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A fully automated news aggregation and newsletter system that crawls Munich news sources, generates AI summaries, and sends daily newsletters with engagement tracking.
**🚀 NEW:** GPU acceleration support for 5-10x faster AI processing! See [QUICK_START_GPU.md](QUICK_START_GPU.md)
## 🚀 Quick Start
```bash
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### Components
- **Ollama**: AI service for summarization and translation (port 11434)
- **MongoDB**: Data storage (articles, subscribers, tracking)
- **Backend API**: Flask API for tracking and analytics (port 5001)
- **News Crawler**: Automated RSS feed crawler with AI summarization
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- Python 3.11
- MongoDB 7.0
- Ollama (phi3:latest model for AI)
- Docker & Docker Compose
- Flask (API)
- Ollama (AI summarization)
- Schedule (automation)
- Jinja2 (email templates)
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### Prerequisites
- Docker & Docker Compose
- (Optional) Ollama for AI summarization
- 4GB+ RAM (for Ollama AI models)
- (Optional) NVIDIA GPU for 5-10x faster AI processing
### Setup
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# Edit backend/.env with your settings
```
3. **Start the system**
3. **Configure Ollama (AI features)**
```bash
docker-compose up -d
# Option 1: Use integrated Docker Compose Ollama (recommended)
./configure-ollama.sh
# Select option 1
# Option 2: Use external Ollama server
# Install from https://ollama.ai/download
# Then run: ollama pull phi3:latest
```
4. **Start the system**
```bash
# Auto-detect GPU and start (recommended)
./start-with-gpu.sh
# Or start manually
docker-compose up -d
# First time: Wait for Ollama model download (2-5 minutes)
docker-compose logs -f ollama-setup
```
📖 **For detailed Ollama setup & GPU acceleration:** See [docs/OLLAMA_SETUP.md](docs/OLLAMA_SETUP.md)
## ⚙️ Configuration
Edit `backend/.env`: