Illuminate your codebase. Upload any project and instantly visualize its architecture, dependencies, and code quality with AI-powered insights.

• 🚀 Instant Analysis - Upload a ZIP or connect a GitHub repository.
• 🏗️ Interactive Architecture Maps - Visual tree diagrams of your file structure.
• 🔗 Dependency Graphs - Track file and function-level dependencies visually with Cytoscape.js.
• 🤖 Multi-LLM AI Insights - Powered by Groq (Llama 3), Gemini, and Cohere with automatic fallback.
• 📊 Complexity Heatmaps - Identify technical debt and complex hotspots with AST-based cyclomatic complexity.
• 🔒 Privacy-First - All code analysis happens locally; your code never leaves your machine (unless you opt-in to AI insights).
• ⚡ Rate Limiting & Caching - Smart resource management to keep costs low (or free).
• 🧹 Auto-Cleanup - Old projects are automatically removed after 1 hour.
• 🎨 Premium UI - Glassmorphism design, smooth animations, and responsive layout.

Code Lantern uses Tree-sitter for accurate AST-based code analysis, supporting:

• 🐍 Python (.py)
• 📜 JavaScript (.js, .jsx)
• 💙 TypeScript (.ts, .tsx)
• ☕ Java (.java)
• ⚙️ C++ (.cpp, .cc, .cxx, .h, .hpp)
• 🦀 Rust (.rs)

# Clone the repository
git clone https://github.com/Tjindl/code-lantern.git
cd code-lantern

# Create backend .env file
cp backend/.env.example backend/.env
# Add your API keys (GROQ_API_KEY, GEMINI_API_KEY, etc.) to backend/.env

# Start with Docker Compose
docker-compose up --build

# Access the application
# Frontend: http://localhost (Port 80)
# Backend API: http://localhost:8002

# Clone the repository
git clone https://github.com/Tjindl/code-lantern.git
cd code-lantern/backend

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

# Install dependencies
pip install -r requirements.txt

# Set up environment variables
cp .env.example .env
# Add API keys (GROQ_API_KEY, GEMINI_API_KEY, etc.) to .env

# Start the server
python main.py

cd ../frontend

# Install dependencies
npm install

# Start development server
npm run dev

Visit http://localhost:5173 to start analyzing!

Create a .env file in the backend/ directory:

# Primary Provider (Ultrafast)
GROQ_API_KEY=your_groq_key

# Fallback Provider 1 (Reliable)
GEMINI_API_KEY=your_gemini_key

# Fallback Provider 2 (Backup)
COHERE_API_KEY=your_cohere_key

# GitHub Integration (Optional)
GITHUB_CLIENT_ID=your_github_client_id
GITHUB_CLIENT_SECRET=your_github_client_secret
GITHUB_REDIRECT_URI=http://localhost:8000/api/github/callback

Note: You can run Code Lantern without AI providers - all architecture analysis works locally. AI is only used for optional function insights.

• FastAPI: High-performance async API framework.
• Tree-sitter Analysis Engine: Industry-standard AST parsing (same technology used by GitHub) for 6 languages.
• Multi-LLM Provider: Robust abstraction layer handling automatic failovers between AI providers (Groq → Gemini → Cohere).
• Rate Limiter: In-memory tracking to prevent abuse and manage API quotas.
• Gunicorn + Uvicorn: Production-ready ASGI server with async workers.

• React 18 + Vite: Blazing fast development and optimized production builds.
• Cytoscape.js: Powerful graph visualization for dependency mapping.
• Tailwind CSS: Modern, utility-first styling for premium UI.
• React Router: Client-side routing for seamless navigation.

• Docker: Multi-stage builds for optimized containers.
• Nginx: Production-grade static file serving.
• Docker Compose: Easy orchestration of frontend and backend services.

• Local Analysis: All code parsing happens on your server using Tree-sitter AST parsers.
• No Database: Your code is never stored in a database.
• Auto-Cleanup: Uploaded projects are automatically deleted after 1 hour.
• Opt-in AI: AI insights are triggered per-function only when you click. You control what gets analyzed.
• No Tracking: No user analytics or telemetry.

We welcome contributions! Please feel free to submit a Pull Request.

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

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

Built with ❤️ for developers who love clean code.