PDF Text Summarization

PDF Text Summarization is a web application that allows users to upload PDF files and get summarized text using a pre-trained NLP model. The application uses the Hugging Face Transformers library and Flask for the backend server.

Features

• Upload a PDF file and receive a summarized version of its text content.
• Uses a pre-trained summarization model from Hugging Face.
• Simple and intuitive web interface.

Installation

Set Up the Virtual Environment

Using Anaconda: conda create --name myenv python=3.10 conda activate myenv

Install Dependencies

pip install -r requirements.txt.txt

Run the Application

flask run

Open your browser and navigate to http://127.0.0.1:5000.

Prerequisites

• Python 3.7 or higher
• Anaconda or virtualenv for managing dependencies

Clone the Repository

git clone https://github.com/Daniel15568/Text-Summarization.git

Usage

• Open the web application in your browser.
• Upload a PDF file by clicking the "Choose File" button and selecting your PDF.
• Click the "Upload" button to submit the file.
• The application will process the file and display a summarized version of the text.

Dependencies

Flask: A micro web framework for Python. PyMuPDF (fitz): A library to read, manipulate, and convert PDF files. Transformers: Hugging Face library for state-of-the-art NLP models. Torch: A deep learning framework for NLP models.

Contributing

Contributions are welcome! Please open an issue or submit a pull request for any changes.

Possible additions

• Include word files
• Add pssible subtopics
• Restructure html file with css (web-dev)

License

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

This project was created as part of a learning exercise in hugging face transformers and flask framework.