Flowise

Flowise vector API

The vector API from Flowise — 1 operation(s) for vector.

Documentation GitHub OpenAPI

Operations 1

POST /vector/upsert/{id} Upsert vector embeddings #

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OpenAPI Specification

openapi: 3.2.0
info:
  title: Flowise APIs assistants Vector API
  version: 1.0.0
  description: 'Flowise REST API for managing AI agent flows, chatflows, assistants, document stores, tools, variables, and predictions.

    Bearer token authentication uses an API key generated in the Flowise admin UI. The default server is your local or hosted Flowise instance at /api/v1.

    '
  license:
    name: Apache 2.0
    url: https://github.com/FlowiseAI/Flowise/blob/main/LICENSE.md
  contact:
    name: FlowiseAI
    email: support@flowiseai.com
servers:
- url: http://localhost:3000/api/v1
  description: Local Flowise server
- url: https://{instance}.flowiseai.com/api/v1
  description: Flowise Cloud instance
  variables:
    instance:
      default: app
tags:
- name: vector
paths:
  /vector/upsert/{id}:
    post:
      tags:
      - vector
      security:
      - bearerAuth: []
      operationId: vectorUpsert
      summary: Upsert vector embeddings
      description: Upsert vector embeddings of documents in a chatflow
      parameters:
      - in: path
        name: id
        required: true
        schema:
          type: string
        description: Chatflow ID
      requestBody:
        content:
          application/json:
            schema:
              type: object
              properties:
                stopNodeId:
                  type: string
                  description: In cases when you have multiple vector store nodes, you can specify the node ID to store the vectors
                  example: node_1
                overrideConfig:
                  type: object
                  description: The configuration to override the default vector upsert settings (optional)
          multipart/form-data:
            schema:
              type: object
              properties:
                files:
                  type: array
                  items:
                    type: string
                    format: binary
                  description: Files to be uploaded
                modelName:
                  type:
                  - string
                  - 'null'
                  example: ''
                  description: Other override configurations
              required:
              - files
        required: true
      responses:
        '200':
          description: Vector embeddings upserted successfully
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorUpsertResponse'
        '400':
          description: Invalid input provided
        '404':
          description: Chatflow not found
        '422':
          description: Validation error
        '500':
          description: Internal server error
components:
  schemas:
    Document:
      type: object
      properties:
        pageContent:
          type: string
          example: This is the content of the page.
        metadata:
          type: object
          additionalProperties:
            type: string
          example:
            author: John Doe
            date: '2024-08-24'
    VectorUpsertResponse:
      type: object
      properties:
        numAdded:
          type: number
          description: Number of vectors added
          example: 1
        numDeleted:
          type: number
          description: Number of vectors deleted
          example: 1
        numUpdated:
          type: number
          description: Number of vectors updated
          example: 1
        numSkipped:
          type: number
          description: Number of vectors skipped (not added, deleted, or updated)
          example: 1
        addedDocs:
          type: array
          items:
            $ref: '#/components/schemas/Document'
  securitySchemes:
    bearerAuth:
      type: http
      scheme: bearer
      bearerFormat: JWT