Marqo Embeddings API

openapi: 3.1.0
info:
  title: Marqo REST Documents Embeddings API
  version: '2.26'
  summary: Open-source multimodal vector search engine REST API.
  description: 'Marqo is an open-source vector search engine that bundles index storage

    (Vespa) and embedding inference (Sentence Transformers, OpenCLIP, ONNX)

    behind a single FastAPI HTTP surface. The engine is reachable at

    `http://{host}:8882` by default and publishes its live OpenAPI schema at

    `/openapi.json` with interactive Swagger UI at `/docs`. The same surface

    is exposed by the hosted Marqo Cloud product at `https://api.marqo.ai`

    with bearer-token authentication.


    This profile is a hand-curated, best-effort companion spec covering the

    most-used operations across indexes, documents, search, embeddings,

    models, and telemetry. For the canonical, version-pinned specification

    of a deployment, fetch `/openapi.json` directly from the running engine.

    '
  contact:
    name: Marqo
    url: https://www.marqo.ai
  license:
    name: Apache 2.0
    url: https://github.com/marqo-ai/marqo/blob/mainline/LICENSE
servers:
- url: http://localhost:8882
  description: Default Marqo open-source engine endpoint
- url: https://api.marqo.ai
  description: Marqo Cloud endpoint (bearer authentication)
security: []
tags:
- name: Embeddings
  description: Generate embedding vectors using engine-loaded models.
paths:
  /indexes/{index_name}/embed:
    post:
      tags:
      - Embeddings
      summary: Generate Embeddings
      operationId: embed
      parameters:
      - $ref: '#/components/parameters/IndexName'
      requestBody:
        required: true
        content:
          application/json:
            schema:
              type: object
              required:
              - content
              properties:
                content:
                  oneOf:
                  - type: string
                  - type: array
                    items:
                      type: string
                  description: Text and/or image URLs to embed using the index model.
      responses:
        '200':
          description: Embedding vectors.
components:
  parameters:
    IndexName:
      in: path
      name: index_name
      required: true
      schema:
        type: string
      description: Name of the Marqo index.
  securitySchemes:
    BearerAuth:
      type: http
      scheme: bearer
      description: 'Marqo Cloud API key passed as `Authorization: Bearer {api_key}`.

        The open-source engine accepts unauthenticated requests by default.

        '