📚 GnyanSetu – AI-Powered Interactive Learning Platform

Transform static educational content into dynamic, AI-powered interactive lessons

Features • Tech Stack • Getting Started • Architecture • API Documentation

📖 Overview

GnyanSetu (Bridge to Knowledge) is an advanced AI-powered learning platform that revolutionizes education by converting static study materials into interactive, personalized learning experiences. The platform combines cutting-edge AI technology with real-time visualization and adaptive learning mechanisms.

What Makes GnyanSetu Different?

🎓 Interactive AI Teaching - Not just content, but a virtual teacher that explains step-by-step
🎨 Visual Learning - Dynamic whiteboard with animations, diagrams, and real-time drawing
📝 Smart Assessment - AI-generated quizzes that adapt to your learning pace
📓 Intelligent Notes - Auto-generated, organized notes with key concepts highlighted
⚡ Real-time Interaction - WebSocket-powered live learning experience
📊 Progress Tracking - Comprehensive analytics to monitor learning journey

✨ Features

🎯 Core Learning Features

1. PDF Upload & Processing

Drag-and-drop interface for easy file upload
Supports PDFs up to 50MB
Intelligent text extraction with PyMuPDF
OCR support for scanned documents
Automatic content structuring

2. AI-Powered Lesson Generation

Google Gemini AI integration for content analysis
Breaks complex topics into digestible steps
Context-aware explanations
Adaptive difficulty levels
Multi-format content support (PDF, text, images)

3. Interactive Whiteboard Teaching

Real-time Canvas Rendering with Konva.js
Dynamic text animation (typewriter effect)
Shape drawing (rectangles, circles, arrows, lines)
Color-coded elements for better understanding
Step-by-step progression with visual cues
Fullscreen mode for immersive learning
Export whiteboard content as images

4. AI-Generated Quizzes

Automatic question generation from lesson content
Multiple question types (MCQ, True/False, Fill blanks, Short answer)
Instant feedback with explanations
Score tracking and analytics
Adaptive difficulty system

5. Smart Notes System

AI-generated summaries of lessons
Key points extraction
Downloadable PDF with formatting
Searchable note database
Highlighting and annotations support

6. User Management

Google OAuth 2.0 integration
Email/password authentication with JWT
User profiles and dashboards
Learning history tracking

7. Technical Features

Microservices architecture
API Gateway (Port 8000)
WebSocket real-time communication
MongoDB database
RESTful APIs
Comprehensive logging

🛠️ Tech Stack

Backend Services

Service	Technology	Port	Purpose
API Gateway	Flask 2.3	8000	Request routing, load balancing
User Service	Django 4.2 + DRF	8002	Authentication, user management
Lesson Service	Django 4.2 + DRF	8003	PDF processing, AI lesson generation
Teaching Service	Django 4.2 + Channels	8004	WebSocket, real-time teaching
Quiz Service	FastAPI (Planned)	8005	Quiz generation and management
Notes Service	FastAPI (Planned)	8006	Notes generation and storage

Core Technologies

Backend

Django 4.2.16 - Web framework with ORM
Django REST Framework - RESTful API development
Channels & Daphne - WebSocket and ASGI server
Flask 2.3 - Lightweight API gateway
FastAPI (Planned) - Modern, fast API framework for Quiz/Notes services

AI & ML

Google Generative AI (Gemini Pro) - Content generation and analysis
LangChain - AI orchestration and prompt management
OpenAI API - Alternative AI model support

Database & Caching

MongoDB 4.4+ - Primary NoSQL database
Motor - Async MongoDB driver
PyMongo - Sync MongoDB driver
Redis - Caching and session storage
Celery - Distributed task queue

Frontend

React 18 - Component-based UI library
Tailwind CSS 3 - Utility-first styling
Framer Motion - Smooth animations
Konva.js - Canvas rendering for whiteboard
jsPDF - Client-side PDF generation
Lucide React - Modern icon library
Axios - HTTP client

Development & DevOps

Git - Version control
Docker (Planned) - Containerization
Nginx (Planned) - Reverse proxy
pytest - Testing framework
ESLint - JavaScript linting
Black - Python code formatting

🏗️ Project Architecture

Directory Structure

GnyanSetu/
│
├── microservices/              # Backend microservices
│   │
│   ├── api-gateway/           # Port 8000 - Flask API Gateway
│   │   ├── app.py            # Main gateway application
│   │   ├── config.py         # Service registry configuration
│   │   ├── requirements.txt  # Gateway dependencies
│   │   └── README.md         # Gateway documentation
│   │
│   ├── user-service-django/  # Port 8002 - User Management
│   │   ├── accounts/         # User authentication app
│   │   │   ├── models.py    # User models
│   │   │   ├── views.py     # Auth endpoints
│   │   │   ├── serializers.py # DRF serializers
│   │   │   └── urls.py      # URL routing
│   │   ├── manage.py         # Django management
│   │   ├── settings.py       # Django configuration
│   │   ├── requirements.txt  # Service dependencies
│   │   └── .env.example      # Environment variables template
│   │
│   ├── lesson-service/       # Port 8003 - Lesson Generation
│   │   ├── lessons/          # Lesson app
│   │   │   ├── views.py     # API endpoints
│   │   │   ├── models.py    # Lesson models
│   │   │   └── ai_engine.py # AI lesson generator
│   │   ├── pdf_processor/    # PDF extraction module
│   │   ├── manage.py
│   │   ├── requirements.txt
│   │   └── celery_config.py  # Async task configuration
│   │
│   ├── teaching-service/     # Port 8004 - Real-time Teaching
│   │   ├── teaching/         # Teaching app
│   │   │   ├── consumers.py # WebSocket consumers
│   │   │   ├── views.py     # API endpoints
│   │   │   ├── models.py    # Teaching models
│   │   │   └── routing.py   # WebSocket routing
│   │   ├── manage.py
│   │   └── requirements.txt
│   │
│   ├── quiz-service/         # Port 8005 - Quiz Management (Planned)
│   │   ├── main.py          # FastAPI application
│   │   ├── models.py        # Pydantic models
│   │   ├── quiz_generator.py # AI quiz generation
│   │   ├── routes/          # API routes
│   │   └── requirements.txt
│   │
│   ├── notes-service/        # Port 8006 - Notes Generation (Planned)
│   │   ├── main.py          # FastAPI application
│   │   ├── models.py        # Pydantic models
│   │   ├── notes_generator.py # AI notes generation
│   │   ├── pdf_export.py    # PDF export functionality
│   │   └── requirements.txt
│   │
│   ├── requirements.txt      # Microservices dependencies
│   ├── start_project.bat     # All services startup script
│   └── logs/                 # Service logs directory
│
├── virtual_teacher_project/   # Legacy Django Project
│   ├── teacher_app/          # Core teaching application
│   │   ├── views.py          # API endpoints
│   │   ├── consumers.py      # WebSocket handlers
│   │   ├── models.py         # Django models
│   │   ├── mongo.py          # MongoDB integration
│   │   └── urls.py           # URL routing
│   │
│   ├── UI/                   # Frontend applications
│   │   │
│   │   ├── landing_page/     # Landing & Auth (Port 3000)
│   │   │   ├── src/
│   │   │   │   ├── App.jsx   # Main landing component
│   │   │   │   ├── components/
│   │   │   │   │   ├── Hero.jsx
│   │   │   │   │   ├── Features.jsx
│   │   │   │   │   ├── LoginModal.jsx
│   │   │   │   │   └── SignupModal.jsx
│   │   │   │   └── index.js
│   │   │   ├── public/
│   │   │   ├── package.json
│   │   │   └── tailwind.config.js
│   │   │
│   │   └── Dashboard/        # Main Dashboard (Port 3001)
│   │       └── Dashboard/
│   │           ├── src/
│   │           │   ├── App.jsx
│   │           │   ├── components/
│   │           │   │   ├── Whiteboard.jsx      # Interactive canvas
│   │           │   │   ├── TeachingCanvas.jsx  # Drawing engine
│   │           │   │   ├── UploadBox.jsx       # PDF upload
│   │           │   │   ├── Quiz.jsx            # Quiz component
│   │           │   │   ├── Notes.jsx           # Notes viewer
│   │           │   │   ├── ChatHistory.jsx     # Conversation history
│   │           │   │   └── SessionManager.jsx  # State management
│   │           │   ├── utils/
│   │           │   │   ├── api.js             # API client
│   │           │   │   └── websocket.js       # WebSocket client
│   │           │   └── index.js
│   │           ├── public/
│   │           ├── package.json
│   │           └── tailwind.config.js
│   │
│   ├── virtual_teacher_project/ # Django project settings
│   │   ├── settings.py       # Configuration
│   │   ├── urls.py           # Main URL routing
│   │   ├── asgi.py           # ASGI application
│   │   └── wsgi.py           # WSGI application
│   │
│   ├── manage.py
│   ├── requirements.txt
│   └── .env.example
│
├── requirements.txt          # Consolidated project dependencies
├── .gitignore               # Git ignore rules
├── .env.example             # Environment variables template
├── README.md                # This file
├── LICENSE                  # MIT License
├── CONTRIBUTING.md          # Contribution guidelines
└── docker-compose.yml       # Docker configuration (Planned)

System Architecture

┌──────────────────────────────────────────────────────┐
│                   Client Layer                        │
│  ┌────────────────┐         ┌────────────────┐      │
│  │  Landing Page  │         │   Dashboard    │       │
│  │  (Port 3000)   │         │  (Port 3001)   │       │
│  │  - Auth UI     │         │  - Whiteboard  │       │
│  │  - Google OAuth│         │  - Quiz UI     │       │
│  └────────┬───────┘         └───────┬────────┘       │
└───────────┼─────────────────────────┼────────────────┘
            │                         │
            ▼                         ▼
┌──────────────────────────────────────────────────────┐
│              API Gateway (Port 8000)                  │
│  - Request Routing                                    │
│  - Load Balancing                                     │
│  - Service Discovery                                  │
│  - Health Checks                                      │
└──────────────────┬───────────────────────────────────┘
                   │
        ┌──────────┼──────────┬──────────┬──────────┐
        ▼          ▼          ▼          ▼          ▼
┌─────────────┐ ┌────────┐ ┌────────┐ ┌──────┐ ┌──────┐
│User Service │ │Lesson  │ │Teaching│ │Quiz  │ │Notes │
│(Port 8002)  │ │Service │ │Service │ │Svc   │ │ Svc  │
│             │ │(8003)  │ │(8004)  │ │(8005)│ │(8006)│
│- Auth       │ │        │ │        │ │      │ │      │
│- Google     │ │- PDF   │ │- WS    │ │- Gen │ │- Gen │
│  OAuth      │ │  Upload│ │- Real  │ │- Eval│ │- PDF │
│- JWT        │ │- AI Gen│ │  time  │ │      │ │      │
│- Users CRUD │ │- Store │ │- Teach │ │      │ │      │
└──────┬──────┘ └───┬────┘ └───┬────┘ └───┬──┘ └───┬──┘
       │            │          │          │        │
       └────────────┴──────────┴──────────┴────────┘
                            │
                            ▼
               ┌────────────────────────┐
               │      MongoDB           │
               │  - users               │
               │  - lessons             │
               │  - conversations       │
               │  - quizzes             │
               │  - notes               │
               │  - progress            │
               └────────────────────────┘
                            │
               ┌────────────┴────────────┐
               │                         │
               ▼                         ▼
        ┌─────────────┐        ┌──────────────┐
        │   Redis     │        │  Celery      │
        │   Cache     │        │  Task Queue  │
        └─────────────┘        └──────────────┘

🚀 Getting Started

Prerequisites

Ensure you have the following installed:

Python 3.8+ - Download
Node.js 16+ - Download
MongoDB 4.4+ - Download
Git - Download
Google API Key - Get Key

Quick Start (Windows - Recommended)

# 1. Clone the repository
git clone https://github.com/AaryaKhatate/GnyanSetu.git
cd GnyanSetu

# 2. Run the automated startup script
cd microservices
start_project.bat

This will automatically:

✅ Install all Python dependencies
✅ Install all Node.js dependencies
✅ Start MongoDB
✅ Start all microservices (Ports 8000-8004)
✅ Start React applications (Ports 3000, 3001)
✅ Open browser to landing page

Manual Setup

Step 1: Clone Repository

git clone https://github.com/AaryaKhatate/GnyanSetu.git
cd GnyanSetu

Step 2: Backend Setup

# Create and activate virtual environment
python -m venv venv

# Windows
venv\Scripts\activate

# Linux/Mac
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

Step 3: Configure Environment

Create .env files in each service directory:

microservices/user-service-django/.env

SECRET_KEY=your-django-secret-key-here
DEBUG=True
MONGODB_URI=mongodb://localhost:27017/gnyansetu
GOOGLE_CLIENT_ID=your-google-client-id
GOOGLE_CLIENT_SECRET=your-google-client-secret
JWT_SECRET_KEY=your-jwt-secret-key

microservices/lesson-service/.env

GOOGLE_API_KEY=your-gemini-api-key
MONGODB_URI=mongodb://localhost:27017/gnyansetu
CELERY_BROKER_URL=redis://localhost:6379/0

microservices/teaching-service/.env

MONGODB_URI=mongodb://localhost:27017/gnyansetu
REDIS_URL=redis://localhost:6379/1

Step 4: Start Services

Open 4 separate terminals:

# Terminal 1 - API Gateway (Port 8000)
cd microservices/api-gateway
python app.py

# Terminal 2 - User Service (Port 8002)
cd microservices/user-service-django
python manage.py runserver 8002

# Terminal 3 - Lesson Service (Port 8003)
cd microservices/lesson-service
python manage.py runserver 8003

# Terminal 4 - Teaching Service (Port 8004)
cd microservices/teaching-service
daphne -b 0.0.0.0 -p 8004 teaching_service.asgi:application

Step 5: Start Frontend

Open 2 more terminals:

# Terminal 5 - Landing Page (Port 3000)
cd virtual_teacher_project/UI/landing_page/landing_page
npm install
npm start

# Terminal 6 - Dashboard (Port 3001)
cd virtual_teacher_project/UI/Dashboard/Dashboard
npm install
set PORT=3001 && npm start  # Windows
PORT=3001 npm start          # Linux/Mac

Step 6: Access Application

🌐 Landing Page: http://localhost:3000
📊 Dashboard: http://localhost:3001
🔧 API Gateway: http://localhost:8000/health

📡 API Documentation

Authentication Endpoints

User Service (Port 8002)

Method	Endpoint	Description	Request Body
POST	`/api/v1/auth/signup/`	Register new user	`{full_name, email, password, password_confirm, username}`
POST	`/api/v1/auth/login/`	User login	`{email, password}`
POST	`/api/v1/auth/logout/`	User logout	-
POST	`/api/v1/auth/google/`	Google OAuth login	`{credential}`
GET	`/api/v1/users/profile/`	Get user profile	Headers: `Authorization: Bearer <token>`
PUT	`/api/v1/users/profile/`	Update profile	`{full_name, email}`
GET	`/api/v1/health/`	Health check	-

Lesson Management

Lesson Service (Port 8003)

Method	Endpoint	Description	Request Body
POST	`/api/upload/`	Upload PDF file	FormData: `{file: <pdf>}`
POST	`/api/generate-lesson/`	Generate AI lesson	`{topic, pdf_text, difficulty}`
GET	`/api/lessons/`	Get all lessons	Query: `?user_id=<id>`
GET	`/api/lessons/<id>/`	Get specific lesson	-
DELETE	`/api/lessons/<id>/`	Delete lesson	-
GET	`/health`	Health check	-

Real-time Teaching

Teaching Service (Port 8004)

Method	Endpoint	Description	Request Body
GET	`/api/conversations/`	Get conversations	Query: `?user_id=<id>`
POST	`/api/conversations/create/`	Create conversation	`{user_id, lesson_id, topic}`
DELETE	`/api/conversations/<id>/`	Delete conversation	-
GET	`/api/teaching/<session_id>/`	Get teaching session	-
WS	`/ws/teaching/<session_id>/`	WebSocket connection	-
GET	`/health`	Health check	-

Quiz System (Planned - Port 8005)

Method	Endpoint	Description	Request Body
POST	`/api/quizzes/generate/`	Generate quiz	`{lesson_id, question_count, difficulty}`
GET	`/api/quizzes/<lesson_id>/`	Get quizzes	-
POST	`/api/quizzes/<quiz_id>/submit/`	Submit answers	`{answers: [{question_id, answer}]}`
GET	`/api/quizzes/<quiz_id>/results/`	Get quiz results	-
GET	`/api/quizzes/<quiz_id>/review/`	Review quiz with answers	-

Notes System (Planned - Port 8006)

Method	Endpoint	Description	Request Body
POST	`/api/notes/generate/`	Generate notes	`{lesson_id, format, detail_level}`
GET	`/api/notes/<lesson_id>/`	Get notes	-
GET	`/api/notes/<note_id>/download/`	Download as PDF	Query: `?format=pdf`
PUT	`/api/notes/<note_id>/`	Update notes	`{content, highlights}`
POST	`/api/notes/<note_id>/export/`	Export notes	`{format: 'pdf'

WebSocket Protocol

Connection URL: ws://localhost:8004/ws/teaching/<session_id>/

Client → Server Messages:

// Start lesson
{
  "type": "start_lesson",
  "lesson_id": "12345",
  "user_id": "user_abc"
}

// Request next step
{
  "type": "next_step"
}

// Pause lesson
{
  "type": "pause"
}

Server → Client Messages:

// Lesson step
{
  "type": "step",
  "step": 1,
  "total_steps": 10,
  "speech_text": "Let's learn about...",
  "drawing_commands": [
    {
      "type": "text",
      "text": "Hello World",
      "x": 100,
      "y": 50,
      "fontSize": 24,
      "color": "#000000"
    }
  ]
}

// Lesson complete
{
  "type": "lesson_complete",
  "quiz_available": true,
  "notes_available": true
}

🗺️ Roadmap

✅ Phase 1: Core Platform (Completed)

Microservices architecture
PDF upload and processing
AI lesson generation (Gemini 2.0)
Real-time whiteboard with WebSocket
User authentication (Google OAuth + JWT)
Interactive teaching canvas
Visualization service with percentage-based coordinates

🚧 Phase 2: Enhancement (Current)

Quiz system improvements
Notes generation enhancements
Performance optimization
Mobile responsiveness

📅 Phase 3: Advanced Features (2026)

🔧 Phase 4: Scale & Deploy

Docker containerization
Cloud deployment
Performance optimization
Security audits

🤝 Contributing

We welcome contributions! Here's how:

Fork the repository
Create a branch: git checkout -b feature/YourFeature
Make your changes
Commit: git commit -m 'Add YourFeature'
Push: git push origin feature/YourFeature
Open a Pull Request

Guidelines

Follow PEP 8 for Python
Use ESLint for JavaScript
Write meaningful commit messages
Add tests for new features
Update documentation

📄 License

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

👥 Contributors

Aarya Khatate - @AaryaKhatate
Vinay Gone - @VinayGone2006
Yashraj Patil - @Yashrajpatil22

📧 Contact & Support

Email: [email protected]
Issues: Report Bug
Features: Request Feature

🙏 Acknowledgments

Google Gemini AI for language models
MongoDB for database solutions
React and Django communities
All contributors and supporters

Made with ❤️ for Education

GnyanSetu - Building Bridges to Knowledge

⭐ Star this repository if you find it helpful!

Report Bug • Request Feature

Name		Name	Last commit message	Last commit date
Latest commit History 76 Commits
UI		UI
microservices		microservices
.gitignore		.gitignore
LICENSE		LICENSE
README.md		README.md
requirements.txt		requirements.txt
start_gnyansetu.bat		start_gnyansetu.bat

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📚 GnyanSetu – AI-Powered Interactive Learning Platform

📖 Overview

What Makes GnyanSetu Different?

✨ Features

🎯 Core Learning Features

1. PDF Upload & Processing

2. AI-Powered Lesson Generation

3. Interactive Whiteboard Teaching

4. AI-Generated Quizzes

5. Smart Notes System

6. User Management

7. Technical Features

🛠️ Tech Stack

Backend Services

Core Technologies

Backend

AI & ML

Database & Caching

Frontend

Development & DevOps

🏗️ Project Architecture

Directory Structure

System Architecture

🚀 Getting Started

Prerequisites

Quick Start (Windows - Recommended)

Manual Setup

Step 1: Clone Repository

Step 2: Backend Setup

Step 3: Configure Environment

Step 4: Start Services

Step 5: Start Frontend

Step 6: Access Application

📡 API Documentation

Authentication Endpoints

User Service (Port 8002)

Lesson Management

Lesson Service (Port 8003)

Real-time Teaching

Teaching Service (Port 8004)

Quiz System (Planned - Port 8005)

Notes System (Planned - Port 8006)

WebSocket Protocol

🗺️ Roadmap

✅ Phase 1: Core Platform (Completed)

🚧 Phase 2: Enhancement (Current)

📅 Phase 3: Advanced Features (2026)

🔧 Phase 4: Scale & Deploy

🤝 Contributing

Guidelines

📄 License

👥 Contributors

📧 Contact & Support

🙏 Acknowledgments

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