🚀 CFanatic

AI-Powered Codeforces Performance Analyzer

Unlock your competitive programming potential with intelligent insights powered by Google Gemini

Features • Quick Start • Demo Video • Tech Stack • Contributing

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✨ Features

🤖 AI-Powered Analysis Leveraging Google Gemini and LangGraph to provide: Deep performance insights Personalized problem recommendations Contest strategy suggestions Weakness identification and improvement paths	📊 Comprehensive Metrics Real-time analysis of your Codeforces profile: Rating trends and predictions Topic-wise problem distribution Contest performance analytics Submission history analysis
💬 Persistent Chat History Never lose your insights: Multi-session conversation support Searchable chat history Context-aware responses Session management	🔒 Security First Your data, your control: End-to-end API key encryption Secure authentication (JWT) No API key storage on servers Privacy-focused architecture

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🎯 Why CFanatic?

Traditional practice tracking tools show you what you solved.
CFanatic tells you why it matters and what to do next.

• 💡 Smart Recommendations: Not just random problems - get personalized suggestions based on your strengths and weaknesses
• 🎓 Learning Path: AI-curated problem sets that match your skill level and learning goals
• 📈 Performance Tracking: Visualize your growth and identify patterns in your problem-solving journey
• 🤝 Conversational Interface: Ask questions naturally - "What topics should I focus on?" or "Why did my rating drop?"

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🎬 Demo Video

👆 Click to watch CFanatic in action - AI-powered Codeforces analysis

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🚀 Quick Start

Prerequisites

Before you begin, ensure you have:

• Python 3.11+ (Download)
• Node.js 20+ (Download)
• Gemini API Key (Get one free)
• Git (Download)

Installation

1️⃣ Clone the Repository

git clone https://github.com/yourusername/cfanatic.git
cd cfanatic

2️⃣ Backend Setup

# Navigate to backend directory
cd backend

# Install Python dependencies
pip install -r requirements.txt

# Generate encryption keys
python ../generate_keys.py

# Create .env file
# Copy the generated keys to .env (see env.template)

Create a .env file in the backend directory:

SECRET_KEY=<generated-from-script>
ENCRYPTION_KEY=<generated-from-script>
PORT=8000

3️⃣ Frontend Setup

# Navigate to frontend directory
cd ../frontend

# Install dependencies
npm install

# Start development server
npm run dev

4️⃣ Start the Backend

# In a new terminal, from the backend directory
cd backend
uvicorn main:app --reload

5️⃣ Access the Application

Open your browser and navigate to:

• Frontend: http://localhost:5173
• Backend API: http://localhost:8000
• API Docs: http://localhost:8000/docs

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🛠️ Tech Stack

Frontend

• ⚛️ React 19.2 - Modern UI library
• 📘 TypeScript - Type-safe JavaScript
• 🎨 TailwindCSS - Utility-first CSS framework
• ✨ Framer Motion - Smooth animations
• 🔥 Vite - Lightning-fast build tool
• 🧭 React Router - Client-side routing

Backend

• ⚡ FastAPI - High-performance Python web framework
• 🗄️ SQLAlchemy - SQL toolkit and ORM
• 🔐 JWT Authentication - Secure user sessions
• 🔒 Cryptography - API key encryption
• 🤖 LangChain - LLM application framework
• 🧠 LangGraph - Agentic workflow orchestration

AI & Data

• 🌟 Google Gemini - Advanced language model
• 📊 Codeforces API - Contest and user data
• 🔍 Sentence Transformers - Semantic search
• 📚 FAISS - Vector similarity search (RAG)

DevOps

• 🐳 Docker - Containerization
• 🤗 Hugging Face Spaces - Deployment platform
• 🔄 Git - Version control

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📁 Project Structure

cfanatic/
├── backend/                # FastAPI backend
│   ├── main.py            # Application entry point
│   ├── auth.py            # Authentication logic
│   ├── models.py          # Database models
│   ├── mcp_server.py      # LangGraph agent
│   ├── cf_api.py          # Codeforces API integration
│   ├── rag.py             # RAG system for embeddings
│   ├── database.py        # Database configuration
│   └── requirements.txt   # Python dependencies
│
├── frontend/              # React frontend
│   ├── src/
│   │   ├── components/    # Reusable UI components
│   │   ├── pages/         # Page components
│   │   ├── config.ts      # API configuration
│   │   └── App.tsx        # Main app component
│   ├── package.json       # Node dependencies
│   └── vite.config.ts     # Vite configuration
│
├── Dockerfile             # Docker build configuration
├── .dockerignore          # Docker ignore patterns
├── README.md              # This file
├── DEPLOYMENT.md          # Deployment guide
├── generate_keys.py       # Security key generator
└── env.template           # Environment template

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🎮 Usage Guide

1. Create an Account

Register with your username, email, and password.

2. Configure API Keys

• Get a free Gemini API key from Google AI Studio
• Enter your Codeforces handle
• API keys are encrypted and stored securely

3. Start Analyzing

Ask questions like:

• "Analyze my recent contest performance"
• "What topics should I focus on to reach Expert?"
• "Give me 5 problems to improve my DP skills"
• "Why did my rating drop in the last contest?"

4. Track Progress

• View your chat history
• Continue previous conversations
• Export insights for future reference

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🤝 Contributing

Contributions are welcome! Here's how you can help:

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

📝 License

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

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🙏 Acknowledgments

• Codeforces for providing the amazing competitive programming platform
• Google for the powerful Gemini AI model
• LangChain team for the excellent LLM framework
• The open-source community for all the amazing tools

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⭐ Star this repo if you find it useful!

Made with ❤️ for the competitive programming community