Telnyx OpenAI Embeddings API

openapi: 3.2.0
info:
  contact:
    email: support@telnyx.com
  description: Telnyx provides global communications and connectivity APIs for developers — including SIP trunking, programmable voice, SMS, MMS, WhatsApp Business Messaging, Call Control, Fax, Wireless (IoT & eSIM), Phone Numbers (DID provisioning & porting), Emergency Services, and Network APIs for private interconnects and edge connectivity. Build, scale, and manage voice, messaging, and data networks with Telnyx's carrier-grade global infrastructure and API-first platform.
  title: Telnyx OpenAI Embeddings API
  version: 2.0.0
  x-endpoint-cost: light
servers:
- description: Version 2.0.0 of the Telnyx API
  url: https://api.telnyx.com/v2
security:
- bearerAuth: []
tags:
- description: OpenAI-compatible embeddings endpoints for generating vector representations of text
  name: OpenAI Embeddings
paths:
  /ai/openai/embeddings:
    post:
      description: Creates an embedding vector representing the input text. This endpoint is compatible with the OpenAI Embeddings API and may be used with the OpenAI JS or Python SDK by setting the base URL to `https://api.telnyx.com/v2/ai/openai`.
      operationId: create_openai_embeddings
      requestBody:
        content:
          application/json:
            example:
              input: The quick brown fox jumps over the lazy dog
              model: thenlper/gte-large
            schema:
              $ref: '#/components/schemas/OpenAIEmbeddingRequest'
        required: true
      responses:
        '200':
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/OpenAIEmbeddingResponse'
          description: Successful Response
        '422':
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
          description: Validation Error
      summary: Create embeddings
      tags:
      - OpenAI Embeddings
      x-latency-category: responsive
  /ai/openai/embeddings/models:
    get:
      description: Returns a list of available embedding models. This endpoint is compatible with the OpenAI Models API format.
      operationId: list_openai_embedding_models
      responses:
        '200':
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/OpenAIEmbeddingModelsResponse'
          description: Successful Response
        '422':
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
          description: Validation Error
      summary: List embedding models
      tags:
      - OpenAI Embeddings
      x-latency-category: responsive
components:
  schemas:
    OpenAIEmbeddingUsage:
      properties:
        prompt_tokens:
          description: Number of tokens in the input
          type: integer
        total_tokens:
          description: Total number of tokens used
          type: integer
      required:
      - prompt_tokens
      - total_tokens
      title: OpenAIEmbeddingUsage
      type: object
    OpenAIEmbeddingResponse:
      properties:
        data:
          description: List of embedding objects
          items:
            $ref: '#/components/schemas/OpenAIEmbeddingData'
          type: array
        model:
          description: The model used for embedding
          type: string
        object:
          default: list
          description: The object type, always 'list'
          type: string
        usage:
          $ref: '#/components/schemas/OpenAIEmbeddingUsage'
      required:
      - object
      - data
      - model
      - usage
      title: OpenAIEmbeddingResponse
      type: object
    OpenAIEmbeddingModelsResponse:
      properties:
        data:
          description: List of available embedding models
          items:
            $ref: '#/components/schemas/OpenAIEmbeddingModelMetadata'
          type: array
        object:
          default: list
          description: The object type, always 'list'
          type: string
      required:
      - object
      - data
      title: OpenAIEmbeddingModelsResponse
      type: object
    OpenAIEmbeddingData:
      properties:
        embedding:
          description: The embedding vector
          items:
            type: number
          type: array
        index:
          description: The index of the embedding in the list of embeddings
          type: integer
        object:
          default: embedding
          description: The object type, always 'embedding'
          type: string
      required:
      - object
      - embedding
      - index
      title: OpenAIEmbeddingData
      type: object
    ValidationError:
      properties:
        loc:
          items:
            anyOf:
            - type: string
            - type: integer
          title: Location
          type: array
        msg:
          title: Message
          type: string
        type:
          title: Error Type
          type: string
      required:
      - loc
      - msg
      - type
      title: ValidationError
      type: object
    OpenAIEmbeddingModelMetadata:
      properties:
        created:
          description: Unix timestamp of when the model was created
          type: integer
        id:
          description: The model identifier
          example: thenlper/gte-large
          type: string
        object:
          default: model
          description: The object type, always 'model'
          type: string
        owned_by:
          description: The organization that owns the model
          example: telnyx
          type: string
      required:
      - id
      - object
      - created
      - owned_by
      title: OpenAIEmbeddingModelMetadata
      type: object
    OpenAIEmbeddingRequest:
      properties:
        dimensions:
          description: The number of dimensions the resulting output embeddings should have. Only supported in some models.
          type: integer
        encoding_format:
          default: float
          description: The format to return the embeddings in.
          enum:
          - float
          - base64
          type: string
        input:
          description: Input text to embed. Can be a string or array of strings.
          oneOf:
          - description: A single text string to embed
            type: string
          - description: An array of text strings to embed
            items:
              type: string
            type: array
        model:
          description: ID of the model to use. Use the List embedding models endpoint to see available models.
          example: thenlper/gte-large
          type: string
        user:
          description: A unique identifier representing your end-user for monitoring and abuse detection.
          type: string
      required:
      - input
      - model
      title: OpenAIEmbeddingRequest
      type: object
    HTTPValidationError:
      properties:
        detail:
          items:
            $ref: '#/components/schemas/ValidationError'
          title: Detail
          type: array
      title: HTTPValidationError
      type: object
  securitySchemes:
    bearerAuth:
      scheme: bearer
      type: http
    branded-calling_bearerAuth:
      description: API key passed as a Bearer token in the Authorization header
      scheme: bearer
      type: http
    oauthClientAuth:
      description: OAuth 2.0 authentication for Telnyx API and MCP integrations
      flows:
        authorizationCode:
          authorizationUrl: https://api.telnyx.com/v2/oauth/authorize
          refreshUrl: https://api.telnyx.com/v2/oauth/token
          scopes:
            admin: Administrative access to Telnyx resources
          tokenUrl: https://api.telnyx.com/v2/oauth/token
        clientCredentials:
          scopes:
            admin: Administrative access to Telnyx resources
          tokenUrl: https://api.telnyx.com/v2/oauth/token
      type: oauth2
    outbound-voice-profiles_bearerAuth:
      bearerFormat: JWT
      scheme: bearer
      type: http
    pronunciation-dicts_bearerAuth:
      description: Telnyx API v2 key. Obtain from https://portal.telnyx.com
      scheme: bearer
      type: http
    stored-payment-transactions_bearerAuth:
      bearerFormat: JWT
      scheme: bearer
      type: http