Chess Bot API

A chess engine application with three different bot difficulty levels and a React-based frontend interface.

Project Structure

• Backend: FastAPI-based REST API with three chess engines
• Frontend: React + Vite with chess.js and react-chessboard

Features

Chess Engines

1. Bot V1: Simple alpha-beta pruning engine
2. Bot V2: Enhanced with iterative deepening, transposition tables, and late move reduction
3. Bot VIP: Advanced engine with static exchange evaluation, aspiration windows, and pawn hash tables

Quick Start with Docker

Local Development

docker-compose up -d

Services will be available at:

• Backend API: http://localhost:8000/docs
• Frontend: http://localhost:5000

Production Deployment

1. Create production environment file:

cp .env.prod.example .env.prod

2. Configure environment variables in .env.prod:

# Docker Hub credentials
DOCKERHUB_USERNAME=your_dockerhub_username

# Frontend API URL - IMPORTANT!
# Use relative path /api for nginx reverse proxy setup
VITE_API_URL=/api

# Or use full URL if not using reverse proxy:
# VITE_API_URL=https://your-domain.com/api

3. Build images with production config:

# Use the build script (recommended)
./scripts/build-prod.sh

# Or manually with docker-compose
docker-compose -f docker-compose.prod.yml build

# Or build directly with docker
docker build --build-arg VITE_API_URL=/api -t username/chess-bot-frontend:latest ./Frontend

4. Deploy: ./scripts/deploy.sh

> **Note**: `VITE_API_URL` is a build-time variable for Vite. If you change it, you must rebuild the frontend image.

### Stop Services

```bash
docker-compose down

View Logs

docker-compose logs -f

Manual Setup

Backend

1. Navigate to Backend folder:

cd Backend

2. Install dependencies:

pip install -r requirements.txt

3. Run the server:

uvicorn main:app --reload --host 0.0.0.0 --port 8000

API documentation: http://localhost:8000/docs

Frontend

1. Navigate to Frontend folder:

cd Frontend

2. Setup environment variables:

cp .env.example .env

Edit .env to configure API URL:

VITE_API_URL=http://localhost:8000

3. Install dependencies:

5pm install

4. Run development server:

npm run dev

Application: http://localhost:5173

4. Build for production:

npm run build

API Endpoints

Get Best Move

POST /api/v1/best-move
POST /api/v2/best-move
POST /api/vip/best-move

Request body:

{
  "fen": "rnbqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR w KQkq - 0 1",
  "depth": 4
}

Response:

{
  "move": "e2e4",
  "eval": 0.5
}

Development

Run Tests

Backend:

cd Backend
pytest

Frontend:

cd Frontend
npm run lint

Technology Stack

Backend

• FastAPI
• python-chess
• uvicorn
• numpy
• pydantic-settings

Frontend

• React 19
• Vite
• chess.js
• react-chessboard
• axios

Docker Images

• Backend: Python 3.11-slim based (approximately 150-200MB)
• Frontend: Multi-stage Nginx Alpine based (approximately 25-35MB)

🚀 CI/CD Deployment

This project includes automated CI/CD pipeline for deploying to Google Cloud Platform.

Quick Setup

1. Docker Hub: Create account and access token
2. GCP VM: Setup Ubuntu VM with Docker installed
3. GitHub Secrets: Configure deployment secrets
4. Nginx: Setup reverse proxy on GCP
5. Deploy: Push to GitHub → Auto deploy!

Documentation

• CI/CD Quick Start - 10-step setup guide
• Complete Deployment Guide - Detailed documentation with monitoring and troubleshooting

GitHub Actions Workflow

Pipeline automatically:

1. ✅ Builds Docker images
2. ✅ Pushes to Docker Hub with version tags
3. ✅ Deploys to GCP via SSH
4. ✅ Runs health checks

Triggers on:

• Push to main or prod branch
• Manual workflow dispatch

Required GitHub Secrets

| Secret | Description | |--------|-------------| | DOCKERHUB_USERNAME | Docker Hub username | | DOCKERHUB_TOKEN | Docker Hub access token | | GCP_HOST | GCP VM public IP | | GCP_USERNAME | SSH username | | GCP_SSH_KEY | SSH private key |

Production URLs

After deployment, access your application:

• Frontend: http://YOUR_GCP_IP/
• API Docs: http://YOUR_GCP_IP/docs
• API Endpoint: http://YOUR_GCP_IP/api/

License

[Add your license here]