""" RoutePilot - GNN-LLM Intelligent Selection System Hugging Face Spaces Entry Point This is the main entry point for the Hugging Face Spaces deployment. It imports the necessary components from the existing application and sets up the Gradio interface for deployment. """ import os import sys import gradio as gr # Add the current directory to Python path for imports sys.path.append(os.path.dirname(__file__)) # Import the main application components from demo import create_interface # Set up environment variables for Hugging Face Spaces def setup_environment(): """Set up environment variables for Hugging Face Spaces deployment""" # Check if we're running on Hugging Face Spaces if os.getenv("SPACE_ID"): print("🚀 Running on Hugging Face Spaces") # Check for NVIDIA API key if not os.getenv("NVIDIA_API_KEY"): print("âš ī¸ NVIDIA_API_KEY not set in Space secrets.") print(" Please set NVIDIA_API_KEY in the Space Repository Secrets.") print(" Some features may be limited without API access.") else: print("✅ NVIDIA_API_KEY found in Space secrets") # Set CUDA device for Spaces (usually limited resources) os.environ["CUDA_VISIBLE_DEVICES"] = "0" # Set memory optimization flags os.environ["PYTORCH_CUDA_ALLOC_CONF"] = "max_split_size_mb:128" else: print("🏠 Running locally") # Check for local .env file if not os.getenv("NVIDIA_API_KEY"): print("â„šī¸ NVIDIA_API_KEY not found. For local development, create a .env file") print(" or set the environment variable manually.") def main(): """Main function to launch the application""" # Set up environment setup_environment() # Create the Gradio interface print("đŸŽ¯ Creating RoutePilot interface...") demo = create_interface() # Launch the application # For Hugging Face Spaces, we don't need to specify server_name and port # The platform handles this automatically demo.launch( show_error=True, debug=False, # Set to False for production show_api=False ) if __name__ == "__main__": main()