A Flask web application that transforms lengthy news articles into concise, readable summaries using AI, with multi-language translation support.

• 🚀 News Scraping: Extract content from news article URLs
• 📝 AI Summarization: Generate concise summaries of articles
• 🌐 Multi-language Translation: Translate summaries to different languages
• 🎨 Modern UI: Clean, responsive design with dark/light mode toggle
• 📱 Mobile Friendly: Optimized for all device sizes

PulsePoint/
├── main.py                   # Production entry point
├── src/
│   └── app.py               # Development entry point
├── api/
│   ├── index.py             # API routes
│   └── services/
│       ├── news_scraper.py  # Web scraping service
│       ├── summarizer.py    # AI summarization service
│       └── translator.py    # Translation service
├── templates/
│   ├── base.html            # Base template
│   ├── index.html           # Homepage
│   └── summary.html         # Summary display
├── static/
│   ├── css/
│   │   └── styles.css       # Application styles
│   └── js/
│       └── main.js          # Client-side JavaScript
├── tests/
│   ├── test_app.py          # Application tests
│   └── test_flow.py         # Flow tests
└── requirements.txt         # Python dependencies

1. Clone the repository:

   git clone <repository-url>
   cd PulsePoint

2. Install dependencies:

   pip install -r requirements.txt
   playwright install chromium

3. Run locally:

   # Development mode
   python src/app.py
   
   # Production mode
   python main.py

Railway is a modern deployment platform that's perfect for Flask applications.

1. Sign up for Railway:

   • Go to railway.app
   • Sign up with your GitHub account

2. Deploy your repository:

   • Click "New Project"
   • Select "Deploy from GitHub repo"
   • Choose your PulsePoint repository
   • Railway will automatically detect it's a Python project

3. Configure Environment Variables:

   • In your Railway project dashboard, go to "Variables"
   • Add the following environment variables:

     SECRET_KEY=your-secure-secret-key-here
     FLASK_ENV=production
     

4. Deploy:

   • Railway will automatically build and deploy your application
   • Your app will be available at: https://your-app-name.railway.app

1. Sign up for Render:

   • Go to render.com
   • Sign up with your GitHub account

2. Create a new Web Service:

   • Click "New +" and select "Web Service"
   • Connect your GitHub repository
   • Use these settings:
     • Build Command: pip install -r requirements.txt
     • Start Command: gunicorn --bind 0.0.0.0:$PORT main:app
     • Environment: Python 3

3. Configure Environment Variables:

   • Add environment variables:

     SECRET_KEY=your-secure-secret-key-here
     FLASK_ENV=production
     

1. Install Heroku CLI:

   # Windows (using chocolatey)
   choco install heroku-cli
   
   # Or download from https://devcenter.heroku.com/articles/heroku-cli

2. Deploy to Heroku:

   heroku create your-app-name
   heroku config:set SECRET_KEY=your-secure-secret-key-here
   heroku config:set FLASK_ENV=production
   git push heroku main

Create a .env file for local development:

SECRET_KEY=your-secret-key-for-development
PORT=5000
FLASK_ENV=development
FLASK_DEBUG=True

• Playwright: The app uses Playwright for web scraping. Most cloud platforms support it, but you may need to install additional dependencies.
• Memory: Web scraping can be memory-intensive. Consider using platforms with at least 512MB RAM.
• Security: Always use a strong SECRET_KEY in production.

1. Playwright Installation:

   playwright install chromium

2. Missing Dependencies:

   pip install -r requirements.txt

3. Port Issues on Windows:

   • Use the provided run_app.py script
   • Or run with specific settings: python main.py

• Backend: Flask (Python)
• Frontend: HTML, CSS, JavaScript
• Web Scraping: Playwright, BeautifulSoup
• AI/NLP: Custom summarization algorithms
• Translation: Custom translation service
• Deployment: Railway/Render/Heroku compatible

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Test thoroughly
5. Submit a pull request

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