PDF Learning Hub

A full-stack web application that allows users to upload PDF documents, engage in conversational chat with the content using Retrieval-Augmented Generation (RAG), and generate multiple-choice questions (MCQs) for learning and assessment.

Features

• PDF Upload and Processing: Upload PDF files and extract text content for analysis.
• Conversational Chat: Interact with your PDF content through an AI-powered chat interface using RAG technology.
• MCQ Generation: Automatically generate multiple-choice questions from the PDF content.
• Quiz Mode: Take quizzes with generated MCQs, submit answers, and receive instant feedback with scores and explanations.
• Responsive UI: Modern, responsive frontend built with Next.js and Tailwind CSS.

Tech Stack

Backend

• FastAPI: High-performance web framework for building APIs.
• Python: Core programming language.
• PyPDF: PDF text extraction.
• Qdrant: Vector database for document embeddings.
• HuggingFace Mistral-7B-Instruct-v0.2: Large language model for chat and MCQ generation.
• LangChain: Framework for building LLM applications.

Frontend

• Next.js: React framework for server-side rendering and static site generation.
• React: JavaScript library for building user interfaces.
• TypeScript: Typed superset of JavaScript.
• Tailwind CSS: Utility-first CSS framework for styling.
• Axios: HTTP client for API requests.

Infrastructure

• Docker: Containerization for easy deployment.
• Docker Compose: Orchestration of multi-container applications.

Prerequisites

Before running this application, ensure you have the following installed:

• Python 3.8 or higher
• Node.js 18 or higher
• Docker and Docker Compose
• HuggingFace API key (set in .env file)

Installation

Option 1: Docker (Recommended)

1. Clone the repository:

   git clone <repository-url>
   cd pdf-learning-hub

2. Create a .env file in the root directory with your HuggingFace API key:

   HUGGINGFACE_API_KEY=your_huggingface_api_key_here
   

3. Run the application using Docker Compose:

   docker-compose up --build

4. Access the application at http://localhost:3000

Option 2: Local Development

Backend Setup

1. Navigate to the backend directory:

   cd backend

2. Create a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

   pip install -r requirements.txt

4. Create a .env file with your OpenAI API key:

   HUGGINGFACE_API_KEY=your_huggingface_api_key_here
   

5. Start the backend server:

   python main.py

   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 frontend will be available at http://localhost:3000

Usage

1. Upload a PDF: Click on the upload section and select a PDF file to process.
2. Chat Mode: After uploading, switch to chat mode to ask questions about the PDF content.
3. MCQ Mode: Generate multiple-choice questions from the PDF and take a quiz.
4. New Session: Start a new session to upload and work with different PDFs.

API Endpoints

The backend provides the following REST API endpoints:

Core Endpoints

• GET / - Health check endpoint
• POST /upload - Upload and process a PDF file
• POST /chat - Send a chat query and receive a response
• POST /generate-mcq - Generate MCQ questions from the PDF
• POST /submit-mcq - Submit MCQ answers and get results
• DELETE /session/{session_id} - Delete a session and its data

Request/Response Examples

Upload PDF

curl -X POST "http://localhost:8000/upload" \
     -H "accept: application/json" \
     -H "Content-Type: multipart/form-data" \
     -F "file=@example.pdf"

Chat Query

curl -X POST "http://localhost:8000/chat" \
     -H "Content-Type: application/json" \
     -d '{"session_id": "your-session-id", "query": "What is the main topic?"}'

Generate MCQs

curl -X POST "http://localhost:8000/generate-mcq" \
     -H "Content-Type: application/json" \
     -d '{"session_id": "your-session-id", "num_questions": 5}'

Project Structure

pdf-learning-hub/
├── backend/
│   ├── main.py                 # FastAPI application
│   ├── requirements.txt        # Python dependencies
│   └── services/
│       ├── pdf_processor.py    # PDF text extraction
│       ├── rag_service.py      # RAG implementation
│       └── mcq_generator.py    # MCQ generation logic
├── frontend/
│   ├── app/
│   │   ├── page.tsx            # Main page component
│   │   ├── layout.tsx          # Layout component
│   │   └── components/         # React components
│   │       ├── UploadSection.tsx
│   │       ├── ChatSection.tsx
│   │       └── MCQSection.tsx
│   ├── package.json            # Node.js dependencies
│   └── tailwind.config.js      # Tailwind CSS configuration
├── docker/
│   └── docker-compose.yml      # Docker orchestration
└── README.md                   # This file