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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)}") | |
| This implementation includes: | |
| 1. A complete Dockerfile for deployment | |
| 2. The main Streamlit application with all workflow components | |
| 3. Proper requirements file with all dependencies | |
| 4. Utility functions in a separate file | |
| 5. Session state management | |
| 6. Error handling | |
| 7. Clean UI layout with columns | |
| 8. Form submission handling | |
| 9. Results display section | |
| The application is ready to run and can be deployed directly. You can replace the placeholder implementations (LLM, image generation, API calls) with your actual implementations as needed. |