Vector Database API

REST API for vector database operations using Milvus.

Base URL

https://api.cloud.tenzro.com/vec

Endpoints

Create Database

POST /vec/databases
Content-Type: application/json
X-Project-ID: proj_xyz

{
  "name": "embeddings",
  "dimension": 1536,
  "metric": "COSINE",
  "index_type": "HNSW",
  "index_params": {
    "M": 16,
    "efConstruction": 256
  }
}

# Response
{
  "vec_db_id": "vec_abc123",
  "name": "embeddings",
  "dimension": 1536,
  "metric": "COSINE",
  "status": "ready",
  "created_at": "2024-01-15T00:00:00Z"
}

List Databases

GET /vec/databases
X-Project-ID: proj_xyz

# Response
{
  "databases": [
    {
      "vec_db_id": "vec_abc123",
      "name": "embeddings",
      "dimension": 1536,
      "vector_count": 10000,
      "status": "ready"
    }
  ]
}

Insert Vectors

POST /vec/databases/{vec_db_id}/vectors
Content-Type: application/json

{
  "vectors": [
    {
      "id": "doc_1",
      "vector": [0.1, 0.2, ...],
      "metadata": {
        "title": "Document 1",
        "category": "tech"
      }
    }
  ]
}

# Response
{
  "inserted": 1,
  "ids": ["doc_1"]
}

Search Vectors

POST /vec/databases/{vec_db_id}/search
Content-Type: application/json

{
  "vector": [0.1, 0.2, ...],
  "top_k": 10,
  "filter": {
    "category": "tech"
  },
  "include_metadata": true,
  "include_vectors": false
}

# Response
{
  "results": [
    {
      "id": "doc_1",
      "score": 0.95,
      "metadata": {
        "title": "Document 1",
        "category": "tech"
      }
    }
  ]
}

Get Vector

GET /vec/databases/{vec_db_id}/vectors/{vector_id}

# Response
{
  "id": "doc_1",
  "vector": [0.1, 0.2, ...],
  "metadata": {
    "title": "Document 1"
  }
}

Delete Vectors

DELETE /vec/databases/{vec_db_id}/vectors
Content-Type: application/json

{
  "ids": ["doc_1", "doc_2"]
}

# Response
{
  "deleted": 2
}

Delete Database

DELETE /vec/databases/{vec_db_id}

# Response
{
  "success": true,
  "deleted_at": "2024-01-15T12:00:00Z"
}

Filter Syntax

{
  "filter": {
    "category": "tech",
    "score": { "$gte": 0.5 },
    "tags": { "$in": ["ai", "ml"] },
    "$and": [
      { "status": "active" },
      { "date": { "$gte": "2024-01-01" } }
    ]
  }
}

Error Responses

{
  "error": {
    "code": "dimension_mismatch",
    "message": "Vector dimension 768 does not match database dimension 1536",
    "status": 400
  }
}