Lamini

Lamini Embeddings API

Text embedding generation.

Documentation GitHub OpenAPI

Operations 1

POST /v1/embedding Generate embeddings #

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OpenAPI Specification

openapi: 3.2.0
info:
  title: Lamini Platform Classify Embeddings API
  description: REST API for the Lamini enterprise LLM platform covering inference (completions), fine-tuning and Memory Tuning jobs, classification, and embeddings over open base and tuned models. All requests are authenticated with a Bearer API key and served from https://api.lamini.ai. Endpoints and request fields are derived from the official Lamini Python client (github.com/lamini-ai/lamini) and the Lamini REST API documentation.
  termsOfService: https://www.lamini.ai/terms
  contact:
    name: Lamini Support
    url: https://www.lamini.ai
  version: '1.0'
servers:
- url: https://api.lamini.ai
security:
- bearerAuth: []
tags:
- name: Embeddings
  description: Text embedding generation.
paths:
  /v1/embedding:
    post:
      operationId: createEmbedding
      tags:
      - Embeddings
      summary: Generate embeddings
      description: Encode one or more text prompts into embedding vectors for similarity search, retrieval, and indexing.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/EmbeddingRequest'
      responses:
        '200':
          description: Generated embedding vectors.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/EmbeddingResponse'
components:
  schemas:
    EmbeddingRequest:
      type: object
      required:
      - prompt
      properties:
        prompt:
          oneOf:
          - type: string
          - type: array
            items:
              type: string
          description: One or more texts to embed.
    EmbeddingResponse:
      type: object
      properties:
        embedding:
          type: array
          items:
            type: array
            items:
              type: number
          description: One embedding vector per input prompt.
  securitySchemes:
    bearerAuth:
      type: http
      scheme: bearer
      description: 'Lamini platform API key passed as Authorization: Bearer <API_KEY>. Requests may also include a Lamini-Version header.'