Dukem Learning

An AI-powered learning platform that helps students study more effectively through intelligent document processing, flashcard generation, quizzes, and interactive AI chat.

Live Demo

https://dukem-learning.xyz

🚀 Features

• 📄 Document Upload & Processing: Upload PDF and Markdown files for automatic text extraction and chunking
• 
• 🤖 AI-Powered Study Tools:
  • Generate flashcards automatically from your documents
  • Create custom quizzes with multiple-choice questions
  • Get AI-generated summaries of complex materials
  • Interactive chat with document context (RAG)
• Smart Flashcards: Review, star favorites, and track progress with spaced repetition
• 
• Quiz System: Take quizzes, get instant feedback, and track scores
• Progress Dashboard: Monitor your study statistics, streaks, and achievements
• Secure Authentication: JWT-based user authentication and authorization

Tech Stack

Frontend

• React 19 with TypeScript
• Vite for fast development and optimized builds
• Tailwind CSS v4 for modern, responsive styling
• React Router v7 for client-side routing
• Axios for API communication
• React Hot Toast for notifications

Backend

• Node.js with Express 5
• TypeScript for type safety
• MongoDB Atlas for cloud database
• Mongoose for object modeling
• JWT for authentication
• Multer for file uploads
• Helmet for security headers

AI Integration

• Google Gemini AI for content generation
• RAG (Retrieval-Augmented Generation) for context-aware responses
• Text Chunking for efficient document processing
• PDF Parser for text extraction

DevOps

• Docker & Docker Compose for containerization
• Nginx for reverse proxy and static file serving
• Let's Encrypt for SSL certificates (production)
• GitHub Actions ready for CI/CD

Prerequisites

• Node.js 20.x or higher
• Docker & Docker Compose
• MongoDB Atlas account (or local MongoDB)
• Google Gemini API key

Quick Start

1. Clone the Repository

git clone https://github.com/vvduth/dukem-learning.git
cd dukem-learning

2. Set Up Environment Variables

Create a .env file in the project root:

# MongoDB Connection
MONGO_URI=mongodb+srv://username:password@cluster.mongodb.net/database

# JWT Secret (generate a strong random string)
JWT_SECRET=your-super-secret-jwt-key-change-this-in-production

# Google Gemini API Key
GOOGLE_API_KEY=your-google-gemini-api-key

3. Run with Docker Compose (Recommended)

# Build and start all services
docker-compose up -d

# Check status
docker-compose ps

# View logs
docker-compose logs -f

Access the application:

• Frontend: http://localhost
• Backend API: http://localhost:5000

4. Run Locally (Development)

Backend:

cd backend
npm install
npm run dev

Frontend:

cd frontend
npm install
npm run dev

Access the application:

• Frontend: http://localhost:5173
• Backend API: http://localhost:5000

🐳 Docker Deployment

Build and Push Images

# Build images
docker build -t vvduth/dukem-learning-backend:latest ./backend
docker build -t vvduth/dukem-learning-frontend:latest ./frontend

# Push to Docker Hub
docker push vvduth/dukem-learning-backend:latest
docker push vvduth/dukem-learning-frontend:latest

Deploy to EC2 (Production)

See DEPLOYMENT.md for detailed deployment instructions including:

• AWS EC2 setup
• Domain configuration
• SSL certificate setup
• Performance optimization for t3.micro instances

📁 Project Structure

dukem-learning/
├── backend/                 # Node.js Express backend
│   ├── src/
│   │   ├── controllers/    # Request handlers
│   │   ├── models/         # Mongoose schemas
│   │   ├── routes/         # API routes
│   │   ├── middleware/     # Auth & error handling
│   │   ├── utils/          # AI services & helpers
│   │   └── index.ts        # Entry point
│   ├── uploads/            # File storage
│   └── Dockerfile
│
├── frontend/               # React frontend
│   ├── src/
│   │   ├── components/    # Reusable components
│   │   ├── pages/         # Page components
│   │   ├── services/      # API service layer
│   │   ├── context/       # React context (Auth)
│   │   ├── utils/         # Axios instance, helpers
│   │   └── types/         # TypeScript definitions
│   ├── nginx.conf         # Nginx configuration
│   └── Dockerfile
│
├── docker-compose.yml     # Docker orchestration
├── .env.example           # Environment template
└── README.md

🔑 Key Features Explained

RAG (Retrieval-Augmented Generation)

The platform uses RAG to provide context-aware AI responses:

1. Document Upload: PDFs/Markdown files are uploaded and text is extracted
2. Text Chunking: Documents are split into manageable chunks
3. Semantic Search: Relevant chunks are retrieved based on user queries
4. AI Generation: Google Gemini uses retrieved context to generate accurate responses

Document Processing Flow

Upload → Parse (PDF/MD) → Extract Text → Chunk → Store → AI Process

Authentication Flow

Register → JWT Token → Store in localStorage → Auto-attach to requests

🔧 Configuration

Backend Configuration

Edit backend/src/index.ts for:

• CORS origins
• Port settings
• Middleware configuration
• Static file serving

Frontend Configuration

Edit frontend/src/utils/apiPaths.ts for:

• API base URL
• Endpoint paths

Nginx Configuration

Edit frontend/nginx.conf for:

• Reverse proxy settings
• SSL certificates (production)
• Caching rules

📊 API Endpoints

Authentication

• POST /api/auth/register - Register new user
• POST /api/auth/login - Login user
• GET /api/auth/profile - Get user profile
• PUT /api/auth/profile - Update profile
• POST /api/auth/change-password - Change password

Documents

• POST /api/documents/upload - Upload document
• GET /api/documents - Get all documents
• GET /api/documents/:id - Get document by ID
• DELETE /api/documents/:id - Delete document

AI Services

• POST /api/ai/generate-flashcards - Generate flashcards
• POST /api/ai/generate-quiz - Generate quiz
• POST /api/ai/generate-summary - Generate summary
• POST /api/ai/chat - Chat with document context
• POST /api/ai/explain-concept - Explain concept

Flashcards

• GET /api/flashcards/:documentId - Get flashcards by document
• POST /api/flashcards/:cardId/review - Mark card as reviewed
• POST /api/flashcards/:cardId/star - Toggle star
• DELETE /api/flashcards/:setId - Delete flashcard set

Quizzes

• GET /api/quizzes/:documentId - Get quizzes by document
• GET /api/quizzes/quiz/:id - Get quiz by ID
• POST /api/quizzes/:id/submit - Submit quiz answers
• GET /api/quizzes/:id/results - Get quiz results

Progress

• GET /api/progress/dashboard - Get dashboard statistics

Monitoring

# View container stats
docker stats

# Check logs
docker-compose logs -f

# Monitor system resources
htop
free -h
df -h

🤝 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.

👨‍💻 Author

Duc Thai

• GitHub: @vvduth
• Docker Hub: vvduth

🙏 Acknowledgments

• Google Gemini AI for powerful language model capabilities
• MongoDB Atlas for reliable cloud database hosting
• React team for the excellent frontend framework
• Docker for simplifying deployment

📞 Support

For issues, questions, or suggestions:

• Open an issue on GitHub
• Check DEPLOYMENT.md for deployment help
• Review .github/copilot-instructions.md for AI coding guidelines

🔄 Updates

See CHANGELOG.md for version history and updates.

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Live Demo: https://dukem-learning.xyz

Deployed on: AWS EC2 (t3.micro) with Docker containers