#!/usr/bin/env python3 """ BACKUP of complex ui_function_wrapper that causes schema validation issues This is the original function from app_backup.py that triggers: TypeError: argument of type 'bool' is not iterable """ def ui_function_wrapper(vehicle_type, user_description): """ Main UI wrapper function that yields real-time updates to multiple Gradio components Returns tuples in the order: process_log, current_design_specs, progress_bar, final_status, simulation_video, best_design_specs, download_json, performance_summary, llm_rationale """ global designer # Reset designer for new task designer.reset_design_session() designer.vehicle_type = vehicle_type.lower() designer.user_task_description = user_description # Initial setup - yield initial states yield ( "šŸš€ Initializing Agent2Robot system...\n", # process_log_output {}, # current_design_specs_output 0, # progress_bar_output "", # final_status_output None, # simulation_video_output {}, # best_design_specs_output None, # download_json_output "", # performance_summary_output "" # llm_rationale_output ) # Parse user criteria designer.log_process_step("šŸŽÆ Analyzing user task and success criteria...") criteria = designer.parse_user_task_for_criteria(user_description) designer.log_process_step(f"šŸ“‹ Interpreted success criteria:") for criterion in criteria: designer.log_process_step(f" ā€¢ {criterion}") # Update with criteria interpretation current_log = "\n".join(designer.process_log) yield ( current_log, # process_log_output {"interpreted_criteria": criteria}, # current_design_specs_output 0, # progress_bar_output "", # final_status_output None, # simulation_video_output {}, # best_design_specs_output None, # download_json_output "", # performance_summary_output "" # llm_rationale_output ) # Start design process designer.log_process_step(f"šŸš€ Starting {vehicle_type} design process...") designer.log_process_step(f"šŸŽÆ Target: {user_description}") current_log = "\n".join(designer.process_log) yield ( current_log, # process_log_output {"status": "Design process starting..."}, # current_design_specs_output 0, # progress_bar_output "", # final_status_output None, # simulation_video_output {}, # best_design_specs_output None, # download_json_output "", # performance_summary_output "" # llm_rationale_output ) # Run iterations for iteration in range(1, MAX_ITERATIONS + 1): designer.log_process_step(f"\n=== Starting Iteration {iteration}/{MAX_ITERATIONS} ===") # Update progress at start of iteration current_log = "\n".join(designer.process_log) progress_value = (iteration - 0.5) / MAX_ITERATIONS * 100 # Convert to percentage yield ( current_log, # process_log_output {"current_iteration": iteration, "max_iterations": MAX_ITERATIONS, "status": "Running..."}, # current_design_specs_output progress_value, # progress_bar_output "", # final_status_output None, # simulation_video_output {}, # best_design_specs_output None, # download_json_output "", # performance_summary_output "" # llm_rationale_output ) # Run the iteration try: success = designer.run_single_iteration(iteration) # Get current design specs for display if designer.all_attempts: current_attempt = designer.all_attempts[-1] current_specs = current_attempt['vehicle_specs'] design_reasoning = current_attempt.get('design_reasoning', 'No reasoning provided') # Update with current iteration results current_log = "\n".join(designer.process_log) progress_value = iteration / MAX_ITERATIONS * 100 current_specs_display = { "iteration": iteration, "vehicle_specs": current_specs, "design_reasoning_preview": design_reasoning[:200] + "..." if len(design_reasoning) > 200 else design_reasoning, "status": "āœ… SUCCESS" if success else "šŸ”„ Completed - Evaluating..." } yield ( current_log, # process_log_output current_specs_display, # current_design_specs_output progress_value, # progress_bar_output "", # final_status_output None, # simulation_video_output {}, # best_design_specs_output None, # download_json_output "", # performance_summary_output "" # llm_rationale_output ) if success: designer.log_process_step("šŸŽ‰ SUCCESS! Design meets all criteria!") break except Exception as e: designer.log_process_step(f"āŒ Error in iteration {iteration}: {str(e)}") current_log = "\n".join(designer.process_log) progress_value = iteration / MAX_ITERATIONS * 100 yield ( current_log, # process_log_output {"error": f"Iteration {iteration} failed", "details": str(e)}, # current_design_specs_output progress_value, # progress_bar_output "", # final_status_output None, # simulation_video_output {}, # best_design_specs_output None, # download_json_output "", # performance_summary_output "" # llm_rationale_output ) # Generate final results designer.log_process_step("šŸ“Š Generating final results and visualizations...") current_log = "\n".join(designer.process_log) yield ( current_log, # process_log_output {"status": "Generating final results..."}, # current_design_specs_output 100, # progress_bar_output - complete "", # final_status_output None, # simulation_video_output {}, # best_design_specs_output None, # download_json_output "", # performance_summary_output "" # llm_rationale_output ) # Prepare final outputs if designer.overall_success: final_status = "## šŸŽ‰ SUCCESS!\n\nThe LLM agent successfully designed a vehicle that meets all criteria!" status_emoji = "āœ…" else: final_status = "## āš ļø PROCESS COMPLETED\n\nThe agent completed all iterations. Showing best attempt found." status_emoji = "šŸ”„" # Get best design specs best_specs = designer.best_attempt['vehicle_specs'] if designer.best_attempt else {} # Create visualization simulation_gif_path = None try: simulation_gif_path = designer.create_final_visualization() except Exception as e: designer.log_process_step(f"āš ļø Error creating visualization: {str(e)}") # Format performance summary if designer.best_attempt: eval_results = designer.best_attempt['evaluation_results'] performance_summary = f"""## šŸ“Š Performance Summary of Best Design **Iteration Found**: {designer.best_iteration}/{len(designer.all_attempts)} **Final Position**: {eval_results.get('final_robot_x_position', 0.0):.3f}m **Crossed Obstacle**: {'āœ… Yes' if eval_results.get('robot_crossed_obstacle', False) else 'āŒ No'} **Remained Stable**: {'āœ… Yes' if eval_results.get('robot_remains_upright', False) else 'āŒ No'} **Clean Pass**: {'āœ… Yes' if eval_results.get('no_significant_collision_with_obstacle_during_pass', False) else 'āŒ No'} **Overall Success**: {'āœ… ACHIEVED' if eval_results.get('overall_success', False) else 'āŒ NOT FULLY ACHIEVED'} **Target Distance**: 0.8m (obstacle clearance) **Achieved Distance**: {eval_results.get('final_robot_x_position', 0.0):.3f}m **Success Rate**: {100 if eval_results.get('overall_success', False) else 0}% {status_emoji} **Status**: {'Complete Success' if designer.overall_success else 'Best Effort'} """ else: performance_summary = "## āŒ No successful attempts recorded\n\nThe system was unable to generate valid designs." # Get LLM rationale llm_rationale = designer.best_attempt['design_reasoning'] if designer.best_attempt else "No design reasoning available" # Create downloadable specs download_specs_path = None try: download_specs_path = designer.save_design_specs_json() except Exception as e: designer.log_process_step(f"āš ļø Error saving specs: {str(e)}") # Final log update designer.log_process_step(f"\nšŸ DESIGN PROCESS COMPLETED") designer.log_process_step(f"šŸ“Š Total iterations: {len(designer.all_attempts)}") designer.log_process_step(f"šŸ† Best iteration: {designer.best_iteration}") designer.log_process_step(f"āœ… Overall success: {designer.overall_success}") final_log = "\n".join(designer.process_log) # Final yield with all results yield ( final_log, # process_log_output {"final_summary": f"Process completed. {len(designer.all_attempts)} iterations run."}, # current_design_specs_output 100, # progress_bar_output final_status, # final_status_output simulation_gif_path, # simulation_video_output best_specs, # best_design_specs_output download_specs_path, # download_json_output performance_summary, # performance_summary_output llm_rationale # llm_rationale_output )