openapi: 3.0.0 info: title: 'OpenAI embeddings' description: Needs description. version: 2.0.0 termsOfService: https://openai.com/policies/terms-of-use contact: name: OpenAI Support url: https://help.openai.com/ license: name: MIT url: https://github.com/openai/openai-openapi/blob/master/LICENSE servers: - url: https://api.openai.com/v1 tags: - name: Embeddings description: >- Get a vector representation of a given input that can be easily consumed by machine learning models and algorithms. paths: /embeddings: post: operationId: createEmbedding tags: - Embeddings summary: OpenAI Creates an embedding vector representing the input text. requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/CreateEmbeddingRequest' responses: '200': description: OK content: application/json: schema: $ref: '#/components/schemas/CreateEmbeddingResponse' x-oaiMeta: name: Create embeddings group: embeddings returns: A list of [embedding](/docs/api-reference/embeddings/object) objects. examples: request: curl: | curl https://api.openai.com/v1/embeddings \ -H "Authorization: Bearer $OPENAI_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "input": "The food was delicious and the waiter...", "model": "text-embedding-ada-002", "encoding_format": "float" }' python: | from openai import OpenAI client = OpenAI() client.embeddings.create( model="text-embedding-ada-002", input="The food was delicious and the waiter...", encoding_format="float" ) node.js: |- import OpenAI from "openai"; const openai = new OpenAI(); async function main() { const embedding = await openai.embeddings.create({ model: "text-embedding-ada-002", input: "The quick brown fox jumped over the lazy dog", encoding_format: "float", }); console.log(embedding); } main(); response: | { "object": "list", "data": [ { "object": "embedding", "embedding": [ 0.0023064255, -0.009327292, .... (1536 floats total for ada-002) -0.0028842222, ], "index": 0 } ], "model": "text-embedding-ada-002", "usage": { "prompt_tokens": 8, "total_tokens": 8 } } components: securitySchemes: ApiKeyAuth: type: http scheme: bearer schemas: CreateEmbeddingResponse: type: object properties: data: type: array description: The list of embeddings generated by the model. items: $ref: '#/components/schemas/Embedding' model: type: string description: The name of the model used to generate the embedding. object: type: string description: The object type, which is always "list". enum: - list usage: type: object description: The usage information for the request. properties: prompt_tokens: type: integer description: The number of tokens used by the prompt. total_tokens: type: integer description: The total number of tokens used by the request. required: - prompt_tokens - total_tokens required: - object - model - data - usage security: - ApiKeyAuth: [] x-oaiMeta: groups: - id: audio title: Audio description: | Learn how to turn audio into text or text into audio. Related guide: [Speech to text](/docs/guides/speech-to-text) sections: - type: endpoint key: createSpeech path: createSpeech - type: endpoint key: createTranscription path: createTranscription - type: endpoint key: createTranslation path: createTranslation - id: chat title: Chat description: > Given a list of messages comprising a conversation, the model will return a response. Related guide: [Chat Completions](/docs/guides/text-generation) sections: - type: endpoint key: createChatCompletion path: create - type: object key: CreateChatCompletionResponse path: object - type: object key: CreateChatCompletionStreamResponse path: streaming - id: embeddings title: Embeddings description: > Get a vector representation of a given input that can be easily consumed by machine learning models and algorithms. Related guide: [Embeddings](/docs/guides/embeddings) sections: - type: endpoint key: createEmbedding path: create - type: object key: Embedding path: object - id: fine-tuning title: Fine-tuning description: > Manage fine-tuning jobs to tailor a model to your specific training data. Related guide: [Fine-tune models](/docs/guides/fine-tuning) sections: - type: endpoint key: createFineTuningJob path: create - type: endpoint key: listPaginatedFineTuningJobs path: list - type: endpoint key: listFineTuningEvents path: list-events - type: endpoint key: retrieveFineTuningJob path: retrieve - type: endpoint key: cancelFineTuningJob path: cancel - type: object key: FineTuningJob path: object - type: object key: FineTuningJobEvent path: event-object - id: files title: Files description: > Files are used to upload documents that can be used with features like [Assistants](/docs/api-reference/assistants) and [Fine-tuning](/docs/api-reference/fine-tuning). sections: - type: endpoint key: createFile path: create - type: endpoint key: listFiles path: list - type: endpoint key: retrieveFile path: retrieve - type: endpoint key: deleteFile path: delete - type: endpoint key: downloadFile path: retrieve-contents - type: object key: OpenAIFile path: object - id: images title: Images description: > Given a prompt and/or an input image, the model will generate a new image. Related guide: [Image generation](/docs/guides/images) sections: - type: endpoint key: createImage path: create - type: endpoint key: createImageEdit path: createEdit - type: endpoint key: createImageVariation path: createVariation - type: object key: Image path: object - id: models title: Models description: > List and describe the various models available in the API. You can refer to the [Models](/docs/models) documentation to understand what models are available and the differences between them. sections: - type: endpoint key: listModels path: list - type: endpoint key: retrieveModel path: retrieve - type: endpoint key: deleteModel path: delete - type: object key: Model path: object - id: moderations title: Moderations description: > Given a input text, outputs if the model classifies it as violating OpenAI's content policy. Related guide: [Moderations](/docs/guides/moderation) sections: - type: endpoint key: createModeration path: create - type: object key: CreateModerationResponse path: object - id: assistants title: Assistants beta: true description: | Build assistants that can call models and use tools to perform tasks. [Get started with the Assistants API](/docs/assistants) sections: - type: endpoint key: createAssistant path: createAssistant - type: endpoint key: createAssistantFile path: createAssistantFile - type: endpoint key: listAssistants path: listAssistants - type: endpoint key: listAssistantFiles path: listAssistantFiles - type: endpoint key: getAssistant path: getAssistant - type: endpoint key: getAssistantFile path: getAssistantFile - type: endpoint key: modifyAssistant path: modifyAssistant - type: endpoint key: deleteAssistant path: deleteAssistant - type: endpoint key: deleteAssistantFile path: deleteAssistantFile - type: object key: AssistantObject path: object - type: object key: AssistantFileObject path: file-object - id: threads title: Threads beta: true description: | Create threads that assistants can interact with. Related guide: [Assistants](/docs/assistants/overview) sections: - type: endpoint key: createThread path: createThread - type: endpoint key: getThread path: getThread - type: endpoint key: modifyThread path: modifyThread - type: endpoint key: deleteThread path: deleteThread - type: object key: ThreadObject path: object - id: messages title: Messages beta: true description: | Create messages within threads Related guide: [Assistants](/docs/assistants/overview) sections: - type: endpoint key: createMessage path: createMessage - type: endpoint key: listMessages path: listMessages - type: endpoint key: listMessageFiles path: listMessageFiles - type: endpoint key: getMessage path: getMessage - type: endpoint key: getMessageFile path: getMessageFile - type: endpoint key: modifyMessage path: modifyMessage - type: object key: MessageObject path: object - type: object key: MessageFileObject path: file-object - id: runs title: Runs beta: true description: | Represents an execution run on a thread. Related guide: [Assistants](/docs/assistants/overview) sections: - type: endpoint key: createRun path: createRun - type: endpoint key: createThreadAndRun path: createThreadAndRun - type: endpoint key: listRuns path: listRuns - type: endpoint key: listRunSteps path: listRunSteps - type: endpoint key: getRun path: getRun - type: endpoint key: getRunStep path: getRunStep - type: endpoint key: modifyRun path: modifyRun - type: endpoint key: submitToolOuputsToRun path: submitToolOutputs - type: endpoint key: cancelRun path: cancelRun - type: object key: RunObject path: object - type: object key: RunStepObject path: step-object - id: completions title: Completions legacy: true description: > Given a prompt, the model will return one or more predicted completions along with the probabilities of alternative tokens at each position. Most developer should use our [Chat Completions API](/docs/guides/text-generation/text-generation-models) to leverage our best and newest models. Most models that support the legacy Completions endpoint [will be shut off on January 4th, 2024](/docs/deprecations/2023-07-06-gpt-and-embeddings). sections: - type: endpoint key: createCompletion path: create - type: object key: CreateCompletionResponse path: object