> ## Documentation Index
> Fetch the complete documentation index at: https://docs.runflow.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Update vector store (CLI/SDK)

> Updates vector store information.



## OpenAPI

````yaml /api-reference/openapi.json patch /api/v1/runtime/vector-stores/{id}
openapi: 3.0.0
info:
  title: Runflow Runtime API
  description: >-
    Programmatic surface for the Runflow platform — used by the SDK, the CLI,
    the execution engine, and any server-to-server caller. Authenticate with an
    `x-api-key` header (or `Authorization: Bearer ...`).
  version: 1.0.0
  contact: {}
servers:
  - url: https://api.runflow.ai
    description: Production
  - url: http://localhost:3000
    description: Local development
security: []
tags: []
paths:
  /api/v1/runtime/vector-stores/{id}:
    patch:
      tags:
        - Runtime API - Vector Stores Management
      summary: Update vector store (CLI/SDK)
      description: Updates vector store information.
      operationId: RuntimeVectorStoresController_updateVectorStore
      parameters:
        - name: id
          required: true
          in: path
          description: Vector store ID or name
          schema:
            type: string
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/UpdateVectorStoreDto'
      responses:
        '200':
          description: Vector store updated successfully.
      security:
        - bearer: []
components:
  schemas:
    UpdateVectorStoreDto:
      type: object
      properties:
        name:
          type: string
          description: Vector store name
        description:
          type: string
          description: Description
        type:
          type: string
          description: Change type to KNOWLEDGE (only STRUCTURED → KNOWLEDGE allowed)
          enum:
            - KNOWLEDGE
        llmProviderConfigId:
          type: string
          description: >-
            New LLM Provider Config ID for the embedding credential. Must be
            sent together with `llmModelConfigId`. The new model must produce
            embeddings with the same `dimensions` as the current config —
            otherwise stored vectors become unusable.
        llmModelConfigId:
          type: string
          description: >-
            New LLM Model Config ID for the embedding model. Must be sent
            together with `llmProviderConfigId`. Must be of type EMBEDDING and
            dimensions must match the current config.

````