GenAI for PDF Summarizer & Question Generator

📌 Project Overview

GenAI-for-Pdf-Summarizer is an AI-powered web application designed to summarize PDF documents and generate meaningful questions using advanced language models (GPT-4o or compatible models). The system reads the content from uploaded PDF files, produces concise summaries (around 250 words), and generates six context-based, relevant questions derived solely from the PDF content.

This project is ideal for students, researchers, analysts, and professionals who want to quickly extract insights from lengthy documents.

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🚀 Key Features

• 📄 Upload and Process PDF Files
• 🧠 AI-Powered Summarization using Generative AI models
• ❓ Automated Question Generation (6 context-aware questions)
• 📂 Artifacts Folder for Uploaded PDFs
• 🌐 User-Friendly Interface (HTML, CSS, JavaScript frontend)
• ⚙️ Backend Powered by Python & Flask (or FastAPI if applicable)

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📁 Project Structure

GenAI-for-Pdf-Summarizer/
│
├── artifacts/           # Stores uploaded PDF files
├── src/                 # Backend logic, PDF reader, AI service handlers
├── static/              # CSS, JavaScript, images
├── templates/           # HTML templates (UI pages)
├── app.py               # Main application entry point
├── requirements.txt     # Python dependencies
├── LICENSE              # License information
└── README.md            # Project documentation

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🛠️ Technologies Used

Component	Technology
Frontend	HTML, CSS, JavaScript
Backend	Python (Flask/FastAPI)
AI Model	GPT-4o / OpenAI API
PDF Processing	PyPDF2, pdfplumber
Deployment Ready	Azure / Docker ready

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📦 Installation & Setup

1️⃣ Clone the Repository

git clone https://github.com/yourusername/GenAI-for-Pdf-Summarizer.git
cd GenAI-for-Pdf-Summarizer

2️⃣ Install Dependencies

pip install -r requirements.txt

3️⃣ Add API Keys

Create a .env file and add your OpenAI or API credentials:

OPENAI_API_KEY=your_api_key_here

4️⃣ Run the Application

python app.py

Then open your browser and navigate to:

http://127.0.0.1:5000

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▶️ How It Works

1. User uploads a PDF file.
2. System reads and extracts text from the PDF.
3. GenAI generates a concise 250-word summary.
4. AI generates 6 meaningful questions from the PDF content.
5. Results are displayed and available for download or copy.

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📊 Dataset Used (For Testing)

This project has been tested using the “Dataset of PDF Files” from Kaggle: 🔗 https://www.kaggle.com/datasets/manisha717/dataset-of-pdf-files

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📌 Future Enhancements

• ✅ Multi-page PDF summarization with context retention
• ✅ Support for multiple summary lengths (short, medium, detailed)
• ✅ Export results as PDF / DOCX
• ✅ Add voice-based summary playback (Text-to-Speech)

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🤝 Contributing

Contributions are welcome! Feel free to open issues or submit pull requests.

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📜 License

This project is licensed under the MIT License. See the LICENSE file for more details.

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🙌 Acknowledgements

• OpenAI GPT models
• PyPDF2, pdfplumber
• Flask Framework
• Kaggle Dataset Providers

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⭐ Show Your Support

If you like this project, please ⭐ the repository and share it with others!