A Flask-based web application that scrapes an article from a given URL and generates a concise summary using NLP techniques.
✅ Extracts text content from any article URL
✅ Cleans and processes text for summarization
✅ Uses NLP techniques like tokenization, stopword removal, and frequency-based scoring
✅ Web-based interface for input and output
✅ Deployed with configurable port support
git clone https://github.com/your-username/article-summarizer.git
cd article-summarizer- Set Up a Virtual Environment (Optional but Recommended)
python -m venv venv
source venv/bin/activate # On Windows, use 'venv\Scripts\activate'
- Install Dependencies
pip install -r requirements.txt
- Run the Application
python app.py
By default, the app runs on http://localhost:5000.
- Open the web app in a browser.
- Enter a valid article URL.
- Click submit to generate a summary.
To configure the application, you can set the following environment variables:
| Variable | Description | Default |
|---|---|---|
PORT |
The port number to run the app | 5000 |
For deployment on Render, Heroku, or any cloud platform, ensure the PORT environment variable is set.
- Python (Flask)
- BeautifulSoup (Web Scraping)
- NLTK (Natural Language Processing)
- Feel free to contribute! Open an issue or submit a pull request.
This project is licensed under the MIT License.