# k-openai-openapi-20250315

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

                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-4o",
                  });

                  console.log(myAssistant);
                }


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

                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-4o"
                  });

                  console.log(myAssistant);
                }


                main();
            response: >
              {
                "id": "asst_abc123",
                "object": "assistant",
                "created_at": 1699009403,
                "name": "HR Helper",
                "description": null,
                "model": "gpt-4o",
                "instructions": "You are an HR bot, and you have access to files to answer employee questions about company policies.",
                "tools": [
                  {
                    "type": "file_search"
                  }
                ],
                "tool_resources": {
                  "file_search": {
                    "vector_store_ids": ["vs_123"]
                  }
                },
                "metadata": {},
                "top_p": 1.0,
                "temperature": 1.0,
                "response_format": "auto"
              }
  /assistants/{assistant_id}:
    get:
      operationId: getAssistant
      tags:
        - Assistants
      summary: Retrieves an assistant.
      parameters:
        - in: path
          name: assistant_id
          required: true
          schema:
            type: string
          description: The ID of the assistant to retrieve.
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/AssistantObject"
      x-oaiMeta:
        name: Retrieve assistant
        group: assistants
        beta: true
        returns: The [assistant](/docs/api-reference/assistants/object) object matching
          the specified ID.
        examples:
          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-4o",
              "instructions": "You are an HR bot, and you have access to files to answer employee questions about company policies.",
              "tools": [
                {
                  "type": "file_search"
                }
              ],
              "metadata": {},
              "top_p": 1.0,
              "temperature": 1.0,
              "response_format": "auto"
            }
    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-4o"
                  }'
            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-4o"
              )


              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-4o"
                  }
                );

                console.log(myUpdatedAssistant);
              }


              main();
          response: >
            {
              "id": "asst_123",
              "object": "assistant",
              "created_at": 1699009709,
              "name": "HR Helper",
              "description": null,
              "model": "gpt-4o",
              "instructions": "You are an HR bot, and you have access to files to answer employee questions about company policies. Always response with info from either of the files.",
              "tools": [
                {
                  "type": "file_search"
                }
              ],
              "tool_resources": {
                "file_search": {
                  "vector_store_ids": []
                }
              },
              "metadata": {},
              "top_p": 1.0,
              "temperature": 1.0,
              "response_format": "auto"
            }
    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
            }
  /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();
            csharp: |
              using System;
              using System.IO;

              using OpenAI.Audio;

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

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

              using FileStream stream = File.OpenWrite("speech.mp3");
              speech.ToStream().CopyTo(stream);
  /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();
              csharp: >
                using System;


                using OpenAI.Audio;

                string audioFilePath = "audio.mp3";


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


                AudioTranscription transcription =
                client.TranscribeAudio(audioFilePath);


                Console.WriteLine($"{transcription.Text}");
            response: >
              {
                "text": "Imagine the wildest idea that you've ever had, and you're curious about how it might scale to something that's a 100, a 1,000 times bigger. This is a place where you can get to do that."
              }
          - title: 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();
              csharp: >
                using System;


                using OpenAI.Audio;


                string audioFilePath = "audio.mp3";


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


                AudioTranscriptionOptions options = new()

                {
                    ResponseFormat = AudioTranscriptionFormat.Verbose,
                    TimestampGranularities = AudioTimestampGranularities.Word,
                };


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


                Console.WriteLine($"{transcription.Text}");
            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();
              csharp: >
                using System;


                using OpenAI.Audio;


                string audioFilePath = "audio.mp3";


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


                AudioTranscriptionOptions options = new()

                {
                    ResponseFormat = AudioTranscriptionFormat.Verbose,
                    TimestampGranularities = AudioTimestampGranularities.Segment,
                };


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


                Console.WriteLine($"{transcription.Text}");
            response: >
              {
                "task": "transcribe",
                "language": "english",
                "duration": 8.470000267028809,
                "text": "The beach was a popular spot on a hot summer day. People were swimming in the ocean, building sandcastles, and playing beach volleyball.",
                "segments": [
                  {
                    "id": 0,
                    "seek": 0,
                    "start": 0.0,
                    "end": 3.319999933242798,
                    "text": " The beach was a popular spot on a hot summer day.",
                    "tokens": [
                      50364, 440, 7534, 390, 257, 3743, 4008, 322, 257, 2368, 4266, 786, 13, 50530
                    ],
                    "temperature": 0.0,
                    "avg_logprob": -0.2860786020755768,
                    "compression_ratio": 1.2363636493682861,
                    "no_speech_prob": 0.00985979475080967
                  },
                  ...
                ]
              }
  /audio/translations:
    post:
      operationId: createTranslation
      tags:
        - Audio
      summary: Translates audio into English.
      requestBody:
        required: true
        content:
          multipart/form-data:
            schema:
              $ref: "#/components/schemas/CreateTranslationRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                oneOf:
                  - $ref: "#/components/schemas/CreateTranslationResponseJson"
                  - $ref: "#/components/schemas/CreateTranslationResponseVerboseJson"
      x-oaiMeta:
        name: Create translation
        group: audio
        returns: The translated text.
        examples:
          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();
            csharp: >
              using System;


              using OpenAI.Audio;


              string audioFilePath = "audio.mp3";


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


              AudioTranscription transcription =
              client.TranscribeAudio(audioFilePath);


              Console.WriteLine($"{transcription.Text}");
          response: >
            {
              "text": "Hello, my name is Wolfgang and I come from Germany. Where are you heading today?"
            }
  /batches:
    post:
      summary: Creates and executes a batch from an uploaded file of requests
      operationId: createBatch
      tags:
        - Batch
      requestBody:
        required: true
        content:
          application/json:
            schema:
              type: object
              required:
                - input_file_id
                - endpoint
                - completion_window
              properties:
                input_file_id:
                  type: string
                  description: >
                    The ID of an uploaded file that contains requests for the
                    new batch.


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


                    Your input file must be formatted as a [JSONL
                    file](/docs/api-reference/batch/request-input), and must be
                    uploaded with the purpose `batch`. The file can contain up
                    to 50,000 requests, and can be up to 200 MB in size.
                endpoint:
                  type: string
                  enum:
                    - /v1/chat/completions
                    - /v1/embeddings
                    - /v1/completions
                  description: The endpoint to be used for all requests in the batch. Currently
                    `/v1/chat/completions`, `/v1/embeddings`, and
                    `/v1/completions` are supported. Note that `/v1/embeddings`
                    batches are also restricted to a maximum of 50,000 embedding
                    inputs across all requests in the batch.
                completion_window:
                  type: string
                  enum:
                    - 24h
                  description: The time frame within which the batch should be processed.
                    Currently only `24h` is supported.
                metadata:
                  $ref: "#/components/schemas/Metadata"
      responses:
        "200":
          description: Batch created successfully.
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/Batch"
      x-oaiMeta:
        name: Create batch
        group: batch
        returns: The created [Batch](/docs/api-reference/batch/object) object.
        examples:
          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/chat/completions",
              "errors": null,
              "input_file_id": "file-abc123",
              "completion_window": "24h",
              "status": "validating",
              "output_file_id": null,
              "error_file_id": null,
              "created_at": 1711471533,
              "in_progress_at": null,
              "expires_at": null,
              "finalizing_at": null,
              "completed_at": null,
              "failed_at": null,
              "expired_at": null,
              "cancelling_at": null,
              "cancelled_at": null,
              "request_counts": {
                "total": 0,
                "completed": 0,
                "failed": 0
              },
              "metadata": {
                "customer_id": "user_123456789",
                "batch_description": "Nightly eval job",
              }
            }
    get:
      operationId: listBatches
      tags:
        - Batch
      summary: List your organization's batches.
      parameters:
        - in: query
          name: after
          required: false
          schema:
            type: string
          description: >
            A cursor for use in pagination. `after` is an object ID that defines
            your place in the list. For instance, if you make a list request and
            receive 100 objects, ending with obj_foo, your subsequent call can
            include after=obj_foo in order to fetch the next page of the list.
        - name: limit
          in: query
          description: >
            A limit on the number of objects to be returned. Limit can range
            between 1 and 100, and the default is 20.
          required: false
          schema:
            type: integer
            default: 20
      responses:
        "200":
          description: Batch listed successfully.
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ListBatchesResponse"
      x-oaiMeta:
        name: List batch
        group: batch
        returns: A list of paginated [Batch](/docs/api-reference/batch/object) objects.
        examples:
          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/chat/completions",
                  "errors": null,
                  "input_file_id": "file-abc123",
                  "completion_window": "24h",
                  "status": "completed",
                  "output_file_id": "file-cvaTdG",
                  "error_file_id": "file-HOWS94",
                  "created_at": 1711471533,
                  "in_progress_at": 1711471538,
                  "expires_at": 1711557933,
                  "finalizing_at": 1711493133,
                  "completed_at": 1711493163,
                  "failed_at": null,
                  "expired_at": null,
                  "cancelling_at": null,
                  "cancelled_at": null,
                  "request_counts": {
                    "total": 100,
                    "completed": 95,
                    "failed": 5
                  },
                  "metadata": {
                    "customer_id": "user_123456789",
                    "batch_description": "Nightly job",
                  }
                },
                { ... },
              ],
              "first_id": "batch_abc123",
              "last_id": "batch_abc456",
              "has_more": true
            }
  /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: |
            {
              "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. The batch will be in status `cancelling`
        for up to 10 minutes, before changing to `cancelled`, where it will have
        partial results (if any) available in the output file.
      parameters:
        - in: path
          name: batch_id
          required: true
          schema:
            type: string
          description: The ID of the batch to cancel.
      responses:
        "200":
          description: Batch is cancelling. Returns the cancelling batch's details.
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/Batch"
      x-oaiMeta:
        name: Cancel batch
        group: batch
        returns: The [Batch](/docs/api-reference/batch/object) object matching the
          specified ID.
        examples:
          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/chat/completions",
              "errors": null,
              "input_file_id": "file-abc123",
              "completion_window": "24h",
              "status": "cancelling",
              "output_file_id": null,
              "error_file_id": null,
              "created_at": 1711471533,
              "in_progress_at": 1711471538,
              "expires_at": 1711557933,
              "finalizing_at": null,
              "completed_at": null,
              "failed_at": null,
              "expired_at": null,
              "cancelling_at": 1711475133,
              "cancelled_at": null,
              "request_counts": {
                "total": 100,
                "completed": 23,
                "failed": 1
              },
              "metadata": {
                "customer_id": "user_123456789",
                "batch_description": "Nightly eval job",
              }
            }
  /chat/completions:
    get:
      operationId: listChatCompletions
      tags:
        - Chat
      summary: >
        List stored Chat Completions. Only Chat Completions that have been
        stored

        with the `store` parameter set to `true` will be returned.
      parameters:
        - name: model
          in: query
          description: The model used to generate the Chat Completions.
          required: false
          schema:
            type: string
        - name: metadata
          in: query
          description: |
            A list of metadata keys to filter the Chat Completions by. Example:

            `metadata[key1]=value1&metadata[key2]=value2`
          required: false
          schema:
            $ref: "#/components/schemas/Metadata"
        - name: after
          in: query
          description: Identifier for the last chat completion from the previous
            pagination request.
          required: false
          schema:
            type: string
        - name: limit
          in: query
          description: Number of Chat Completions to retrieve.
          required: false
          schema:
            type: integer
            default: 20
        - name: order
          in: query
          description: Sort order for Chat Completions by timestamp. Use `asc` for
            ascending order or `desc` for descending order. Defaults to `asc`.
          required: false
          schema:
            type: string
            enum:
              - asc
              - desc
            default: asc
      responses:
        "200":
          description: A list of Chat Completions
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ChatCompletionList"
      x-oaiMeta:
        name: List Chat Completions
        group: chat
        returns: A list of [Chat Completions](/docs/api-reference/chat/list-object)
          matching the specified filters.
        path: list
        examples:
          request:
            curl: |
              curl https://api.openai.com/v1/chat/completions \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json"
            python: |
              from openai import OpenAI
              client = OpenAI()

              completions = client.chat.completions.list()
              print(completions)
          response: >
            {
              "object": "list",
              "data": [
                {
                  "object": "chat.completion",
                  "id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2",
                  "model": "gpt-4o-2024-08-06",
                  "created": 1738960610,
                  "request_id": "req_ded8ab984ec4bf840f37566c1011c417",
                  "tool_choice": null,
                  "usage": {
                    "total_tokens": 31,
                    "completion_tokens": 18,
                    "prompt_tokens": 13
                  },
                  "seed": 4944116822809979520,
                  "top_p": 1.0,
                  "temperature": 1.0,
                  "presence_penalty": 0.0,
                  "frequency_penalty": 0.0,
                  "system_fingerprint": "fp_50cad350e4",
                  "input_user": null,
                  "service_tier": "default",
                  "tools": null,
                  "metadata": {},
                  "choices": [
                    {
                      "index": 0,
                      "message": {
                        "content": "Mind of circuits hum,  \nLearning patterns in silence—  \nFuture's quiet spark.",
                        "role": "assistant",
                        "tool_calls": null,
                        "function_call": null
                      },
                      "finish_reason": "stop",
                      "logprobs": null
                    }
                  ],
                  "response_format": null
                }
              ],
              "first_id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2",
              "last_id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2",
              "has_more": false
            }
    post:
      operationId: createChatCompletion
      tags:
        - Chat
      summary: >
        **Starting a new project?** We recommend trying
        [Responses](/docs/api-reference/responses) 

        to take advantage of the latest OpenAI platform features. Compare

        [Chat Completions with
        Responses](/docs/guides/responses-vs-chat-completions?api-mode=responses).


        ---


        Creates a model response for the given chat conversation. Learn more in
        the

        [text generation](/docs/guides/text-generation),
        [vision](/docs/guides/vision),

        and [audio](/docs/guides/audio) guides.


        Parameter support can differ depending on the model used to generate the

        response, particularly for newer reasoning models. Parameters that are
        only

        supported for reasoning models are noted below. For the current state
        of 

        unsupported parameters in reasoning models, 

        [refer to the reasoning guide](/docs/guides/reasoning).
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/CreateChatCompletionRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/CreateChatCompletionResponse"
            text/event-stream:
              schema:
                $ref: "#/components/schemas/CreateChatCompletionStreamResponse"
      x-oaiMeta:
        name: Create chat completion
        group: chat
        returns: >
          Returns a [chat completion](/docs/api-reference/chat/object) object,
          or a streamed sequence of [chat completion
          chunk](/docs/api-reference/chat/streaming) objects if the request is
          streamed.
        path: create
        examples:
          - title: Default
            request:
              curl: |
                curl https://api.openai.com/v1/chat/completions \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -d '{
                    "model": "VAR_chat_model_id",
                    "messages": [
                      {
                        "role": "developer",
                        "content": "You are a helpful assistant."
                      },
                      {
                        "role": "user",
                        "content": "Hello!"
                      }
                    ]
                  }'
              python: >
                from openai import OpenAI

                client = OpenAI()


                completion = client.chat.completions.create(
                  model="VAR_chat_model_id",
                  messages=[
                    {"role": "developer", "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: "developer", content: "You are a helpful assistant." }],
                    model: "VAR_chat_model_id",
                    store: true,
                  });

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


                main();
              csharp: |
                using System;
                using System.Collections.Generic;

                using OpenAI.Chat;

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

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

                ChatCompletion completion = client.CompleteChat(messages);

                Console.WriteLine(completion.Content[0].Text);
            response: |
              {
                "id": "chatcmpl-B9MBs8CjcvOU2jLn4n570S5qMJKcT",
                "object": "chat.completion",
                "created": 1741569952,
                "model": "gpt-4o-2024-08-06",
                "choices": [
                  {
                    "index": 0,
                    "message": {
                      "role": "assistant",
                      "content": "Hello! How can I assist you today?",
                      "refusal": null,
                      "annotations": []
                    },
                    "logprobs": null,
                    "finish_reason": "stop"
                  }
                ],
                "usage": {
                  "prompt_tokens": 19,
                  "completion_tokens": 10,
                  "total_tokens": 29,
                  "prompt_tokens_details": {
                    "cached_tokens": 0,
                    "audio_tokens": 0
                  },
                  "completion_tokens_details": {
                    "reasoning_tokens": 0,
                    "audio_tokens": 0,
                    "accepted_prediction_tokens": 0,
                    "rejected_prediction_tokens": 0
                  }
                },
                "service_tier": "default"
              }
          - title: Image input
            request:
              curl: >
                curl https://api.openai.com/v1/chat/completions \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -d '{
                    "model": "gpt-4o",
                    "messages": [
                      {
                        "role": "user",
                        "content": [
                          {
                            "type": "text",
                            "text": "What is in this image?"
                          },
                          {
                            "type": "image_url",
                            "image_url": {
                              "url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
                            }
                          }
                        ]
                      }
                    ],
                    "max_tokens": 300
                  }'
              python: >
                from openai import OpenAI


                client = OpenAI()


                response = client.chat.completions.create(
                    model="gpt-4o",
                    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,
                )


                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-4o",
                    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",
                            },
                          }
                        ],
                      },
                    ],
                  });
                  console.log(response.choices[0]);
                }

                main();
              csharp: >
                using System;

                using System.Collections.Generic;


                using OpenAI.Chat;


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


                List<ChatMessage> messages =

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


                ChatCompletion completion = client.CompleteChat(messages);


                Console.WriteLine(completion.Content[0].Text);
            response: >
              {
                "id": "chatcmpl-B9MHDbslfkBeAs8l4bebGdFOJ6PeG",
                "object": "chat.completion",
                "created": 1741570283,
                "model": "gpt-4o-2024-08-06",
                "choices": [
                  {
                    "index": 0,
                    "message": {
                      "role": "assistant",
                      "content": "The image shows a wooden boardwalk path running through a lush green field or meadow. The sky is bright blue with some scattered clouds, giving the scene a serene and peaceful atmosphere. Trees and shrubs are visible in the background.",
                      "refusal": null,
                      "annotations": []
                    },
                    "logprobs": null,
                    "finish_reason": "stop"
                  }
                ],
                "usage": {
                  "prompt_tokens": 1117,
                  "completion_tokens": 46,
                  "total_tokens": 1163,
                  "prompt_tokens_details": {
                    "cached_tokens": 0,
                    "audio_tokens": 0
                  },
                  "completion_tokens_details": {
                    "reasoning_tokens": 0,
                    "audio_tokens": 0,
                    "accepted_prediction_tokens": 0,
                    "rejected_prediction_tokens": 0
                  }
                },
                "service_tier": "default"
              }
          - title: Streaming
            request:
              curl: |
                curl https://api.openai.com/v1/chat/completions \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -d '{
                    "model": "VAR_chat_model_id",
                    "messages": [
                      {
                        "role": "developer",
                        "content": "You are a helpful assistant."
                      },
                      {
                        "role": "user",
                        "content": "Hello!"
                      }
                    ],
                    "stream": true
                  }'
              python: >
                from openai import OpenAI

                client = OpenAI()


                completion = client.chat.completions.create(
                  model="VAR_chat_model_id",
                  messages=[
                    {"role": "developer", "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_chat_model_id",
                    messages: [
                      {"role": "developer", "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();
              csharp: >
                using System;

                using System.ClientModel;

                using System.Collections.Generic;

                using System.Threading.Tasks;


                using OpenAI.Chat;


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


                List<ChatMessage> messages =

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


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


                await foreach (StreamingChatCompletionUpdate completionUpdate in
                completionUpdates)

                {
                    if (completionUpdate.ContentUpdate.Count > 0)
                    {
                        Console.Write(completionUpdate.ContentUpdate[0].Text);
                    }
                }
            response: >
              {"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"gpt-4o-mini",
              "system_fingerprint": "fp_44709d6fcb",
              "choices":[{"index":0,"delta":{"role":"assistant","content":""},"logprobs":null,"finish_reason":null}]}


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


              ....


              {"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"gpt-4o-mini",
              "system_fingerprint": "fp_44709d6fcb",
              "choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}]}
          - title: Functions
            request:
              curl: >
                curl https://api.openai.com/v1/chat/completions \

                -H "Content-Type: application/json" \

                -H "Authorization: Bearer $OPENAI_API_KEY" \

                -d '{
                  "model": "gpt-4o",
                  "messages": [
                    {
                      "role": "user",
                      "content": "What is the weather like in Boston today?"
                    }
                  ],
                  "tools": [
                    {
                      "type": "function",
                      "function": {
                        "name": "get_current_weather",
                        "description": "Get the current weather in a given location",
                        "parameters": {
                          "type": "object",
                          "properties": {
                            "location": {
                              "type": "string",
                              "description": "The city and state, e.g. San Francisco, CA"
                            },
                            "unit": {
                              "type": "string",
                              "enum": ["celsius", "fahrenheit"]
                            }
                          },
                          "required": ["location"]
                        }
                      }
                    }
                  ],
                  "tool_choice": "auto"
                }'
              python: >
                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_chat_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-4o",
                    messages: messages,
                    tools: tools,
                    tool_choice: "auto",
                  });

                  console.log(response);
                }


                main();
              csharp: >
                using System;

                using System.Collections.Generic;


                using OpenAI.Chat;


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


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


                List<ChatMessage> messages =

                [
                    new UserChatMessage("What's the weather like in Boston today?"),
                ];


                ChatCompletionOptions options = new()

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


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

                completion = client.chat.completions.create(
                  model="VAR_chat_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_chat_model_id",
                    logprobs: true,
                    top_logprobs: 2,
                  });

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

                main();
              csharp: >
                using System;

                using System.Collections.Generic;


                using OpenAI.Chat;


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


                List<ChatMessage> messages =

                [
                    new UserChatMessage("Hello!")
                ];


                ChatCompletionOptions options = new()

                {
                    IncludeLogProbabilities = true,
                    TopLogProbabilityCount = 2
                };


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


                Console.WriteLine(completion.Content[0].Text);
            response: |
              {
                "id": "chatcmpl-123",
                "object": "chat.completion",
                "created": 1702685778,
                "model": "gpt-4o-mini",
                "choices": [
                  {
                    "index": 0,
                    "message": {
                      "role": "assistant",
                      "content": "Hello! How can I assist you today?"
                    },
                    "logprobs": {
                      "content": [
                        {
                          "token": "Hello",
                          "logprob": -0.31725305,
                          "bytes": [72, 101, 108, 108, 111],
                          "top_logprobs": [
                            {
                              "token": "Hello",
                              "logprob": -0.31725305,
                              "bytes": [72, 101, 108, 108, 111]
                            },
                            {
                              "token": "Hi",
                              "logprob": -1.3190403,
                              "bytes": [72, 105]
                            }
                          ]
                        },
                        {
                          "token": "!",
                          "logprob": -0.02380986,
                          "bytes": [
                            33
                          ],
                          "top_logprobs": [
                            {
                              "token": "!",
                              "logprob": -0.02380986,
                              "bytes": [33]
                            },
                            {
                              "token": " there",
                              "logprob": -3.787621,
                              "bytes": [32, 116, 104, 101, 114, 101]
                            }
                          ]
                        },
                        {
                          "token": " How",
                          "logprob": -0.000054669687,
                          "bytes": [32, 72, 111, 119],
                          "top_logprobs": [
                            {
                              "token": " How",
                              "logprob": -0.000054669687,
                              "bytes": [32, 72, 111, 119]
                            },
                            {
                              "token": "<|end|>",
                              "logprob": -10.953937,
                              "bytes": null
                            }
                          ]
                        },
                        {
                          "token": " can",
                          "logprob": -0.015801601,
                          "bytes": [32, 99, 97, 110],
                          "top_logprobs": [
                            {
                              "token": " can",
                              "logprob": -0.015801601,
                              "bytes": [32, 99, 97, 110]
                            },
                            {
                              "token": " may",
                              "logprob": -4.161023,
                              "bytes": [32, 109, 97, 121]
                            }
                          ]
                        },
                        {
                          "token": " I",
                          "logprob": -3.7697225e-6,
                          "bytes": [
                            32,
                            73
                          ],
                          "top_logprobs": [
                            {
                              "token": " I",
                              "logprob": -3.7697225e-6,
                              "bytes": [32, 73]
                            },
                            {
                              "token": " assist",
                              "logprob": -13.596657,
                              "bytes": [32, 97, 115, 115, 105, 115, 116]
                            }
                          ]
                        },
                        {
                          "token": " assist",
                          "logprob": -0.04571125,
                          "bytes": [32, 97, 115, 115, 105, 115, 116],
                          "top_logprobs": [
                            {
                              "token": " assist",
                              "logprob": -0.04571125,
                              "bytes": [32, 97, 115, 115, 105, 115, 116]
                            },
                            {
                              "token": " help",
                              "logprob": -3.1089056,
                              "bytes": [32, 104, 101, 108, 112]
                            }
                          ]
                        },
                        {
                          "token": " you",
                          "logprob": -5.4385737e-6,
                          "bytes": [32, 121, 111, 117],
                          "top_logprobs": [
                            {
                              "token": " you",
                              "logprob": -5.4385737e-6,
                              "bytes": [32, 121, 111, 117]
                            },
                            {
                              "token": " today",
                              "logprob": -12.807695,
                              "bytes": [32, 116, 111, 100, 97, 121]
                            }
                          ]
                        },
                        {
                          "token": " today",
                          "logprob": -0.0040071653,
                          "bytes": [32, 116, 111, 100, 97, 121],
                          "top_logprobs": [
                            {
                              "token": " today",
                              "logprob": -0.0040071653,
                              "bytes": [32, 116, 111, 100, 97, 121]
                            },
                            {
                              "token": "?",
                              "logprob": -5.5247097,
                              "bytes": [63]
                            }
                          ]
                        },
                        {
                          "token": "?",
                          "logprob": -0.0008108172,
                          "bytes": [63],
                          "top_logprobs": [
                            {
                              "token": "?",
                              "logprob": -0.0008108172,
                              "bytes": [63]
                            },
                            {
                              "token": "?\n",
                              "logprob": -7.184561,
                              "bytes": [63, 10]
                            }
                          ]
                        }
                      ]
                    },
                    "finish_reason": "stop"
                  }
                ],
                "usage": {
                  "prompt_tokens": 9,
                  "completion_tokens": 9,
                  "total_tokens": 18,
                  "completion_tokens_details": {
                    "reasoning_tokens": 0,
                    "accepted_prediction_tokens": 0,
                    "rejected_prediction_tokens": 0
                  }
                },
                "system_fingerprint": null
              }
  /chat/completions/{completion_id}:
    get:
      operationId: getChatCompletion
      tags:
        - Chat
      summary: >
        Get a stored chat completion. Only Chat Completions that have been
        created

        with the `store` parameter set to `true` will be returned.
      parameters:
        - in: path
          name: completion_id
          required: true
          schema:
            type: string
          description: The ID of the chat completion to retrieve.
      responses:
        "200":
          description: A chat completion
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/CreateChatCompletionResponse"
      x-oaiMeta:
        name: Get chat completion
        group: chat
        returns: The [ChatCompletion](/docs/api-reference/chat/object) object matching
          the specified ID.
        examples:
          request:
            curl: |
              curl https://api.openai.com/v1/chat/completions/chatcmpl-abc123 \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json"
            python: >
              from openai import OpenAI

              client = OpenAI()


              completions = client.chat.completions.list()

              first_id = completions[0].id

              first_completion =
              client.chat.completions.retrieve(completion_id=first_id)

              print(first_completion)
          response: >
            {
              "object": "chat.completion",
              "id": "chatcmpl-abc123",
              "model": "gpt-4o-2024-08-06",
              "created": 1738960610,
              "request_id": "req_ded8ab984ec4bf840f37566c1011c417",
              "tool_choice": null,
              "usage": {
                "total_tokens": 31,
                "completion_tokens": 18,
                "prompt_tokens": 13
              },
              "seed": 4944116822809979520,
              "top_p": 1.0,
              "temperature": 1.0,
              "presence_penalty": 0.0,
              "frequency_penalty": 0.0,
              "system_fingerprint": "fp_50cad350e4",
              "input_user": null,
              "service_tier": "default",
              "tools": null,
              "metadata": {},
              "choices": [
                {
                  "index": 0,
                  "message": {
                    "content": "Mind of circuits hum,  \nLearning patterns in silence—  \nFuture's quiet spark.",
                    "role": "assistant",
                    "tool_calls": null,
                    "function_call": null
                  },
                  "finish_reason": "stop",
                  "logprobs": null
                }
              ],
              "response_format": null
            }
    post:
      operationId: updateChatCompletion
      tags:
        - Chat
      summary: >
        Modify a stored chat completion. Only Chat Completions that have been

        created with the `store` parameter set to `true` can be modified.
        Currently,

        the only supported modification is to update the `metadata` field.
      parameters:
        - in: path
          name: completion_id
          required: true
          schema:
            type: string
          description: The ID of the chat completion to update.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              type: object
              required:
                - metadata
              properties:
                metadata:
                  $ref: "#/components/schemas/Metadata"
      responses:
        "200":
          description: A chat completion
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/CreateChatCompletionResponse"
      x-oaiMeta:
        name: Update chat completion
        group: chat
        returns: The [ChatCompletion](/docs/api-reference/chat/object) object matching
          the specified ID.
        examples:
          request:
            curl: >
              curl -X POST
              https://api.openai.com/v1/chat/completions/chat_abc123 \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json" \
                -d '{"metadata": {"foo": "bar"}}'
            python: >
              from openai import OpenAI

              client = OpenAI()


              completions = client.chat.completions.list()

              first_id = completions[0].id

              updated_completion =
              client.chat.completions.update(completion_id=first_id,
              request_body={"metadata": {"foo": "bar"}})

              print(updated_completion)
          response: >
            {
              "object": "chat.completion",
              "id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2",
              "model": "gpt-4o-2024-08-06",
              "created": 1738960610,
              "request_id": "req_ded8ab984ec4bf840f37566c1011c417",
              "tool_choice": null,
              "usage": {
                "total_tokens": 31,
                "completion_tokens": 18,
                "prompt_tokens": 13
              },
              "seed": 4944116822809979520,
              "top_p": 1.0,
              "temperature": 1.0,
              "presence_penalty": 0.0,
              "frequency_penalty": 0.0,
              "system_fingerprint": "fp_50cad350e4",
              "input_user": null,
              "service_tier": "default",
              "tools": null,
              "metadata": {
                "foo": "bar"
              },
              "choices": [
                {
                  "index": 0,
                  "message": {
                    "content": "Mind of circuits hum,  \nLearning patterns in silence—  \nFuture's quiet spark.",
                    "role": "assistant",
                    "tool_calls": null,
                    "function_call": null
                  },
                  "finish_reason": "stop",
                  "logprobs": null
                }
              ],
              "response_format": null
            }
    delete:
      operationId: deleteChatCompletion
      tags:
        - Chat
      summary: |
        Delete a stored chat completion. Only Chat Completions that have been
        created with the `store` parameter set to `true` can be deleted.
      parameters:
        - in: path
          name: completion_id
          required: true
          schema:
            type: string
          description: The ID of the chat completion to delete.
      responses:
        "200":
          description: The chat completion was deleted successfully.
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ChatCompletionDeleted"
      x-oaiMeta:
        name: Delete chat completion
        group: chat
        returns: A deletion confirmation object.
        examples:
          request:
            curl: >
              curl -X DELETE
              https://api.openai.com/v1/chat/completions/chat_abc123 \
                -H "Authorization: Bearer $OPENAI_API_KEY" \
                -H "Content-Type: application/json"
            python: >
              from openai import OpenAI

              client = OpenAI()


              completions = client.chat.completions.list()

              first_id = completions[0].id

              delete_response =
              client.chat.completions.delete(completion_id=first_id)

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

              client = OpenAI()


              completions = client.chat.completions.list()

              first_id = completions[0].id

              first_completion =
              client.chat.completions.retrieve(completion_id=first_id)

              messages =
              client.chat.completions.messages.list(completion_id=first_id)

              print(messages)
          response: |
            {
              "object": "list",
              "data": [
                {
                  "id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2-0",
                  "role": "user",
                  "content": "write a haiku about ai",
                  "name": null,
                  "content_parts": null
                }
              ],
              "first_id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2-0",
              "last_id": "chatcmpl-AyPNinnUqUDYo9SAdA52NobMflmj2-0",
              "has_more": false
            }
  /completions:
    post:
      operationId: createCompletion
      tags:
        - Completions
      summary: Creates a completion for the provided prompt and parameters.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/CreateCompletionRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/CreateCompletionResponse"
      x-oaiMeta:
        name: Create completion
        group: completions
        returns: >
          Returns a [completion](/docs/api-reference/completions/object) object,
          or a sequence of completion objects if the request is streamed.
        legacy: true
        examples:
          - title: No streaming
            request:
              curl: |
                curl https://api.openai.com/v1/completions \
                  -H "Content-Type: application/json" \
                  -H "Authorization: Bearer $OPENAI_API_KEY" \
                  -d '{
                    "model": "VAR_completion_model_id",
                    "prompt": "Say this is a test",
                    "max_tokens": 7,
                    "temperature": 0
                  }'
              python: |
                from openai import OpenAI
                client = OpenAI()

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

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