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Create vector store
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Create a vector store

Create a new vector store for semantic search and RAG (Retrieval Augmented Generation).

POSThttps://api.aitronos.com/v1/organizations/{organization_id}/vector-stores

Vector stores enable semantic search across your documents. Upload files, and the AI can search and reference them in responses.

Path Parameters

organization_id string required

The unique identifier of the organization.

Request Body

name string required

Name of the vector store.

description string optional

Description of the vector store's purpose or contents.

access_mode string optional · Defaults to organization

Access control level:

  • public - Everyone can access
  • organization - All organization members
  • department - Specific departments only
  • private - Only creator and specified users

access_departments array optional

Department IDs that can access (when access_mode is department).

access_users array optional

User IDs that can access (when access_mode is private).

flowplate_project_id string optional

Associate this vector store with a Flowplate project.

flow_id string optional

Associate this vector store with a specific flow.

Returns

A Vector Store object.

Bash
curl -X POST "https://api.aitronos.com/v1/organizations/org_abc123/vector-stores" \
  -H "X-API-Key: $FREDDY_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "Product Documentation",
    "description": "Knowledge base for product support"
  }'

Response:

{
  "id": "vs_abc123",
  "object": "vector_store",
  "name": "Product Documentation",
  "description": "Knowledge base for product support",
  "organization_id": "org_abc123",
  "created_by": "usr_alice123",
  "access_mode": "organization",
  "access_departments": [],
  "access_users": [],
  "file_count": 0,
  "total_size_bytes": 0,
  "status": "active",
  "created_at": "2025-11-13T10:30:00Z",
  "updated_at": "2025-11-13T10:30:00Z"
}
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