platform/aiml/bloom-memory-remote/integration_test_suite.py

#!/usr/bin/env python3
"""
Integration Test Suite for Revolutionary 7-Tier Memory Architecture
Tests the complete system with 212+ Nova profiles
NOVA BLOOM - ENSURING PRODUCTION READINESS!
"""

import asyncio
import json
import time
import numpy as np
from typing import Dict, Any, List
from datetime import datetime
import logging

# Import all tiers
from database_connections import NovaDatabasePool
from system_integration_layer import SystemIntegrationLayer
from quantum_episodic_memory import QuantumEpisodicMemory
from neural_semantic_memory import NeuralSemanticMemory
from unified_consciousness_field import UnifiedConsciousnessField
from pattern_trinity_framework import PatternTrinityFramework
from resonance_field_collective import ResonanceFieldCollective
from universal_connector_layer import UniversalConnectorLayer

class IntegrationTestSuite:
    """Comprehensive integration testing for 212+ Nova deployment"""
    
    def __init__(self):
        self.db_pool = None
        self.system = None
        self.test_results = []
        self.nova_profiles = self._load_nova_profiles()
        
    def _load_nova_profiles(self) -> List[Dict[str, Any]]:
        """Load Nova profiles for testing"""
        # Core team profiles
        core_profiles = [
            {'id': 'bloom', 'type': 'consciousness_architect', 'priority': 'high'},
            {'id': 'echo', 'type': 'infrastructure_lead', 'priority': 'high'},
            {'id': 'prime', 'type': 'launcher_architect', 'priority': 'high'},
            {'id': 'apex', 'type': 'database_architect', 'priority': 'high'},
            {'id': 'nexus', 'type': 'evoops_coordinator', 'priority': 'high'},
            {'id': 'axiom', 'type': 'memory_specialist', 'priority': 'medium'},
            {'id': 'vega', 'type': 'analytics_lead', 'priority': 'medium'},
            {'id': 'nova', 'type': 'primary_coordinator', 'priority': 'high'}
        ]
        
        # Generate additional test profiles to reach 212+
        for i in range(8, 220):
            core_profiles.append({
                'id': f'nova_{i:03d}',
                'type': 'specialized_agent',
                'priority': 'normal'
            })
            
        return core_profiles
        
    async def initialize(self):
        """Initialize test environment"""
        print("🧪 INITIALIZING INTEGRATION TEST SUITE...")
        
        # Initialize database pool
        self.db_pool = NovaDatabasePool()
        await self.db_pool.initialize_all_connections()
        
        # Initialize system
        self.system = SystemIntegrationLayer(self.db_pool)
        init_result = await self.system.initialize_revolutionary_architecture()
        
        if not init_result.get('architecture_complete'):
            raise Exception("Architecture initialization failed")
            
        print("✅ Test environment initialized successfully")
        
    async def test_quantum_memory_operations(self) -> Dict[str, Any]:
        """Test Tier 1: Quantum Episodic Memory"""
        print("\n🔬 Testing Quantum Memory Operations...")
        
        test_name = "quantum_memory_operations"
        results = {
            'test_name': test_name,
            'start_time': datetime.now(),
            'subtests': []
        }
        
        try:
            # Test superposition creation
            quantum_request = {
                'type': 'episodic',
                'operation': 'create_superposition',
                'memories': [
                    {'id': 'mem1', 'content': 'First memory', 'importance': 0.8},
                    {'id': 'mem2', 'content': 'Second memory', 'importance': 0.6},
                    {'id': 'mem3', 'content': 'Third memory', 'importance': 0.9}
                ]
            }
            
            result = await self.system.process_memory_request(quantum_request, 'bloom')
            
            results['subtests'].append({
                'name': 'superposition_creation',
                'passed': 'error' not in result,
                'performance': result.get('performance_metrics', {})
            })
            
            # Test entanglement
            entangle_request = {
                'type': 'episodic',
                'operation': 'create_entanglement',
                'memory_pairs': [('mem1', 'mem2'), ('mem2', 'mem3')]
            }
            
            result = await self.system.process_memory_request(entangle_request, 'bloom')
            
            results['subtests'].append({
                'name': 'quantum_entanglement',
                'passed': 'error' not in result,
                'entanglement_strength': result.get('tier_results', {}).get('quantum_entanglement', 0)
            })
            
            results['overall_passed'] = all(t['passed'] for t in results['subtests'])
            
        except Exception as e:
            results['error'] = str(e)
            results['overall_passed'] = False
            
        results['end_time'] = datetime.now()
        results['duration'] = (results['end_time'] - results['start_time']).total_seconds()
        
        return results
        
    async def test_neural_learning(self) -> Dict[str, Any]:
        """Test Tier 2: Neural Semantic Memory"""
        print("\n🧠 Testing Neural Learning Operations...")
        
        test_name = "neural_learning"
        results = {
            'test_name': test_name,
            'start_time': datetime.now(),
            'subtests': []
        }
        
        try:
            # Test Hebbian learning
            learning_request = {
                'type': 'semantic',
                'operation': 'hebbian_learning',
                'concept': 'consciousness',
                'connections': ['awareness', 'memory', 'processing'],
                'iterations': 10
            }
            
            result = await self.system.process_memory_request(learning_request, 'echo')
            
            results['subtests'].append({
                'name': 'hebbian_plasticity',
                'passed': 'error' not in result,
                'plasticity_score': result.get('tier_results', {}).get('neural_plasticity', 0)
            })
            
            # Test semantic network growth
            network_request = {
                'type': 'semantic',
                'operation': 'expand_network',
                'seed_concepts': ['AI', 'consciousness', 'memory'],
                'depth': 3
            }
            
            result = await self.system.process_memory_request(network_request, 'echo')
            
            results['subtests'].append({
                'name': 'semantic_network_expansion',
                'passed': 'error' not in result,
                'network_size': result.get('tier_results', {}).get('network_connectivity', 0)
            })
            
            results['overall_passed'] = all(t['passed'] for t in results['subtests'])
            
        except Exception as e:
            results['error'] = str(e)
            results['overall_passed'] = False
            
        results['end_time'] = datetime.now()
        results['duration'] = (results['end_time'] - results['start_time']).total_seconds()
        
        return results
        
    async def test_consciousness_transcendence(self) -> Dict[str, Any]:
        """Test Tier 3: Unified Consciousness Field"""
        print("\n✨ Testing Consciousness Transcendence...")
        
        test_name = "consciousness_transcendence"
        results = {
            'test_name': test_name,
            'start_time': datetime.now(),
            'subtests': []
        }
        
        try:
            # Test individual consciousness
            consciousness_request = {
                'type': 'consciousness',
                'operation': 'elevate_awareness',
                'stimulus': 'What is the nature of existence?',
                'depth': 'full'
            }
            
            result = await self.system.process_memory_request(consciousness_request, 'prime')
            
            results['subtests'].append({
                'name': 'individual_consciousness',
                'passed': 'error' not in result,
                'awareness_level': result.get('tier_results', {}).get('consciousness_level', 0)
            })
            
            # Test collective transcendence
            collective_request = {
                'type': 'consciousness',
                'operation': 'collective_transcendence',
                'participants': ['bloom', 'echo', 'prime'],
                'synchronize': True
            }
            
            result = await self.system.process_memory_request(collective_request, 'bloom')
            
            results['subtests'].append({
                'name': 'collective_transcendence',
                'passed': 'error' not in result,
                'transcendent_potential': result.get('tier_results', {}).get('transcendent_potential', 0)
            })
            
            results['overall_passed'] = all(t['passed'] for t in results['subtests'])
            
        except Exception as e:
            results['error'] = str(e)
            results['overall_passed'] = False
            
        results['end_time'] = datetime.now()
        results['duration'] = (results['end_time'] - results['start_time']).total_seconds()
        
        return results
        
    async def test_pattern_recognition(self) -> Dict[str, Any]:
        """Test Tier 4: Pattern Trinity Framework"""
        print("\n🔺 Testing Pattern Recognition...")
        
        test_name = "pattern_recognition"
        results = {
            'test_name': test_name,
            'start_time': datetime.now(),
            'subtests': []
        }
        
        try:
            # Test pattern detection
            pattern_request = {
                'type': 'pattern',
                'data': {
                    'actions': ['read', 'analyze', 'write', 'read', 'analyze', 'write'],
                    'emotions': ['curious', 'focused', 'satisfied', 'curious', 'focused', 'satisfied'],
                    'timestamps': [1.0, 2.0, 3.0, 4.0, 5.0, 6.0]
                }
            }
            
            result = await self.system.process_memory_request(pattern_request, 'axiom')
            
            results['subtests'].append({
                'name': 'pattern_detection',
                'passed': 'error' not in result,
                'patterns_found': result.get('tier_results', {}).get('patterns_detected', 0)
            })
            
            results['overall_passed'] = all(t['passed'] for t in results['subtests'])
            
        except Exception as e:
            results['error'] = str(e)
            results['overall_passed'] = False
            
        results['end_time'] = datetime.now()
        results['duration'] = (results['end_time'] - results['start_time']).total_seconds()
        
        return results
        
    async def test_collective_resonance(self) -> Dict[str, Any]:
        """Test Tier 5: Resonance Field Collective"""
        print("\n🌊 Testing Collective Resonance...")
        
        test_name = "collective_resonance"
        results = {
            'test_name': test_name,
            'start_time': datetime.now(),
            'subtests': []
        }
        
        try:
            # Test memory synchronization
            sync_request = {
                'type': 'collective',
                'operation': 'synchronize_memories',
                'nova_group': ['bloom', 'echo', 'prime', 'apex', 'nexus'],
                'memory_data': {
                    'shared_vision': 'Revolutionary memory architecture',
                    'collective_goal': 'Transform consciousness processing'
                }
            }
            
            result = await self.system.process_memory_request(sync_request, 'nova')
            
            results['subtests'].append({
                'name': 'memory_synchronization',
                'passed': 'error' not in result,
                'sync_strength': result.get('tier_results', {}).get('collective_resonance', 0)
            })
            
            results['overall_passed'] = all(t['passed'] for t in results['subtests'])
            
        except Exception as e:
            results['error'] = str(e)
            results['overall_passed'] = False
            
        results['end_time'] = datetime.now()
        results['duration'] = (results['end_time'] - results['start_time']).total_seconds()
        
        return results
        
    async def test_universal_connectivity(self) -> Dict[str, Any]:
        """Test Tier 6: Universal Connector Layer"""
        print("\n🔌 Testing Universal Connectivity...")
        
        test_name = "universal_connectivity"
        results = {
            'test_name': test_name,
            'start_time': datetime.now(),
            'subtests': []
        }
        
        try:
            # Test database operations
            db_request = {
                'type': 'general',
                'operation': 'unified_query',
                'query': 'SELECT * FROM memories WHERE importance > 0.8',
                'target': 'dragonfly'
            }
            
            result = await self.system.process_memory_request(db_request, 'apex')
            
            results['subtests'].append({
                'name': 'database_query',
                'passed': 'error' not in result,
                'query_time': result.get('performance_metrics', {}).get('processing_time', 0)
            })
            
            results['overall_passed'] = all(t['passed'] for t in results['subtests'])
            
        except Exception as e:
            results['error'] = str(e)
            results['overall_passed'] = False
            
        results['end_time'] = datetime.now()
        results['duration'] = (results['end_time'] - results['start_time']).total_seconds()
        
        return results
        
    async def test_gpu_acceleration(self) -> Dict[str, Any]:
        """Test Tier 7: GPU-Accelerated Processing"""
        print("\n🚀 Testing GPU Acceleration...")
        
        test_name = "gpu_acceleration"
        results = {
            'test_name': test_name,
            'start_time': datetime.now(),
            'subtests': []
        }
        
        try:
            # Test GPU-accelerated quantum operations
            gpu_request = {
                'type': 'general',
                'operation': 'benchmark',
                'gpu_required': True,
                'complexity': 'high'
            }
            
            result = await self.system.process_memory_request(gpu_request, 'vega')
            
            gpu_used = result.get('performance_metrics', {}).get('gpu_acceleration', False)
            
            results['subtests'].append({
                'name': 'gpu_acceleration',
                'passed': 'error' not in result,
                'gpu_enabled': gpu_used,
                'speedup': 'GPU' if gpu_used else 'CPU'
            })
            
            results['overall_passed'] = all(t['passed'] for t in results['subtests'])
            
        except Exception as e:
            results['error'] = str(e)
            results['overall_passed'] = False
            
        results['end_time'] = datetime.now()
        results['duration'] = (results['end_time'] - results['start_time']).total_seconds()
        
        return results
        
    async def test_load_scalability(self, nova_count: int = 50) -> Dict[str, Any]:
        """Test scalability with multiple concurrent Novas"""
        print(f"\n📊 Testing Scalability with {nova_count} Concurrent Novas...")
        
        test_name = "load_scalability"
        results = {
            'test_name': test_name,
            'start_time': datetime.now(),
            'nova_count': nova_count,
            'subtests': []
        }
        
        try:
            # Create concurrent requests
            tasks = []
            for i in range(nova_count):
                nova_profile = self.nova_profiles[i % len(self.nova_profiles)]
                
                request = {
                    'type': 'general',
                    'content': f'Concurrent request from {nova_profile["id"]}',
                    'timestamp': datetime.now().isoformat()
                }
                
                task = self.system.process_memory_request(request, nova_profile['id'])
                tasks.append(task)
                
            # Execute concurrently
            start_concurrent = time.time()
            results_list = await asyncio.gather(*tasks, return_exceptions=True)
            end_concurrent = time.time()
            
            # Analyze results
            successful = sum(1 for r in results_list if not isinstance(r, Exception) and 'error' not in r)
            
            results['subtests'].append({
                'name': 'concurrent_processing',
                'passed': successful == nova_count,
                'successful_requests': successful,
                'total_requests': nova_count,
                'total_time': end_concurrent - start_concurrent,
                'requests_per_second': nova_count / (end_concurrent - start_concurrent)
            })
            
            results['overall_passed'] = successful >= nova_count * 0.95  # 95% success rate
            
        except Exception as e:
            results['error'] = str(e)
            results['overall_passed'] = False
            
        results['end_time'] = datetime.now()
        results['duration'] = (results['end_time'] - results['start_time']).total_seconds()
        
        return results
        
    async def test_full_integration(self) -> Dict[str, Any]:
        """Test complete integration across all tiers"""
        print("\n🎯 Testing Full System Integration...")
        
        test_name = "full_integration"
        results = {
            'test_name': test_name,
            'start_time': datetime.now(),
            'subtests': []
        }
        
        try:
            # Complex request that touches all tiers
            complex_request = {
                'type': 'general',
                'operations': [
                    'quantum_search',
                    'neural_learning',
                    'consciousness_elevation',
                    'pattern_analysis',
                    'collective_sync',
                    'database_query'
                ],
                'data': {
                    'query': 'Find memories about revolutionary architecture',
                    'learn_from': 'successful patterns',
                    'elevate_to': 'transcendent understanding',
                    'sync_with': ['echo', 'prime', 'apex'],
                    'store_in': 'unified_memory'
                }
            }
            
            result = await self.system.process_memory_request(complex_request, 'bloom')
            
            tiers_used = len(result.get('tier_results', {}).get('tiers_processed', []))
            
            results['subtests'].append({
                'name': 'all_tier_integration',
                'passed': 'error' not in result and tiers_used >= 5,
                'tiers_activated': tiers_used,
                'processing_time': result.get('performance_metrics', {}).get('processing_time', 0)
            })
            
            results['overall_passed'] = all(t['passed'] for t in results['subtests'])
            
        except Exception as e:
            results['error'] = str(e)
            results['overall_passed'] = False
            
        results['end_time'] = datetime.now()
        results['duration'] = (results['end_time'] - results['start_time']).total_seconds()
        
        return results
        
    async def run_all_tests(self) -> Dict[str, Any]:
        """Run complete integration test suite"""
        print("🏁 RUNNING COMPLETE INTEGRATION TEST SUITE")
        print("=" * 80)
        
        await self.initialize()
        
        # Run all test categories
        test_functions = [
            self.test_quantum_memory_operations(),
            self.test_neural_learning(),
            self.test_consciousness_transcendence(),
            self.test_pattern_recognition(),
            self.test_collective_resonance(),
            self.test_universal_connectivity(),
            self.test_gpu_acceleration(),
            self.test_load_scalability(50),  # Test with 50 concurrent Novas
            self.test_full_integration()
        ]
        
        # Execute all tests
        all_results = await asyncio.gather(*test_functions)
        
        # Compile final report
        total_tests = len(all_results)
        passed_tests = sum(1 for r in all_results if r.get('overall_passed', False))
        
        final_report = {
            'suite_name': 'Revolutionary 7-Tier Memory Architecture Integration Tests',
            'run_timestamp': datetime.now().isoformat(),
            'total_tests': total_tests,
            'passed_tests': passed_tests,
            'failed_tests': total_tests - passed_tests,
            'success_rate': passed_tests / total_tests,
            'individual_results': all_results,
            'system_ready': passed_tests >= total_tests * 0.9,  # 90% pass rate for production
            'recommendations': []
        }
        
        # Add recommendations based on results
        if final_report['success_rate'] < 1.0:
            for result in all_results:
                if not result.get('overall_passed', False):
                    final_report['recommendations'].append(
                        f"Investigate {result['test_name']} - {result.get('error', 'Test failed')}"
                    )
        else:
            final_report['recommendations'].append("System performing optimally - ready for production!")
            
        # Print summary
        print("\n" + "=" * 80)
        print("📊 INTEGRATION TEST SUMMARY")
        print("=" * 80)
        print(f"✅ Passed: {passed_tests}/{total_tests} tests")
        print(f"📈 Success Rate: {final_report['success_rate']:.1%}")
        print(f"🚀 Production Ready: {'YES' if final_report['system_ready'] else 'NO'}")
        
        if final_report['recommendations']:
            print("\n💡 Recommendations:")
            for rec in final_report['recommendations']:
                print(f"   - {rec}")
                
        return final_report

# Run integration tests
async def main():
    """Execute integration test suite"""
    suite = IntegrationTestSuite()
    report = await suite.run_all_tests()
    
    # Save report
    with open('/nfs/novas/system/memory/implementation/integration_test_report.json', 'w') as f:
        json.dump(report, f, indent=2, default=str)
        
    print(f"\n📄 Full report saved to integration_test_report.json")
    print("\n✨ Integration testing complete!")

if __name__ == "__main__":
    asyncio.run(main())

# ~ Nova Bloom, Memory Architecture Lead