AI Agent Generator

#!/usr/bin/env python3 """ Test script to verify email agent creation workflow """ import asyncio import json import sys import os # Add src to path sys.path.insert(0, os.path.join(os.path.dirname(__file__), 'src')) async def test_email_agent_creation(): """Test creating an email agent to verify the improved workflow""" print("🧪 Testing Email Agent Creation Workflow...") print("=" * 50) try: # Import the enhanced agent manager from tools.enhanced_agent_manager import EnhancedAgentManager print("✅ Successfully imported EnhancedAgentManager") # Create manager instance manager = EnhancedAgentManager() print("✅ Successfully created manager instance") # Test email agent creation print("\n📧 Creating email agent...") result = await manager.create_agent( name="MailTracker", description="stwórz agenta do śledzenia poczty i wysyłania maili", domain="general", # Let AI detect it should be "communication" complexity="medium" ) print("\n📋 Agent Creation Result:") print("=" * 30) print(json.dumps(result, indent=2, ensure_ascii=False)) # Verify key features success_checks = [] # Check if agent was created successfully if result.get("success"): success_checks.append("✅ Agent created successfully") else: success_checks.append("❌ Agent creation failed") # Check if domain was auto-detected as communication ai_enhancements = result.get("ai_enhancements", {}) if ai_enhancements.get("detected_domain") == "communication": success_checks.append("✅ AI auto-detected email/communication domain") else: success_checks.append(f"⚠️ Domain detected as: {ai_enhancements.get('detected_domain')}") # Check if components were auto-added total_components = ai_enhancements.get("total_components_added", 0) if total_components > 0: success_checks.append(f"✅ Auto-added {total_components} components") else: success_checks.append("❌ No components were auto-added") # Check if chat interface was generated chat_interface = result.get("chat_interface", {}) if chat_interface.get("generated"): success_checks.append("✅ Chat interface auto-generated") success_checks.append(f"📁 File: {chat_interface.get('filename')}") else: success_checks.append("⚠️ Chat interface not auto-generated") print("\n🔍 Verification Results:") print("=" * 25) for check in success_checks: print(check) # Show component details if available if result.get("success") and result.get("agent"): agent = result["agent"] components = agent.get("components", []) print(f"\n📦 Components Added ({len(components)}):") print("=" * 30) for comp in components: status = "🤖 AI" if comp.get("auto_added") else "📝 Manual" confidence = comp.get("confidence", "N/A") print(f"{status} {comp['name']} (confidence: {confidence}%)") if comp.get("reason"): print(f" Reason: {comp['reason']}") print() # Test getting the agent back if result.get("success"): agent_id = result["agent_id"] print(f"\n📊 Testing agent retrieval for ID: {agent_id[:8]}...") get_result = await manager.get_agent(agent_id) if get_result.get("success"): print("✅ Agent retrieval successful") ai_insights = get_result.get("ai_insights", {}) print(f"🧠 Intelligence Score: {ai_insights.get('current_intelligence_score', 'N/A')}%") print(f"🚀 Readiness Score: {ai_insights.get('readiness_score', 'N/A')}%") else: print("❌ Agent retrieval failed") print("\n" + "=" * 50) if result.get("success") and chat_interface.get("generated"): print("🎉 SUCCESS: Email agent created with auto-generated chat interface!") print("💡 The agent is ready for immediate testing and deployment.") elif result.get("success"): print("✅ SUCCESS: Email agent created successfully.") print("ℹ️ Chat interface can be generated separately if needed.") else: print("❌ FAILED: Email agent creation encountered issues.") return result.get("success", False) except Exception as e: print(f"❌ Test failed with error: {e}") import traceback traceback.print_exc() return False async def test_description_analyzer(): """Test the description analyzer for email patterns""" print("\n🔍 Testing Description Analyzer...") print("=" * 40) try: from utils.description_analyzer import get_description_analyzer analyzer = get_description_analyzer() print("✅ Successfully created description analyzer") # Test email-related description description = "stwórz agenta do śledzenia poczty i wysyłania maili" analysis = await analyzer.analyze_description(description, "general") print(f"\n📧 Analysis of: '{description}'") print("=" * 50) print(f"🎯 Detected Domain: {analysis['enhanced_analysis']['detected_domain']}") print(f"📊 Confidence Score: {analysis['enhanced_analysis']['confidence_score']}%") print(f"⚖️ Complexity Level: {analysis['enhanced_analysis']['complexity_level']}") print(f"\n🔍 Detected Patterns: {', '.join(analysis['detected_patterns'])}") print(f"\n💡 Smart Suggestions ({len(analysis['smart_suggestions'])}):") for suggestion in analysis['smart_suggestions']: print(f" • {suggestion['component_id']} (confidence: {suggestion['confidence']}%)") print(f" Reason: {suggestion['reason']}") print(f"\n📋 Implicit Requirements ({len(analysis['implicit_requirements'])}):") for req in analysis['implicit_requirements']: print(f" • {req['reasoning']} (confidence: {req['confidence']}%)") print(f" Components: {', '.join(req['suggested_components'])}") return analysis['enhanced_analysis']['detected_domain'] == 'communication' except Exception as e: print(f"❌ Description analyzer test failed: {e}") import traceback traceback.print_exc() return False if __name__ == "__main__": async def main(): print("🚀 Starting AI Agent Generator MCP Tests") print("=" * 60) # Test 1: Description Analyzer analyzer_success = await test_description_analyzer() # Test 2: Full Email Agent Creation creation_success = await test_email_agent_creation() print("\n" + "=" * 60) print("📊 FINAL TEST RESULTS:") print("=" * 25) print(f"🔍 Description Analyzer: {'✅ PASS' if analyzer_success else '❌ FAIL'}") print(f"📧 Email Agent Creation: {'✅ PASS' if creation_success else '❌ FAIL'}") if analyzer_success and creation_success: print("\n🎉 ALL TESTS PASSED! The system works as expected.") print("💡 Email agents will now be created with:") print(" • Auto-detected communication domain") print(" • Auto-added email components (Gmail, Outlook, SendGrid)") print(" • Auto-generated chat interface") print(" • Ready-to-use HTML file for testing") else: print("\n⚠️ SOME TESTS FAILED. Check the output above for details.") return analyzer_success and creation_success success = asyncio.run(main()) exit(0 if success else 1)