Transform any document into personalized, adaptive quizzes with AI-powered insights and study recommendations.

• 📄 Smart Document Processing: Upload PDFs and automatically extract content with AI-powered chunking
• 🤖 AI Quiz Generation: Generate personalized quizzes using Google Gemini AI with adaptive difficulty
• 📊 Performance Analytics: Comprehensive analytics with AI recommendations and performance tracking
• 📚 Study Reports: Personalized study guides with document references and external learning resources
• 🎯 Adaptive Learning: Dynamic difficulty adjustment based on user performance

• 🌙 Dark Theme: Beautiful, consistent dark theme throughout the application
• 📱 Responsive Design: Works seamlessly on desktop, tablet, and mobile devices
• ⚡ Real-time Feedback: Instant quiz results with detailed explanations
• 🔍 ELI5 Explanations: Complex concepts explained in simple terms

• 🎯 Performance Tracking: Track scores, timing, and improvement over time
• 🗺️ Knowledge Heatmaps: Visual representation of topic mastery
• 🤖 AI Recommendations: Personalized study suggestions based on performance
• 📊 Mistake Analysis: Detailed breakdown of errors and learning opportunities

• Next.js 14 - React framework with App Router
• TypeScript - Type-safe development
• Tailwind CSS - Utility-first CSS framework
• Lucide React - Beautiful icons

• Node.js - JavaScript runtime
• Express.js - Web application framework
• MongoDB Atlas - Cloud database
• Mongoose - MongoDB object modeling

• Google Gemini AI - Advanced language model for content generation
• PDF Processing - Intelligent document parsing and chunking
• Embedding Generation - Vector embeddings for content similarity

• Node.js 18+ installed
• MongoDB Atlas account
• Google Gemini API key

1. Clone the repository

git clone https://github.com/Rajatjadhav10/quizlo.git
cd quizlo

2. Install dependencies

# Install backend dependencies
cd backend
npm install

# Install frontend dependencies
cd ../frontend
npm install

3. Environment Setup

# Backend environment
cd backend
cp .env.example .env
# Edit .env with your configuration

Required environment variables:

MONGODB_URI=your_mongodb_atlas_connection_string
GEMINI_API_KEY=your_google_gemini_api_key
PORT=3001

4. Start the application

# Start backend server (from backend directory)
npm start

# Start frontend development server (from frontend directory)
npm run dev

5. Access the application

• Frontend: http://localhost:3000
• Backend API: http://localhost:3001

• Navigate to the upload page
• Select a PDF document
• Wait for AI processing and content extraction

• Choose your uploaded document
• Select difficulty level and number of questions
• Let AI generate personalized quiz questions

• Answer questions with real-time feedback
• Get instant explanations for each answer
• Use "Explain Like I'm 5" for complex topics

• Check your performance dashboard
• Review detailed analytics and AI recommendations
• Track improvement over time

• Generate personalized study guides
• View document references with page numbers
• Access curated external learning resources

quizlo/
├── backend/
│   ├── config/          # Database and service configurations
│   ├── models/          # MongoDB schemas
│   ├── routes/          # API endpoints
│   ├── services/        # Business logic and AI services
│   └── server.js        # Express server setup
├── frontend/
│   ├── src/
│   │   ├── app/         # Next.js app router pages
│   │   └── components/  # Reusable React components
│   └── public/          # Static assets
└── README.md

• POST /api/documents/upload - Upload and process PDF
• GET /api/documents/user/:userId - Get user documents

• POST /api/quiz/generate - Generate AI quiz
• POST /api/quiz/submit - Submit quiz answers
• GET /api/quiz/result/:resultId - Get quiz results

• GET /api/analytics/user/:userId - User performance analytics
• POST /api/analytics/study-guide - Generate study report
• GET /api/analytics/advanced/:userId - Advanced analytics

• Uses Google Gemini AI to analyze document content
• Generates contextually relevant questions
• Adapts difficulty based on user performance
• Provides detailed explanations for each answer

• AI-powered personalized study guides
• Document references with specific page numbers
• Curated external learning resources
• Actionable study plans and recommendations

• Comprehensive performance tracking
• AI-generated insights and recommendations
• Visual knowledge heatmaps
• Progress tracking over time

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

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

• Google Gemini AI for powerful language model capabilities
• MongoDB Atlas for reliable cloud database services
• Next.js Team for the excellent React framework
• Tailwind CSS for beautiful, utility-first styling

For support, email rajatjadhav10@example.com or create an issue in this repository.

Built with ❤️ by Rajat Jadhav

Transforming learning through AI-powered personalization