- Add GPU detection utility functions in compat.py
- Modify vidai.py to detect GPUs at startup and configure backends
- Update cluster_client.py to detect GPUs and send capabilities to master
- Modify cluster_master.py to handle client capabilities and model distribution
- Update config.html template to dynamically show/hide backend options
- Update web.py config route to handle dynamic backend availability
- Add model file transfer functionality between master and clients
- Update worker processes to handle model downloads from master
- Test GPU detection and configuration
- Update API documentation for new capabilities

Features implemented:
- Automatic detection of NVIDIA CUDA and AMD ROCm GPUs
- Dynamic configuration of analysis/training backends based on available hardware
- Cluster clients report GPU capabilities to master
- Model distribution from master to clients when needed
- Admin config page hides unavailable backend options
- Updated API documentation reflecting new GPU detection capabilities