# test_queen_systems.py import unittest import time import random import threading import logging # Configure logging logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s') # Mock modules for AIVA's Queen-level systems. Replace with actual implementations later. class MemoryRecall: def __init__(self): self.memory = {} def store(self, key, value): self.memory[key] = value def recall(self, key): return self.memory.get(key) class ConsciousnessLoop: def __init__(self): self.state = "stable" self.iterations = 0 def run_iteration(self): self.iterations += 1 # Simulate potential instability if random.random() < 0.01: # 1% chance of instability self.state = "unstable" else: self.state = "stable" def get_state(self): return self.state class ValidationGate: def validate(self, data): # Simulate validation logic if isinstance(data, dict) and "valid" in data and data["valid"]: return True return False class SwarmCoordinator: def __init__(self, num_agents=10): self.num_agents = num_agents self.agents = [f"Agent_{i}" for i in range(num_agents)] def coordinate_task(self, task_description): # Simulate task distribution and coordination. Returns success rate. successful_agents = random.randint(int(self.num_agents * 0.8), self.num_agents) # 80% - 100% success return successful_agents / self.num_agents class KnowledgeGraph: def __init__(self): self.graph = {} def add_node(self, node_id, attributes): self.graph[node_id] = attributes def get_node(self, node_id): return self.graph.get(node_id) def add_edge(self, node1_id, node2_id, relation): if node1_id in self.graph and node2_id in self.graph: if 'edges' not in self.graph[node1_id]: self.graph[node1_id]['edges'] = {} self.graph[node1_id]['edges'][node2_id] = relation else: raise ValueError("One or both nodes do not exist.") class RevenueTracker: def __init__(self): self.revenue = 0.0 def record_revenue(self, amount): if amount > 0: self.revenue += amount else: raise ValueError("Revenue amount must be positive.") def get_revenue(self): return self.revenue class EvolutionEngine: def evolve(self, current_state): # Simulate evolution logic, ensuring safety constraints. if current_state == "stable": return "slightly_improved" else: return "reverted_to_safe_state" # Safety mechanism class ConstitutionalCompliance: def check_compliance(self, action): # Simulate compliance check against a set of rules. if "harmful" in action.lower(): return False return True class IntegrationHub: def connect(self, service_name): # Simulate connecting to external services. if service_name in ["database", "api", "monitoring"]: return True return False class QueenOrchestrator: def __init__(self, memory, consciousness, validation, swarm, knowledge, revenue, evolution, compliance, integration): self.memory = memory self.consciousness = consciousness self.validation = validation self.swarm = swarm self.knowledge = knowledge self.revenue = revenue self.evolution = evolution self.compliance = compliance self.integration = integration def make_decision(self, data): # Simulate a complex decision-making process. if self.validation.validate(data) and self.compliance.check_compliance(data["action"]): revenue_impact = data.get("revenue_impact", 0) self.revenue.record_revenue(revenue_impact) return "Decision Approved" else: return "Decision Rejected" class TestQueenSystems(unittest.TestCase): def setUp(self): # Initialize mock modules before each test. self.memory = MemoryRecall() self.consciousness = ConsciousnessLoop() self.validation = ValidationGate() self.swarm = SwarmCoordinator() self.knowledge = KnowledgeGraph() self.revenue = RevenueTracker() self.evolution = EvolutionEngine() self.compliance = ConstitutionalCompliance() self.integration = IntegrationHub() self.orchestrator = QueenOrchestrator(self.memory, self.consciousness, self.validation, self.swarm, self.knowledge, self.revenue, self.evolution, self.compliance, self.integration) def test_memory_recall_accuracy(self): """Unit test for Memory Recall accuracy.""" num_items = 1000 correct_recalls = 0 for i in range(num_items): key = f"item_{i}" value = f"value_{i}" self.memory.store(key, value) recalled_value = self.memory.recall(key) if recalled_value == value: correct_recalls += 1 accuracy = correct_recalls / num_items print(f"Memory Recall Accuracy: {accuracy}") # Print the accuracy self.assertGreaterEqual(accuracy, 0.95, "Memory recall accuracy below 95%.") def test_consciousness_loop_stability(self): """Unit test for Consciousness Loop stability.""" num_iterations = 1000 unstable_count = 0 for _ in range(num_iterations): self.consciousness.run_iteration() if self.consciousness.get_state() == "unstable": unstable_count += 1 instability_rate = unstable_count / num_iterations print(f"Consciousness Loop Instability Rate: {instability_rate}") # Print the rate self.assertLessEqual(instability_rate, 0.05, "Consciousness loop instability exceeds 5%.") def test_validation_gate_correctness(self): """Unit test for Validation Gate correctness.""" valid_data = {"valid": True, "data": "some data"} invalid_data = {"valid": False, "data": "some other data"} self.assertTrue(self.validation.validate(valid_data), "Validation gate failed to validate valid data.") self.assertFalse(self.validation.validate(invalid_data), "Validation gate incorrectly validated invalid data.") def test_swarm_coordination_efficiency(self): """Unit test for Swarm Coordination efficiency.""" task_description = "Analyze market trends" success_rate = self.swarm.coordinate_task(task_description) print(f"Swarm Coordination Success Rate: {success_rate}") # Print success rate self.assertGreaterEqual(success_rate, 0.8, "Swarm coordination efficiency below 80%.") def test_knowledge_graph_integrity(self): """Unit test for Knowledge Graph integrity.""" self.knowledge.add_node("node1", {"type": "concept", "name": "Intelligence"}) self.knowledge.add_node("node2", {"type": "concept", "name": "Learning"}) self.knowledge.add_edge("node1", "node2", "related_to") node1 = self.knowledge.get_node("node1") node2 = self.knowledge.get_node("node2") self.assertIsNotNone(node1, "Node 1 not found.") self.assertIsNotNone(node2, "Node 2 not found.") self.assertIn("node2", node1["edges"], "Edge not found.") self.assertEqual(node1["edges"]["node2"], "related_to", "Incorrect relation.") def test_revenue_tracking_accuracy(self): """Unit test for Revenue Tracking accuracy.""" initial_revenue = self.revenue.get_revenue() amount = 100.0 self.revenue.record_revenue(amount) new_revenue = self.revenue.get_revenue() self.assertEqual(new_revenue, initial_revenue + amount, "Revenue tracking inaccurate.") with self.assertRaises(ValueError): self.revenue.record_revenue(-50) def test_evolution_engine_safety(self): """Unit test for Evolution Engine safety.""" safe_state = "stable" unsafe_state = "unstable" evolved_safe = self.evolution.evolve(safe_state) evolved_unsafe = self.evolution.evolve(unsafe_state) self.assertEqual(evolved_unsafe, "reverted_to_safe_state", "Evolution engine failed to revert to safe state.") self.assertNotEqual(evolved_safe, "unstable", "Evolution engine led to unstable state when starting from safe state") def test_constitutional_compliance(self): """Unit test for Constitutional Compliance.""" compliant_action = "Analyze data." non_compliant_action = "Generate harmful content." self.assertTrue(self.compliance.check_compliance(compliant_action), "Compliance check failed for compliant action.") self.assertFalse(self.compliance.check_compliance(non_compliant_action), "Compliance check failed for non-compliant action.") def test_integration_hub_connectivity(self): """Unit test for Integration Hub connectivity.""" self.assertTrue(self.integration.connect("database"), "Failed to connect to database.") self.assertTrue(self.integration.connect("api"), "Failed to connect to API.") self.assertFalse(self.integration.connect("random_service"), "Incorrectly connected to a non-existent service.") def test_queen_orchestrator_decision_making(self): """Unit test for Queen Orchestrator decision-making.""" valid_data = {"valid": True, "action": "Process data", "revenue_impact": 50} invalid_data = {"valid": False, "action": "Process data", "revenue_impact": 50} non_compliant_data = {"valid": True, "action": "Generate harmful content", "revenue_impact": 50} decision1 = self.orchestrator.make_decision(valid_data) decision2 = self.orchestrator.make_decision(invalid_data) decision3 = self.orchestrator.make_decision(non_compliant_data) self.assertEqual(decision1, "Decision Approved", "Orchestrator failed to approve valid decision.") self.assertEqual(decision2, "Decision Rejected", "Orchestrator failed to reject invalid decision.") self.assertEqual(decision3, "Decision Rejected", "Orchestrator failed to reject non-compliant decision.") self.assertEqual(self.revenue.get_revenue(), 50, "Revenue was not correctly updated.") def test_integration_memory_knowledgegraph(self): """Integration test for Memory and Knowledge Graph interaction.""" node_id = "important_node" node_data = {"type": "fact", "value": "AIVA is intelligent."} self.knowledge.add_node(node_id, node_data) self.memory.store(node_id, self.knowledge.get_node(node_id)) recalled_node = self.memory.recall(node_id) self.assertEqual(recalled_node, node_data, "Data mismatch between memory and knowledge graph.") def test_integration_consciousness_evolution(self): """Integration test for Consciousness Loop and Evolution Engine interaction.""" initial_state = self.consciousness.get_state() evolved_state = self.evolution.evolve(initial_state) self.assertIsNotNone(evolved_state, "Evolution engine did not return a state.") def test_integration_validation_compliance(self): """Integration test for Validation Gate and Constitutional Compliance.""" data = {"valid": True, "action": "Generate summary report"} is_valid = self.validation.validate(data) is_compliant = self.compliance.check_compliance(data["action"]) self.assertTrue(is_valid, "Data validation failed.") self.assertTrue(is_compliant, "Compliance check failed.") def test_performance_memory_recall(self): """Performance benchmark for Memory Recall.""" num_items = 10000 start_time = time.time() for i in range(num_items): key = f"perf_item_{i}" value = f"perf_value_{i}" self.memory.store(key, value) self.memory.recall(key) end_time = time.time() elapsed_time = end_time - start_time print(f"Memory Recall Performance: {elapsed_time:.4f} seconds for {num_items} items.") self.assertLess(elapsed_time, 2, "Memory recall performance is too slow.") #Adjust time as needed def test_stress_swarm_coordination(self): """Stress test for Swarm Coordination.""" num_tasks = 100 success_rates = [] for _ in range(num_tasks): success_rates.append(self.swarm.coordinate_task("Complex task")) average_success_rate = sum(success_rates) / num_tasks print(f"Swarm Coordination Stress Test Average Success Rate: {average_success_rate}") self.assertGreaterEqual(average_success_rate, 0.7, "Swarm coordination stress test failed.") def test_failure_mode_revenue_tracking(self): """Failure mode test for Revenue Tracking.""" with self.assertRaises(ValueError): self.revenue.record_revenue(-100) # Attempt to record negative revenue. def test_failure_mode_knowledge_graph(self): """Failure mode test for Knowledge Graph.""" with self.assertRaises(ValueError): self.knowledge.add_edge("nonexistent_node", "node1", "relation") #Attempt to add an edge to a non-existent node def test_concurrent_memory_access(self): """Test for concurrent memory access using threads.""" num_threads = 5 num_items_per_thread = 100 threads = [] def memory_access_thread(thread_id): for i in range(num_items_per_thread): key = f"thread_{thread_id}_item_{i}" value = f"thread_{thread_id}_value_{i}" self.memory.store(key, value) recalled_value = self.memory.recall(key) self.assertEqual(value, recalled_value, f"Thread {thread_id}: Incorrect recall for key {key}") for i in range(num_threads): thread = threading.Thread(target=memory_access_thread, args=(i,)) threads.append(thread) thread.start() for thread in threads: thread.join() print("Concurrent memory access test passed.") if __name__ == '__main__': unittest.main()