PDF Text Summarization and Q&A Chatbot

Overview

This project is a web application that enables users to upload PDF documents, extract and summarize their text content, and interact with a Q&A chatbot to get answers related to the document. The application leverages advanced models for text summarization and question-answering to provide valuable insights and answers.

Features

• PDF Upload: Upload PDF files for processing.
• Text Extraction: Extract and clean text from the uploaded PDF.
• Text Summarization: Generate concise summaries of the extracted text.
• Q&A Chatbot: Ask questions related to the PDF content and receive relevant answers.
• User-Friendly UI: Clean and interactive interface with logo integration.

Technologies

• Streamlit: Framework for building the web application.
• Hugging Face Transformers: For text summarization and question-answering models.
• PyPDF2: For extracting text from PDF files.
• Python: Programming language used for development.

Setup Instructions

Prerequisites

Ensure Python 3.7 or higher is installed. Check your Python version with:

Installation

1. Clone the repository:

git clone <repository_url>
cd <repository_directory>

2. Create a virtual environment (recommended):

python -m venv venv

3. Activate the virtual environment:

venv\Scripts\activate

4. Install the required packages:

pip install -r requirements.txt

Configuration

1. Update app.py:

Make sure the path to the logo image and any other local paths are correctly set in the app.py file.

2. Set up your models:

Ensure that the models used in QA_chatbot.py are properly downloaded and accessible.

Usage

1. Run the application:

streamlit run app.py

2. Interact with the application:

Upload PDF: Click the "Upload a PDF file" button to upload your PDF document. Summarize: Click the "Summarize" button to get a summary of the extracted text. Ask Questions: Enter your question in the text input field to get answers based on the PDF content.

Contributing

Contributions are welcome! Please fork the repository and submit a pull request with your changes. Ensure your code adheres to the project’s coding standards and includes tests where applicable.

License

This project is licensed under the MIT License.

Acknowledgements

Hugging Face: For providing powerful NLP models. Streamlit: For making it easy to build interactive web applications.