rename

app.py

@@ -17,13 +17,12 @@ pipe = None
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
 
-@spaces.GPU(duration=1000)
-def load_pipeline(
+def _load_pipeline_internal(
     pretrained_model_path="THUDM/CogVideoX-5b",
     ef_net_path="weights/EF_Net.pth",
     dtype_str="bfloat16",
 ):
-    """Load the Sci-Fi pipeline"""
+    """Internal function to load the Sci-Fi pipeline"""
     global pipe
 
     dtype = torch.float16 if dtype_str == "float16" else torch.bfloat16
@@ -77,6 +76,16 @@ def load_pipeline(
     return "Pipeline loaded successfully!"
 
 
+@spaces.GPU(duration=1000)
+def load_pipeline(
+    pretrained_model_path="THUDM/CogVideoX-5b",
+    ef_net_path="weights/EF_Net.pth",
+    dtype_str="bfloat16",
+):
+    """Load the Sci-Fi pipeline (Gradio wrapper)"""
+    return _load_pipeline_internal(pretrained_model_path, ef_net_path, dtype_str)
+
+
 @spaces.GPU(duration=1000)
 def generate_inbetweening(
     first_image: Image.Image,
@@ -289,7 +298,7 @@ if __name__ == "__main__":
     # Automatically load pipeline on startup
     print("Loading pipeline automatically on startup...")
     try:
-        load_pipeline()
+        _load_pipeline_internal()
         print("Pipeline loaded successfully!")
     except Exception as e:
         print(f"Failed to load pipeline on startup: {e}")