feat: add GPU/CUDA acceleration support (:cuda Docker tag)

Add a :cuda Docker image tag that auto-detects NVIDIA GPU at runtime
and falls back gracefully to CPU. Same pattern as Immich.

- New gpu.py shared utility for cached CUDA detection
- Background removal (rembg): pass CUDAExecutionProvider to ONNX Runtime
- Upscaling (Real-ESRGAN): use CUDA device + FP16 when GPU available
- OCR (PaddleOCR): enable use_gpu when CUDA detected
- Dispatcher reports GPU status at startup via readiness signal
- Admin health endpoint exposes GPU availability
- Dockerfile uses ARG GPU=false with conditional NVIDIA CUDA base image
- docker-compose.gpu.yml override for GPU users
- CI/CD workflows build and publish :cuda tag (amd64 only)

Three tags: :latest (CPU), :lite (no AI), :cuda (GPU with CPU fallback)

packages/ai/python/upscale.py

@@ -26,7 +26,12 @@ def main():
         try:
             from basicsr.archs.rrdbnet_arch import RRDBNet
             from realesrgan import RealESRGANer
+            from gpu import gpu_available
             import numpy as np
+            import torch
+
+            use_gpu = gpu_available()
+            device = torch.device("cuda" if use_gpu else "cpu")
 
             model = RRDBNet(
                 num_in_ch=3,
@@ -40,7 +45,8 @@ def main():
                 scale=scale,
                 model_path=None,
                 model=model,
-                half=False,
+                half=use_gpu,
+                device=device,
             )
             emit_progress(20, "Model ready")
             img_array = np.array(img.convert("RGB"))