🏎️ F1 Pulse

An AI-powered Formula 1 race result predictor with a beautiful, user-friendly interface. Perfect for both F1 enthusiasts and newcomers to the sport.

• 🤖 AI-Powered Predictions: Get instant race predictions using machine learning
• 🎨 Beautiful UI: Modern, intuitive interface that's easy to use
• 🚀 Fast Performance: Built with Next.js for optimal speed
• 📱 Responsive Design: Works perfectly on desktop and mobile devices
• 🌙 Dark Mode: Automatic dark mode support
• 🗺️ Interactive Map: Select races visually on a world map
• 🎯 Custom Scenarios: Create your own race scenarios for predictions

This project consists of two separate, independently deployable applications:

• Frontend: Next.js application (deployed to Vercel)
• Backend: FastAPI application (deployed to Railway/Render)

They communicate via REST API calls. See DEPLOYMENT.md for deployment instructions.

f1-pulse/
├── app/                    # Next.js frontend application
│   ├── page.tsx           # Main prediction interface
│   ├── components/        # React components
│   ├── utils/             # Utility functions
│   └── ...
├── backend/               # FastAPI backend (standalone)
│   ├── main.py           # FastAPI application
│   ├── F1_predict_md.py  # ML model integration
│   ├── requirements.txt  # Python dependencies
│   ├── Procfile          # Deployment config
│   ├── railway.json      # Railway config
│   ├── render.yaml       # Render config
│   └── README.md         # Backend documentation
├── public/                # Static assets
├── DEPLOYMENT.md          # Deployment guide
└── README.md              # This file

• For Frontend: Node.js 18+ and npm
• For Backend: Python 3.11+ and pip

1. Install dependencies:

   npm install

2. Set environment variable (create .env.local):

   NEXT_PUBLIC_API_URL=http://localhost:8000

3. Run the development server:

   npm run dev

4. Open http://localhost:3000 in your browser

See backend/README.md for detailed setup instructions.

Quick start:

cd backend
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -r requirements.txt
uvicorn main:app --reload --host 0.0.0.0 --port 8000

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

1. Start both servers:

   • Frontend: npm run dev (runs on port 3000)
   • Backend: uvicorn main:app --reload (runs on port 8000)

2. Open the app in your browser at http://localhost:3000

3. Select a race from the map or dropdown, or create a custom scenario

4. Click "Generate Prediction" to see AI-powered race predictions!

• GET / - Health check
• GET /health - Health check
• POST /predict - Get race predictions
  • Request: { "race_name": "Monaco Grand Prix", "circuit_name": "...", "race_date": "..." }
  • Response: { "predicted_winner": "...", "top_3": [...], "confidence": 0.85, ... }

When the backend is running, visit:

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

Create .env.local in the root directory:

NEXT_PUBLIC_API_URL=http://localhost:8000

For production, set this in your deployment platform (e.g., Vercel).

Set ALLOWED_ORIGINS to allow frontend requests:

export ALLOWED_ORIGINS="http://localhost:3000,https://your-app.vercel.app"

For production, set this in your deployment platform (e.g., Railway/Render).

• Frontend: Next.js 16, React 19, TypeScript, Tailwind CSS, Leaflet
• Backend: FastAPI, Python 3.11+, CatBoost, FastF1, Pandas
• Deployment:
  • Frontend: Vercel (or any Next.js hosting)
  • Backend: Railway, Render, or any Python hosting platform

npm run dev      # Start dev server
npm run build    # Build for production
npm run start    # Start production server
npm run lint     # Run linter

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

See backend/README.md for more details.

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Submit a pull request

MIT License - feel free to use this project for your own purposes!

For detailed deployment instructions, see DEPLOYMENT.md.

Quick summary:

1. Deploy backend to Railway/Render (set ALLOWED_ORIGINS)
2. Deploy frontend to Vercel (set NEXT_PUBLIC_API_URL)
3. Both services communicate via HTTP API

For issues or questions:

• Backend: See backend/README.md
• Deployment: See DEPLOYMENT.md
• API docs: http://localhost:8000/docs (when backend is running)

Built with ❤️ for F1 fans and AI enthusiasts