RadioCheck-F1-Assistant 🏎️📻

RadioCheck-F1-Assistant is an AI-powered assistant that delivers real-time Formula 1 insights through natural conversation. Ask about driver and constructor standings, championship odds with Monte Carlo simulations, race weather forecasts, and watch official YouTube highlights—all presented in a clean, interactive interface. Built with React, Python agents powered by Google Gemini, and orchestrated through LangGraph, RadioCheck brings the paddock to your fingertips.

✨ Features

🏆 Driver & Constructor Standings

Get real-time F1 championship standings with detailed points breakdowns for drivers and teams.

📊 Championship Predictions

Ask about any driver's championship chances and get Monte Carlo simulation-based probability estimates with detailed race-by-race projections.

🌤️ Race Weather Forecasts

Check weather conditions for upcoming or past Grand Prix locations with conversational, human-readable summaries.

🎥 YouTube Highlights

Watch official Formula 1 race highlights directly through the chat interface. Supports event-specific searches with year filtering.

💬 Rich Chat Interface

• Markdown rendering with tables, links, and formatting
• Authentication with Google Sign-In
• Session management to track conversation history
• Responsive design optimized for desktop and mobile

🔧 AI-Powered Agent System

• Built with LangGraph for intelligent agent orchestration
• Powered by Google Gemini for natural language understanding
• Modular agent architecture for easy extensibility

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🚀 Tech Stack

Frontend

• React 18 with Vite for fast development
• Tailwind CSS for styling
• React Markdown for rich text rendering
• Axios for API communication

Backend

• Python 3.12+ with FastAPI
• LangGraph for agent orchestration
• Google Gemini API for LLM capabilities
• YouTube Data API v3 for video search
• OpenWeather API for weather data
• Web scraping for F1 standings data

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📦 Installation

Prerequisites

• Node.js (v18 or higher)
• Python 3.12+
• npm or yarn
• API Keys:
  • Google Gemini API Key
  • YouTube Data API v3 Key
  • OpenWeather API Key

1. Clone the Repository

git clone https://github.com/Arfa-Ahsan/RadioCheck-F1-Assistant.git
cd RadioCheck-F1-Assistant

2. Backend Setup

cd backend

# Create virtual environment
python -m venv .venv

# Activate virtual environment
# Windows:
.venv\Scripts\activate
# macOS/Linux:
source .venv/bin/activate

# Install dependencies
pip install -r requirements.txt

# Create .env file and add your API keys
# See .env.example for required variables

Environment Variables (create a .env file in the backend/ directory):

GEMINI_API_KEY=your_gemini_api_key_here
YOUTUBE_API_KEY=your_youtube_api_key_here
OPENWEATHER_API_KEY=your_openweather_api_key_here

3. Frontend Setup

cd ../frontend

# Install dependencies
npm install

# Start development server
npm run dev

4. Run the Application

Terminal 1 - Backend:

cd backend
.venv\Scripts\activate  # Windows
python main.py

Terminal 2 - Frontend:

cd frontend
npm run dev

The frontend will be available at http://localhost:5173 (or the port Vite assigns).

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🎯 Usage

1. Sign in with your Google account
2. Ask questions like:
   • "Give me the driver standings"
   • "What chance does Max Verstappen have to win the championship?"
   • "Show me highlights of the Monaco Grand Prix 2024"
   • "What is the weather at the Singapore Grand Prix?"
3. View results formatted with tables, links, and rich text
4. Browse sessions to revisit previous conversations

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🗂️ Project Structure

RadioCheck-F1-Assistant/
├── backend/
│   ├── agents/                  # AI agent modules
│   │   ├── standings_agent.py   # Driver/constructor standings
│   │   ├── champ_estimate.py    # Championship predictions
│   │   ├── weather_agent.py     # Weather forecasts
│   │   └── youtube_highlights_agent.py  # YouTube search
│   ├── scraped_data/            # F1 standings JSON data
│   ├── web_scraping/            # Data scraping scripts
│   ├── uploads/                 # User uploaded files
│   ├── main.py                  # FastAPI + LangGraph orchestrator
│   ├── app.py                   # Additional backend logic
│   ├── requirements.txt         # Python dependencies
│   └── .env                     # Environment variables (not committed)
├── frontend/
│   ├── src/
│   │   ├── components/          # React components
│   │   │   ├── ChatAssistant.jsx
│   │   │   ├── Landing.jsx
│   │   │   ├── GoogleSignIn.jsx
│   │   │   └── ProfileModal.jsx
│   │   ├── api/                 # API client
│   │   ├── assets/              # Images and static files
│   │   ├── App.jsx
│   │   └── main.jsx
│   ├── public/
│   ├── package.json
│   └── vite.config.js
└── README.md

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🤖 Agents Overview

Standings Agent

Fetches and formats driver and constructor championship standings from scraped F1 data.

Championship Estimator

Uses Monte Carlo simulations to predict championship probabilities based on current points, remaining races, and historical performance.

Weather Agent

Provides location-based weather forecasts for Grand Prix circuits using OpenWeather API and F1 circuit location data.

YouTube Highlights Agent

Searches the official Formula 1 YouTube channel for race highlights with:

• Event-specific queries (e.g., "Monza Grand Prix")
• Year filtering and extraction
• Relevance-based ordering with date fallback
• Event alias mapping (Monza ↔ Italian Grand Prix)

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🛠️ Development

Run Tests

# Backend tests
cd backend
pytest

# Frontend tests
cd frontend
npm test

Build for Production

Frontend:

cd frontend
npm run build

Backend: Deploy with your preferred Python hosting service (e.g., Railway, Render, AWS Lambda).

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🔒 Security Notes

• Never commit .env files or API keys
• Use environment variables for all secrets
• Backend validates authentication tokens
• CORS is configured for frontend origin only

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🤝 Contributing

Contributions are welcome! Please follow these steps:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

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📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

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🙏 Acknowledgments

• Formula 1 for the sport and data
• Google Gemini for LLM capabilities
• LangChain/LangGraph for agent orchestration
• OpenWeather for weather data
• YouTube Data API for video search

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📧 Contact

Arfa Ahsan

• GitHub: @Arfa-Ahsan
• Repository: RadioCheck-F1-Assistant

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🏁 Roadmap

• Add support for driver/team comparison
• Implement real-time race updates
• Add lap time analysis
• Support for historical season data
• Voice input support

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Built with ❤️ for Formula 1 fans by fans.