Langdock Embeddings API

openapi: 3.2.0
info:
  title: Langdock Embeddings API
  version: 3.0.0
servers:
- url: https://api.langdock.com
  description: Production
security:
- bearerAuth: []
tags:
- name: Embeddings
paths:
  /openai/{region}/v1/embeddings:
    post:
      tags:
      - Embeddings
      summary: Creates embeddings for the given input text
      parameters:
      - name: region
        in: path
        required: true
        description: The region of the API to use.
        schema:
          type: string
          enum:
          - eu
          - us
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateEmbeddingRequest'
            example:
              model: text-embedding-ada-002
              input: The quick brown fox jumps over the lazy dog
              encoding_format: float
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/CreateEmbeddingResponse'
              example:
                data:
                - embedding:
                  - 0.0023064255
                  - -0.009327292
                  - '...'
                  index: 0
                  object: embedding
                model: text-embedding-ada-002
                object: list
                usage:
                  prompt_tokens: 9
                  total_tokens: 9
        '400':
          description: Bad Request
          content:
            application/json:
              schema:
                type: object
                properties:
                  message:
                    type: string
                    oneOf:
                    - example: No embedding models available for the ${region} region
                description: Error message indicating either no models are available in the region or the requested model is not available
        '401':
          description: Unauthorized
          content:
            application/json:
              schema:
                type: object
                properties:
                  message:
                    type: string
                    example: The provided API key is invalid.
        '429':
          description: Rate Limit Exceeded
          content:
            application/json:
              schema:
                type: object
                properties:
                  message:
                    type: string
                    example: Rate limit for public API exceeded
        '500':
          description: Internal Server Error
          content:
            application/json:
              schema:
                type: object
                properties:
                  message:
                    type: string
                    example: Internal Server Error
      security:
      - bearerAuth: []
      operationId: postOpenaiByRegionV1Embeddings
      x-operation-id-source: derived
components:
  schemas:
    CreateEmbeddingRequest:
      type: object
      properties:
        input:
          description: Input text to get embeddings for, encoded as a string or array of tokens. To get embeddings for multiple inputs in a single request, pass an array of strings or array of tokens, e.g. `["text1", "text2"]`. Each input must not exceed 8192 tokens in length.
          oneOf:
          - type: string
          - type: array
            items:
              type: string
          - type: array
            items:
              type: number
          - type: array
            items:
              type: array
              items:
                type: number
        model:
          description: ID of the model to use. You can use the [List models](https://platform.openai.com/docs/api-reference/models/list) API to see all of your available models, or see OpenAI's [Model overview](https://platform.openai.com/docs/models/overview) for descriptions of them.
          oneOf:
          - type: string
          - type: string
            enum:
            - text-embedding-ada-002
            - text-embedding-3-small
            - text-embedding-3-large
        encoding_format:
          description: The format to return the embeddings in. Can be either `float` or `base64`.
          type: string
          enum:
          - float
          - base64
          default: float
        dimensions:
          description: The number of dimensions the resulting output embeddings should have. Only supported in `text-embedding-3` and later models.
          type: integer
          minimum: 1
        user:
          description: A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse.
          type: string
      required:
      - model
      - input
    CreateEmbeddingResponse:
      type: object
      properties:
        data:
          type: array
          items:
            $ref: '#/components/schemas/Embedding'
          description: The list of embeddings generated by the model.
        model:
          type: string
          description: The name of the model used to generate the embedding.
        object:
          type: string
          enum:
          - list
          description: The object type, which is always "list".
        usage:
          type: object
          properties:
            prompt_tokens:
              type: integer
              description: The number of tokens used for the prompt(s).
            total_tokens:
              type: integer
              description: The total number of tokens used by the request.
          required:
          - prompt_tokens
          - total_tokens
      required:
      - data
      - model
      - object
      - usage
    Embedding:
      type: object
      properties:
        index:
          type: integer
          description: The index of the embedding in the list of embeddings.
        embedding:
          type: array
          items:
            type: number
          description: The embedding vector, which is a list of floats. The length of vector depends on the model as listed in the [embedding guide](https://platform.openai.com/docs/guides/embeddings).
        object:
          type: string
          enum:
          - embedding
          description: The object type, which is always "embedding".
      required:
      - index
      - embedding
      - object
  securitySchemes:
    bearerAuth:
      type: http
      scheme: bearer
      bearerFormat: API Key
      description: API key as Bearer token. Format "Bearer YOUR_API_KEY"