AlgoTutorAI - AI-Powered Algorithm Learning Platform

AlgoTutorAI is a comprehensive web-based platform that helps students learn data structures, algorithms, and technical interview topics through AI-generated problems and adaptive learning. Built with modern web technologies and powered by OpenAI's GPT models, it provides a personalized learning experience that adapts to each student's skill level and progress.

Features

AI-Powered Learning

• Intelligent Problem Generation: AI creates unique coding problems based on topic, difficulty, and learning objectives
• Adaptive Difficulty: Problems automatically adjust to match your skill level
• Real-time Feedback: Get instant AI analysis of your code with suggestions for improvement
• Smart Hints: Progressive hints that guide you toward solutions without giving them away
• Personalized Recommendations: AI suggests problems based on your learning patterns and weak areas

Comprehensive Topic Coverage

• Data Structures: Arrays, Strings, Linked Lists, Stacks, Queues, Trees, Graphs, Heaps, Hash Tables
• Algorithms: Dynamic Programming, Greedy, Backtracking, Two Pointers, Sliding Window, Binary Search
• Advanced Topics: Sorting, Recursion, Bit Manipulation, Math, Geometry, Game Theory, System Design
• Interview Preparation: All topics commonly covered in technical coding interviews

Learning Features

• Progress Tracking: Monitor your improvement with detailed analytics
• Achievement System: Earn badges and rewards for milestones
• Streak Tracking: Maintain daily learning habits
• Performance Analytics: Detailed insights into your strengths and weaknesses
• Learning Paths: Structured progression through topics

Development Environment

• Multi-language Support: JavaScript, Python, Java, C++
• Code Editor: Monaco Editor with syntax highlighting and autocomplete
• Test Execution: Run your code against test cases
• Solution Comparison: Compare your approach with optimal solutions

User Experience

• Modern UI/UX: Beautiful, responsive design with dark/light mode
• Mobile Responsive: Works seamlessly on all devices
• Real-time Updates: Live progress tracking and notifications
• Community Features: Leaderboards and user rankings

Technology Stack

Backend

• Node.js with Express.js framework
• MongoDB with Mongoose ODM
• OpenRouter API for AI-powered features
• JWT for authentication
• bcryptjs for password hashing
• Rate limiting and security middleware

Frontend

• React 18 with modern hooks
• Tailwind CSS for styling
• Framer Motion for animations
• React Query for data fetching
• Monaco Editor for code editing
• Lucide React for icons

Development Tools

• ESLint for code quality
• Prettier for code formatting
• Nodemon for backend development
• Concurrently for running both servers

Quick Start

Prerequisites

• Node.js 16+ and npm
• MongoDB (local or cloud)
• OpenRouter API Key

1. Clone the Repository

git clone https://github.com/yourusername/algotutor-ai.git
cd algotutor-ai

2. Install Dependencies

# Install backend dependencies
npm install

# Install frontend dependencies
cd client
npm install
cd ..

3. Environment Configuration

Create a .env file in the root directory:

# Server Configuration
PORT=5000
NODE_ENV=development

# MongoDB Configuration
MONGODB_URI=mongodb://localhost:27017/algotutor-ai

# JWT Configuration
JWT_SECRET=your-super-secret-jwt-key-change-this-in-production

# OpenAI Configuration
OPENAI_API_KEY=your-openai-api-key-here

# Client Configuration
CLIENT_URL=http://localhost:3000

4. Start the Application

# Development mode (runs both backend and frontend)
npm run dev

# Or run separately:
# Backend only
npm run server

# Frontend only
npm run client

The application will be available at:

• Frontend: http://localhost:3000
• Backend API: http://localhost:5000

📁 Project Structure

algotutor-ai/
├── server/                 # Backend server
│   ├── config/            # Database and configuration
│   ├── middleware/        # Express middleware
│   ├── models/            # MongoDB models
│   ├── routes/            # API routes
│   └── index.js           # Server entry point
├── client/                # React frontend
│   ├── src/
│   │   ├── components/    # Reusable components
│   │   ├── contexts/      # React contexts
│   │   ├── pages/         # Page components
│   │   ├── services/      # API services
│   │   └── App.js         # Main app component
│   ├── public/            # Static assets
│   └── package.json       # Frontend dependencies
├── package.json           # Backend dependencies
└── README.md              # This file

Usage Guide

For Students

1. Create an Account: Sign up with email and password
2. Choose Topics: Select topics you want to learn
3. Set Difficulty: Start with beginner level
4. Practice Problems: Solve AI-generated problems
5. Get Feedback: Review AI analysis of your solutions
6. Track Progress: Monitor your improvement over time

For Educators

1. Review Problems: AI-generated problems are reviewed before publication
2. Custom Problems: Create custom problems for specific learning objectives
3. Student Analytics: Monitor class performance and progress
4. Adaptive Learning: Let AI adjust difficulty based on student performance

Security Features

• JWT Authentication: Secure token-based authentication
• Password Hashing: bcryptjs for secure password storage
• Rate Limiting: Prevent API abuse
• Input Validation: Sanitize and validate all inputs
• CORS Protection: Configured for production use
• Helmet.js: Security headers and protection

API Endpoints

Authentication

• POST /api/auth/register - User registration
• POST /api/auth/login - User login
• GET /api/auth/me - Get current user
• PUT /api/auth/profile - Update profile

Problems

• GET /api/problems - List all problems
• GET /api/problems/:id - Get problem details
• POST /api/problems/:id/submit - Submit solution
• GET /api/problems/topics/list - List all topics

AI Features

• POST /api/ai/generate-problem - Generate new problem
• POST /api/ai/analyze-solution - Analyze user solution
• POST /api/ai/get-hint - Get problem hint
• POST /api/ai/recommend-problems - Get recommendations

User Management

• GET /api/users/progress - Get learning progress
• GET /api/users/submissions - Get submission history
• GET /api/users/achievements - Get user achievements
• GET /api/users/leaderboard - Get leaderboard

Deployment

Backend Deployment

1. Set environment variables for production
2. Use PM2 or similar process manager
3. Configure MongoDB connection
4. Set up reverse proxy (Nginx)

Frontend Deployment

1. Build the React app: npm run build
2. Serve static files with Nginx or similar
3. Configure API proxy

Environment Variables for Production

NODE_ENV=production
MONGODB_URI=your-production-mongodb-uri
JWT_SECRET=your-production-jwt-secret
CLIENT_URL=https://yourdomain.com

Contributing

1. Fork the repository
2. Create a feature branch: git checkout -b feature-name
3. Make your changes
4. Add tests if applicable
5. Commit your changes: git commit -m 'Add feature'
6. Push to the branch: git push origin feature-name
7. Submit a pull request

📝 License

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

🔮 Roadmap

• Mobile App: React Native mobile application
• Video Tutorials: Integrated video learning content
• Collaborative Learning: Pair programming features
• Advanced Analytics: Machine learning insights
• Interview Simulator: Mock technical interviews
• Code Review System: Peer code review features
• Integration APIs: Connect with other learning platforms

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