MCP Agent Tracker

#!/usr/bin/env python3 """ Seamless Integration Demo This script demonstrates how to seamlessly integrate the enhanced chat system with your existing workflow, showing the before/after comparison. """ import sys import time from typing import Dict, Any def print_header(title: str): """Print a formatted header.""" print("\n" + "="*70) print(f"🚀 {title}") print("="*70) def print_section(title: str): """Print a formatted section.""" print(f"\n📋 {title}") print("-" * 50) def print_success(message: str): """Print a success message.""" print(f"✅ {message}") def print_info(message: str): """Print an info message.""" print(f"ℹ️ {message}") def print_warning(message: str): """Print a warning message.""" print(f"⚠️ {message}") def demo_before_after(): """Demonstrate before/after integration.""" print_header("Seamless Integration Demo - Before vs After") print_info("This demo shows how your existing enhanced_chat function works") print_info("and how it seamlessly integrates with semantic capabilities.") # Test message test_message = "How can I improve my MCP conversation system with embeddings?" print_section("BEFORE: Your Existing enhanced_chat Function") try: # Import your existing function from main import enhanced_chat as original_enhanced_chat print_info("Using your existing enhanced_chat function...") start_time = time.time() # Call your existing function original_result = original_enhanced_chat(test_message) processing_time = time.time() - start_time print_success(f"Original function response: {len(original_result)} characters") print_info(f"Processing time: {processing_time*1000:.2f}ms") print_info("Response preview: " + original_result[:100] + "...") except Exception as e: print_warning(f"Original function not available: {e}") original_result = "Original function response placeholder" print_section("AFTER: Enhanced Chat with Semantic Integration") try: # Import the enhanced version from enhanced_chat_integration import enhanced_chat, enhanced_chat_semantic print_info("Using enhanced_chat with semantic integration...") start_time = time.time() # Call enhanced version (backward compatible) enhanced_result = enhanced_chat(test_message) processing_time = time.time() - start_time if isinstance(enhanced_result, dict): print_success(f"Enhanced response: {enhanced_result['status']}") metrics = enhanced_result.get('performance_metrics', {}) print_info(f"Processing time: {metrics.get('processing_time_ms', 0)}ms") print_info(f"Enhancement ratio: {metrics.get('enhancement_ratio', 0):.2f}") print_info(f"Context richness: {metrics.get('context_richness_score', 0):.2f}") # Show semantic insights if enhanced_result.get('semantic_insights'): insights = enhanced_result['semantic_insights'] print_info(f"Semantic insights available: {insights.get('status', 'unknown')}") if insights.get('recommendations'): print_info("Recommendations:") for i, rec in enumerate(insights['recommendations'][:3], 1): print(f" {i}. {rec}") else: print_success(f"Enhanced response: {len(enhanced_result)} characters") print_info(f"Processing time: {processing_time*1000:.2f}ms") except Exception as e: print_warning(f"Enhanced function not available: {e}") print_section("COMPARISON: What Changed") print_info("🔍 **What You Get Now:**") print(" ✅ Same function call: enhanced_chat('your message')") print(" ✅ Same response format (string) for backward compatibility") print(" ✅ Automatic semantic enhancement when available") print(" ✅ Rich context analysis and insights") print(" ✅ Performance metrics and monitoring") print(" ✅ Graceful fallback if semantic system unavailable") print_info("\n🚀 **New Capabilities:**") print(" • enhanced_chat_semantic() - Full semantic control") print(" • get_semantic_insights_quick() - Quick semantic analysis") print(" • get_context_analysis_quick() - Rich context analysis") print(" • get_enhanced_chat_status() - Integration monitoring") print(" • toggle_semantic_enhancement() - Feature control") def demo_usage_patterns(): """Demonstrate different usage patterns.""" print_header("Usage Patterns Demo") test_message = "What are the best practices for MCP conversation systems?" print_section("Pattern 1: Drop-in Replacement") try: from enhanced_chat_integration import enhanced_chat print_info("Simply replace your existing enhanced_chat import:") print(" # Before: from main import enhanced_chat") print(" # After: from enhanced_chat_integration import enhanced_chat") print("\nYour existing code continues to work unchanged!") result = enhanced_chat(test_message) if isinstance(result, str): print_success(f"Response received: {len(result)} characters") else: print_success(f"Enhanced response: {result['status']}") except Exception as e: print_warning(f"Demo failed: {e}") print_section("Pattern 2: Semantic Control") try: from enhanced_chat_integration import enhanced_chat_semantic print_info("Full control over semantic features:") # High precision mode high_precision = enhanced_chat_semantic( test_message, use_semantic_enhancement=True, similarity_threshold=0.9, return_enhanced=True ) if isinstance(high_precision, dict): print_success("High precision mode:") metrics = high_precision.get('performance_metrics', {}) print(f" Processing time: {metrics.get('processing_time_ms', 0)}ms") print(f" Enhancement ratio: {metrics.get('enhancement_ratio', 0):.2f}") # Fast mode (no semantic enhancement) fast_mode = enhanced_chat_semantic( test_message, use_semantic_enhancement=False, return_enhanced=False ) print_success("Fast mode (no semantic enhancement):") print(f" Response length: {len(fast_mode)} characters") except Exception as e: print_warning(f"Demo failed: {e}") print_section("Pattern 3: Quick Semantic Analysis") try: from enhanced_chat_integration import get_semantic_insights_quick, get_context_analysis_quick print_info("Quick semantic analysis without full chat:") # Get semantic insights insights = get_semantic_insights_quick(test_message) if insights.get('status') == 'success': print_success("Semantic insights available") richness = insights.get('context_richness_score', 0) print(f" Context richness: {richness:.2f}") # Get context analysis context = get_context_analysis_quick(test_message) if 'error' not in context: print_success("Context analysis available") recommendations = context.get('bridge_enhancements', {}).get('recommendations', []) if recommendations: print(f" Recommendations: {len(recommendations)} found") except Exception as e: print_warning(f"Demo failed: {e}") def demo_integration_status(): """Demonstrate integration status monitoring.""" print_header("Integration Status Monitoring") try: from enhanced_chat_integration import get_enhanced_chat_status, toggle_semantic_enhancement print_section("Current Integration Status") status = get_enhanced_chat_status() print_info("Integration Status:") print(f" Semantic enhancement: {status['semantic_enhancement_enabled']}") print(f" Integration status: {status['integration_status']}") print(f" Bridge available: {status['bridge_available']}") print(f" Enhanced tools available: {status['enhanced_tools_available']}") print(f" Timestamp: {status['timestamp']}") print_section("Feature Toggle Demo") print_info("You can toggle semantic enhancement on/off:") # Toggle off current_state = toggle_semantic_enhancement(False) print(f" Semantic enhancement: {current_state}") # Toggle on current_state = toggle_semantic_enhancement(True) print(f" Semantic enhancement: {current_state}") # Toggle (flip current state) current_state = toggle_semantic_enhancement() print(f" Semantic enhancement: {current_state}") except Exception as e: print_warning(f"Status monitoring failed: {e}") def demo_migration_strategy(): """Demonstrate migration strategy.""" print_header("Migration Strategy Demo") print_section("Phase 1: Parallel Implementation") print_info("Keep both systems running while testing:") print(""" # Keep existing functionality from main import enhanced_chat as original_enhanced_chat # Test enhanced functionality from enhanced_chat_integration import enhanced_chat as new_enhanced_chat # Use both for comparison original_response = original_enhanced_chat("Test message") enhanced_response = new_enhanced_chat("Test message") """) print_section("Phase 2: Gradual Replacement") print_info("Replace imports with fallback:") print(""" try: # Try enhanced version first from enhanced_chat_integration import enhanced_chat print("Using enhanced chat with semantic capabilities") except ImportError: # Fallback to original from main import enhanced_chat print("Using original enhanced chat") """) print_section("Phase 3: Full Integration") print_info("Use enhanced system exclusively:") print(""" # Full enhanced system from enhanced_chat_integration import ( enhanced_chat, enhanced_chat_semantic, get_semantic_insights_quick, get_context_analysis_quick ) """) def main(): """Main demonstration function.""" print_header("Seamless Integration with Your enhanced_chat Function") print_info("This demo shows how to seamlessly integrate semantic capabilities") print_info("with your existing enhanced_chat function while maintaining full compatibility.") # Run demonstrations demo_before_after() demo_usage_patterns() demo_integration_status() demo_migration_strategy() print_header("Integration Complete! 🎉") print_success("Your enhanced_chat function now has seamless semantic integration!") print_info("\n🔗 **Key Benefits:**") print(" ✅ Zero code changes required for basic usage") print(" ✅ Automatic semantic enhancement when available") print(" ✅ Rich semantic insights and context analysis") print(" ✅ Performance monitoring and optimization") print(" ✅ Easy toggle between enhanced and basic modes") print(" ✅ Graceful fallback for maximum reliability") print_info("\n🚀 **Next Steps:**") print(" 1. Test the integration: python enhanced_chat_integration.py") print(" 2. Replace your import: from enhanced_chat_integration import enhanced_chat") print(" 3. Enjoy automatic semantic enhancement!") print(" 4. Explore advanced features as needed") print_info("\n📚 **Documentation:**") print(" • enhanced_chat_integration.py - Main integration module") print(" • INTEGRATION_GUIDE.md - Comprehensive integration guide") print(" • Test files - Examples and usage patterns") if __name__ == "__main__": main()