📰 AI News Summarizer

This Streamlit application leverages a powerful pre-trained Large Language Model (LLM) to instantly summarize news articles. Users can input a URL to a news article, and the AI will generate a concise summary, making it easy to quickly grasp the main points without reading the entire piece.

Click here to open the Dashboard!

✨ Features

• Article Summarization: Generates quick summaries of news articles from provided URLs.
• Intuitive User Interface: Built with Streamlit for a clean and interactive web application.
• Local LLM Integration: Utilizes a transformer-based model from Hugging Face's transformers library for efficient local inference.
• Error Handling: Provides informative feedback for invalid URLs or summarization issues.

🛠️ Technologies Used

• Python
• Streamlit: For building the interactive web application.
• Hugging Face Transformers: For the pre-trained summarization LLM (sshleifer/distilbart-cnn-12-6).
• Requests: For fetching web page content.
• BeautifulSoup4: For parsing HTML and extracting article text.
• PyTorch (or TensorFlow): Backend for the transformers library.

🚀 How to Run Locally

1. Clone the repository:

   git clone [https://github.com/belohith/ainews](https://github.com/belohith/ainews)
   cd ainews

2. Create a virtual environment:

   python3 -m venv venv
   source venv/bin/activate  # On Windows: `venv\Scripts\activate`

3. Install dependencies:

   pip install streamlit transformers torch requests beautifulsoup4

4. Run the Streamlit app:

   streamlit run app.py

5. The application will open in your web browser, usually at http://localhost:8501.

💡 Usage

1. Enter the URL of a news article in the input field.
2. Click the "Summarize Article" button.
3. View the generated summary and original article title.

✍️ Author

Lohith Bollineni

📄 License

This project is open source and available under the MIT License.