lazy import torch/cordon for ZeroGPU compatibility

app.py

@@ -11,9 +11,10 @@ from pathlib import Path
 
 import gradio as gr
 import spaces
-import torch
 
-from cordon import AnalysisConfig, SemanticLogAnalyzer
+# NOTE: Do NOT import torch or cordon at module level!
+# ZeroGPU requires all CUDA-related imports to happen inside @spaces.GPU functions.
+# Importing torch at module level can trigger CUDA initialization and hang the space.
 
 # Configure logging for HuggingFace Spaces visibility
 logging.basicConfig(
@@ -57,7 +58,13 @@ def analyze_logs(
     
     This function is decorated with @spaces.GPU to run on ZeroGPU.
     The GPU is allocated when this function is called.
+    
+    IMPORTANT: torch and cordon are imported here (not at module level)
+    because ZeroGPU only allocates GPU resources inside @spaces.GPU functions.
     """
+    # Lazy imports - only load when GPU is allocated
+    import torch
+    from cordon import AnalysisConfig, SemanticLogAnalyzer
     
     start_time = time.time()
     logger.info("=" * 60)
@@ -338,13 +345,12 @@ result = analyzer.analyze_file(Path("system.log"))
 
 
 # Startup logging
-# NOTE: Do NOT check torch.cuda here - ZeroGPU only allocates GPU inside @spaces.GPU functions
+# NOTE: torch is imported lazily inside @spaces.GPU function for ZeroGPU compatibility
 logger.info("=" * 60)
 logger.info("Cordon Space starting...")
 logger.info(f"Python version: {sys.version}")
 logger.info(f"Gradio version: {gr.__version__}")
-logger.info(f"PyTorch version: {torch.__version__}")
-logger.info("CUDA check deferred to @spaces.GPU function (ZeroGPU)")
+logger.info("PyTorch/Cordon loaded lazily inside @spaces.GPU function")
 logger.info("=" * 60)
 
 # Create and launch the demo