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# π Quick Deployment Guide
## π― Choose Your Deployment Method
### π’ **Option 1: Quick Demo (Recommended for Interviews)**
Perfect for demonstrations and quick testing.
**Windows:**
```bash
# Double-click or run:
start_demo.bat
```
**Linux/Mac:**
```bash
./start_demo.sh
```
**What it does:**
- Starts backend on port 8001
- Starts frontend on port 8501
- Opens browser automatically
- Shows progress in separate windows
---
### π‘ **Option 2: Docker Deployment (Recommended for Production)**
Professional containerized deployment.
**Prerequisites:**
- Install [Docker Desktop](https://www.docker.com/products/docker-desktop)
**Windows:**
```bash
# Double-click or run:
deploy_docker.bat
```
**Linux/Mac:**
```bash
./deploy_docker.sh
```
**What it does:**
- Builds Docker containers
- Sets up networking
- Provides health checks
- Includes nginx reverse proxy (optional)
---
## π **Check Deployment Status**
**Windows:**
```bash
check_status.bat
```
**Linux/Mac:**
```bash
curl http://localhost:8001/ # Backend health
curl http://localhost:8501/ # Frontend health
```
---
## π **Access Your Application**
Once deployed, access these URLs:
- **π¨ Frontend UI:** http://localhost:8501
- **β‘ Backend API:** http://localhost:8001
- **π API Documentation:** http://localhost:8001/docs
---
## π **Stop Services**
**Quick Demo:**
- Windows: Run `stop_services.bat` or close command windows
- Linux/Mac: Press `Ctrl+C` in terminal
**Docker:**
```bash
docker-compose down
```
---
## π **Troubleshooting**
### Common Issues:
1. **Port already in use:**
```bash
# Kill existing processes
taskkill /f /im python.exe # Windows
pkill -f python # Linux/Mac
```
2. **Models not loading:**
- Check if `models/indictrans2/` directory exists
- Ensure models were downloaded properly
- Check backend logs for errors
3. **Frontend can't connect to backend:**
- Verify backend is running on port 8001
- Check `frontend/app.py` has correct API_BASE_URL
4. **Docker issues:**
```bash
# Check Docker status
docker ps
docker-compose logs
# Reset Docker
docker-compose down
docker system prune -f
docker-compose up --build
```
---
## π§ **Configuration**
### Environment Variables:
Create `.env` file in root directory:
```bash
MODEL_TYPE=indictrans2
MODEL_PATH=models/indictrans2
DEVICE=cpu
DATABASE_PATH=data/translations.db
```
### For Production:
- Copy `.env.production` to `.env`
- Update database settings
- Configure CORS origins
- Set up monitoring
---
## π **Performance Tips**
1. **Use GPU if available:**
```bash
DEVICE=cuda # in .env file
```
2. **Increase memory for Docker:**
- Docker Desktop β Settings β Resources β Memory: 8GB+
3. **Monitor resource usage:**
```bash
docker stats # Docker containers
htop # System resources
```
---
## π **Success Indicators**
β
**Deployment Successful When:**
- Backend responds at http://localhost:8001
- Frontend loads at http://localhost:8501
- Can translate "Hello" to Hindi
- API docs accessible at http://localhost:8001/docs
- No error messages in logs
---
## π **Need Help?**
1. Check the logs:
- Quick Demo: Look at command windows
- Docker: `docker-compose logs -f`
2. Verify prerequisites:
- Python 3.11+ installed
- All dependencies in requirements.txt
- Models downloaded in correct location
3. Test individual components:
- Backend: `curl http://localhost:8001/`
- Frontend: Open browser to http://localhost:8501
---
**π― For Interview Demos: Use Quick Demo option - it's fastest and shows everything working!**
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