Text Summarization Web Application

Overview

This project is a text summarization web application developed using Natural Language Processing (NLP) techniques. The application allows users to input text and receive concise summaries, making it easier to understand lengthy articles, papers, or any substantial body of text.

Features

• NLP-Based Summarization: Utilizes advanced NLP algorithms to generate summaries.
• User-Friendly Interface: Built with Flask, providing a simple and intuitive web interface for users.
• Customizable Input: Users can input any text and receive a summary tailored to the input content.

Technologies Used

• Python: Main programming language.
• Flask: Web framework for creating the web interface.
• NLP Libraries: Libraries such as NLTK, SpaCy, or Transformers for text analysis and summarization.

Installation

1. Clone the repository:

   git clone https://github.com/DynamicDebugger/text-summarizer.git

2. Navigate to the project directory:

   cd text-summarizer

3. Install the required packages:

   pip install -r requirements.txt

4. Run the application:

   python app.py

5. Open your web browser and go to http://127.0.0.1:5000.

Usage

1. Enter the text you want to summarize in the input field.
2. Click the "Summarize" button.
3. View the generated summary displayed on the page.

Demo

Exploring-ai.-.Made.with.Clipchamp.3.mp4

Acknowledgments

• Thanks to the creators of the NLP libraries that made this project possible.
• Special thanks to the participants and organizers of the Exploring AI Event for their inspiration and support, where this project was awarded first place.