Groq Embeddings API

openapi: 3.2.0
info:
  title: GroqCloud Audio Embeddings API
  description: Specification of the Groq cloud API
  termsOfService: https://groq.com/terms-of-use/
  contact:
    name: Groq Support
    email: support@groq.com
  version: '2.1'
servers:
- url: https://api.groq.com
security:
- api_key: []
tags:
- name: Embeddings
paths:
  /openai/v1/embeddings:
    post:
      operationId: createEmbedding
      tags:
      - Embeddings
      summary: Creates an embedding vector representing the input text.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateEmbeddingRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/CreateEmbeddingResponse'
components:
  schemas:
    CreateEmbeddingRequest:
      type: object
      additionalProperties: false
      properties:
        input:
          description: 'Input text to embed, encoded as a string or array of tokens. To embed multiple inputs in a single request, pass an array of strings or array of token arrays. The input must not exceed the max input tokens for the model, cannot be an empty string, and any array must be 2048 dimensions or less.

            '
          example: The quick brown fox jumped over the lazy dog
          oneOf:
          - type: string
            title: string
            description: The string that will be turned into an embedding.
            default: ''
            example: This is a test.
          - type: array
            title: array
            description: The array of strings that will be turned into an embeddings.
            minItems: 1
            maxItems: 2048
            items:
              type: string
              default: ''
              example: '[''This is a test.'']'
          x-groq-meta:
            validator: EmbeddingInput
        model:
          description: 'ID of the model to use.

            '
          example: nomic-embed-text-v1_5
          anyOf:
          - type: string
          - type: string
            enum:
            - nomic-embed-text-v1_5
        encoding_format:
          description: The format to return the embeddings in. Can only be `float` or `base64`.
          example: float
          default: float
          type: string
          enum:
          - float
          - base64
        user:
          type:
          - string
          - 'null'
          description: A unique identifier representing your end-user, which can help us monitor and detect abuse.
      required:
      - model
      - input
    CreateEmbeddingResponse:
      type: object
      properties:
        data:
          type: array
          description: The list of embeddings generated by the model.
          items:
            $ref: '#/components/schemas/Embedding'
        model:
          type: string
          description: The name of the model used to generate the embedding.
        object:
          type: string
          description: The object type, which is always "list".
          enum:
          - list
        usage:
          type: object
          description: The usage information for the request.
          properties:
            prompt_tokens:
              type: integer
              description: The number of tokens used by the prompt.
            total_tokens:
              type: integer
              description: The total number of tokens used by the request.
          required:
          - prompt_tokens
          - total_tokens
      required:
      - object
      - model
      - data
      - usage
    Embedding:
      type: object
      description: 'Represents an embedding vector returned by embedding endpoint.

        '
      properties:
        index:
          type: integer
          description: The index of the embedding in the list of embeddings.
        embedding:
          oneOf:
          - type: array
            description: 'The embedding vector, which is a list of floats. The length of vector depends on the model as listed in the [embedding guide](/docs/guides/embeddings).

              '
            items:
              type: number
          - type: string
            description: 'The embedding vector, which is a base64 encoded string. The length of vector depends on the model as listed in the [embedding guide](/docs/guides/embeddings).

              '
        object:
          type: string
          description: The object type, which is always "embedding".
          enum:
          - embedding
      required:
      - index
      - object
      - embedding
  securitySchemes:
    api_key:
      type: http
      scheme: bearer
      bearerFormat: apiKey
x-groq-metadata:
  groups:
  - id: chat
    type: endpoints
    title: Chat
    description: ''
    sections:
    - type: endpoint
      key: createChatCompletion
      path: create
  - id: responses
    type: endpoints
    title: Responses (beta)
    description: ''
    sections:
    - type: endpoint
      key: createResponse
      path: create
  - id: audio
    type: endpoints
    title: Audio
    description: ''
    sections:
    - type: endpoint
      key: createTranscription
      path: transcription
    - type: endpoint
      key: createTranslation
      path: translation
    - type: endpoint
      key: createSpeech
      path: speech
  - id: models
    type: endpoints
    title: Models
    description: ''
    sections:
    - type: endpoint
      key: listModels
      path: list
    - type: endpoint
      key: retrieveModel
      path: retrieve
  - id: batches
    type: endpoints
    title: Batches
    description: ''
    sections:
    - type: endpoint
      key: createBatch
      path: create
    - type: endpoint
      key: retrieveBatch
      path: retrieve
    - type: endpoint
      key: listBatches
      path: list
    - type: endpoint
      key: cancelBatch
      path: cancel
  - id: files
    type: endpoints
    title: Files
    description: ''
    sections:
    - type: endpoint
      key: uploadFile
      path: upload
    - type: endpoint
      key: listFiles
      path: list
    - type: endpoint
      key: deleteFile
      path: delete
    - type: endpoint
      key: retrieveFile
      path: retrieve
    - type: endpoint
      key: downloadFile
      path: download
  - id: fine-tuning
    type: endpoints
    title: Fine Tuning
    description: ''
    sections:
    - type: endpoint
      key: listFineTunings
      path: list
    - type: endpoint
      key: createFineTuning
      path: create
    - type: endpoint
      key: getFineTuning
      path: get
    - type: endpoint
      key: deleteFineTuning
      path: delete