ui_function_backup.py

#!/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 (
        "🚀 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("🎯 Analyzing user task and success criteria...")
    criteria = designer.parse_user_task_for_criteria(user_description)
    
    designer.log_process_step(f"📋 Interpreted success criteria:")
    for criterion in criteria:
        designer.log_process_step(f"  • {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"🚀 Starting {vehicle_type} design process...")
    designer.log_process_step(f"🎯 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": "✅ SUCCESS" if success else "🔄 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("🎉 SUCCESS! Design meets all criteria!")
                break
                
        except Exception as e:
            designer.log_process_step(f"❌ 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("📊 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 = "## 🎉 SUCCESS!\n\nThe LLM agent successfully designed a vehicle that meets all criteria!"
        status_emoji = "✅"
    else:
        final_status = "## ⚠️ PROCESS COMPLETED\n\nThe agent completed all iterations. Showing best attempt found."
        status_emoji = "🔄"
    
    # 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"⚠️ Error creating visualization: {str(e)}")
    
    # Format performance summary
    if designer.best_attempt:
        eval_results = designer.best_attempt['evaluation_results']
        performance_summary = f"""## 📊 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**: {'✅ Yes' if eval_results.get('robot_crossed_obstacle', False) else '❌ No'}
**Remained Stable**: {'✅ Yes' if eval_results.get('robot_remains_upright', False) else '❌ No'}
**Clean Pass**: {'✅ Yes' if eval_results.get('no_significant_collision_with_obstacle_during_pass', False) else '❌ No'}

**Overall Success**: {'✅ ACHIEVED' if eval_results.get('overall_success', False) else '❌ 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 = "## ❌ 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"⚠️ Error saving specs: {str(e)}")
    
    # Final log update
    designer.log_process_step(f"\n🏁 DESIGN PROCESS COMPLETED")
    designer.log_process_step(f"📊 Total iterations: {len(designer.all_attempts)}")
    designer.log_process_step(f"🏆 Best iteration: {designer.best_iteration}")
    designer.log_process_step(f"✅ 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
    )