StudyGenius - AI PDF Study Companion

An AI-powered study companion that transforms PDFs into interactive learning experiences. Built with FastAPI backend and React frontend, powered by LangChain and OpenRouter.

Features

For Students

• Upload PDFs - Drag and drop your study materials
• Smart Q&A - Ask questions and get accurate, context-aware answers
• Auto Summaries - Generate concise summaries of any document
• Practice Quizzes - Create interactive quizzes to test your understanding
• Clear Doubts - Get explanations of complex topics

For Teachers

• Upload Course Material - Upload PDFs containing topic content
• Configure Question Papers - Set topic, difficulty, and number of questions
• Multiple Question Types - MCQs, short answer, and long answer questions
• Download as PDF - Generate and download professional question papers

Tech Stack

Backend

• FastAPI - High-performance Python web framework
• LangChain - LLM application framework
• OpenRouter - Cloud LLM API (supports various models including LLaMA, Gemma, etc.)
• FAISS - Vector similarity search
• Sentence Transformers - Text embeddings
• PyPDF2 - PDF text extraction

Frontend

• React - UI library
• Vite - Build tool
• React Router - Client-side routing
• jsPDF - PDF generation
• Axios - HTTP client

Project Structure

EL_project/
├── backend/                    # FastAPI Backend
│   ├── app/
│   │   ├── main.py            # FastAPI app entry point
│   │   ├── config.py          # Configuration settings
│   │   ├── services/
│   │   │   ├── pdf_service.py     # PDF processing
│   │   │   ├── vector_store.py    # FAISS vector store
│   │   │   └── llm_service.py     # LangChain + OpenRouter
│   │   ├── routers/
│   │   │   ├── student.py     # Student API endpoints
│   │   │   └── teacher.py     # Teacher API endpoints
│   │   └── models/
│   │       └── schemas.py     # Pydantic models
│   ├── requirements.txt
│   └── .env.example
│
├── frontend/                   # React Frontend
│   ├── src/
│   │   ├── components/        # Reusable UI components
│   │   ├── pages/             # Page components
│   │   ├── services/          # API service
│   │   └── index.css          # Global styles
│   ├── index.html
│   └── package.json
│
└── Chat-With-PDF-Using-LangChain-Gemini/  # Original Streamlit app (reference)

Getting Started

Prerequisites

• Python 3.9+
• Node.js 18+
• OpenRouter API Key - Get your free API key from OpenRouter

Backend Setup

1. Navigate to the backend directory:

   cd backend

2. Create a virtual environment:

   python -m venv venv
   venv\Scripts\activate  # Windows
   # or
   source venv/bin/activate  # Linux/Mac

3. Install dependencies:

   pip install -r requirements.txt

4. Copy environment file and configure your API key:

   copy .env.example .env  # Windows
   # or
   cp .env.example .env  # Linux/Mac

5. Edit the .env file and add your OpenRouter API key:

   OPENROUTER_API_KEY=your_actual_api_key_here

6. Start the backend server:

   uvicorn app.main:app --reload

   The API will be available at http://localhost:8000

Frontend Setup

1. Navigate to the frontend directory:

   cd frontend

2. Install dependencies:

   npm install

3. Start the development server:

   npm run dev

   The app will be available at http://localhost:5173

API Endpoints

Method	Endpoint	Description
GET	/health	Health check
POST	/student/upload	Upload PDF for student
POST	/student/ask	Ask any question (queries, summaries, quizzes, etc.)
POST	/teacher/upload	Upload topic material
POST	/teacher/generate-paper	Generate question paper

Design

The application features a modern dark theme with:

• Glassmorphism effects
• Animated backgrounds
• Smooth micro-animations
• Responsive layout
• Color-coded themes for Student (blue) and Teacher (green)

Usage

Student Flow

1. Click "For Students" on the home page
2. Upload a PDF document
3. Once processed, ask questions in the chat interface
4. Use quick actions for summaries or quizzes

Teacher Flow

1. Click "For Teachers" on the home page
2. Upload course material PDF
3. Configure question paper settings (topic, difficulty, number of questions)
4. Click "Generate Question Paper"
5. Preview and download as PDF

Configuration

Edit .env in the backend directory:

# Server settings
HOST=0.0.0.0
PORT=8000
DEBUG=True

# OpenRouter settings (REQUIRED)
OPENROUTER_API_KEY=your_openrouter_api_key_here
OPENROUTER_MODEL=meta-llama/llama-3.1-8b-instruct:free

# Vector store path
VECTOR_STORE_PATH=./vector_stores

Available Free Models on OpenRouter

You can change OPENROUTER_MODEL to use different models:

• meta-llama/llama-3.1-8b-instruct:free (default)
• google/gemma-3-27b-it:free
• mistralai/mistral-7b-instruct:free

Check OpenRouter Models for more options.

License

This project is for educational purposes.

Contributing

Feel free to open issues or submit pull requests!