AI Question Answering from PDF 📄🤖

This project allows you to upload a PDF and ask a question about its content. The AI will process the uploaded file and provide an answer to your question using Natural Language Processing (NLP).

Features 🚀

• 📄 Upload PDF files.
• ❓ Ask questions based on the content of the uploaded PDF.
• 🤖 AI-powered question answering.
• 🌐 Built with modern web technologies for a smooth user experience.

Technologies Used 🛠️

• Python 3.9
• Flask
• Bootstrap 5
• Font Awesome Icons
• JavaScript ES6
• ngrok for tunneling (used for demo purposes)

How to Use 🧑‍💻

1. Clone the repository:

   git clone https://github.com/saeidsaadatigero/ai-question-answering-pdf.git

2. Install dependencies:

   
   pip install -r requirements.txt
   

3. Run the Flask server:

   python app.py

4. Open the provided URL in your browser and upload a PDF to start asking questions!

Project Demo 🎥

Here’s a demo of how the application looks:

How It Works ⚙️

1. Upload PDF: The user uploads a PDF file containing the document they want to ask questions about.
2. Ask a Question: The user enters a question related to the content of the PDF.
3. AI Processing: The backend processes the file and the question using NLP techniques.
4. Answer: The AI generates an answer based on the context extracted from the PDF and returns it to the user.

Features 🚀

• User-Friendly Interface: Built using Bootstrap for responsive and clean design.
• Fast Processing: Quickly processes PDFs and answers questions.
• Icons & Aesthetics: Enhanced UI with Font Awesome icons for a modern look.

Installation Instructions 🛠️

1. Clone this repository:

   git clone https://github.com/saeidsaadatigero/ai-question-answering-pdf.git

2. Install Python dependencies:

   pip install -r requirements.txt

3. Run the app:

   python app.py

   Open your browser and go to http://localhost:5000.

Technologies Used 🧑‍💻

• Frontend:

  • HTML, CSS, JavaScript
  • Bootstrap 5
  • Font Awesome Icons

• Backend:

  • Python 3.x
  • Flask
  • Natural Language Processing (NLP)

• Deployment:

  • ngrok (for tunneling in demo mode)

Contributing 🤝

1. Fork this repository.
2. Create your branch (git checkout -b feature/your-feature).
3. Commit your changes (git commit -am 'Add feature').
4. Push to the branch (git push origin feature/your-feature).
5. Create a new Pull Request.

License 📄

This project is licensed under the MIT License - see the LICENSE file for details.

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Contact 💬

Feel free to reach out if you have any questions or suggestions!

• Email: [email protected]
• GitHub: @saeidsaadatigero
• LinkedIn: @saeidsaadatigero