📄 AI PDF Notes & Quiz Generator

An AI-powered web application that transforms PDF documents into concise study notes and automatically generates quiz questions with answers using a Large Language Model (LLM). The application provides an intuitive interface for uploading PDFs and instantly receiving structured learning material, making studying more efficient and interactive.

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📌 Overview

Reading lengthy PDFs and creating notes manually can be time-consuming. This project simplifies the learning process by allowing users to upload a PDF document and automatically generate:

• Well-structured study notes
• AI-generated quiz questions with answers

The application leverages LangChain for prompt orchestration, DeepSeek LLM for content generation, and PyMuPDF for extracting text from PDF documents.

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✨ Features

• Upload multiple PDF documents through an interactive web interface
• Automatically generate concise and structured study notes
• Generate quiz questions with answers from the uploaded document
• AI-powered content generation using the DeepSeek LLM
• Fast and user-friendly Streamlit interface
• Supports educational documents, lecture notes, and study materials

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🛠️ Tech Stack

Programming Language

• Python

Frontend

• Streamlit

AI Framework

• LangChain

Large Language Model

• DeepSeek LLM

PDF Processing

• PyMuPDF (fitz)

Environment Variables

• python-dotenv

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🏗️ Project Architecture

                 Upload PDF
                      │
                      ▼
            Extract Text (PyMuPDF)
                      │
                      ▼
              LangChain Pipeline
                      │
          ┌───────────┴───────────┐
          ▼                       ▼
    Generate Notes          Generate Quiz
          │                       │
          └───────────┬───────────┘
                      ▼
              Display Results
                (Streamlit UI)

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⚙️ Installation

1️⃣ Clone the repository

git clone https://github.com/your-username/AI-PDF-Notes-Quiz-Generator.git

2️⃣ Navigate to the project folder

cd AI-PDF-Notes-Quiz-Generator

3️⃣ Create a virtual environment (Recommended)

python -m venv venv

4️⃣ Activate the virtual environment

Windows

venv\Scripts\activate

macOS/Linux

source venv/bin/activate

5️⃣ Install dependencies

pip install -r requirements.txt

6️⃣ Configure environment variables

Create a .env file in the project directory.

Example:

DEEPSEEK_API_KEY=your_api_key_here

Replace the variable name if your project uses a different environment variable.

7️⃣ Run the application

streamlit run AI_pdf_notes_generator.py

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🚀 How to Use

1. Launch the Streamlit application.
2. Upload a PDF document.
3. Click the Generate button.
4. Wait for the AI to process the document.
5. View the generated study notes.
6. Review the quiz questions and answers.

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📸 Application Screenshots

Home Page

<img width="1276" height="422" alt="image" src="https://github.com/user-attachments/assets/859562e0-94c4-4b38-9c8e-a9f8b76c5092" />

PDF Upload

<img width="865" height="348" alt="image" src="https://github.com/user-attachments/assets/e7f2b0db-1eb6-4c07-9b58-e712d9d0ef5f" />

Generated Notes

<img width="1076" height="727" alt="image" src="https://github.com/user-attachments/assets/273b186b-eace-41fb-9787-b026e9dd49ea" />

Quiz Generation

<img width="928" height="342" alt="image" src="https://github.com/user-attachments/assets/c51b2b7a-4c16-4da5-8ad5-5b4260d09320" />

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💡 Use Cases

• Student exam preparation
• Lecture note summarization
• Learning from eBooks
• Quick revision before interviews
• Educational content generation
• Self-paced learning

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🔮 Future Enhancements

• Export notes as PDF
• Flashcard generation
• Difficulty-based quizzes
• Chat with uploaded PDFs using Retrieval-Augmented Generation (RAG)
• Multi-language support
• Save previous sessions

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📚 Key Concepts Demonstrated

• Large Language Models (LLMs)
• Prompt Engineering
• LangChain Pipelines
• PDF Text Extraction
• AI-powered Content Generation
• Streamlit Application Development
• Environment Variable Management

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🤝 Contributing

Contributions are welcome.

If you'd like to improve the project:

1. Fork the repository.
2. Create a feature branch.
3. Commit your changes.
4. Open a Pull Request.

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📄 License

This project is licensed under the MIT License.

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👩‍💻 Author

Ishika Negi

If you found this project useful, consider giving it a ⭐ on GitHub.