cyborgdb-service 0.11.0

CyborgDB Service

CyborgDB Service

A FastAPI-based REST API wrapper for CyborgDB, providing Confidential Vector DB capabilities over HTTP. It enables you to ingest & search vectors emeddings in a privacy-preserving manner, without revealing the contents of the vectors themselves. CyborgDB works with existing DBs (e.g., Postgres, Redis) and enables you to add, query and retrieve vector embeddings with transparent end-to-end encryption.

Features

• End-to-End Encryption: Vector embeddings remain encrypted throughout their lifecycle, including at search time
• Zero-Trust Design: Novel architecture keeps confidential inference data secure
• High Performance: GPU-accelerated indexing and retrieval with CUDA support
• Familiar API: Easy integration with existing AI workflows
• Multiple Backing Stores: Works with PostgreSQL, Redis, and in-memory storage
• Cloud Ready: Supports AWS RDS, AWS ElastiCache, Azure Database for PostgreSQL, Azure Cache for Redis, Google Cloud SQL, and Google Cloud Memorystore

Getting Started

Prerequisites

• Python 3.11+
• Conda/Mamba environment manager

Installation

1. Install cyborgdb-service from pip

   pip install cyborgdb-service
   

2. Set environment variables

   export CYBORGDB_API_KEY=your_api_key_here
   export CYBORGDB_DB_TYPE='redis|postgres'
   export CYBORGDB_CONNECTION_STRING=your_connection_string_here
   

   For connection string examples run cyborgdb-service --help

3. Run the server

   cyborgdb-service
   

API Key Configuration

You need to provide your API key using any of these methods:

Method 1: Environment Variable (Easiest)

export CYBORGDB_API_KEY=your_api_key_here
docker-compose up

Method 2: .env File (Most Convenient)

Create a .env file in the project root:

CYBORGDB_API_KEY=your_api_key_here

Then run:

docker-compose up

Method 3: Inline with Docker Compose

CYBORGDB_API_KEY=your_api_key_here docker-compose up

Build from Source

1. Clone the repository

   git clone https://github.com/yourusername/cyborgdb-service.git
   cd cyborgdb-service
   

2. Create and activate the conda environment

   conda env create -f environment.yml
   conda activate cyborgdb-service
   

3. Attach a git tag based on the version of core you want installed

   git tag v0.11.0-dev
   

4. Install cyborgdb-service as a local pip package

   pip install -e .
   

5. Run the server

   cyborgdb-service
   

6. Visit the API documentation at http://localhost:8000/v1/docs

Running Tests

pytest --cov=cyborgdb_service

Documentation

For more information on API endpoints and usage, see the API Documentation.