PDF Question Answering App

Overview

This Streamlit-based application allows users to upload PDF files, summarize their content, and ask questions about the extracted text using AI.

Features

• Extracts text from PDF files.
• Summarizes extracted text using the Groq API.
• Answers user queries based on the PDF content.
• Interactive and user-friendly interface.

Technologies Used

• Streamlit: front-end For the web User interface.
• PyMuPDF (fitz): used in the backend, For extracting text from PDF files.
• Groq API: AI source For summarization and question answering.
• Python: Primary programming language for the backend and front-end

Prerequisites

1. Python 3.7 or higher installed on your system.
2. A Groq API key (store this in a .env file). you can get it here https://console.groq.com/keys

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/pdf-question-answering-app.git
   cd pdf-question-answering-app

2. Install dependences:

   pip install -r requirements.txt

3. Add Your GroqCloud key here

   # Initialize the Groq client
   client = Groq(api_key='key') # change 'key' and add your API key 

4. Run the application and enjoy :)

   streamlit run app.py

How to use

• Upload a PDF file via the provided file uploader.
• View extracted text and summarize it using the Summarize Text button.
• Ask questions about the PDF content in the input box.

Example

• Upload a sample PDF file.
• Extracted text will appear in the app interface.
• Click Summarize Text to get a concise summary.
• Ask a question like, "What is the main topic?" and receive an answer.

Troubleshooting

If PDF text isn't extracted:

• Ensure the file is a valid PDF.
• Check dependencies are correctly installed.
• If summarization or question answering fails:
• Verify the Groq API key in .env.