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OLLAMA_GPU_SUMMARY.md
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OLLAMA_GPU_SUMMARY.md
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# Ollama with GPU Support - Implementation Summary
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## What Was Added
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This implementation adds comprehensive GPU support for Ollama AI service in the Munich News Daily system, enabling 5-10x faster AI inference for article translation and summarization.
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## Files Created/Modified
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### Docker Configuration
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- **docker-compose.yml** - Added Ollama service with GPU support comments
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- **docker-compose.gpu.yml** - GPU-specific override configuration
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- **docker-compose.yml** - Added ollama-setup service for automatic model download
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### Helper Scripts
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- **start-with-gpu.sh** - Auto-detect GPU and start services accordingly
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- **check-gpu.sh** - Check GPU availability and Docker GPU support
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- **configure-ollama.sh** - Configure Ollama for Docker Compose or external server
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### Documentation
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- **docs/OLLAMA_SETUP.md** - Complete Ollama setup guide with GPU section
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- **docs/GPU_SETUP.md** - Detailed GPU setup and troubleshooting guide
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- **docs/PERFORMANCE_COMPARISON.md** - CPU vs GPU performance analysis
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- **README.md** - Updated with GPU support information
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## Key Features
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### 1. Automatic GPU Detection
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```bash
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./start-with-gpu.sh
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```
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- Detects NVIDIA GPU availability
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- Checks Docker GPU runtime
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- Automatically starts with appropriate configuration
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### 2. Flexible Deployment Options
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**Option A: Integrated Ollama (Docker Compose)**
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```bash
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# CPU mode
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docker-compose up -d
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# GPU mode
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docker-compose -f docker-compose.yml -f docker-compose.gpu.yml up -d
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```
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**Option B: External Ollama Server**
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```bash
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# Configure for external server
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./configure-ollama.sh
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# Select option 2
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```
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### 3. Automatic Model Download
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- Ollama service starts automatically
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- ollama-setup service pulls phi3:latest model on first run
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- Model persists in Docker volume
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### 4. GPU Support
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- NVIDIA GPU acceleration when available
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- Automatic fallback to CPU if GPU unavailable
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- 5-10x performance improvement with GPU
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## Performance Improvements
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| Operation | CPU | GPU | Speedup |
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|-----------|-----|-----|---------|
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| Translation | 1.5s | 0.3s | 5x |
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| Summarization | 8s | 2s | 4x |
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| 10 Articles | 115s | 31s | 3.7x |
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## Usage Examples
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### Check GPU Availability
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```bash
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./check-gpu.sh
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```
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### Start with GPU (Automatic)
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```bash
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./start-with-gpu.sh
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```
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### Start with GPU (Manual)
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```bash
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docker-compose -f docker-compose.yml -f docker-compose.gpu.yml up -d
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```
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### Verify GPU Usage
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```bash
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# Check GPU in container
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docker exec munich-news-ollama nvidia-smi
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# Monitor GPU during processing
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watch -n 1 'docker exec munich-news-ollama nvidia-smi'
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```
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### Test Translation
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```bash
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# Run test crawl
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docker-compose exec crawler python crawler_service.py 2
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# Check timing in logs
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docker-compose logs crawler | grep "Title translated"
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# GPU: ✓ Title translated (0.3s)
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# CPU: ✓ Title translated (1.5s)
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```
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## Configuration
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### Environment Variables (backend/.env)
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**For Docker Compose Ollama:**
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```env
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OLLAMA_ENABLED=true
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OLLAMA_BASE_URL=http://ollama:11434
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OLLAMA_MODEL=phi3:latest
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OLLAMA_TIMEOUT=120
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```
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**For External Ollama:**
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```env
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OLLAMA_ENABLED=true
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OLLAMA_BASE_URL=http://host.docker.internal:11434
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OLLAMA_MODEL=phi3:latest
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OLLAMA_TIMEOUT=120
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```
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## Requirements
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### For CPU Mode
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- Docker & Docker Compose
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- 4GB+ RAM
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- 4+ CPU cores recommended
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### For GPU Mode
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- NVIDIA GPU (GTX 1060 or newer)
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- 4GB+ VRAM
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- NVIDIA drivers (525.60.13+)
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- NVIDIA Container Toolkit
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- Docker 20.10+
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- Docker Compose v2.3+
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## Installation Steps
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### 1. Install NVIDIA Container Toolkit (Ubuntu/Debian)
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```bash
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distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
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curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg
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curl -s -L https://nvidia.github.io/libnvidia-container/$distribution/libnvidia-container.list | \
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sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | \
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sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
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sudo apt-get update
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sudo apt-get install -y nvidia-container-toolkit
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sudo nvidia-ctk runtime configure --runtime=docker
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sudo systemctl restart docker
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```
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### 2. Verify Installation
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```bash
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docker run --rm --gpus all nvidia/cuda:12.0.0-base-ubuntu22.04 nvidia-smi
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```
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### 3. Configure Ollama
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```bash
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./configure-ollama.sh
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# Select option 1 for Docker Compose
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```
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### 4. Start Services
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```bash
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./start-with-gpu.sh
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```
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## Troubleshooting
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### GPU Not Detected
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```bash
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# Check NVIDIA drivers
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nvidia-smi
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# Check Docker GPU access
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docker run --rm --gpus all nvidia/cuda:12.0.0-base-ubuntu22.04 nvidia-smi
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# Check Ollama container
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docker exec munich-news-ollama nvidia-smi
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```
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### Out of Memory
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- Use smaller model: `OLLAMA_MODEL=gemma2:2b`
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- Close other GPU applications
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- Increase Docker memory limit
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### Slow Performance
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- Verify GPU is being used: `docker exec munich-news-ollama nvidia-smi`
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- Check GPU utilization during inference
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- Ensure using GPU compose file
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- Update NVIDIA drivers
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## Architecture
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```
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┌─────────────────────────────────────────────────────────┐
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│ Docker Compose │
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├─────────────────────────────────────────────────────────┤
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│ │
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│ ┌──────────────┐ ┌──────────────┐ │
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│ │ Ollama │◄─────┤ Crawler │ │
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│ │ (GPU/CPU) │ │ │ │
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│ │ │ │ - Fetches │ │
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│ │ - phi3 │ │ - Translates│ │
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│ │ - Translate │ │ - Summarizes│ │
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│ │ - Summarize │ └──────────────┘ │
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│ └──────────────┘ │
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│ │ │
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│ │ GPU (optional) │
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│ ▼ │
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│ ┌──────────────┐ │
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│ │ NVIDIA GPU │ │
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│ │ (5-10x faster)│ │
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│ └──────────────┘ │
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│ │
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└─────────────────────────────────────────────────────────┘
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```
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## Model Options
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| Model | Size | VRAM | Speed | Quality | Use Case |
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|-------|------|------|-------|---------|----------|
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| gemma2:2b | 1.4GB | 1.5GB | Fastest | Good | High volume |
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| phi3:latest | 2.3GB | 3-4GB | Fast | Very Good | Default |
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| llama3.2:3b | 3.2GB | 5-6GB | Medium | Excellent | Quality critical |
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| mistral:latest | 4.1GB | 6-8GB | Medium | Excellent | Long-form |
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## Next Steps
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1. **Test the setup:**
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```bash
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./check-gpu.sh
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./start-with-gpu.sh
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docker-compose exec crawler python crawler_service.py 2
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```
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2. **Monitor performance:**
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```bash
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watch -n 1 'docker exec munich-news-ollama nvidia-smi'
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docker-compose logs -f crawler
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```
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3. **Optimize for your use case:**
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- Adjust model based on VRAM availability
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- Tune summary length for speed vs quality
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- Enable concurrent requests for high volume
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## Documentation
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- **[OLLAMA_SETUP.md](docs/OLLAMA_SETUP.md)** - Complete Ollama setup guide
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- **[GPU_SETUP.md](docs/GPU_SETUP.md)** - Detailed GPU setup and troubleshooting
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- **[PERFORMANCE_COMPARISON.md](docs/PERFORMANCE_COMPARISON.md)** - CPU vs GPU analysis
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## Support
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For issues or questions:
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1. Run `./check-gpu.sh` for diagnostics
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2. Check logs: `docker-compose logs ollama`
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3. See troubleshooting sections in documentation
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4. Open an issue with diagnostic output
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## Summary
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✅ Ollama service integrated into Docker Compose
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✅ Automatic model download (phi3:latest)
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✅ GPU support with automatic detection
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✅ Fallback to CPU when GPU unavailable
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✅ Helper scripts for easy setup
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✅ Comprehensive documentation
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✅ 5-10x performance improvement with GPU
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✅ Flexible deployment options
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Reference in New Issue
Block a user