Troubleshooting
Common issues and solutions
Installation Issues
GPU Not Detected
Symptoms: ALICE falls back to CPU, slow generation
Solutions:
- Verify CUDA/ROCm installation
- Check PyTorch GPU support:
python -c "import torch; print(torch.cuda.is_available())"
- Reinstall PyTorch with correct GPU support
Out of Memory Errors
Symptoms: Generation fails with OOM error
Solutions:
- Reduce image resolution
- Lower cache_size in config
- Enable auto_unload
- Close other GPU applications
- Use smaller models (SD 1.5 instead of SDXL)
Generation Issues
Slow Generation
Causes:
- CPU fallback (no GPU)
- Large resolution
- Too many steps
- Complex model
Solutions:
- Enable GPU acceleration
- Use native resolution for model
- Reduce steps (20-30 is usually enough)
- Try Turbo models for faster results
Poor Quality Images
Solutions:
- Increase steps (try 30-50)
- Adjust guidance scale (7-10 recommended)
- Use better prompts (be specific)
- Add negative prompts
- Try different schedulers
- Use higher quality models
API Issues
Connection Refused
Solutions:
- Verify ALICE is running
- Check port (default 8080)
- Check firewall rules
- Verify bind address in config
Authentication Errors
Solutions:
- Verify API key is correct
- Check Authorization header format
- Confirm auth is enabled in config
Next Steps