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/ocr.py

@@ -34,9 +34,10 @@ def run_paddleocr(input_path, language):
     """Run PaddleOCR."""
     os.environ["PADDLE_PDX_DISABLE_MODEL_SOURCE_CHECK"] = "True"
     from paddleocr import PaddleOCR
+    from gpu import gpu_available
 
     emit_progress(20, "Loading")
-    ocr = PaddleOCR(lang=language)
+    ocr = PaddleOCR(lang=language, use_gpu=gpu_available())
     emit_progress(30, "Scanning")
     result = ocr.ocr(input_path)
     emit_progress(70, "Extracting text")