Vector DB API

A FastAPI-based backend service for vector database operations, providing efficient storage and retrieval of vector embeddings.

Features

• FastAPI-based REST API
• Vector database operations
• Docker containerization support
• Kubernetes deployment configuration
• Comprehensive logging system
• Test suite included

Prerequisites

• Python 3.8+
• Docker (optional, for containerized deployment)
• Kubernetes (optional, for cluster deployment)

Installation

1. Clone the repository:

git clone https://github.com/bluesky0724/backend-vector-db.git
cd backend-vector-db

2. Create and activate a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

pip install -r requirements.txt

Running the Application

Local Development

Run the application using:

python main.py

The API will be available at http://localhost:8000

Docker Deployment

Build and run the Docker container:

docker build -t vector-db-api .
docker run -p 8000:8000 vector-db-api

Kubernetes Deployment

Deploy using the provided Kubernetes configurations:

kubectl apply -f deployment.yaml
kubectl apply -f service.yaml

Project Structure

backend-vector-db/
├── src/                # Source code
├── tests/             # Test files
├── main.py            # Application entry point
├── requirements.txt   # Python dependencies
├── Dockerfile         # Docker configuration
├── deployment.yaml    # Kubernetes deployment config
├── service.yaml       # Kubernetes service config
└── setup.sh           # Setup script

API Documentation

Once the application is running, you can access the interactive API documentation at:

• Swagger UI: http://localhost:8000/docs

Testing

Run the test suite:

pytest tests/