Enable running scope on non-gpu machines

pyproject.toml

@@ -51,7 +51,7 @@ dependencies = [
     "torchcodec==0.7.0",
     "torchao==0.13.0",
     "kernels>=0.10.4",
-    "triton==3.4.0; sys_platform != 'win32'",
+    "triton==3.4.0; sys_platform == 'linux'",
     "triton-windows==3.4.0.post21; sys_platform == 'win32'",
 ]
 

src/scope/core/pipelines/passthrough/pipeline.py

@@ -27,7 +27,11 @@ def __init__(
     ):
         self.height = height
         self.width = width
-        self.device = device if device is not None else torch.device("cuda")
+        self.device = (
+            device
+            if device is not None
+            else torch.device("cuda" if torch.cuda.is_available() else "cpu")
+        )
         self.dtype = dtype
         self.prompts = None
 

src/scope/server/app.py

@@ -181,15 +181,14 @@ async def lifespan(app: FastAPI):
     # Startup
     global webrtc_manager, pipeline_manager
 
-    # Check CUDA availability before proceeding
+    # Check CUDA availability and warn if not available
     if not torch.cuda.is_available():
-        error_msg = (
+        warning_msg = (
             "CUDA is not available on this system. "
-            "This application currently requires a CUDA-compatible GPU and "
-            "other hardware will be supported in the future."
+            "Some pipelines may not work without a CUDA-compatible GPU. "
+            "The application will start, but pipeline functionality may be limited."
         )
-        logger.error(error_msg)
-        sys.exit(1)
+        logger.warning(warning_msg)
 
     # Log logs directory
     logs_dir = get_logs_dir()

src/scope/server/pipeline_manager.py

@@ -14,6 +14,11 @@
 logger = logging.getLogger(__name__)
 
 
+def get_device() -> torch.device:
+    """Get the appropriate device (CUDA if available, CPU otherwise)."""
+    return torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+
 class PipelineNotAvailableException(Exception):
     """Exception raised when pipeline is not available for processing."""
 
@@ -328,7 +333,7 @@ def _load_pipeline_implementation(
             pipeline = PassthroughPipeline(
                 height=height,
                 width=width,
-                device=torch.device("cuda"),
+                device=get_device(),
                 dtype=torch.bfloat16,
             )
             logger.info("Passthrough pipeline initialized")