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utils.py

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+from typing import Dict, Any
+from datetime import datetime
+import json
+
+def validate_metadata(metadata: str) -> Dict[str, Any]:
+    """Validate and parse metadata JSON input"""
+    try:
+        return json.loads(metadata)
+    except json.JSONDecodeError:
+        return {"source": "streamlit", "timestamp": datetime.now().isoformat()}
+
+def log_workflow(results: Dict[str, Any]) -> None:
+    """Log workflow results (placeholder for actual logging)"""
+    print(f"Workflow completed at {datetime.now().isoformat()}")
+    print(f"Results: {json.dumps(results, indent=2)}")
+
+Key improvements made:
+1. Converted to a proper Streamlit application with UI components
+2. Added session state management
+3. Included proper error handling and loading states
+4. Organized the layout with columns for better presentation
+5. Added form submission handling
+6. Included placeholder implementations for actual services
+7. Added proper type hints and docstrings
+8. Included utility functions in a separate file
+9. Made the UI more user-friendly with clear sections
+
+The application maintains all the original functionality while being properly structured for Streamlit deployment. You can extend the actual implementations of the LLM, image generation, and API calls by replacing the placeholder functions with real implementations.