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91 lines
2.0 KiB
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91 lines
2.0 KiB
Markdown
# ⚡ Quick Start Guide
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Get Munich News Daily running in 5 minutes!
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## 📋 Prerequisites
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- **Docker** & **Docker Compose** installed
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- **4GB+ RAM** (for AI models)
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- *(Optional)* NVIDIA GPU for faster processing
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## 🚀 Setup Steps
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### 1. Configure Environment
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```bash
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cp backend/.env.example backend/.env
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nano backend/.env
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```
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**Required:** Update `SMTP_SERVER`, `EMAIL_USER`, and `EMAIL_PASSWORD`.
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### 2. Start the System
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```bash
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# Auto-detects GPU capabilities and starts services
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./start-with-gpu.sh
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# Watch installation progress (first time model download ~2GB)
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docker-compose logs -f ollama-setup
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```
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### 3. Add News Sources
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```bash
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# Connect to database
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docker-compose exec mongodb mongosh munich_news
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# Paste this into the mongo shell:
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db.rss_feeds.insertMany([
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{
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name: "Süddeutsche Zeitung München",
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url: "https://www.sueddeutsche.de/muenchen/rss",
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active: true
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},
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{
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name: "Merkur München",
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url: "https://www.merkur.de/lokales/muenchen/rss/feed.rss",
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active: true
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}
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])
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```
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### 4. Add Yourself as Subscriber
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```bash
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# Still in mongo shell:
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db.subscribers.insertOne({
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email: "your-email@example.com",
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active: true,
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tracking_enabled: true,
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subscribed_at: new Date()
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})
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```
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### 5. Verify Installation
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```bash
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# 1. Run the crawler manually to fetch news
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docker-compose exec crawler python crawler_service.py 5
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# 2. Send a test email to yourself
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docker-compose exec sender python sender_service.py test your-email@example.com
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```
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## 🎮 Dashboard Access
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Once running, access the services:
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- **Dashboard**: [http://localhost:3000](http://localhost:3000)
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- **API**: [http://localhost:5001](http://localhost:5001)
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## ⏭️ What's Next?
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The system is now fully automated:
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1. **6:00 AM**: Crawls news and generates AI summaries.
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2. **7:00 AM**: Sends the daily newsletter.
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### Useful Commands
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```bash
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# Stop everything
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docker-compose down
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# View logs for a service
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docker-compose logs -f crawler
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# Update code & rebuild
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docker-compose up -d --build
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```
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