PathTree 🌳

A complete web application that converts PDFs, PPTX files, and text documents into interactive knowledge trees, summaries, flashcards, mind maps, and provides an AI-powered tutor experience.

🚀 Features

Core Functionality

• Document Upload: Support for PDF, PPTX, and text files
• Multi-Agent AI Processing: 7 specialized AI agents for different tasks
• Knowledge Tree Visualization: Interactive React Flow-based knowledge graphs
• Smart Summaries: 1-page, 5-page, and chapter-based summaries
• Flashcard Generation: Intelligent Q&A pairs with difficulty levels
• AI Tutor: Interactive chat-based learning assistant
• Assessment Tools: Quizzes, MCQs, and adaptive testing

Technology Stack

Frontend

• Next.js 14 - React framework with App Router
• React 18 - Modern React with hooks
• TailwindCSS - Utility-first CSS framework
• React Flow - Interactive node-based graphs
• Lucide React - Beautiful icons

Backend

• FastAPI - High-performance Python web framework
• Python 3.12 - Latest Python with type hints
• pdfplumber - PDF text extraction
• python-pptx - PowerPoint processing
• Mistral AI - Advanced language model integration

🎨 Design

The application features a modern dark theme inspired by JoyCode's design language:

• Primary Colors: Deep blues and purples
• Accent Colors: Bright gradients (blue to pink)
• Typography: Clean, modern fonts
• Layout: Responsive grid-based design

🏗️ Architecture

Multi-Agent System

1. Extraction Agent - Extracts chapters, sections, concepts, and definitions
2. Simplifier Agent - Rewrites complex concepts into simple explanations
3. Knowledge Tree Agent - Creates hierarchical knowledge structures
4. Summary Agent - Generates various types of summaries
5. Flashcard Agent - Creates Q&A pairs for learning
6. Tutor Agent - Provides interactive explanations and guidance
7. Assessment Agent - Generates quizzes and evaluations

API Endpoints

• POST /upload - Upload and process documents
• POST /generate/graph - Generate knowledge tree
• POST /generate/summary - Create summaries
• POST /generate/flashcards - Generate flashcards
• POST /tutor - Interactive tutoring
• POST /generate/quiz - Create assessments

🛠️ Installation

Prerequisites

• Python 3.12+
• Node.js 18+
• npm or yarn

Backend Setup

1. Clone the repository

   git clone <repository-url>
   cd pathtree/backend

2. Install Python dependencies

   # Using conda/micromamba (recommended)
   micromamba install -c conda-forge fastapi uvicorn python-multipart pdfplumber python-pptx mistralai aiofiles pillow nltk scikit-learn pandas -y
   
   # Or using pip
   pip install fastapi uvicorn python-multipart pdfplumber python-pptx mistralai python-dotenv aiofiles Pillow nltk scikit-learn pandas

3. Set up environment variables

   # Create .env file
   echo "MISTRAL_API_KEY=your_mistral_api_key_here" > .env

4. Start the backend server

   python main.py

   Server will run on http://localhost:8000

Frontend Setup

1. Navigate to frontend directory

   cd ../frontend

2. Install Node.js dependencies

   npm install

3. Start the development server

   npm run dev

   Frontend will run on http://localhost:3000

🚀 Usage

1. Upload Documents

• Navigate to the dashboard
• Click the upload area or drag & drop files
• Supported formats: PDF, PPTX, TXT

2. Generate Knowledge Tree

• After upload, click "Generate Knowledge Tree"
• View interactive node-based visualization
• Click nodes to explore details

3. Create Summaries

• Access the Summaries page
• Choose from 1-page, 5-page, or detailed summaries
• Export or share summaries

4. Study with Flashcards

• Visit the Flashcards page
• Flip cards to reveal answers
• Mark cards as learned
• Shuffle for random practice

5. Chat with AI Tutor

• Open the Tutor Chat page
• Ask questions about your documents
• Get explanations, examples, and practice problems

🧪 Testing

Backend Testing

cd backend
python -m pytest tests/

Frontend Testing

cd frontend
npm test

Integration Testing

# Start both servers
cd backend && python main.py &
cd frontend && npm run dev &

# Test upload functionality
curl -X POST http://localhost:8000/upload -F "file=@test_document.pdf"

📁 Project Structure

pathtree/
├── backend/
│   ├── agents/                 # AI agent implementations
│   │   ├── extraction_agent.py
│   │   ├── simplifier_agent.py
│   │   ├── knowledge_tree_agent.py
│   │   ├── summary_agent.py
│   │   ├── flashcard_agent.py
│   │   ├── tutor_agent.py
│   │   └── assessment_agent.py
│   ├── utils/                  # Utility functions
│   │   ├── mistral_client.py
│   │   ├── document_processor.py
│   │   └── text_chunker.py
│   ├── uploads/               # Uploaded files storage
│   ├── main.py               # FastAPI application
│   └── requirements.txt      # Python dependencies
├── frontend/
│   ├── src/
│   │   ├── app/              # Next.js app directory
│   │   ├── components/       # React components
│   │   └── lib/             # Utility functions
│   ├── public/              # Static assets
│   ├── package.json         # Node.js dependencies
│   └── tailwind.config.js   # Tailwind configuration
├── test_document.txt        # Sample test file
└── README.md               # This file

🔧 Configuration

Environment Variables

Backend (.env)

MISTRAL_API_KEY=your_mistral_api_key_here
UPLOAD_DIR=./uploads
MAX_FILE_SIZE=50MB

Frontend (.env.local)

NEXT_PUBLIC_API_URL=http://localhost:8000

🤝 Contributing

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.

🙏 Acknowledgments

• Mistral AI for providing the language model API
• React Flow for the knowledge graph visualization
• FastAPI for the high-performance backend framework
• Next.js for the modern React framework
• TailwindCSS for the utility-first CSS framework

🐛 Troubleshooting

Common Issues

1. Module not found errors

   • Ensure all dependencies are installed
   • Check Python path and virtual environment

2. API connection issues

   • Verify Mistral API key is set correctly
   • Check network connectivity

3. File upload failures

   • Ensure file size is under limit
   • Check file format is supported

4. Frontend build errors

   • Clear node_modules and reinstall
   • Check Node.js version compatibility

Getting Help

• Open an issue on GitHub
• Check the documentation
• Review the troubleshooting guide

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PathTree - Transform your documents into interactive learning experiences! 🌳✨