Text Summarizer

📌 Introduction

The Text Summarizer is a Python-based application that helps users generate concise summaries from large text documents. It utilizes Natural Language Processing (NLP) techniques to extract the most important information while maintaining coherence.

🚀 Features

• Supports summarization of plain text, PDFs, and Word documents (.docx)
• Uses LexRank Algorithm for efficient text summarization
• GUI-based interface using Tkinter for easy interaction
• File Import Option for uploading documents
• Allows users to copy summaries to clipboard
• Saves output as a text file
• Dark Mode & Light Mode Toggle for better usability
• Works completely offline

🛠️ Installation

Prerequisites

Ensure you have Python 3.8+ installed.

1️⃣ Clone the Repository

git clone https://github.com/Burhanali2211/Text-Summarizer.git
cd text-summarizer

2️⃣ Install Dependencies

Run the following command to install required Python packages:

pip install -r requirements.txt

3️⃣ Download Required NLTK Resources

import nltk
nltk.download('punkt')
nltk.download('stopwords')

🎯 Usage

Run the application

python Text_Summarizer.py

How to Use

1. Enter or Upload Text: Paste text or load a file (PDF, DOCX, or TXT).
2. Click Summarize: The tool extracts the key points.
3. Copy or Save: Copy the summary to the clipboard or save it as a file.

📜 Requirements (requirements.txt)

nltk
sumy
pdfplumber
python-docx
PyPDF2
tkinter

🛠️ Troubleshooting

• Error: Missing NLTK Data Run the following in Python:

  import nltk
  nltk.download('punkt')
  nltk.download('stopwords')
• GUI not opening? Ensure Tkinter is installed (pre-installed with Python).

🤝 Contributing

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

📄 License

This project is licensed under the MIT License.