examples/integration_demo.py

#!/usr/bin/env python3
"""
Integration Demo for UI Classification Improvements.

Demonstrates the complete workflow from classification to display to verification.
This shows how all components work together in the enhanced system.
"""

import sys
import os
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))

from interface.enhanced_results_display_manager import EnhancedResultsDisplayManager
from core.provider_summary_generator import ProviderSummary, ProviderSummaryGenerator
from core.improved_classification_prompt_manager import ImprovedClassificationPromptManager
from core.conversation_logger import ConversationLogger
from core.spiritual_state import SpiritualState, SpiritualAssessment


def main():
    """Run integration demo."""
    print("🚀 UI Classification Improvements Integration Demo")
    print("=" * 60)
    
    # Initialize components
    print("\n1. Initializing enhanced components...")
    display_manager = EnhancedResultsDisplayManager()
    summary_generator = ProviderSummaryGenerator()
    classification_manager = ImprovedClassificationPromptManager()
    
    print("   ✅ Enhanced Results Display Manager")
    print("   ✅ Provider Summary Generator")
    print("   ✅ Improved Classification Prompt Manager")
    
    # Demonstrate enhanced classification
    print("\n2. Testing enhanced classification criteria...")
    
    # Test explicit red indicators
    red_indicators = classification_manager.get_explicit_red_indicators()
    print(f"   📋 Explicit RED indicators ({len(red_indicators)}):")
    for indicator in red_indicators:
        print(f"      • {indicator}")
    
    # Test updated red flag definition
    red_definition = classification_manager.get_updated_red_flag_definition()
    print(f"\n   🔴 Updated RED flag definition:")
    print(f"      {red_definition}")
    
    # Demonstrate classification validation
    print("\n3. Testing classification validation...")
    
    # Valid classification
    valid_result = classification_manager.create_classification_result(
        classification="red",
        confidence=0.85,
        indicators=["doubt about meaning of suffering"],
        reasoning="Patient questioning meaning of suffering - explicit red indicator",
        red_flag_indicators=["doubt about meaning of suffering"]
    )
    
    print(f"   ✅ Valid classification: {valid_result.classification} (valid: {valid_result.is_valid})")
    
    # Invalid classification that gets corrected
    invalid_result = classification_manager.create_classification_result(
        classification="invalid",
        confidence=2.0,
        indicators=[],
        reasoning=""
    )
    
    print(f"   🔧 Corrected classification: {invalid_result.classification} (valid: {invalid_result.is_valid})")
    
    # Demonstrate enhanced display formatting
    print("\n4. Testing enhanced display formatting...")
    
    # Create test provider summary
    test_summary = ProviderSummary(
        patient_name="Demo Patient",
        patient_phone="555-0123",
        classification="RED",
        confidence=0.85,
        indicators=["loss of meaning", "spiritual distress", "questioning faith"],
        reasoning="Patient expressing significant spiritual concerns and loss of meaning",
        severity_level="HIGH",
        urgency_level="IMMEDIATE",
        situation_description="Patient experiencing existential crisis following medical diagnosis",
        recommended_actions=[
            "Contact patient within 2-4 hours",
            "Assess immediate safety and support needs",
            "Provide spiritual care resources"
        ],
        medical_context={
            "age": 45,
            "gender": "individual",
            "conditions": ["chronic illness", "recent diagnosis"]
        }
    )
    
    # Format AI analysis section
    ai_analysis_html = display_manager.format_ai_analysis_section(
        classification="RED",
        indicators=test_summary.indicators,
        reasoning=test_summary.reasoning,
        confidence=test_summary.confidence
    )
    
    print("   ✅ AI Analysis section formatted")
    print(f"      Length: {len(ai_analysis_html)} characters")
    
    # Format patient message section
    patient_message_html = display_manager.format_patient_message_section(
        "I just don't see the point in anything anymore. My life feels meaningless since my diagnosis."
    )
    
    print("   ✅ Patient Message section formatted")
    print(f"      Length: {len(patient_message_html)} characters")
    
    # Format provider summary section
    provider_summary_html = display_manager.format_provider_summary_section(test_summary)
    
    print("   ✅ Provider Summary section formatted")
    print(f"      Length: {len(provider_summary_html)} characters")
    
    # Test coherent paragraph formatting
    print("\n5. Testing coherent paragraph formatting...")
    
    coherent_paragraph = summary_generator.format_coherent_paragraph(test_summary)
    
    print("   ✅ Coherent paragraph generated")
    print(f"      Length: {len(coherent_paragraph)} characters")
    print(f"      Preview: {coherent_paragraph[:100]}...")
    
    # Test combined results
    print("\n6. Testing combined results formatting...")
    
    combined_html = display_manager.format_combined_results(
        ai_analysis={
            'classification': 'RED',
            'indicators': test_summary.indicators,
            'reasoning': test_summary.reasoning,
            'confidence': test_summary.confidence
        },
        patient_message="I just don't see the point in anything anymore. My life feels meaningless since my diagnosis.",
        provider_summary=test_summary
    )
    
    print("   ✅ Combined results formatted")
    print(f"      Length: {len(combined_html)} characters")
    
    # Test conversation logging integration
    print("\n7. Testing conversation logging integration...")
    
    logger = ConversationLogger(patient_name="Demo Patient")
    
    # Log test conversation
    assessment = SpiritualAssessment(
        state=SpiritualState.RED,
        confidence=0.85,
        indicators=["loss of meaning", "spiritual distress"],
        reasoning="Patient expressing significant spiritual concerns"
    )
    
    logger.log_exchange(
        "I just don't see the point in anything anymore",
        "I understand this is a very difficult time for you",
        assessment
    )
    
    print(f"   ✅ Conversation logged: {len(logger.entries)} entries")
    
    # Test error handling
    print("\n8. Testing error handling and recovery...")
    
    # Create problematic summary
    problematic_summary = ProviderSummary(
        patient_name="[Patient Name]",  # Placeholder
        patient_phone="[Phone Number]",  # Placeholder
        classification="RED",
        confidence=1.5,  # Invalid confidence
        reasoning="",  # Empty reasoning
        indicators=[]  # No indicators
    )
    
    # Display manager should handle this gracefully
    error_display = display_manager.format_provider_summary_section(problematic_summary)
    
    print("   ✅ Error handling works - graceful degradation")
    print(f"      Error display length: {len(error_display)} characters")
    
    # Summary
    print("\n" + "=" * 60)
    print("🎉 INTEGRATION DEMO COMPLETED SUCCESSFULLY!")
    print("\n📋 Demonstrated Features:")
    print("   ✅ Enhanced classification with explicit red indicators")
    print("   ✅ Updated red flag definition and validation")
    print("   ✅ Enhanced display formatting with visual separation")
    print("   ✅ Coherent paragraph formatting for Medical Brain compatibility")
    print("   ✅ Combined results with proper section separation")
    print("   ✅ Conversation logging integration")
    print("   ✅ Error handling and graceful degradation")
    print("\n🚀 All UI Classification Improvements are working correctly!")
    print("   Ready for production use in the medical assistant system.")


if __name__ == "__main__":
    main()