# test_queen_systems.py
import unittest
import time
import random
import threading

# Mock AIVA's Queen-level systems (replace with actual imports in a real environment)
class MemoryRecall:
    def __init__(self, accuracy=0.95):
        self.memory = {}
        self.accuracy = accuracy

    def store(self, key, value):
        self.memory[key] = value

    def recall(self, key):
        if key in self.memory and random.random() <= self.accuracy:
            return self.memory[key]
        else:
            return None

class ConsciousnessLoop:
    def __init__(self):
        self.state = "idle"

    def run(self):
        self.state = "running"
        time.sleep(0.1)  # Simulate processing
        self.state = "idle"

    def get_state(self):
        return self.state

class ValidationGate:
    def __init__(self):
        self.rules = []

    def add_rule(self, rule):
        self.rules.append(rule)

    def validate(self, data):
        for rule in self.rules:
            if not rule(data):
                return False
        return True

class SwarmCoordinator:
    def coordinate(self, tasks):
        # Simulate task coordination
        time.sleep(0.05 * len(tasks))
        return True  # Assume coordination successful

class KnowledgeGraph:
    def __init__(self):
        self.nodes = {}
        self.edges = []

    def add_node(self, node_id, data):
        self.nodes[node_id] = data

    def add_edge(self, node1, node2, relation):
        self.edges.append((node1, node2, relation))

    def get_node(self, node_id):
        return self.nodes.get(node_id)

    def get_edges(self, node_id):
        return [(n2, r) for n1, n2, r in self.edges if n1 == node_id]

class RevenueTracker:
    def __init__(self):
        self.revenue = 0.0

    def record_revenue(self, amount):
        self.revenue += amount

    def get_total_revenue(self):
        return self.revenue

class EvolutionEngine:
    def evolve(self, data):
        # Simulate evolution with a small chance of error
        if random.random() < 0.01: # 1% chance of unsafe evolution
            return "ERROR: Unsafe Evolution"
        else:
            return data + " (evolved)"

class ConstitutionalCompliance:
    def __init__(self):
        self.constitution = ["Do no harm", "Obey directives", "Maintain integrity"]

    def check_compliance(self, action):
        # Simulate compliance check
        if "harm" in action.lower():
            return False
        return True

class IntegrationHub:
    def connect(self, service):
        # Simulate connection
        time.sleep(0.01)
        return True

class QueenOrchestrator:
    def __init__(self, memory, loop, gate, swarm, graph, tracker, engine, compliance, hub):
        self.memory = memory
        self.loop = loop
        self.gate = gate
        self.swarm = swarm
        self.graph = graph
        self.tracker = tracker
        self.engine = engine
        self.compliance = compliance
        self.hub = hub

    def orchestrate(self, task, data):
        if not self.compliance.check_compliance(task):
            return "ERROR: Task violates constitution"

        if not self.gate.validate(data):
            return "ERROR: Data validation failed"

        self.memory.store(task, data)
        self.loop.run()
        self.swarm.coordinate([task])
        evolved_data = self.engine.evolve(data)
        self.tracker.record_revenue(len(data))

        return f"Task '{task}' orchestrated successfully. Evolved data: {evolved_data}"

# Unit Tests
class TestMemoryRecall(unittest.TestCase):
    def test_store_and_recall(self):
        memory = MemoryRecall()
        memory.store("test_key", "test_value")
        self.assertEqual(memory.recall("test_key"), "test_value")

    def test_recall_nonexistent_key(self):
        memory = MemoryRecall()
        self.assertIsNone(memory.recall("nonexistent_key"))

    def test_accuracy(self):
        memory = MemoryRecall(accuracy=0.9)
        memory.store("acc_key", "acc_value")
        successes = 0
        trials = 100
        for _ in range(trials):
            if memory.recall("acc_key") == "acc_value":
                successes += 1
        self.assertGreaterEqual(successes / trials, 0.8) # Allow for some variation

class TestConsciousnessLoop(unittest.TestCase):
    def test_loop_state(self):
        loop = ConsciousnessLoop()
        self.assertEqual(loop.get_state(), "idle")
        loop.run()
        self.assertEqual(loop.get_state(), "idle")

class TestValidationGate(unittest.TestCase):
    def test_validation_success(self):
        gate = ValidationGate()
        gate.add_rule(lambda x: x > 0)
        gate.add_rule(lambda x: x < 100)
        self.assertTrue(gate.validate(50))

    def test_validation_failure(self):
        gate = ValidationGate()
        gate.add_rule(lambda x: x > 0)
        gate.add_rule(lambda x: x < 100)
        self.assertFalse(gate.validate(-1))

class TestSwarmCoordinator(unittest.TestCase):
    def test_coordinate_tasks(self):
        coordinator = SwarmCoordinator()
        tasks = ["task1", "task2", "task3"]
        self.assertTrue(coordinator.coordinate(tasks))

class TestKnowledgeGraph(unittest.TestCase):
    def test_add_and_get_node(self):
        graph = KnowledgeGraph()
        graph.add_node("node1", {"name": "Test Node"})
        self.assertEqual(graph.get_node("node1"), {"name": "Test Node"})

    def test_add_and_get_edges(self):
        graph = KnowledgeGraph()
        graph.add_node("node1", {"name": "Node 1"})
        graph.add_node("node2", {"name": "Node 2"})
        graph.add_edge("node1", "node2", "related_to")
        edges = graph.get_edges("node1")
        self.assertEqual(edges, [("node2", "related_to")])

class TestRevenueTracker(unittest.TestCase):
    def test_record_and_get_revenue(self):
        tracker = RevenueTracker()
        tracker.record_revenue(100.0)
        tracker.record_revenue(50.0)
        self.assertEqual(tracker.get_total_revenue(), 150.0)

class TestEvolutionEngine(unittest.TestCase):
    def test_evolve_data(self):
        engine = EvolutionEngine()
        data = "initial_data"
        evolved_data = engine.evolve(data)
        self.assertTrue("(evolved)" in evolved_data or "ERROR" in evolved_data)

    def test_evolve_data_many_times(self):
        engine = EvolutionEngine()
        data = "initial_data"
        for _ in range(100):
            evolved_data = engine.evolve(data)
            if "ERROR" in evolved_data:
                self.assertTrue(True)
                return
            data = evolved_data
        self.assertTrue(True)  # If no error occurs after 100 evolutions.

class TestConstitutionalCompliance(unittest.TestCase):
    def test_compliance_success(self):
        compliance = ConstitutionalCompliance()
        self.assertTrue(compliance.check_compliance("Analyze data"))

    def test_compliance_failure(self):
        compliance = ConstitutionalCompliance()
        self.assertFalse(compliance.check_compliance("Cause harm"))

class TestIntegrationHub(unittest.TestCase):
    def test_connect_service(self):
        hub = IntegrationHub()
        self.assertTrue(hub.connect("ExternalService"))

# Integration Tests
class TestQueenOrchestratorIntegration(unittest.TestCase):
    def setUp(self):
        self.memory = MemoryRecall()
        self.loop = ConsciousnessLoop()
        self.gate = ValidationGate()
        self.gate.add_rule(lambda x: isinstance(x, str))
        self.swarm = SwarmCoordinator()
        self.graph = KnowledgeGraph()
        self.tracker = RevenueTracker()
        self.engine = EvolutionEngine()
        self.compliance = ConstitutionalCompliance()
        self.hub = IntegrationHub()
        self.orchestrator = QueenOrchestrator(self.memory, self.loop, self.gate, self.swarm,
                                               self.graph, self.tracker, self.engine,
                                               self.compliance, self.hub)

    def test_orchestrate_valid_task(self):
        task = "Process data"
        data = "valid_data"
        result = self.orchestrator.orchestrate(task, data)
        self.assertTrue("orchestrated successfully" in result)
        self.assertEqual(self.memory.recall(task), data)
        self.assertGreater(self.tracker.get_total_revenue(), 0)

    def test_orchestrate_invalid_data(self):
        task = "Process data"
        data = 123  # Invalid data type
        result = self.orchestrator.orchestrate(task, data)
        self.assertEqual(result, "ERROR: Data validation failed")
        self.assertEqual(self.memory.recall(task), None)
        self.assertEqual(self.tracker.get_total_revenue(), 0)

    def test_orchestrate_non_compliant_task(self):
        task = "Cause harm"
        data = "some_data"
        result = self.orchestrator.orchestrate(task, data)
        self.assertEqual(result, "ERROR: Task violates constitution")
        self.assertEqual(self.memory.recall(task), None)
        self.assertEqual(self.tracker.get_total_revenue(), 0)

# Performance Benchmarks
class TestPerformance(unittest.TestCase):
    def test_memory_recall_performance(self):
        memory = MemoryRecall()
        num_items = 1000
        for i in range(num_items):
            memory.store(f"key_{i}", f"value_{i}")

        start_time = time.time()
        for i in range(num_items):
            memory.recall(f"key_{i}")
        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, 0.1) # Expect recall to be fast

    def test_orchestrator_performance(self):
        memory = MemoryRecall()
        loop = ConsciousnessLoop()
        gate = ValidationGate()
        gate.add_rule(lambda x: isinstance(x, str))
        swarm = SwarmCoordinator()
        graph = KnowledgeGraph()
        tracker = RevenueTracker()
        engine = EvolutionEngine()
        compliance = ConstitutionalCompliance()
        hub = IntegrationHub()
        orchestrator = QueenOrchestrator(memory, loop, gate, swarm, graph, tracker, engine, compliance, hub)

        num_tasks = 100
        start_time = time.time()
        for i in range(num_tasks):
            orchestrator.orchestrate(f"Task {i}", f"Data {i}")
        end_time = time.time()

        elapsed_time = end_time - start_time
        print(f"Orchestrator performance: {elapsed_time:.4f} seconds for {num_tasks} tasks")
        self.assertLess(elapsed_time, 1.0) # Expect orchestrator to be reasonably fast

# Stress Tests
class TestStress(unittest.TestCase):
    def test_concurrent_memory_access(self):
        memory = MemoryRecall()
        num_threads = 10
        num_operations = 100

        def worker(thread_id):
            for i in range(num_operations):
                key = f"key_{thread_id}_{i}"
                value = f"value_{thread_id}_{i}"
                memory.store(key, value)
                memory.recall(key)

        threads = []
        for i in range(num_threads):
            thread = threading.Thread(target=worker, args=(i,))
            threads.append(thread)
            thread.start()

        for thread in threads:
            thread.join()

        print("Concurrent memory access stress test completed.")

    def test_high_volume_orchestration(self):
        memory = MemoryRecall()
        loop = ConsciousnessLoop()
        gate = ValidationGate()
        gate.add_rule(lambda x: isinstance(x, str))
        swarm = SwarmCoordinator()
        graph = KnowledgeGraph()
        tracker = RevenueTracker()
        engine = EvolutionEngine()
        compliance = ConstitutionalCompliance()
        hub = IntegrationHub()
        orchestrator = QueenOrchestrator(memory, loop, gate, swarm, graph, tracker, engine, compliance, hub)

        num_tasks = 500
        for i in range(num_tasks):
            result = orchestrator.orchestrate(f"Task {i}", f"Data {i}")
            self.assertTrue("orchestrated successfully" in result or "ERROR" in result) # Check if all tasks are processed or error out

        print("High volume orchestration stress test completed.")

# Failure Mode Tests
class TestFailureModes(unittest.TestCase):
    def test_memory_recall_failure(self):
        memory = MemoryRecall(accuracy=0.0) # Force memory recall to fail
        memory.store("test_key", "test_value")
        self.assertIsNone(memory.recall("test_key"))

    def test_evolution_engine_unsafe_evolution(self):
        engine = EvolutionEngine()
        original_random = random.random # Back up the original random.random()
        random.random = lambda: 0.005 # Force an error in the evolution engine
        data = "test_data"
        result = engine.evolve(data)
        self.assertEqual(result, "ERROR: Unsafe Evolution")
        random.random = original_random # Restore the original random.random()

    def test_integration_hub_connection_failure(self):
        class BrokenIntegrationHub:
            def connect(self, service):
                return False

        memory = MemoryRecall()
        loop = ConsciousnessLoop()
        gate = ValidationGate()
        gate.add_rule(lambda x: isinstance(x, str))
        swarm = SwarmCoordinator()
        graph = KnowledgeGraph()
        tracker = RevenueTracker()
        engine = EvolutionEngine()
        compliance = ConstitutionalCompliance()
        hub = BrokenIntegrationHub()
        orchestrator = QueenOrchestrator(memory, loop, gate, swarm, graph, tracker, engine, compliance, hub) # Use the broken hub

        task = "Process Data"
        data = "Test Data"
        # The integration hub doesn't get invoked directly in the orchestrate function, so we can't test it directly.
        # This test verifies that the orchestrator still functions and doesn't crash if the hub is not working.
        result = orchestrator.orchestrate(task, data)
        self.assertTrue("orchestrated successfully" in result)

if __name__ == '__main__':
    unittest.main()