llmatic/api.oas.yml

Use self-hosted LLMs with an OpenAI compatible API

openapi: 3.0.0
info:
  title: OpenAI API
  description: APIs for sampling from and fine-tuning language models
  version: "1.2.0"
servers:
  - url: https://api.openai.com/v1
tags:
  - name: OpenAI
    description: The OpenAI REST API
paths:
  /engines:
    get:
      operationId: listEngines
      deprecated: true
      tags:
        - OpenAI
      summary: Lists the currently available (non-finetuned) models, and provides basic information about each one such as the owner and availability.
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ListEnginesResponse"
      x-oaiMeta:
        name: List engines
        group: engines
        path: list
        examples:
          curl: |
            curl https://api.openai.com/v1/engines \
              -H 'Authorization: Bearer YOUR_API_KEY'
          python: |
            import os
            import openai
            openai.api_key = os.getenv("OPENAI_API_KEY")
            openai.Engine.list()
          node.js: |
            const { Configuration, OpenAIApi } = require("openai");
            const configuration = new Configuration({
              apiKey: process.env.OPENAI_API_KEY,
            });
            const openai = new OpenAIApi(configuration);
            const response = await openai.listEngines();
        response: |
          {
            "data": [
              {
                "id": "engine-id-0",
                "object": "engine",
                "owner": "organization-owner",
                "ready": true
              },
              {
                "id": "engine-id-2",
                "object": "engine",
                "owner": "organization-owner",
                "ready": true
              },
              {
                "id": "engine-id-3",
                "object": "engine",
                "owner": "openai",
                "ready": false
              },
            ],
            "object": "list"
          }

  /engines/{engine_id}:
    get:
      operationId: retrieveEngine
      deprecated: true
      tags:
        - OpenAI
      summary: Retrieves a model instance, providing basic information about it such as the owner and availability.
      parameters:
        - in: path
          name: engine_id
          required: true
          schema:
            type: string
            # ideally this will be an actual ID, so this will always work from browser
            example: davinci
          description: &engine_id_description >
            The ID of the engine to use for this request
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/Engine"
      x-oaiMeta:
        name: Retrieve engine
        group: engines
        path: retrieve
        examples:
          curl: |
            curl https://api.openai.com/v1/engines/VAR_model_id \
              -H 'Authorization: Bearer YOUR_API_KEY'
          python: |
            import os
            import openai
            openai.api_key = os.getenv("OPENAI_API_KEY")
            openai.Engine.retrieve("VAR_model_id")
          node.js: |
            const { Configuration, OpenAIApi } = require("openai");
            const configuration = new Configuration({
              apiKey: process.env.OPENAI_API_KEY,
            });
            const openai = new OpenAIApi(configuration);
            const response = await openai.retrieveEngine("VAR_model_id");
        response: |
          {
            "id": "VAR_model_id",
            "object": "engine",
            "owner": "openai",
            "ready": true
          }

  /completions:
    post:
      operationId: createCompletion
      tags:
        - OpenAI
      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
        path: create
        examples:
          curl: |
            curl https://api.openai.com/v1/completions \
              -H 'Content-Type: application/json' \
              -H 'Authorization: Bearer YOUR_API_KEY' \
              -d '{
              "model": "VAR_model_id",
              "prompt": "Say this is a test",
              "max_tokens": 7,
              "temperature": 0
            }'
          python: |
            import os
            import openai
            openai.api_key = os.getenv("OPENAI_API_KEY")
            openai.Completion.create(
              model="VAR_model_id",
              prompt="Say this is a test",
              max_tokens=7,
              temperature=0
            )
          node.js: |
            const { Configuration, OpenAIApi } = require("openai");
            const configuration = new Configuration({
              apiKey: process.env.OPENAI_API_KEY,
            });
            const openai = new OpenAIApi(configuration);
            const response = await openai.createCompletion({
              model: "VAR_model_id",
              prompt: "Say this is a test",
              max_tokens: 7,
              temperature: 0,
            });
        parameters: |
          {
            "model": "VAR_model_id",
            "prompt": "Say this is a test",
            "max_tokens": 7,
            "temperature": 0,
            "top_p": 1,
            "n": 1,
            "stream": false,
            "logprobs": null,
            "stop": "\n"
          }
        response: |
          {
            "id": "cmpl-uqkvlQyYK7bGYrRHQ0eXlWi7",
            "object": "text_completion",
            "created": 1589478378,
            "model": "VAR_model_id",
            "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
            }
          }
  /chat/completions:
    post:
      operationId: createChatCompletion
      tags:
        - OpenAI
      summary: Creates a completion for the chat message
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/CreateChatCompletionRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/CreateChatCompletionResponse"

      x-oaiMeta:
        name: Create chat completion
        group: chat
        path: create
        beta: true
        examples:
          curl: |
            curl https://api.openai.com/v1/chat/completions \
              -H 'Content-Type: application/json' \
              -H 'Authorization: Bearer YOUR_API_KEY' \
              -d '{
              "model": "gpt-3.5-turbo",
              "messages": [{"role": "user", "content": "Hello!"}]
            }'
          python: |
            import os
            import openai
            openai.api_key = os.getenv("OPENAI_API_KEY")

            completion = openai.ChatCompletion.create(
              model="gpt-3.5-turbo",
              messages=[
                {"role": "user", "content": "Hello!"}
              ]
            )

            print(completion.choices[0].message)
          node.js: |
            const { Configuration, OpenAIApi } = require("openai");

            const configuration = new Configuration({
              apiKey: process.env.OPENAI_API_KEY,
            });
            const openai = new OpenAIApi(configuration);

            const completion = await openai.createChatCompletion({
              model: "gpt-3.5-turbo",
              messages: [{role: "user", content: "Hello world"}],
            });
            console.log(completion.data.choices[0].message);
        parameters: |
          {
            "model": "gpt-3.5-turbo",
            "messages": [{"role": "user", "content": "Hello!"}]
          }
        response: |
          {
            "id": "chatcmpl-123",
            "object": "chat.completion",
            "created": 1677652288,
            "choices": [{
              "index": 0,
              "message": {
                "role": "assistant",
                "content": "\n\nHello there, how may I assist you today?",
              },
              "finish_reason": "stop"
            }],
            "usage": {
              "prompt_tokens": 9,
              "completion_tokens": 12,
              "total_tokens": 21
            }
          }

  /edits:
    post:
      operationId: createEdit
      tags:
        - OpenAI
      summary: Creates a new edit for the provided input, instruction, and parameters.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/CreateEditRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/CreateEditResponse"
      x-oaiMeta:
        name: Create edit
        group: edits
        path: create
        examples:
          curl: |
            curl https://api.openai.com/v1/edits \
              -H 'Content-Type: application/json' \
              -H 'Authorization: Bearer YOUR_API_KEY' \
              -d '{
              "model": "VAR_model_id",
              "input": "What day of the wek is it?",
              "instruction": "Fix the spelling mistakes"
            }'
          python: |
            import os
            import openai
            openai.api_key = os.getenv("OPENAI_API_KEY")
            openai.Edit.create(
              model="VAR_model_id",
              input="What day of the wek is it?",
              instruction="Fix the spelling mistakes"
            )
          node.js: |
            const { Configuration, OpenAIApi } = require("openai");
            const configuration = new Configuration({
              apiKey: process.env.OPENAI_API_KEY,
            });
            const openai = new OpenAIApi(configuration);
            const response = await openai.createEdit({
              model: "VAR_model_id",
              input: "What day of the wek is it?",
              instruction: "Fix the spelling mistakes",
            });
        parameters: |
          {
            "model": "VAR_model_id",
            "input": "What day of the wek is it?",
            "instruction": "Fix the spelling mistakes",
          }
        response: |
          {
            "object": "edit",
            "created": 1589478378,
            "choices": [
              {
                "text": "What day of the week is it?",
                "index": 0,
              }
            ],
            "usage": {
              "prompt_tokens": 25,
              "completion_tokens": 32,
              "total_tokens": 57
            }
          }

  /images/generations:
    post:
      operationId: createImage
      tags:
        - OpenAI
      summary: Creates an image given a prompt.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/CreateImageRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ImagesResponse"
      x-oaiMeta:
        name: Create image
        group: images
        path: create
        beta: true
        examples:
          curl: |
            curl https://api.openai.com/v1/images/generations \
              -H 'Content-Type: application/json' \
              -H 'Authorization: Bearer YOUR_API_KEY' \
              -d '{
              "prompt": "A cute baby sea otter",
              "n": 2,
              "size": "1024x1024"
            }'
          python: |
            import os
            import openai
            openai.api_key = os.getenv("OPENAI_API_KEY")
            openai.Image.create(
              prompt="A cute baby sea otter",
              n=2,
              size="1024x1024"
            )
          node.js: |
            const { Configuration, OpenAIApi } = require("openai");
            const configuration = new Configuration({
              apiKey: process.env.OPENAI_API_KEY,
            });
            const openai = new OpenAIApi(configuration);
            const response = await openai.createImage({
              prompt: "A cute baby sea otter",
              n: 2,
              size: "1024x1024",
            });
        parameters: |
          {
            "prompt": "A cute baby sea otter",
            "n": 2,
            "size": "1024x1024"
          }
        response: |
          {
            "created": 1589478378,
            "data": [
              {
                "url": "https://..."
              },
              {
                "url": "https://..."
              }
            ]
          }

  /images/edits:
    post:
      operationId: createImageEdit
      tags:
        - OpenAI
      summary: Creates an edited or extended image given an original image and a prompt.
      requestBody:
        required: true
        content:
          multipart/form-data:
            schema:
              $ref: "#/components/schemas/CreateImageEditRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ImagesResponse"
      x-oaiMeta:
        name: Create image edit
        group: images
        path: create-edit
        beta: true
        examples:
          curl: |
            curl https://api.openai.com/v1/images/edits \
              -H 'Authorization: Bearer YOUR_API_KEY' \
              -F image='@otter.png' \
              -F mask='@mask.png' \
              -F prompt="A cute baby sea otter wearing a beret" \
              -F n=2 \
              -F size="1024x1024"
          python: |
            import os
            import openai
            openai.api_key = os.getenv("OPENAI_API_KEY")
            openai.Image.create_edit(
              image=open("otter.png", "rb"),
              mask=open("mask.png", "rb"),
              prompt="A cute baby sea otter wearing a beret",
              n=2,
              size="1024x1024"
            )
          node.js: |
            const { Configuration, OpenAIApi } = require("openai");
            const configuration = new Configuration({
              apiKey: process.env.OPENAI_API_KEY,
            });
            const openai = new OpenAIApi(configuration);
            const response = await openai.createImageEdit(
              fs.createReadStream("otter.png"),
              fs.createReadStream("mask.png"),
              "A cute baby sea otter wearing a beret",
              2,
              "1024x1024"
            );
        response: |
          {
            "created": 1589478378,
            "data": [
              {
                "url": "https://..."
              },
              {
                "url": "https://..."
              }
            ]
          }

  /images/variations:
    post:
      operationId: createImageVariation
      tags:
        - OpenAI
      summary: Creates a variation of a given image.
      requestBody:
        required: true
        content:
          multipart/form-data:
            schema:
              $ref: "#/components/schemas/CreateImageVariationRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ImagesResponse"
      x-oaiMeta:
        name: Create image variation
        group: images
        path: create-variation
        beta: true
        examples:
          curl: |
            curl https://api.openai.com/v1/images/variations \
              -H 'Authorization: Bearer YOUR_API_KEY' \
              -F image='@otter.png' \
              -F n=2 \
              -F size="1024x1024"
          python: |
            import os
            import openai
            openai.api_key = os.getenv("OPENAI_API_KEY")
            openai.Image.create_variation(
              image=open("otter.png", "rb"),
              n=2,
              size="1024x1024"
            )
          node.js: |
            const { Configuration, OpenAIApi } = require("openai");
            const configuration = new Configuration({
              apiKey: process.env.OPENAI_API_KEY,
            });
            const openai = new OpenAIApi(configuration);
            const response = await openai.createImageVariation(
              fs.createReadStream("otter.png"),
              2,
              "1024x1024"
            );
        response: |
          {
            "created": 1589478378,
            "data": [
              {
                "url": "https://..."
              },
              {
                "url": "https://..."
              }
            ]
          }

  /embeddings:
    post:
      operationId: createEmbedding
      tags:
        - OpenAI
      summary: Creates an embedding vector representing the input text.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/CreateEmbeddingRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/CreateEmbeddingResponse"
      x-oaiMeta:
        name: Create embeddings
        group: embeddings
        path: create
        examples:
          curl: |
            curl https://api.openai.com/v1/embeddings \
              -X POST \
              -H "Authorization: Bearer YOUR_API_KEY" \
              -H "Content-Type: application/json" \
              -d '{"input": "The food was delicious and the waiter...",
                   "model": "text-embedding-ada-002"}'

          python: |
            import os
            import openai
            openai.api_key = os.getenv("OPENAI_API_KEY")
            openai.Embedding.create(
              model="text-embedding-ada-002",
              input="The food was delicious and the waiter..."
            )
          node.js: |
            const { Configuration, OpenAIApi } = require("openai");
            const configuration = new Configuration({
              apiKey: process.env.OPENAI_API_KEY,
            });
            const openai = new OpenAIApi(configuration);
            const response = await openai.createEmbedding({
              model: "text-embedding-ada-002",
              input: "The food was delicious and the waiter...",
            });
        parameters: |
          {
            "model": "text-embedding-ada-002",
            "input": "The food was delicious and the waiter..."
          }
        response: |
          {
            "object": "list",
            "data": [
              {
                "object": "embedding",
                "embedding": [
                  0.0023064255,
                  -0.009327292,
                  .... (1536 floats total for ada-002)
                  -0.0028842222,
                ],
                "index": 0
              }
            ],
            "model": "text-embedding-ada-002",
            "usage": {
              "prompt_tokens": 8,
              "total_tokens": 8
            }
          }

  /audio/transcriptions:
    post:
      operationId: createTranscription
      tags:
        - OpenAI
      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:
                $ref: "#/components/schemas/CreateTranscriptionResponse"
      x-oaiMeta:
        name: Create transcription
        group: audio
        path: create
        beta: true
        examples:
          curl: |
            curl https://api.openai.com/v1/audio/transcriptions \
              -X POST \
              -H 'Authorization: Bearer TOKEN' \
              -H 'Content-Type: multipart/form-data' \
              -F file=@/path/to/file/audio.mp3 \
              -F model=whisper-1
          python: |
            import os
            import openai
            openai.api_key = os.getenv("OPENAI_API_KEY")
            audio_file = open("audio.mp3", "rb")
            transcript = openai.Audio.transcribe("whisper-1", audio_file)
          node: |
            const { Configuration, OpenAIApi } = require("openai");
            const configuration = new Configuration({
              apiKey: process.env.OPENAI_API_KEY,
            });
            const openai = new OpenAIApi(configuration);
            const resp = await openai.createTranscription(
              fs.createReadStream("audio.mp3"),
              "whisper-1"
            );
        parameters: |
          {
            "file": "audio.mp3",
            "model": "whisper-1"
          }
        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."
          }

  /audio/translations:
    post:
      operationId: createTranslation
      tags:
        - OpenAI
      summary: Translates audio into into English.
      requestBody:
        required: true
        content:
          multipart/form-data:
            schema:
              $ref: "#/components/schemas/CreateTranslationRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/CreateTranslationResponse"
      x-oaiMeta:
        name: Create translation
        group: audio
        path: create
        beta: true
        examples:
          curl: |
            curl https://api.openai.com/v1/audio/translations \
                -X POST \
                -H 'Authorization: Bearer TOKEN' \
                -H 'Content-Type: multipart/form-data' \
                -F file=@/path/to/file/german.m4a \
                -F model=whisper-1
          python: |
            import os
            import openai
            openai.api_key = os.getenv("OPENAI_API_KEY")
            audio_file = open("german.m4a", "rb")
            transcript = openai.Audio.translate("whisper-1", audio_file)
          node: |
            const { Configuration, OpenAIApi } = require("openai");
            const configuration = new Configuration({
              apiKey: process.env.OPENAI_API_KEY,
            });
            const openai = new OpenAIApi(configuration);
            const resp = await openai.createTranslation(
              fs.createReadStream("audio.mp3"),
              "whisper-1"
            );
        parameters: |
          {
            "file": "german.m4a",
            "model": "whisper-1"
          }
        response: |
          {
            "text": "Hello, my name is Wolfgang and I come from Germany. Where are you heading today?"
          }

  /engines/{engine_id}/search:
    post:
      operationId: createSearch
      deprecated: true
      tags:
        - OpenAI
      summary: |
        The search endpoint computes similarity scores between provided query and documents. Documents can be passed directly to the API if there are no more than 200 of them.

        To go beyond the 200 document limit, documents can be processed offline and then used for efficient retrieval at query time. When `file` is set, the search endpoint searches over all the documents in the given file and returns up to the `max_rerank` number of documents. These documents will be returned along with their search scores.

        The similarity score is a positive score that usually ranges from 0 to 300 (but can sometimes go higher), where a score above 200 usually means the document is semantically similar to the query.
      parameters:
        - in: path
          name: engine_id
          required: true
          schema:
            type: string
            example: davinci
          description: The ID of the engine to use for this request.  You can select one of `ada`, `babbage`, `curie`, or `davinci`.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/CreateSearchRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/CreateSearchResponse"
      x-oaiMeta:
        name: Create search
        group: searches
        path: create
        examples:
          curl: |
            curl https://api.openai.com/v1/engines/davinci/search \
              -H "Content-Type: application/json" \
              -H 'Authorization: Bearer YOUR_API_KEY' \
              -d '{
              "documents": ["White House", "hospital", "school"],
              "query": "the president"
            }'
          python: |
            import os
            import openai
            openai.api_key = os.getenv("OPENAI_API_KEY")
            openai.Engine("davinci").search(
              documents=["White House", "hospital", "school"],
              query="the president"
            )
          node.js: |
            const { Configuration, OpenAIApi } = require("openai");
            const configuration = new Configuration({
              apiKey: process.env.OPENAI_API_KEY,
            });
            const openai = new OpenAIApi(configuration);
            const response = await openai.createSearch("davinci", {
              documents: ["White House", "hospital", "school"],
              query: "the president",
            });
        parameters: |
          {
            "documents": [
              "White House",
              "hospital",
              "school"
            ],
            "query": "the president"
          }
        response: |
          {
            "data": [
              {
                "document": 0,
                "object": "search_result",
                "score": 215.412
              },
              {
                "document": 1,
                "object": "search_result",
                "score": 40.316
              },
              {
                "document": 2,
                "object": "search_result",
                "score":  55.226
              }
            ],
            "object": "list"
          }

  /files:
    get:
      operationId: listFiles
      tags:
        - OpenAI
      summary: Returns a list of files that belong to the user's organization.
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ListFilesResponse"
      x-oaiMeta:
        name: List files
        group: files
        path: list
        examples:
          curl: |
            curl https://api.openai.com/v1/files \
              -H 'Authorization: Bearer YOUR_API_KEY'
          python: |
            import os
            import openai
            openai.api_key = os.getenv("OPENAI_API_KEY")
            openai.File.list()
          node.js: |
            const { Configuration, OpenAIApi } = require("openai");
            const configuration = new Configuration({
              apiKey: process.env.OPENAI_API_KEY,
            });
            const openai = new OpenAIApi(configuration);
            const response = await openai.listFiles();
        response: |
          {
            "data": [
              {
                "id": "file-ccdDZrC3iZVNiQVeEA6Z66wf",
                "object": "file",
                "bytes": 175,
                "created_at": 1613677385,
                "filename": "train.jsonl",
                "purpose": "search"
              },
              {
                "id": "file-XjGxS3KTG0uNmNOK362iJua3",
                "object": "file",
                "bytes": 140,
                "created_at": 1613779121,
                "filename": "puppy.jsonl",
                "purpose": "search"
              }
            ],
            "object": "list"
          }
    post:
      operationId: createFile
      tags:
        - OpenAI
      summary: |
        Upload a file that contains document(s) to be used across various endpoints/features. Currently, the size of all the files uploaded by one organization can be up to 1 GB. Please contact us if you need to increase the storage limit.

      requestBody:
        required: true
        content:
          multipart/form-data:
            schema:
              $ref: "#/components/schemas/CreateFileRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/OpenAIFile"
      x-oaiMeta:
        name: Upload file
        group: files
        path: upload
        examples:
          curl: |
            curl https://api.openai.com/v1/files \
              -H "Authorization: Bearer YOUR_API_KEY" \
              -F purpose="fine-tune" \
              -F file='@mydata.jsonl'

          python: |
            import os
            import openai
            openai.api_key = os.getenv("OPENAI_API_KEY")
            openai.File.create(
              file=open("mydata.jsonl", "rb"),
              purpose='fine-tune'
            )
          node.js: |
            const fs = require("fs");
            const { Configuration, OpenAIApi } = require("openai");
            const configuration = new Configuration({
              apiKey: process.env.OPENAI_API_KEY,
            });
            const openai = new OpenAIApi(configuration);
            const response = await openai.createFile(
              fs.createReadStream("mydata.jsonl"),
              "fine-tune"
            );
        response: |
          {
            "id": "file-XjGxS3KTG0uNmNOK362iJua3",
            "object": "file",
            "bytes": 140,
            "created_at": 1613779121,
            "filename": "mydata.jsonl",
            "purpose": "fine-tune"
          }

  /files/{file_id}:
    delete:
      operationId: deleteFile
      tags:
        - OpenAI
      summary: Delete a file.
      parameters:
        - in: path
          name: file_id
          required: true
          schema:
            type: string
          description: The ID of the file to use for this request
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/DeleteFileResponse"
      x-oaiMeta:
        name: Delete file
        group: files
        path: delete
        examples:
          curl: |
            curl https://api.openai.com/v1/files/file-XjGxS3KTG0uNmNOK362iJua3 \
              -X DELETE \
              -H 'Authorization: Bearer YOUR_API_KEY'
          python: |
            import os
            import openai
            openai.api_key = os.getenv("OPENAI_API_KEY")
            openai.File.delete("file-XjGxS3KTG0uNmNOK362iJua3")
          node.js: |
            const { Configuration, OpenAIApi } = require("openai");
            const configuration = new Configuration({
              apiKey: process.env.OPENAI_API_KEY,
            });
            const openai = new OpenAIApi(configuration);
            const response = await openai.deleteFile("file-XjGxS3KTG0uNmNOK362iJua3");
        response: |
          {
            "id": "file-XjGxS3KTG0uNmNOK362iJua3",
            "object": "file",
            "deleted": true
          }
    get:
      operationId: retrieveFile
      tags:
        - OpenAI
      summary: Returns information about a specific file.
      parameters:
        - in: path
          name: file_id
          required: true
          schema:
            type: string
          description: The ID of the file to use for this request
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/OpenAIFile"
      x-oaiMeta:
        name: Retrieve file
        group: files
        path: retrieve
        examples:
          curl: |
            curl https://api.openai.com/v1/files/file-XjGxS3KTG0uNmNOK362iJua3 \
              -H 'Authorization: Bearer YOUR_API_KEY'
          python: |
            import os
            import openai
            openai.api_key = os.getenv("OPENAI_API_KEY")
            openai.File.retrieve("file-XjGxS3KTG0uNmNOK362iJua3")
          node.js: |
            const { Configuration, OpenAIApi } = require("openai");
            const configuration = new Configuration({
              apiKey: process.env.OPENAI_API_KEY,
            });
            const openai = new OpenAIApi(configuration);
            const response = await openai.retrieveFile("file-XjGxS3KTG0uNmNOK362iJua3");
        response: |
          {
            "id": "file-XjGxS3KTG0uNmNOK362iJua3",
            "object": "file",
            "bytes": 140,
            "created_at": 1613779657,
            "filename": "mydata.jsonl",
            "purpose": "fine-tune"
          }

  /files/{file_id}/content:
    get:
      operationId: downloadFile
      tags:
        - OpenAI
      summary: Returns the contents of the specified file
      parameters:
        - in: path
          name: file_id
          required: true
          schema:
            type: string
          description: The ID of the file to use for this request
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                type: string
      x-oaiMeta:
        name: Retrieve file content
        group: files
        path: retrieve-content
        examples:
          curl: |
            curl https://api.openai.com/v1/files/file-XjGxS3KTG0uNmNOK362iJua3/content \
              -H 'Authorization: Bearer YOUR_API_KEY' > file.jsonl
          python: |
            import os
            import openai
            openai.api_key = os.getenv("OPENAI_API_KEY")
            content = openai.File.download("file-XjGxS3KTG0uNmNOK362iJua3")
          node.js: |
            const { Configuration, OpenAIApi } = require("openai");
            const configuration = new Configuration({
              apiKey: process.env.OPENAI_API_KEY,
            });
            const openai = new OpenAIApi(configuration);
            const response = await openai.downloadFile("file-XjGxS3KTG0uNmNOK362iJua3");

  /answers:
    post:
      operationId: createAnswer
      deprecated: true
      tags:
        - OpenAI
      summary: |
        Answers the specified question using the provided documents and examples.

        The endpoint first [searches](/docs/api-reference/searches) over provided documents or files to find relevant context. The relevant context is combined with the provided examples and question to create the prompt for [completion](/docs/api-reference/completions).
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/CreateAnswerRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/CreateAnswerResponse"
      x-oaiMeta:
        name: Create answer
        group: answers
        path: create
        examples:
          curl: |
            curl https://api.openai.com/v1/answers \
              -X POST \
              -H "Authorization: Bearer YOUR_API_KEY" \
              -H 'Content-Type: application/json' \
              -d '{
                "documents": ["Puppy A is happy.", "Puppy B is sad."],
                "question": "which puppy is happy?",
                "search_model": "ada",
                "model": "curie",
                "examples_context": "In 2017, U.S. life expectancy was 78.6 years.",
                "examples": [["What is human life expectancy in the United States?","78 years."]],
                "max_tokens": 5,
                "stop": ["\n", "<|endoftext|>"]
              }'

          python: |
            import os
            import openai
            openai.api_key = os.getenv("OPENAI_API_KEY")
            openai.Answer.create(
              search_model="ada",
              model="curie",
              question="which puppy is happy?",
              documents=["Puppy A is happy.", "Puppy B is sad."],
              examples_context="In 2017, U.S. life expectancy was 78.6 years.",
              examples=[["What is human life expectancy in the United States?","78 years."]],
              max_tokens=5,
              stop=["\n", "<|endoftext|>"],
            )
          node.js: |
            const { Configuration, OpenAIApi } = require("openai");
            const configuration = new Configuration({
              apiKey: process.env.OPENAI_API_KEY,
            });
            const openai = new OpenAIApi(configuration);
            const response = await openai.createAnswer({
              search_model: "ada",
              model: "curie",
              question: "which puppy is happy?",
              documents: ["Puppy A is happy.", "Puppy B is sad."],
              examples_context: "In 2017, U.S. life expectancy was 78.6 years.",
              examples: [["What is human life expectancy in the United States?","78 years."]],
              max_tokens: 5,
              stop: ["\n", "<|endoftext|>"],
            });
        parameters: |
          {
            "documents": ["Puppy A is happy.", "Puppy B is sad."],
            "question": "which puppy is happy?",
            "search_model": "ada",
            "model": "curie",
            "examples_context": "In 2017, U.S. life expectancy was 78.6 years.",
            "examples": [["What is human life expectancy in the United States?","78 years."]],
            "max_tokens": 5,
            "stop": ["\n", "<|endoftext|>"]
          }
        response: |
          {
            "answers": [
              "puppy A."
            ],
            "completion": "cmpl-2euVa1kmKUuLpSX600M41125Mo9NI",
            "model": "curie:2020-05-03",
            "object": "answer",
            "search_model": "ada",
            "selected_documents": [
              {
                "document": 0,
                "text": "Puppy A is happy. "
              },
              {
                "document": 1,
                "text": "Puppy B is sad. "
              }
            ]
          }

  /classifications:
    post:
      operationId: createClassification
      deprecated: true
      tags:
        - OpenAI
      summary: |
        Classifies the specified `query` using provided examples.

        The endpoint first [searches](/docs/api-reference/searches) over the labeled examples
        to select the ones most relevant for the particular query. Then, the relevant examples
        are combined with the query to construct a prompt to produce the final label via the
        [completions](/docs/api-reference/completions) endpoint.

        Labeled examples can be provided via an uploaded `file`, or explicitly listed in the
        request using the `examples` parameter for quick tests and small scale use cases.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/CreateClassificationRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/CreateClassificationResponse"
      x-oaiMeta:
        name: Create classification
        group: classifications
        path: create
        examples:
          curl: |
            curl https://api.openai.com/v1/classifications \
              -X POST \
              -H "Authorization: Bearer YOUR_API_KEY" \
              -H 'Content-Type: application/json' \
              -d '{
                "examples": [
                  ["A happy moment", "Positive"],
                  ["I am sad.", "Negative"],
                  ["I am feeling awesome", "Positive"]],
                "query": "It is a raining day :(",
                "search_model": "ada",
                "model": "curie",
                "labels":["Positive", "Negative", "Neutral"]
              }'
          python: |
            import os
            import openai
            openai.api_key = os.getenv("OPENAI_API_KEY")
            openai.Classification.create(
              search_model="ada",
              model="curie",
              examples=[
                ["A happy moment", "Positive"],
                ["I am sad.", "Negative"],
                ["I am feeling awesome", "Positive"]
              ],
              query="It is a raining day :(",
              labels=["Positive", "Negative", "Neutral"],
            )
          node.js: |
            const { Configuration, OpenAIApi } = require("openai");
            const configuration = new Configuration({
              apiKey: process.env.OPENAI_API_KEY,
            });
            const openai = new OpenAIApi(configuration);
            const response = await openai.createClassification({
              search_model: "ada",
              model: "curie",
              examples: [
                ["A happy moment", "Positive"],
                ["I am sad.", "Negative"],
                ["I am feeling awesome", "Positive"]
              ],
              query:"It is a raining day :(",
              labels: ["Positive", "Negative", "Neutral"],
            });
        parameters: |
          {
            "examples": [
              ["A happy moment", "Positive"],
              ["I am sad.", "Negative"],
              ["I am feeling awesome", "Positive"]
            ],
            "labels": ["Positive", "Negative", "Neutral"],
            "query": "It is a raining day :(",
            "search_model": "ada",
            "model": "curie"
          }
        response: |
          {
            "completion": "cmpl-2euN7lUVZ0d4RKbQqRV79IiiE6M1f",
            "label": "Negative",
            "model": "curie:2020-05-03",
            "object": "classification",
            "search_model": "ada",
            "selected_examples": [
              {
                "document": 1,
                "label": "Negative",
                "text": "I am sad."
              },
              {
                "document": 0,
                "label": "Positive",
                "text": "A happy moment"
              },
              {
                "document": 2,
                "label": "Positive",
                "text": "I am feeling awesome"
              }
            ]
          }

  /fine-tunes:
    post:
      operationId: createFineTune
      tags:
        - OpenAI
      summary: |
        Creates a job that fine-tunes a specified model from a given dataset.

        Response includes details of the enqueued job including job status and the name of the fine-tuned models once complete.

        [Learn more about Fine-tuning](/docs/guides/fine-tuning)
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/CreateFineTuneRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/FineTune"
      x-oaiMeta:
        name: Create fine-tune
        group: fine-tunes
        path: create
        examples:
          curl: |
            curl https://api.openai.com/v1/fine-tunes \
              -X POST \
              -H "Content-Type: application/json" \
              -H "Authorization: Bearer YOUR_API_KEY" \
              -d '{
              "training_file": "file-XGinujblHPwGLSztz8cPS8XY"
            }'
          python: |
            import os
            import openai
            openai.api_key = os.getenv("OPENAI_API_KEY")
            openai.FineTune.create(training_file="file-XGinujblHPwGLSztz8cPS8XY")
          node.js: |
            const { Configuration, OpenAIApi } = require("openai");
            const configuration = new Configuration({
              apiKey: process.env.OPENAI_API_KEY,
            });
            const openai = new OpenAIApi(configuration);
            const response = await openai.createFineTune({
              training_file: "file-XGinujblHPwGLSztz8cPS8XY",
            });
        response: |
          {
            "id": "ft-AF1WoRqd3aJAHsqc9NY7iL8F",
            "object": "fine-tune",
            "model": "curie",
            "created_at": 1614807352,
            "events": [
              {
                "object": "fine-tune-event",
                "created_at": 1614807352,
                "level": "info",
                "message": "Job enqueued. Waiting for jobs ahead to complete. Queue number: 0."
              }
            ],
            "fine_tuned_model": null,
            "hyperparams": {
              "batch_size": 4,
              "learning_rate_multiplier": 0.1,
              "n_epochs": 4,
              "prompt_loss_weight": 0.1,
            },
            "organization_id": "org-...",
            "result_files": [],
            "status": "pending",
            "validation_files": [],
            "training_files": [
              {
                "id": "file-XGinujblHPwGLSztz8cPS8XY",
                "object": "file",
                "bytes": 1547276,
                "created_at": 1610062281,
                "filename": "my-data-train.jsonl",
                "purpose": "fine-tune-train"
              }
            ],
            "updated_at": 1614807352,
          }
    get:
      operationId: listFineTunes
      tags:
        - OpenAI
      summary: |
        List your organization's fine-tuning jobs
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ListFineTunesResponse"
      x-oaiMeta:
        name: List fine-tunes
        group: fine-tunes
        path: list
        examples:
          curl: |
            curl https://api.openai.com/v1/fine-tunes \
              -H 'Authorization: Bearer YOUR_API_KEY'
          python: |
            import os
            import openai
            openai.api_key = os.getenv("OPENAI_API_KEY")
            openai.FineTune.list()
          node.js: |
            const { Configuration, OpenAIApi } = require("openai");
            const configuration = new Configuration({
              apiKey: process.env.OPENAI_API_KEY,
            });
            const openai = new OpenAIApi(configuration);
            const response = await openai.listFineTunes();
        response: |
          {
            "object": "list",
            "data": [
              {
                "id": "ft-AF1WoRqd3aJAHsqc9NY7iL8F",
                "object": "fine-tune",
                "model": "curie",
                "created_at": 1614807352,
                "fine_tuned_model": null,
                "hyperparams": { ... },
                "organization_id": "org-...",
                "result_files": [],
                "status": "pending",
                "validation_files": [],
                "training_files": [ { ... } ],
                "updated_at": 1614807352,
              },
              { ... },
              { ... }
            ]
          }

  /fine-tunes/{fine_tune_id}:
    get:
      operationId: retrieveFineTune
      tags:
        - OpenAI
      summary: |
        Gets info about the fine-tune job.

        [Learn more about Fine-tuning](/docs/guides/fine-tuning)
      parameters:
        - in: path
          name: fine_tune_id
          required: true
          schema:
            type: string
            example: ft-AF1WoRqd3aJAHsqc9NY7iL8F
          description: |
            The ID of the fine-tune job
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/FineTune"
      x-oaiMeta:
        name: Retrieve fine-tune
        group: fine-tunes
        path: retrieve
        examples:
          curl: |
            curl https://api.openai.com/v1/fine-tunes/ft-AF1WoRqd3aJAHsqc9NY7iL8F \
              -H "Authorization: Bearer YOUR_API_KEY"
          python: |
            import os
            import openai
            openai.api_key = os.getenv("OPENAI_API_KEY")
            openai.FineTune.retrieve(id="ft-AF1WoRqd3aJAHsqc9NY7iL8F")
          node.js: |
            const { Configuration, OpenAIApi } = require("openai");
            const configuration = new Configuration({
              apiKey: process.env.OPENAI_API_KEY,
            });
            const openai = new OpenAIApi(configuration);
            const response = await openai.retrieveFineTune("ft-AF1WoRqd3aJAHsqc9NY7iL8F");
        response: |
          {
            "id": "ft-AF1WoRqd3aJAHsqc9NY7iL8F",
            "object": "fine-tune",
            "model": "curi