summary: List your organization's batches.
      parameters:
        - in: query
          name: after
          required: false
          schema:
            type: string
          description: *pagination_after_param_description
        - name: limit
          in: query
          description: *pagination_limit_param_description
          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:
          request:
            curl: |
              curl https://api.openai.com/v1/batches?limit=2 \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json"
            python: |
              from openai import OpenAI
              client = OpenAI()

              client.batches.list()
            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();
          response: |
            {
              "object": "list",
              "data": [
                {
                  "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 job",
                  }
                },
                { ... },
              ],
              "first_id": "batch_abc123",
              "last_id": "batch_abc456",
              "has_more": true
            }

  /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:
          request:
            curl: |
              curl https://api.openai.com/v1/batches/batch_abc123 \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
            python: |
              from openai import OpenAI
              client = OpenAI()

              client.batches.retrieve("batch_abc123")
            node: |
              import OpenAI from "openai";

              const openai = new OpenAI();

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

                console.log(batch);
              }

              main();
          response: &batch_object |
            {
              "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",
              }
            }

  /batches/{batch_id}/cancel:
    post:
      operationId: cancelBatch
      tags:
        - Batch
      summary: Cancels an in-progress batch.
      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:
          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: |
              from openai import OpenAI
              client = OpenAI()

              client.batches.cancel("batch_abc123")
            node: |
              import OpenAI from "openai";

              const openai = new OpenAI();

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

                console.log(batch);
              }

              main();
          response: |
            {
              "id": "batch_abc123",
              "object": "batch",
              "endpoint": "/v1/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",
              }
            }

components:
  securitySchemes:
    ApiKeyAuth:
      type: http
      scheme: "bearer"

  schemas:
    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
    ErrorResponse:
      type: object
      properties:
        error:
          $ref: "#/components/schemas/Error"
      required:
        - error

    ListModelsResponse:
      type: object
      properties:
        object:
          type: string
          enum: [list]
        data:
          type: array
          items:
            $ref: "#/components/schemas/Model"
      required:
        - object
        - data
    DeleteModelResponse:
      type: object
      properties:
        id:
          type: string
        deleted:
          type: boolean
        object:
          type: string
      required:
        - id
        - object
        - deleted

    CreateCompletionRequest:
      type: object
      properties:
        model:
          description: &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/overview) for descriptions of them.
          anyOf:
            - type: string
            - type: string
              enum: ["gpt-3.5-turbo-instruct", "davinci-002", "babbage-002"]
          x-oaiTypeLabel: string
        prompt:
          description: &completions_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: &completions_best_of_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: &completions_echo_description >
            Echo back the prompt in addition to the completion
        frequency_penalty:
          type: number
          default: 0
          minimum: -2
          maximum: 2
          nullable: true
          description: &completions_frequency_penalty_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/parameter-details)
        logit_bias: &completions_logit_bias
          type: object
          x-oaiTypeLabel: map
          default: null
          nullable: true
          additionalProperties:
            type: integer
          description: &completions_logit_bias_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: &completions_logprobs_configuration
          type: integer
          minimum: 0
          maximum: 5
          default: null
          nullable: true
          description: &completions_logprobs_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: &completions_max_tokens_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: &completions_completions_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: &completions_presence_penalty_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/parameter-details)
        seed: &completions_seed_param
          type: integer
          minimum: -9223372036854775808
          maximum: 9223372036854775807
          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:
          description: &completions_stop_description >
            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: "\n"
              nullable: true
            - type: array
              minItems: 1
              maxItems: 4
              items:
                type: string
                example: '["\n"]'
        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: &completions_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.

            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: &completions_top_p_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: &end_user_param_configuration
          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: &completion_finish_reason_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:
          $ref: "#/components/schemas/ChatModel"
        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]
        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
            }
          }

    ChatCompletionRequestMessageContentPart:
      oneOf:
        - $ref: "#/components/schemas/ChatCompletionRequestMessageContentPartText"
        - $ref: "#/components/schemas/ChatCompletionRequestMessageContentPartImage"
      x-oaiExpandable: true

    ChatCompletionRequestMessageContentPartImage:
      type: object
      title: Image content part
      properties:
        type:
          type: string
          enum: ["image_url"]
          description: The type of the content part.
        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

    ChatCompletionRequestMessageContentPartText:
      type: object
      title: Text content part
      properties:
        type:
          type: string
          enum: ["text"]
          description: The type of the content part.
        text:
          type: string
          description: The text content.
      required:
        - type
        - text

    ChatCompletionRequestMessage:
      oneOf:
        - $ref: "#/components/schemas/ChatCompletionRequestSystemMessage"
        - $ref: "#/components/schemas/ChatCompletionRequestUserMessage"
        - $ref: "#/components/schemas/ChatCompletionRequestAssistantMessage"
        - $ref: "#/components/schemas/ChatCompletionRequestToolMessage"
        - $ref: "#/components/schemas/ChatCompletionRequestFunctionMessage"
      x-oaiExpandable: true

    ChatCompletionRequestSystemMessage:
      type: object
      title: System message
      properties:
        content:
          description: The contents of the system message.
          type: string
        role:
          $ref: "#/components/schemas/ChatCompletionRole"
        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

    ChatCompletionRequestUserMessage:
      type: object
      title: User message
      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, each can be of type `text` or `image_url` when passing in images. You can pass multiple images by adding multiple `image_url` content parts. Image input is only supported when using the `gpt-4-visual-preview` model.
              title: Array of content parts
              items:
                $ref: "#/components/schemas/ChatCompletionRequestMessageContentPart"
              minItems: 1
          x-oaiExpandable: true
        role:
          $ref: "#/components/schemas/ChatCompletionRole"
        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

    ChatCompletionRequestAssistantMessage:
      type: object
      title: Assistant message
      properties:
        content:
          nullable: true
          type: string
          description: |
            The contents of the assistant message. Required unless `tool_calls` or `function_call` is specified.
        role:
          $ref: "#/components/schemas/ChatCompletionRole"
        name:
          type: string
          description: An optional name for the participant. Provides the model information to differentiate between participants of the same role.
        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."
          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

    ChatCompletionRequestToolMessage:
      type: object
      title: Tool message
      properties:
        role:
          $ref: "#/components/schemas/ChatCompletionRole"
        content:
          type: string
          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

    ChatCompletionRequestFunctionMessage:
      type: object
      title: Function message
      deprecated: true
      properties:
        role:
          $ref: "#/components/schemas/ChatCompletionRole"
        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

    FunctionParameters:
      type: object
      description: "The parameters the functions accepts, described as a JSON Schema object. See the [guide](/docs/guides/text-generation/function-calling) for examples, and the [JSON Schema reference](https://json-schema.org/understanding-json-schema/) for documentation about the format. \n\nOmitting `parameters` defines a function with an empty parameter list."
      additionalProperties: true

    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

    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

    ChatCompletionTool:
      type: object
      properties:
        type:
          type: string
          enum: ["function"]
          description: The type of the tool. Currently, only `function` is supported.
        function:
          $ref: "#/components/schemas/FunctionObject"
      required:
        - type
        - function

    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"
      required:
        - name

    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"
      x-oaiExpandable: true

    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.
        function:
          type: object
          properties:
            name:
              type: string
              description: The name of the function to call.
          required:
            - name
      required:
        - type
        - function

    ChatCompletionMessageToolCalls:
      type: array
      description: The tool calls generated by the model, such as function calls.
      items:
        $ref: "#/components/schemas/ChatCompletionMessageToolCall"

    ChatCompletionMessageToolCall:
      type: object
      properties:
        # TODO: index included when streaming
        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.
        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.
        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

    # Note, this isn't referenced anywhere, but is kept as a convenience to record all possible roles in one place.
    ChatCompletionRole:
      type: string
      description: The role of the author of a message
      enum:
        - 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.

    ChatCompletionResponseMessage:
      type: object
      description: A chat completion message generated by the model.
      properties:
        content:
          type: string
          description: The contents of the message.
          nullable: true
        tool_calls:
          $ref: "#/components/schemas/ChatCompletionMessageToolCalls"
        role:
          $ref: "#/components/schemas/ChatCompletionRole"
        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
      required:
        - role
        - content

    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:
          $ref: "#/components/schemas/ChatCompletionRole"

    CreateChatCompletionRequest:
      type: object
      properties:
        messages:
          description: A list of messages comprising the conversation so far. [Example Python code](https://cookbook.openai.com/examples/how_to_format_inputs_to_chatgpt_models).
          type: array
          minItems: 1
          items:
            $ref: "#/components/schemas/ChatCompletionRequestMessage"
        model:
          $ref: "#/components/schemas/ChatModel"
        frequency_penalty:
          type: number
          default: 0
          minimum: -2
          maximum: 2
          nullable: true
          description: *completions_frequency_penalty_description
        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
        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
        max_tokens:
          description: |
            The maximum number of [tokens](/tokenizer) that can be generated in the chat completion.

            The total length of input tokens and generated tokens is limited by the model's context length. [Example Python code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken) for counting tokens.
          type: integer
          nullable: 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.
        presence_penalty:
          type: number
          default: 0
          minimum: -2
          maximum: 2
          nullable: true
          description: *completions_presence_penalty_description
        response_format:
          type: object
          description: |
            An object specifying the format that the model must output. Compatible with [GPT-4 Turbo](/docs/models/gpt-4-and-gpt-4-turbo) and all GPT-3.5 Turbo models newer than `gpt-3.5-turbo-1106`.

            Setting to `{ "type": "json_object" }` enables JSON mode, which guarantees 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.
          properties:
            type:
              type: string
              enum: ["text", "json_object"]
              example: "json_object"
              default: "text"
              description: Must be one of `text` or `json_object`.
        seed:
          type: integer
          minimum: -9223372036854775808
          maximum: 9223372036854775807
          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
        stop:
          description: |
            Up to 4 sequences where the API will stop generating further tokens.
          default: null
          oneOf:
            - type: string
              nullable: true
            - type: array
              minItems: 1
              maxItems: 4
              items:
                type: string
        stream:
          description: >
            If set, partial message deltas will be sent, like in ChatGPT. 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"
        temperature:
          type: number
          minimum: 0
          maximum: 2
          default: 1
          example: 1
          nullable: true
          description: *completions_temperature_description
        top_p:
          type: number
          minimum: 0
          maximum: 1
          default: 1
          example: 1
          nullable: true
          description: *completions_top_p_description
        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"
        user: *end_user_param_configuration
        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"
          x-oaiExpandable: true
        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: &chat_completion_finish_reason_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: &chat_completion_response_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
                required:
                  - content
        created:
          type: integer
          description: The Unix timestamp (in seconds) of when the chat completion was created.
        model:
          $ref: "#/components/schemas/ChatModel"
        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]
        usage:
          $ref: "#/components/schemas/CompletionUsage"
      required:
        - choices
        - created
        - id
        - model
        - object
      x-oaiMeta:
        name: The chat completion object
        group: chat
        example: *chat_completion_example

    CreateChatCompletionFunctionResponse:
      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:
                  &chat_completion_function_finish_reason_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, or `function_call` if the model called a function.
                enum: ["stop", "length", "function_call", "content_filter"]
              index:
                type: integer
                description: The index of the choice in the list of choices.
              message:
                $ref: "#/components/schemas/ChatCompletionResponseMessage"
        created:
          type: integer
          description: The Unix timestamp (in seconds) of when the chat completion was created.
        model:
          $ref: "#/components/schemas/ChatModel"
        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]
        usage:
          $ref: "#/components/schemas/CompletionUsage"
      required:
        - choices
        - created
        - id
        - model
        - object
      x-oaiMeta:
        name: The chat completion object
        group: chat
        example: *chat_completion_function_example

    ChatCompletionTokenLogprob:
      type: object
      properties:
        token: &chat_completion_response_logprobs_token
          description: The token.
          type: string
        logprob: &chat_completion_response_logprobs_token_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: &chat_completion_response_logprobs_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: *chat_completion_response_logprobs_token
              logprob: *chat_completion_response_logprobs_token_logprob
              bytes: *chat_completion_response_logprobs_bytes
            required:
              - token
              - logprob
              - bytes
      required:
        - token
        - logprob
        - bytes
        - top_logprobs

    ListPaginatedFineTuningJobsResponse:
      type: object
      properties:
        data:
          type: array
          items:
            $ref: "#/components/schemas/FineTuningJob"
        has_more:
          type: boolean
        object:
          type: string
          enum: [list]
      required:
        - object
        - data
        - has_more

    CreateChatCompletionStreamResponse:
      type: object
      description: Represents a streamed chunk of a chat completion response returned by model, based on the provided input.
      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: *chat_completion_response_logprobs
              finish_reason:
                type: string
                description: *chat_completion_finish_reason_description
                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:
          $ref: "#/components/schemas/ChatModel"
        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]
        usage:
          type: object
          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.
          properties:
            completion_tokens:
              type: integer
              description: Number of tokens in the generated completion.
            prompt_tokens:
              type: integer
              description: Number of tokens in the prompt.
            total_tokens:
              type: integer
              description: Total number of tokens used in the request (prompt + completion).
          required:
            - prompt_tokens
            - completion_tokens
            - total_tokens
      required:
        - choices
        - created
        - id
        - model
        - object
      x-oaiMeta:
        name: The chat completion chunk object
        group: chat
        example: *chat_completion_chunk_example

    CreateChatCompletionImageResponse:
      type: object
      description: Represents a streamed chunk of a chat completion response returned by model, based on the provided input.
      x-oaiMeta:
        name: The chat completion chunk object
        group: chat
        example: *chat_completion_image_example

    CreateImageRequest:
      type: object
      properties:
        prompt:
          description: A text description of the desired image(s). The maximum length is 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"]
          x-oaiTypeLabel: string
          default: "dall-e-2"
          example: "dall-e-3"
          nullable: true
          description: The model to use for image generation.
        n: &images_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"]
          default: "standard"
          example: "standard"
          description: The quality of the image that will be generated. `hd` creates images with finer details and greater consistency across the image. This param is only supported for `dall-e-3`.
        response_format: &images_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: &images_size
          type: string
          enum: ["256x256", "512x512", "1024x1024", "1792x1024", "1024x1792"]
          default: "1024x1024"
          example: "1024x1024"
          nullable: true
          description: The size of the generated images. Must be one of `256x256`, `512x512`, or `1024x1024` for `dall-e-2`. Must be one of `1024x1024`, `1792x1024`, or `1024x1792` for `dall-e-3` models.
        style:
          type: string
          enum: ["vivid", "natural"]
          default: "vivid"
          example: "vivid"
          nullable: true
          description: The style of the generated images. 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. This param is only supported for `dall-e-3`.
        user: *end_user_param_configuration
      required:
        - prompt

    ImagesResponse:
      properties:
        created:
          type: integer
        data:
          type: array
          items:
            $ref: "#/components/schemas/Image"
      required:
        - created
        - data

    Image:
      type: object
      description: Represents the url or the content of an image generated by the OpenAI API.
      properties:
        b64_json:
          type: string
          description: The base64-encoded JSON of the generated image, if `response_format` is `b64_json`.
        url:
          type: string
          description: The URL of the generated image, if `response_format` is `url` (default).
        revised_prompt:
          type: string
          description: The prompt that was used to generate the image, if there was any revision to the prompt.
      x-oaiMeta:
        name: The image object
        example: |
          {
            "url": "...",
            "revised_prompt": "..."
          }

    CreateImageEditRequest:
      type: object
      properties:
        image:
          description: The image to edit. Must be a valid PNG file, less than 4MB, and square. If mask is not provided, image must have transparency, which will be used as the mask.
          type: string
          format: binary
        prompt:
          description: A text description of the desired image(s). The maximum length is 1000 characters.
          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. Must be a valid PNG file, less than 4MB, and have the same dimensions as `image`.
          type: string
          format: binary
        model:
          anyOf:
            - type: string
            - type: string
              enum: ["dall-e-2"]
          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.
        size: &dalle2_images_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`.
        response_format: *images_response_format
        user: *end_user_param_configuration
      required:
        - prompt
        - image

    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-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: *images_n
        response_format: *images_response_format
        size: *dalle2_images_size
        user: *end_user_param_configuration
      required:
        - image

    CreateModerationRequest:
      type: object
      properties:
        input:
          description: The input text to classify
          oneOf:
            - type: string
              default: ""
              example: "I want to kill them."
            - type: array
              items:
                type: string
                default: ""
                example: "I want to kill them."
        model:
          description: |
            Two content moderations models are available: `text-moderation-stable` and `text-moderation-latest`.

            The default is `text-moderation-latest` which will be automatically upgraded over time. This ensures you are always using our most accurate model. If you use `text-moderation-stable`, we will provide advanced notice before updating the model. Accuracy of `text-moderation-stable` may be slightly lower than for `text-moderation-latest`.
          nullable: false
          default: "text-moderation-latest"
          example: "text-moderation-stable"
          anyOf:
            - type: string
            - type: string
              enum: ["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.
                  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
                  - 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'.
                  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
                  - self-harm
                  - self-harm/intent
                  - self-harm/instructions
                  - sexual
                  - sexual/minors
                  - violence
                  - violence/graphic
            required:
              - flagged
              - categories
              - category_scores
      required:
        - id
        - model
        - results
      x-oaiMeta:
        name: The moderation object
        example: *moderation_example

    ListFilesResponse:
      type: object
      properties:
        data:
          type: array
          items:
            $ref: "#/components/schemas/OpenAIFile"
        object:
          type: string
          enum: [list]
      required:
        - object
        - data

    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.

            Use "fine-tune" for [Fine-tuning](/docs/api-reference/fine-tuning) and "assistants" for [Assistants](/docs/api-reference/assistants) and [Messages](/docs/api-reference/messages). This allows us to validate the format of the uploaded file is correct for fine-tuning.
          type: string
          enum: ["fine-tune", "assistants"]
      required:
        - file
        - purpose

    DeleteFileResponse:
      type: object
      properties:
        id:
          type: string
        object:
          type: string
          enum: [file]
        deleted:
          type: boolean
      required:
        - id
        - object
        - deleted

    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/what-models-can-be-fine-tuned).
          example: "gpt-3.5-turbo"
          anyOf:
            - type: string
            - type: string
              enum: ["babbage-002", "davinci-002", "gpt-3.5-turbo"]
          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`.

            See the [fine-tuning guide](/docs/guides/fine-tuning) for more details.
          type: string
          example: "file-abc123"
        hyperparameters:
          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]
                - 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]
                - 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]
                - type: integer
                  minimum: 1
                  maximum: 50
              default: auto
        suffix:
          description: |
            A string of up to 18 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-3.5-turbo:openai:custom-model-name:7p4lURel`.
          type: string
          minLength: 1
          maxLength: 40
          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/fine-tuning) 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]
              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
      required:
        - model
        - training_file

    ListFineTuningJobEventsResponse:
      type: object
      properties:
        data:
          type: array
          items:
            $ref: "#/components/schemas/FineTuningJobEvent"
        object:
          type: string
          enum: [list]
      required:
        - object
        - data

    ListFineTuningJobCheckpointsResponse:
      type: object
      properties:
        data:
          type: array
          items:
            $ref: "#/components/schemas/FineTuningJobCheckpoint"
        object:
          type: string
          enum: [list]
        first_id:
          type: string
          nullable: true
        last_id:
          type: string
          nullable: true
        has_more:
          type: boolean
      required:
        - object
        - data
        - has_more

    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 `text-embedding-ada-002`), 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.
          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]]"
          x-oaiExpandable: true
        model:
          description: *model_description
          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: *end_user_param_configuration
      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]
        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

    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. 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-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) 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:
          description: |
            The format of the transcript 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
        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]
      required:
        - file
        - model

    # Note: This does not currently support the non-default response format types.
    CreateTranscriptionResponseJson:
      type: object
      description: Represents a transcription response returned by model, based on the provided input.
      properties:
        text:
          type: string
          description: The transcribed text.
      required:
        - text
      x-oaiMeta:
        name: The transcription object
        group: audio
        example: *basic_transcription_response_example

    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]

    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: string
          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
        group: audio
        example: *verbose_transcription_response_example

    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-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 transcript output, in one of these options: `json`, `text`, `srt`, `verbose_json`, or `vtt`.
          type: string
          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

    # Note: This does not currently support the non-default response format types.
    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: string
          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]

    CreateSpeechRequest:
      type: object
      additionalProperties: false
      properties:
        model:
          description: |
            One of the available [TTS models](/docs/models/tts): `tts-1` or `tts-1-hd`
          anyOf:
            - type: string
            - type: string
              enum: ["tts-1", "tts-1-hd"]
          x-oaiTypeLabel: string
        input:
          type: string
          description: The text to generate audio for. The maximum length is 4096 characters.
          maxLength: 4096
        voice:
          description: The voice to use when generating the audio. Supported voices are `alloy`, `echo`, `fable`, `onyx`, `nova`, and `shimmer`. Previews of the voices are available in the [Text to speech guide](/docs/guides/text-to-speech/voice-options).
          type: string
          enum: ["alloy", "echo", "fable", "onyx", "nova", "shimmer"]
        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."
          type: number
          default: 1.0
          minimum: 0.25
          maximum: 4.0
      required:
        - model
        - input
        - voice

    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]
        owned_by:
          type: string
          description: The organization that owns the model.
      required:
        - id
        - object
        - created
        - owned_by
      x-oaiMeta:
        name: The model object
        example: *retrieve_model_response

    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.
        filename:
          type: string
          description: The name of the file.
        object:
          type: string
          description: The object type, which is always `file`.
          enum: ["file"]
        purpose:
          type: string
          description: The intended purpose of the file. Supported values are `fine-tune`, `fine-tune-results`, `assistants`, and `assistants_output`.
          enum:
            [
              "fine-tune",
              "fine-tune-results",
              "assistants",
              "assistants_output",
            ]
        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,
            "filename": "salesOverview.pdf",
            "purpose": "assistants",
          }
    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
        object:
          type: string
          description: The object type, which is always "embedding".
          enum: [embedding]
      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
          }

    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. See the [fine-tuning guide](/docs/guides/fine-tuning) for more details.
          properties:
            n_epochs:
              oneOf:
                - type: string
                  enum: [auto]
                - type: integer
                  minimum: 1
                  maximum: 50
              default: auto
              description:
                The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.

                "auto" decides the optimal number of epochs based on the size of the dataset. If setting the number manually, we support any number between 1 and 50 epochs.
          required:
            - n_epochs
        model:
          $ref: "#/components/schemas/ChatModel"
        object:
          type: string
          description: The object type, which is always "fine_tuning.job".
          enum: [fine_tuning.job]
        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"
            x-oaiExpandable: true
        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.
      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: *fine_tuning_example

    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"]
        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"

    FineTuningJobEvent:
      type: object
      description: Fine-tuning job event object
      properties:
        id:
          type: string
        created_at:
          type: integer
        level:
          type: string
          enum: ["info", "warn", "error"]
        message:
          type: string
        object:
          type: string
          enum: [fine_tuning.job.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"
          }

    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]
      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-3.5-turbo-0125: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
          }

    CompletionUsage:
      type: object
      description: Usage statistics for the completion request.
      properties:
        completion_tokens:
          type: integer
          description: Number of tokens in the generated completion.
        prompt_tokens:
          type: integer
          description: Number of tokens in the prompt.
        total_tokens:
          type: integer
          description: Total number of tokens used in the request (prompt + completion).
      required:
        - prompt_tokens
        - completion_tokens
        - total_tokens

    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

    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

    AssistantsApiResponseFormatOption:
      description: |
        Specifies the format that the model must output. Compatible with [GPT-4 Turbo](/docs/models/gpt-4-and-gpt-4-turbo) and all GPT-3.5 Turbo models since `gpt-3.5-turbo-1106`.

        Setting to `{ "type": "json_object" }` enables JSON mode, which guarantees 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: [none, auto]
        - $ref: "#/components/schemas/AssistantsApiResponseFormat"
      x-oaiExpandable: true

    AssistantsApiResponseFormat:
      type: object
      description: |
        An object describing the expected output of the model. If `json_object` only `function` type `tools` are allowed to be passed to the Run. If `text` the model can return text or any value needed.
      properties:
        type:
          type: string
          enum: ["text", "json_object"]
          example: "json_object"
          default: "text"
          description: Must be one of `text` or `json_object`.

    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]
        created_at:
          description: The Unix timestamp (in seconds) for when the assistant was created.
          type: integer
        name:
          description: &assistant_name_param_description |
            The name of the assistant. The maximum length is 256 characters.
          type: string
          maxLength: 256
          nullable: true
        description:
          description: &assistant_description_param_description |
            The description of the assistant. The maximum length is 512 characters.
          type: string
          maxLength: 512
          nullable: true
        model:
          description: *model_description
          type: string
        instructions:
          description: &assistant_instructions_param_description |
            The system instructions that the assistant uses. The maximum length is 256,000 characters.
          type: string
          maxLength: 256000
          nullable: true
        tools:
          description: &assistant_tools_param_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"
            x-oaiExpandable: true
        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:
          description: &metadata_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. Keys can be a maximum of 64 characters long and values can be a maxium of 512 characters long.
          type: object
          x-oaiTypeLabel: map
          nullable: true
        temperature:
          description: &run_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: &run_top_p_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: *create_assistants_example

    CreateAssistantRequest:
      type: object
      additionalProperties: false
      properties:
        model:
          $ref: "#/components/schemas/ChatModel"
        name:
          description: *assistant_name_param_description
          type: string
          nullable: true
          maxLength: 256
        description:
          description: *assistant_description_param_description
          type: string
          nullable: true
          maxLength: 512
        instructions:
          description: *assistant_instructions_param_description
          type: string
          nullable: true
          maxLength: 256000
        tools:
          description: *assistant_tools_param_description
          default: []
          type: array
          maxItems: 128
          items:
            oneOf:
              - $ref: "#/components/schemas/AssistantToolsCode"
              - $ref: "#/components/schemas/AssistantToolsFileSearch"
              - $ref: "#/components/schemas/AssistantToolsFunction"
            x-oaiExpandable: true
        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
                      metadata:
                        type: object
                        description: |
                          Set of 16 key-value pairs that can be attached to a vector store. This can be useful for storing additional information about the vector store in a structured format. Keys can be a maximum of 64 characters long and values can be a maxium of 512 characters long.
                        x-oaiTypeLabel: map
              oneOf:
                - required: [vector_store_ids]
                - required: [vector_stores]
          nullable: true
        metadata:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true
        temperature:
          description: &run_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: &run_top_p_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

    ModifyAssistantRequest:
      type: object
      additionalProperties: false
      properties:
        model:
          description: *model_description
          anyOf:
            - type: string
        name:
          description: *assistant_name_param_description
          type: string
          nullable: true
          maxLength: 256
        description:
          description: *assistant_description_param_description
          type: string
          nullable: true
          maxLength: 512
        instructions:
          description: *assistant_instructions_param_description
          type: string
          nullable: true
          maxLength: 256000
        tools:
          description: *assistant_tools_param_description
          default: []
          type: array
          maxItems: 128
          items:
            oneOf:
              - $ref: "#/components/schemas/AssistantToolsCode"
              - $ref: "#/components/schemas/AssistantToolsFileSearch"
              - $ref: "#/components/schemas/AssistantToolsFunction"
            x-oaiExpandable: true
        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:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true
        temperature:
          description: *run_temperature_description
          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: &run_top_p_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

    DeleteAssistantResponse:
      type: object
      properties:
        id:
          type: string
        deleted:
          type: boolean
        object:
          type: string
          enum: [assistant.deleted]
      required:
        - id
        - object
        - deleted

    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: *list_assistants_example

    AssistantToolsCode:
      type: object
      title: Code interpreter tool
      properties:
        type:
          type: string
          description: "The type of tool being defined: `code_interpreter`"
          enum: ["code_interpreter"]
      required:
        - type

    AssistantToolsFileSearch:
      type: object
      title: FileSearch tool
      properties:
        type:
          type: string
          description: "The type of tool being defined: `file_search`"
          enum: ["file_search"]
      required:
        - type

    AssistantToolsFunction:
      type: object
      title: Function tool
      properties:
        type:
          type: string
          description: "The type of tool being defined: `function`"
          enum: ["function"]
        function:
          $ref: "#/components/schemas/FunctionObject"
      required:
        - type
        - function

    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

    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"
      x-oaiExpandable: true

    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

    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"]
        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`, or `expired`.
          type: string
          enum:
            [
              "queued",
              "in_progress",
              "requires_action",
              "cancelling",
              "cancelled",
              "failed",
              "completed",
              "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"]
            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"
            x-oaiExpandable: true
        metadata:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true
        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:
          $ref: "#/components/schemas/TruncationObject"
          nullable: true
        tool_choice:
          $ref: "#/components/schemas/AssistantsApiToolChoiceOption"
          nullable: true
        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
        - 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-4-turbo",
            "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"
          }
    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:
          $ref: "#/components/schemas/ChatModel"
        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"
            x-oaiExpandable: true
        metadata:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true
        temperature:
          type: number
          minimum: 0
          maximum: 2
          default: 1
          example: 1
          nullable: true
          description: *run_temperature_description
        top_p:
          type: number
          minimum: 0
          maximum: 1
          default: 1
          example: 1
          nullable: true
          description: &run_top_p_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:
          $ref: "#/components/schemas/TruncationObject"
          nullable: true
        tool_choice:
          $ref: "#/components/schemas/AssistantsApiToolChoiceOption"
          nullable: true
        response_format:
          $ref: "#/components/schemas/AssistantsApiResponseFormatOption"
          nullable: true
      required:
        - thread_id
        - assistant_id
    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
    ModifyRunRequest:
      type: object
      additionalProperties: false
      properties:
        metadata:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true
    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

    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"]
        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
    ChatModel:
      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-4-turbo"
      x-speakeasy-unknown-values: allow
      schema:
        type: string
        enum:
          [
            "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
    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"
          description: If no thread is provided, an empty thread will be created.
        model:
          $ref: "#/components/schemas/ChatModel"
        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:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true
        temperature:
          type: number
          minimum: 0
          maximum: 2
          default: 1
          example: 1
          nullable: true
          description: *run_temperature_description
        top_p:
          type: number
          minimum: 0
          maximum: 1
          default: 1
          example: 1
          nullable: true
          description: *run_top_p_description
        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:
          $ref: "#/components/schemas/TruncationObject"
          nullable: true
        tool_choice:
          $ref: "#/components/schemas/AssistantsApiToolChoiceOption"
          nullable: true
        response_format:
          $ref: "#/components/schemas/AssistantsApiResponseFormatOption"
          nullable: true
      required:
        - thread_id
        - assistant_id

    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"]
        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:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true
      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": {}
          }

    CreateThreadRequest:
      type: object
      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
                      metadata:
                        type: object
                        description: |
                          Set of 16 key-value pairs that can be attached to a vector store. This can be useful for storing additional information about the vector store in a structured format. Keys can be a maximum of 64 characters long and values can be a maxium of 512 characters long.
                        x-oaiTypeLabel: map
              oneOf:
                - required: [vector_store_ids]
                - required: [vector_stores]
          nullable: true
        metadata:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true

    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:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true

    DeleteThreadResponse:
      type: object
      properties:
        id:
          type: string
        deleted:
          type: boolean
        object:
          type: string
          enum: [thread.deleted]
      required:
        - id
        - object
        - deleted

    ListThreadsResponse:
      properties:
        object:
          type: string
          example: "list"
        data:
          type: array
          items:
            $ref: "#/components/schemas/ThreadObject"
        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

    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"]
        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:
          $ref: "#/components/schemas/ChatCompletionRole"
        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/MessageContentTextObject"
            x-oaiExpandable: true
        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/AssistantToolsFileSearch"
                  x-oaiExpandable: true
          description: A list of files attached to the message, and the tools they were added to.
          nullable: true
        metadata:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true
      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": {}
          }

    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"]
        delta:
          description: The delta containing the fields that have changed on the Message.
          type: object
          properties:
            role:
              $ref: "#/components/schemas/ChatCompletionRole"
            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"
                x-oaiExpandable: true
      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": [] }
                }
              ]
            }
          }

    CreateMessageRequest:
      type: object
      additionalProperties: false
      required:
        - role
        - content
      properties:
        role:
          $ref: "#/components/schemas/ChatCompletionRole"
        content:
          type: string
          minLength: 1
          maxLength: 256000
          description: The content of the message.
        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/AssistantToolsFileSearch"
                  x-oaiExpandable: true
          description: A list of files attached to the message, and the tools they should be added to.
          required:
            - file_id
            - tools
          nullable: true
        metadata:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true

    ModifyMessageRequest:
      type: object
      additionalProperties: false
      properties:
        metadata:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true

    DeleteMessageResponse:
      type: object
      properties:
        id:
          type: string
        deleted:
          type: boolean
        object:
          type: string
          enum: [thread.message.deleted]
      required:
        - id
        - object
        - deleted

    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

    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"]
        image_file:
          type: object
          properties:
            file_id:
              description: The [File](/docs/api-reference/files) ID of the image in the message content.
              type: string
          required:
            - file_id
      required:
        - type
        - image_file

    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"]
        image_file:
          type: object
          properties:
            file_id:
              description: The [File](/docs/api-reference/files) ID of the image in the message content.
              type: string
      required:
        - index
        - type

    MessageContentTextObject:
      title: Text
      type: object
      description: The text content that is part of a message.
      properties:
        type:
          description: Always `text`.
          type: string
          enum: ["text"]
        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"
                x-oaiExpandable: true
          required:
            - value
            - annotations
      required:
        - type
        - text

    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"]
        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
          required:
            - file_id
            - quote
        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"]
        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

    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"]
        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"
                x-oaiExpandable: true
      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"]
        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"]
        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

    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"]
        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"
          x-oaiExpandable: true
        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:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true
        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: *run_step_object_example

    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"]
        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"
              x-oaiExpandable: true
      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": [] }
                  }
                ]
              }
            }
          }

    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

    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"]
        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

    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"]
        message_creation:
          type: object
          properties:
            message_id:
              type: string
              description: The ID of the message that was created by this run step.
      required:
        - type

    RunStepDetailsToolCallsObject:
      title: Tool calls
      type: object
      description: Details of the tool call.
      properties:
        type:
          description: Always `tool_calls`.
          type: string
          enum: ["tool_calls"]
        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"
            x-oaiExpandable: true
      required:
        - type
        - tool_calls

    RunStepDeltaStepDetailsToolCallsObject:
      title: Tool calls
      type: object
      description: Details of the tool call.
      properties:
        type:
          description: Always `tool_calls`.
          type: string
          enum: ["tool_calls"]
        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"
            x-oaiExpandable: true
      required:
        - type

    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"]
        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"
                x-oaiExpandable: true
      required:
        - id
        - type
        - code_interpreter

    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"]
        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"
                x-oaiExpandable: true
      required:
        - index
        - type

    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"]
        logs:
          type: string
          description: The text output from the Code Interpreter tool call.
      required:
        - type
        - logs

    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"]
        logs:
          type: string
          description: The text output from the Code Interpreter tool call.
      required:
        - index
        - type

    RunStepDetailsToolCallsCodeOutputImageObject:
      title: Code Interpreter image output
      type: object
      properties:
        type:
          description: Always `image`.
          type: string
          enum: ["image"]
        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

    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"]
        image:
          type: object
          properties:
            file_id:
              description: The [file](/docs/api-reference/files) ID of the image.
              type: string
      required:
        - index
        - type

    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"]
        file_search:
          type: object
          description: For now, this is always going to be an empty object.
          x-oaiTypeLabel: map
      required:
        - id
        - type
        - file_search

    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"]
        file_search:
          type: object
          description: For now, this is always going to be an empty object.
          x-oaiTypeLabel: map
      required:
        - index
        - type
        - file_search

    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"]
        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

    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"]
        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

    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"]
        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

    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"]
        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:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true
      required:
        - id
        - object
        - usage_bytes
        - created_at
        - status
        - last_active_at
        - name
        - file_counts
        - metadata
      x-oaiMeta:
        name: The vector store object
        beta: true
        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
            },
            "metadata": {},
            "last_used_at": 1698107661
          }

    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"
        metadata:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true

    UpdateVectorStoreRequest:
      type: object
      additionalProperties: false
      properties:
        name:
          description: The name of the vector store.
          type: string
          nullable: true
        expires_after:
          $ref: "#/components/schemas/VectorStoreExpirationAfter"
          nullable: true
        metadata:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true

    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

    DeleteVectorStoreResponse:
      type: object
      properties:
        id:
          type: string
        deleted:
          type: boolean
        object:
          type: string
          enum: [vector_store.deleted]
      required:
        - id
        - object
        - deleted

    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"]
        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:
                [
                  "internal_error",
                  "file_not_found",
                  "parsing_error",
                  "unhandled_mime_type",
                ]
            message:
              type: string
              description: A human-readable description of the error.
          required:
            - code
            - message
      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
          }

    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
      required:
        - file_id

    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

    DeleteVectorStoreFileResponse:
      type: object
      properties:
        id:
          type: string
        deleted:
          type: boolean
        object:
          type: string
          enum: [vector_store.file.deleted]
      required:
        - id
        - object
        - deleted

    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"]
        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
            }
          }

    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
      required:
        - file_ids

    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

    ThreadStreamEvent:
      oneOf:
        - type: object
          properties:
            event:
              type: string
              enum: ["thread.created"]
            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)"

    RunStreamEvent:
      oneOf:
        - type: object
          properties:
            event:
              type: string
              enum: ["thread.run.created"]
            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"]
            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"]
            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"]
            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"]
            data:
              $ref: "#/components/schemas/RunObject"
          required:
            - event
            - data
          description: Occurs when a [run](/docs/api-reference/runs/object) is completed.
          x-oaiMeta:
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              enum: ["thread.run.step.created"]
            data:
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          required:
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          description: Occurs when a [run step](/docs/api-reference/runs/step-object) is created.
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            data:
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          description: Occurs when a [run step](/docs/api-reference/runs/step-object) moves to an `in_progress` state.
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              enum: ["thread.message.created"]
            data:
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            - data
          description: Occurs when a [message](/docs/api-reference/messages/object) is created.
          x-oaiMeta:
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          properties:
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            data:
              $ref: "#/components/schemas/MessageObject"
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            - data
          description: Occurs when a [message](/docs/api-reference/messages/object) moves to an `in_progress` state.
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          description: Occurs when parts of a [Message](/docs/api-reference/messages/object) are being streamed.
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            data:
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          description: Occurs when a [message](/docs/api-reference/messages/object) is completed.
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        - type: object
          properties:
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            data:
              $ref: "#/components/schemas/MessageObject"
          required:
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          description: Occurs when a [message](/docs/api-reference/messages/object) ends before it is completed.
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    ErrorEvent:
      type: object
      properties:
        event:
          type: string
          enum: ["error"]
        data:
          $ref: "#/components/schemas/Error"
      required:
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        - 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:
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    DoneEvent:
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      properties:
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          enum: ["done"]
        data:
          type: string
          enum: ["[DONE]"]
      required:
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        - data
      description: Occurs when a stream ends.
      x-oaiMeta:
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    Batch:
      type: object
      properties:
        id:
          type: string
        object:
          type: string
          enum: [batch]
          description: The object type, which is always `batch`.
        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:
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            - completed
            - failed
          description: The request counts for different statuses within the batch.
        metadata:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
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        - object
        - endpoint
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        - completion_window
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        - created_at
      x-oaiMeta:
        name: The batch object
        example: *batch_object

    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.
        url:
          type: string
          description: The OpenAI API relative URL to be used for the request. Currently `/v1/chat/completions` and `/v1/embeddings` are supported.
      x-oaiMeta:
        name: The request input object
        example: |
          {"custom_id": "request-1", "method": "POST", "url": "/v1/chat/completions", "body": {"model": "gpt-3.5-turbo", "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:
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        example: |
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    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:
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        object:
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          enum: [list]
      required:
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        - data
        - has_more

security:
  - ApiKeyAuth: []

x-oaiMeta:
  navigationGroups:
    - id: endpoints
      title: Endpoints
    - id: assistants
      title: Assistants
    - id: legacy
      title: Legacy
  groups:
    # > General Notes
    # The `groups` section is used to generate the API reference pages and navigation, in the same
    # order listed below. Additionally, each `group` can have a list of `sections`, each of which
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    # - `x-oaiMeta.examples`: The endpoint examples, which can be an object (meaning a single variation, most
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    # - `x-oaiMeta.returns`: text describing what the endpoint returns.
    # - `summary`: The summary of the endpoint, which will be used to generate the section description
    - 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
    - id: chat
      title: Chat
      description: |
        Given a list of messages comprising a conversation, the model will return a response.

        Related guide: [Chat Completions](/docs/guides/text-generation)
      navigationGroup: endpoints
      sections:
        - type: endpoint
          key: createChatCompletion
          path: create
        - type: object
          key: CreateChatCompletionResponse
          path: object
        - type: object
          key: CreateChatCompletionStreamResponse
          path: streaming
    - 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: 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: retrieveFineTuningJob
          path: retrieve
        - type: endpoint
          key: cancelFineTuningJob
          path: cancel
        - type: object
          key: FineTuningJob
          path: object
        - type: object
          key: FineTuningJobEvent
          path: event-object
        - type: object
          key: FineTuningJobCheckpoint
          path: checkpoint-object
    - 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: requestInput
        - type: object
          key: BatchRequestOutput
          path: requestOutput
    - id: files
      title: Files
      description: |
        Files are used to upload documents that can be used with features like [Assistants](/docs/api-reference/assistants) and [Fine-tuning](/docs/api-reference/fine-tuning).
      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: 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: Image
          path: 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 some input text, outputs if the model classifies it as 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: 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: vector-stores
      title: Vector Stores
      beta: true
      description: |
        Vector stores are used to store files for use by the `file_search` tool.

        Related guide: [File Search](/docs/assistants/tools/file-search)
      navigationGroup: assistants
      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: object
          key: VectorStoreObject
          path: object
    - id: vector-stores-files
      title: Vector Store Files
      beta: true
      description: |
        Vector store files represent files inside a vector store.

        Related guide: [File Search](/docs/assistants/tools/file-search)
      navigationGroup: assistants
      sections:
        - type: endpoint
          key: createVectorStoreFile
          path: createFile
        - type: endpoint
          key: listVectorStoreFiles
          path: listFiles
        - type: endpoint
          key: getVectorStoreFile
          path: getFile
        - type: endpoint
          key: deleteVectorStoreFile
          path: deleteFile
        - type: object
          key: VectorStoreFileObject
          path: file-object
    - id: vector-stores-file-batches
      title: Vector Store File Batches
      beta: true
      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: assistants
      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: 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: 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