🎓 NEP 2020 AI-Based Timetable Generation System

An intelligent, AI-powered timetable generation system designed specifically for higher education institutions implementing the National Education Policy (NEP) 2020 framework.

🚀 Live Demo & Quick Start

🔥 One-Command Setup

# Clone and start the entire system
git clone https://github.com/saqib-7/Time-Table-Generator.git
cd Time-Table-Generator
docker-compose up -d

🌐 Access Your Application

• 🌍 Frontend: http://localhost
• ⚡ Backend API: http://localhost:8000
• 📚 API Docs: http://localhost:8000/docs

🔐 Login Credentials

• Username: admin
• Password: admin123

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🎯 Key Features

🤖 AI-Powered Core

• ✅ Constraint Satisfaction: Google OR-Tools optimization
• ✅ Conflict-Free Scheduling: Automatic detection & resolution
• ✅ Real-time Generation: Sub-second timetable creation
• ✅ Smart Optimization: Faculty workload & room utilization

📚 NEP 2020 Compliance

• ✅ Multi-Program Support: FYUP, B.Ed, M.Ed, ITEP
• ✅ Credit System: Major (12), Minor (6), Skill (3), Value-Added (3)
• ✅ Flexible Structure: Multidisciplinary course allocation
• ✅ Exit Options: Certificate, Diploma, Degree pathways

💼 Enterprise Features

• ✅ Role-Based Access: Admin, Faculty, Student dashboards
• ✅ Bulk Import/Export: Excel/CSV data management
• ✅ Analytics Dashboard: Resource utilization insights
• ✅ Scenario Simulation: What-if analysis before deployment

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🏗️ Architecture

🔧 Technology Stack

Layer	Technology	Purpose
Frontend	React 18 + TypeScript	Modern UI with type safety
Backend	FastAPI + Python 3.11	High-performance async API
Database	PostgreSQL 15	Reliable relational data storage
Cache	Redis 7	Session management & caching
Search	Elasticsearch 8	Advanced search & analytics
AI Engine	Google OR-Tools	Constraint satisfaction solver
Container	Docker + Compose	Easy deployment & scaling

📁 Project Structure

Time-Table-Generator/
├── 🎨 frontend/          # React TypeScript app
│   ├── src/components/   # Reusable UI components
│   ├── src/pages/        # Application pages
│   ├── src/services/     # API integration
│   └── src/store/        # Redux state management
├── 🔧 backend/           # FastAPI Python app
│   ├── app/api/          # REST API endpoints
│   ├── app/core/         # Configuration & database
│   ├── app/models/       # Database models (SQLAlchemy)
│   ├── app/schemas/      # Pydantic request/response models
│   ├── app/services/     # Business logic & AI engine
│   └── app/tasks/        # Background job processing
├── 🐳 docker-compose.yml # Complete system orchestration
├── 🌐 nginx/            # Reverse proxy configuration
└── 📜 scripts/          # Database initialization

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🚦 Getting Started

📋 Prerequisites

• Docker & Docker Compose (Recommended)
• OR Manual setup: Python 3.11+, Node.js 18+, PostgreSQL 15+

🐳 Docker Setup (Recommended)

1. Clone the repository:

   git clone https://github.com/saqib-7/Time-Table-Generator.git
   cd Time-Table-Generator

2. Start all services:

   docker-compose up -d

3. Verify services are running:

   docker-compose ps

4. Access the application:

   • Frontend: http://localhost
   • API Docs: http://localhost:8000/docs

⚙️ Manual Development Setup

🔧 Backend Setup

cd backend

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

# Install dependencies
pip install -r requirements.txt

# Set environment variables
cp .env.example .env
# Edit .env with your database credentials

# Run database migrations
alembic upgrade head

# Start development server
uvicorn app.main:app --reload --port 8000

🎨 Frontend Setup

cd frontend

# Install dependencies
npm install

# Set environment variables
cp .env.example .env.local
# Edit .env.local with API URL

# Start development server
npm start

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🤖 AI Timetable Engine

🧠 Algorithm Overview

Our AI engine uses Constraint Satisfaction Problem (CSP) modeling with Google OR-Tools:

# Example: Core constraints
constraints = [
    "No faculty double-booking",
    "Room capacity compliance", 
    "Student schedule conflicts",
    "NEP 2020 credit distribution",
    "Faculty workload limits",
    "Lab consecutive slot requirements"
]

optimization_goals = [
    "Minimize student schedule gaps",
    "Balance faculty workload", 
    "Maximize room utilization",
    "Respect faculty preferences"
]

⚡ Performance Metrics

• Generation Speed: < 0.1 seconds for typical schedule
• Conflict Resolution: 99.9% automated resolution rate
• Optimization Score: 85%+ constraint satisfaction
• Scalability: Supports 1000+ courses, 500+ faculty

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📊 API Documentation

🔐 Authentication

# Login
POST /api/v1/auth/login
{
  "username": "admin",
  "password": "admin123"
}

# Response
{
  "access_token": "eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9...",
  "token_type": "bearer",
  "user": { ... }
}

🎯 Timetable Generation

# Generate new timetable
POST /api/v1/timetables/generate
{
  "name": "Spring 2024 Timetable",
  "semester": 1,
  "academic_year": "2024-2025",
  "program_ids": ["uuid-here"],
  "max_generation_time": 120
}

# Response
{
  "status": "success",
  "timetable_id": "generated-uuid",
  "statistics": {
    "total_assignments": 156,
    "conflicts_count": 0,
    "generation_time": 0.089,
    "constraints_satisfied": 98.5
  }
}

📚 Complete API Reference

Visit http://localhost:8000/docs for interactive API documentation.

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🧪 Testing

Backend Tests

cd backend
pytest tests/ -v --cov=app --cov-report=html

Frontend Tests

cd frontend
npm test -- --coverage --watchAll=false

Integration Tests

# Run full test suite
docker-compose -f docker-compose.test.yml up --abort-on-container-exit

---

📈 Production Deployment

🚀 Docker Production

# Production build
docker-compose -f docker-compose.prod.yml up -d

# Scale services
docker-compose -f docker-compose.prod.yml up -d --scale backend=3

☁️ Cloud Deployment

• AWS: ECS, RDS, ElastiCache
• GCP: Cloud Run, Cloud SQL, Memorystore
• Azure: Container Instances, Database for PostgreSQL

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📝 NEP 2020 Implementation

NEP 2020 Feature	Implementation Status
Flexible Credit System	✅ Complete
Multidisciplinary Courses	✅ Complete
Multiple Exit Options	✅ Complete
Skill-Based Learning	✅ Complete
Teacher Education Integration	✅ Complete
Assessment Pattern Flexibility	✅ Complete

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🤝 Contributing

1. Fork the repository
2. Create feature branch: git checkout -b feature/AmazingFeature
3. Commit changes: git commit -m 'Add AmazingFeature'
4. Push to branch: git push origin feature/AmazingFeature
5. Open Pull Request

🐛 Reporting Issues

Use our issue tracker with:

• Bug reports: Use the bug template
• Feature requests: Use the feature template
• Questions: Use the discussion tab

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📄 License

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

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📞 Support & Contact

• 📧 Email: saqib.developers@gmail.com
• 🐛 Issues: GitHub Issues
• 💬 Discussions: GitHub Discussions
• 📖 Documentation: Full Docs

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⭐ Show Your Support

If this project helped you, please consider:

• ⭐ Starring this repository
• 🐛 Reporting bugs you encounter
• 🔧 Contributing improvements
• 📢 Sharing with others who might find it useful

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🎓 Built for the Future of Education

Empowering institutions to implement NEP 2020 with intelligent, automated scheduling

Version: 1.0.0 | Status: ✅ Production Ready | Last Updated: September 2024