212 lines
5.3 KiB
Markdown
212 lines
5.3 KiB
Markdown
# Render.com Deployment Guide
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## Quick Start
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### 1. Render.com Configuration
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**Service Type:** Web Service
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**Build Command:**
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```bash
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pip install -r requirements.txt
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```
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**Start Command (choose one):**
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#### Option A: Shell Script (Recommended)
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```bash
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./start.sh
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```
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#### Option B: Python Supervisor
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```bash
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python start.py
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```
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#### Option C: Direct Command
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```bash
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python scripts/serve.py & python ai_intelligence_layer/main.py
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```
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### 2. Environment Variables
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Set these in Render.com dashboard:
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**Required:**
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```bash
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GEMINI_API_KEY=your_gemini_api_key_here
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ENVIRONMENT=production
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PRODUCTION_URL=https://your-app-name.onrender.com # Your Render app URL
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```
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**Optional:**
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```bash
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ELEVENLABS_API_KEY=your_elevenlabs_api_key_here # For voice features
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GEMINI_MODEL=gemini-2.5-flash
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STRATEGY_COUNT=3
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FAST_MODE=true
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```
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**Auto-configured (no need to set):**
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```bash
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# These are handled automatically by the config system
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AI_SERVICE_PORT=9000
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AI_SERVICE_HOST=0.0.0.0
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ENRICHMENT_SERVICE_URL=http://localhost:8000 # Internal communication
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```
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### Important: Production URL
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After deploying to Render, you'll get a URL like:
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```
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https://your-app-name.onrender.com
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```
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**You MUST set this URL in the environment variables:**
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1. Go to Render dashboard → your service → Environment
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2. Add: `PRODUCTION_URL=https://your-app-name.onrender.com`
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3. The app will automatically use this for WebSocket connections and API URLs
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### 3. Health Check
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**Health Check Path:** `/health` (on port 9000)
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**Health Check Command:**
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```bash
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curl http://localhost:9000/health
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```
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### 4. Port Configuration
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- **Enrichment Service:** 8000 (internal)
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- **AI Intelligence Layer:** 9000 (external, Render will expose this)
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Render will automatically bind to `PORT` environment variable.
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### 5. Files Required
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- ✅ `start.sh` - Shell startup script
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- ✅ `start.py` - Python startup supervisor
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- ✅ `Procfile` - Render configuration
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- ✅ `requirements.txt` - Python dependencies
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### 6. Testing Locally
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Test the startup script before deploying:
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```bash
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# Make executable
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chmod +x start.sh
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# Run locally
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./start.sh
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```
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Or with Python supervisor:
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```bash
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python start.py
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```
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### 7. Deployment Steps
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1. **Push to GitHub:**
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```bash
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git add .
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git commit -m "Add Render deployment configuration"
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git push
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```
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2. **Create Render Service:**
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- Go to [render.com](https://render.com)
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- New → Web Service
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- Connect your GitHub repository
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- Select branch (main)
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3. **Configure Service:**
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- Name: `hpc-simulation-ai`
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- Environment: `Python 3`
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- Build Command: `pip install -r requirements.txt`
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- Start Command: `./start.sh`
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4. **Add Environment Variables:**
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- `GEMINI_API_KEY`
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- `ELEVENLABS_API_KEY` (optional)
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5. **Deploy!** 🚀
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### 8. Monitoring
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Check logs in Render dashboard for:
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- `📊 Starting Enrichment Service on port 8000...`
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- `🤖 Starting AI Intelligence Layer on port 9000...`
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- `✨ All services running!`
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### 9. Connecting Clients
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**WebSocket URL:**
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```
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wss://your-app-name.onrender.com/ws/pi
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```
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**Enrichment API:**
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```
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https://your-app-name.onrender.com/ingest/telemetry
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```
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### 10. Troubleshooting
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**Services won't start:**
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- Check environment variables are set
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- Verify `start.sh` is executable: `chmod +x start.sh`
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- Check build logs for dependency issues
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**Port conflicts:**
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- Render will set `PORT` automatically (9000 by default)
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- Services bind to `0.0.0.0` for external access
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**Memory issues:**
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- Consider Render's paid plans for more resources
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- Free tier may struggle with AI model loading
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## Architecture on Render
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```
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┌─────────────────────────────────────┐
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│ Render.com Container │
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├─────────────────────────────────────┤
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│ │
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│ ┌───────────────────────────────┐ │
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│ │ start.sh / start.py │ │
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│ └──────────┬────────────────────┘ │
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│ │ │
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│ ┌────────┴─────────┐ │
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│ │ │ │
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│ ▼ ▼ │
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│ ┌──────────┐ ┌──────────────┐ │
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│ │Enrichment│ │AI Intelligence│ │
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│ │Service │ │Layer │ │
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│ │:8000 │◄──│:9000 │ │
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│ └──────────┘ └──────┬────────┘ │
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│ │ │
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└────────────────────────┼────────────┘
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│
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Internet
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│
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┌────▼─────┐
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│ Client │
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│(Pi/Web) │
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└──────────┘
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```
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## Next Steps
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1. Test locally with `./start.sh`
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2. Commit and push to GitHub
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3. Create Render service
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4. Configure environment variables
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5. Deploy and monitor logs
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6. Update client connection URLs
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Good luck! 🎉
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