EduGenie - AI-Powered Learning Companion

Transform your documents into interactive learning experiences with the power of AI

✨ Overview

• EduGenie is a modern, full-stack web application that revolutionizes the way students and professionals interact with educational content. Upload any document (PDF, DOCX, TXT) and let our AI-powered system generate summaries, quizzes, flashcards, and Q&A sessions to enhance your learning experience.
• EduGenie’s RAG feature allows context-aware chatting with your documents by chunking files, storing them as vector embeddings, and retrieving the most relevant sections to generate accurate, content-grounded AI responses.

🎯 Key Features

• 📄 Smart Document Analysis - Upload and process multiple document formats
• 🤖 AI-Powered Insights - Generate summaries, quizzes, and study materials
• 📊 Interactive Learning - Flashcards, Q&A sessions, and progress tracking
• 🔐 Secure Authentication - JWT-based user management with protected routes
• 🌗 Light/Dark Mode - Seamless theme toggle across all pages and components
• 📱 Responsive Design - Beautiful UI that works on all devices
• ⚡ Real-time Processing - Fast document analysis with progress tracking
• 🧠 Semantic Search (RAG) - Chat with your documents using advanced vector embeddings and a dedicated Python microservice.

---

🏗️ Architecture

Frontend (Next.js 15)

frontend/
├── src/
│   ├── app/                 # Next.js App Router pages
│   ├── components/          # Reusable UI components
│   │   ├── auth/           # Authentication components
│   │   ├── dashboard/      # Dashboard components
│   │   ├── documents/      # Document management
│   │   ├── analysis/       # Analysis, quiz, flashcard, summary components
│   │   └── ui/             # shadcn/ui components
│   ├── lib/                # Utilities & API clients
│   ├── store/              # Zustand state management
│   └── types/              # TypeScript definitions

Backend (Node.js + Express)

backend/
├── controllers/            # Route handlers & business logic
├── models/                # MongoDB schemas
├── routes/                # API route definitions
├── middleware/            # Authentication & validation
├── utils/                 # Helper functions
└── config/                # Database configuration

AI Service (Python + FastAPI)

Handles vector embedding, semantic search, and LLM interaction.

ai_service/
├── main.py                 # FastAPI entry point & endpoints
├── requirements.txt        # Python dependencies
└── .env                    # AI-specific configuration

---

🛠️ Tech Stack

Frontend

• Framework: Next.js 15 with App Router
• Language: TypeScript
• Styling: Tailwind CSS + shadcn/ui
• State Management: Zustand + React Query
• Forms: React Hook Form + Zod validation
• Icons: Lucide React
• Notifications: Sonner
• Animations: Framer Motion
• Theme: next-themes (light/dark mode toggle)

Backend

• Runtime: Node.js 18+
• Framework: Express.js
• Database: MongoDB Atlas
• Authentication: JWT with httpOnly cookies
• AI Integration: Google Gemini 2.5 Flash
• File Processing: Multer, pdf-parse, mammoth
• Security: bcryptjs, CORS, helmet

Development Tools

• Package Manager: npm
• Linting: ESLint
• Git Hooks: Husky (planned)
• Deployment: Vercel (frontend), Railway (backend)

AI Microservice

• Runtime: Python 3.9+
• Framework: FastAPI
• AI Orchestration: LangChain
• LLM: Google Gemini 1.5 Flash / Gemini Pro
• Vector Database: MongoDB Atlas Vector Search

---

🚀 Installation

Prerequisites

• Node.js 18 or higher
• npm or yarn
• Python 3.9 or higher
• MongoDB Atlas account (with Vector Search enabled)
• Google Gemini API key

1. Clone the Repository

git clone https://github.com/Flames004/Edu-Genie.git
cd Edu-Genie

2. Backend Setup

cd backend
npm install

# Create .env file
cp .env.example .env
# Edit .env with your configuration:
# - MONGO_URI=your_mongodb_connection_string
# - JWT_SECRET=your_jwt_secret
# - GEMINI_API_KEY=your_gemini_api_key
# - FRONTEND_ORIGIN=http://localhost:3000

# Start the backend server
npm start

3. Frontend Setup

cd frontend
npm install

# Create .env.local file
echo "NEXT_PUBLIC_API_BASE_URL=http://localhost:5000/api" > .env.local

# Start the development server
npm run dev

4. AI Service Setup

cd ai_service
# Create virtual environment
python -m venv venv
# Activate it (Windows: .\venv\Scripts\activate | Mac/Linux: source venv/bin/activate)

pip install -r requirements.txt

# Create .env file
# Required vars: GEMINI_API_KEY, MONGO_URI

uvicorn main:app --reload --port 8000

5. Access the Application

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

---

📚 API Documentation

Authentication Endpoints

POST /api/auth/register    # Create new user account
POST /api/auth/login       # Authenticate user
POST /api/auth/logout      # End user session
GET  /api/auth/profile     # Get current user info

Document Management

POST   /api/study/upload           # Upload document
GET    /api/study/documents        # Get user documents
GET    /api/study/documents/:id    # Get specific document
DELETE /api/study/documents/:id    # Delete document

AI Analysis

POST /api/study/analyze/:id     # Generate custom analysis
POST /api/study/summary/:id     # Generate summary
POST /api/study/quiz/:id        # Generate quiz
POST /api/study/flashcards/:id  # Generate flashcards
POST /api/study/questions/:id   # Generate Q&A

RAG & AI Analysis (Powered by Python Service)

POST /ingest         # Chunk & Embed document (Internal)
POST /chat           # Context-aware chat with document (Internal)
POST /api/study/analyze/:id     # Generate custom analysis
POST /api/study/quiz/:id        # Generate quiz

🎨 Screenshots

Landing Page

Authentication

Dashboard

Dark Mode

Chat UI

.

---

🤝 Contributing

We welcome contributions from the community! Please follow these steps:

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

Development Guidelines

• Use TypeScript for type safety
• Follow the existing code style
• Write meaningful commit messages
• Test your changes thoroughly
• Update documentation as needed