Add IPFS HLS streaming and GPU optimizations

- Add IPFSHLSOutput class that uploads segments to IPFS as they're created
- Update streaming task to use IPFS HLS output for distributed streaming
- Add /ipfs-stream endpoint to get IPFS playlist URL
- Update /stream endpoint to redirect to IPFS when available
- Add GPU persistence mode (STREAMING_GPU_PERSIST=1) to keep frames on GPU
- Add hardware video decoding (NVDEC) support for faster video processing
- Add GPU-accelerated primitive libraries: blending_gpu, color_ops_gpu, geometry_gpu
- Add streaming_gpu module with GPUFrame class for tracking CPU/GPU data location
- Add Dockerfile.gpu for building GPU-enabled worker image

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

sexp_effects/primitive_libs/image.py

@@ -8,10 +8,16 @@ import cv2
 
 
 def prim_width(img):
+    if isinstance(img, (list, tuple)):
+        raise TypeError(f"image:width expects an image array, got {type(img).__name__} with {len(img)} elements")
     return img.shape[1]
 
 
 def prim_height(img):
+    if isinstance(img, (list, tuple)):
+        import sys
+        print(f"DEBUG image:height got list: {img[:3]}... (types: {[type(x).__name__ for x in img[:3]]})", file=sys.stderr)
+        raise TypeError(f"image:height expects an image array, got {type(img).__name__} with {len(img)} elements: {img}")
     return img.shape[0]