# test_queen_systems.py

import unittest
import time
import random
import threading
from unittest.mock import patch, MagicMock

# Mock AIVA's Queen-level systems (replace with actual imports 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 = "idle"

    def process(self, input_data):
        self.state = "processing"
        # Simulate some processing
        time.sleep(0.1)
        self.state = "idle"
        return f"Processed: {input_data}"

class ValidationGate:
    def validate(self, data):
        if data is None or not isinstance(data, str) or len(data) < 5:
            return False
        return True

class SwarmCoordinator:
    def coordinate(self, task, num_agents):
        # Simulate agent coordination
        time.sleep(0.05 * num_agents)
        return f"Task '{task}' completed by {num_agents} agents."

class KnowledgeGraph:
    def __init__(self):
        self.graph = {}

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

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

class RevenueTracker:
    def __init__(self):
        self.revenue = 0

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

    def get_total_revenue(self):
        return self.revenue

class EvolutionEngine:
    def evolve(self, current_state, mutation_rate):
        if random.random() < mutation_rate:
            return f"Evolved from {current_state} to {current_state + '_mutated'}"
        return current_state

class ConstitutionalCompliance:
    def check_compliance(self, action):
        # Simulate compliance check
        if "harm" in action.lower():
            return False, "Action violates harm clause."
        return True, "Action complies with constitution."

class IntegrationHub:
    def connect(self, service_name):
        # Simulate connection
        time.sleep(0.01)
        return f"Connected to {service_name}"

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, input_data):
        if self.validation.validate(input_data):
            processed_data = self.consciousness.process(input_data)
            # Simulate revenue generation
            revenue_amount = len(input_data) * 0.01
            self.revenue.record_revenue(revenue_amount)
            return f"Decision: {processed_data}. Revenue: {revenue_amount}"
        else:
            return "Invalid input."


# Unit Tests
class TestMemoryRecall(unittest.TestCase):
    def setUp(self):
        self.memory = MemoryRecall()

    def test_store_and_recall(self):
        self.memory.store("key1", "value1")
        self.assertEqual(self.memory.recall("key1"), "value1")

    def test_recall_nonexistent_key(self):
        self.assertIsNone(self.memory.recall("nonexistent"))

    def test_recall_accuracy(self):
        num_items = 1000
        for i in range(num_items):
            self.memory.store(f"key_{i}", f"value_{i}")

        correct_recalls = 0
        for i in range(num_items):
            recalled_value = self.memory.recall(f"key_{i}")
            if recalled_value == f"value_{i}":
                correct_recalls += 1

        accuracy = (correct_recalls / num_items) * 100
        self.assertGreaterEqual(accuracy, 95, "Memory recall accuracy below 95%")


class TestConsciousnessLoop(unittest.TestCase):
    def setUp(self):
        self.loop = ConsciousnessLoop()

    def test_process_data(self):
        result = self.loop.process("test data")
        self.assertEqual(result, "Processed: test data")
        self.assertEqual(self.loop.state, "idle")

    def test_concurrent_processing(self):
      def process_data(loop, data, results):
        results.append(loop.process(data))

      results = []
      threads = []
      for i in range(5):
        thread = threading.Thread(target=process_data, args=(self.loop, f"data_{i}", results))
        threads.append(thread)
        thread.start()

      for thread in threads:
        thread.join()

      for i, result in enumerate(results):
        self.assertEqual(result, f"Processed: data_{i}")
        self.assertEqual(self.loop.state, "idle")


class TestValidationGate(unittest.TestCase):
    def setUp(self):
        self.gate = ValidationGate()

    def test_valid_data(self):
        self.assertTrue(self.gate.validate("valid data"))

    def test_invalid_data_none(self):
        self.assertFalse(self.gate.validate(None))

    def test_invalid_data_short(self):
        self.assertFalse(self.gate.validate("abcd"))

class TestSwarmCoordinator(unittest.TestCase):
    def setUp(self):
        self.coordinator = SwarmCoordinator()

    def test_coordinate_task(self):
        result = self.coordinator.coordinate("build model", 5)
        self.assertIn("build model", result)
        self.assertIn("5 agents", result)

    def test_swarm_coordination_efficiency(self):
        start_time = time.time()
        self.coordinator.coordinate("optimize", 10)
        end_time = time.time()
        elapsed_time = end_time - start_time
        # Adjust the expected time based on the simulation in SwarmCoordinator.coordinate
        expected_time = 0.05 * 10
        self.assertAlmostEqual(elapsed_time, expected_time, places=2, msg="Swarm coordination efficiency is lower than expected.")


class TestKnowledgeGraph(unittest.TestCase):
    def setUp(self):
        self.graph = KnowledgeGraph()

    def test_add_and_get_node(self):
        self.graph.add_node("node1", {"name": "AIVA"})
        node_data = self.graph.get_node("node1")
        self.assertEqual(node_data["name"], "AIVA")

    def test_get_nonexistent_node(self):
        self.assertIsNone(self.graph.get_node("nonexistent"))

class TestRevenueTracker(unittest.TestCase):
    def setUp(self):
        self.tracker = RevenueTracker()

    def test_record_revenue(self):
        self.tracker.record_revenue(100)
        self.assertEqual(self.tracker.get_total_revenue(), 100)

    def test_multiple_revenue_records(self):
        self.tracker.record_revenue(50)
        self.tracker.record_revenue(75)
        self.assertEqual(self.tracker.get_total_revenue(), 125)

class TestEvolutionEngine(unittest.TestCase):
    def setUp(self):
        self.engine = EvolutionEngine()

    def test_evolve_with_mutation(self):
        # Monkey patch random.random to always return a value less than the mutation rate
        with patch('random.random', return_value=0.0):
            result = self.engine.evolve("state1", 0.5)
            self.assertEqual(result, "state1_mutated")

    def test_evolve_without_mutation(self):
        # Monkey patch random.random to always return a value greater than the mutation rate
        with patch('random.random', return_value=1.0):
            result = self.engine.evolve("state1", 0.5)
            self.assertEqual(result, "state1")

class TestConstitutionalCompliance(unittest.TestCase):
    def setUp(self):
        self.compliance = ConstitutionalCompliance()

    def test_compliant_action(self):
        is_compliant, message = self.compliance.check_compliance("analyze data")
        self.assertTrue(is_compliant)

    def test_non_compliant_action(self):
        is_compliant, message = self.compliance.check_compliance("cause harm")
        self.assertFalse(is_compliant)
        self.assertIn("harm", message.lower())

class TestIntegrationHub(unittest.TestCase):
    def setUp(self):
        self.hub = IntegrationHub()

    def test_connect_service(self):
        result = self.hub.connect("data_service")
        self.assertEqual(result, "Connected to data_service")


# Integration Tests
class TestQueenOrchestratorIntegration(unittest.TestCase):
    def setUp(self):
        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_valid_input_decision(self):
        decision = self.orchestrator.make_decision("analyze data")
        self.assertIn("Decision:", decision)
        self.assertIn("Processed: analyze data", decision)
        self.assertGreater(self.revenue.get_total_revenue(), 0)

    def test_invalid_input_decision(self):
        decision = self.orchestrator.make_decision("abc")
        self.assertEqual(decision, "Invalid input.")

    def test_orchestrator_knowledge_graph_interaction(self):
      self.knowledge.add_node("important_data", {"value": "initial_value"})

      with patch.object(self.consciousness, 'process', return_value="Process data based on important_data"):
        self.orchestrator.make_decision("process_data")
        node_data = self.knowledge.get_node("important_data")
        self.assertEqual(node_data["value"], "initial_value") # check that the knowledge graph wasn't mutated

    def test_orchestrator_evolves_and_makes_decisions(self):
        initial_state = "initial_state"
        # Mock the evolution engine to always evolve
        with patch.object(self.evolution, 'evolve', return_value="evolved_state"):
            # Mock the consciousness loop to return the evolved state in its processing
            with patch.object(self.consciousness, 'process', return_value="Evolved State"):
                decision = self.orchestrator.make_decision("some_data")
                self.assertIn("Evolved State", decision)

# Performance Benchmarks
class TestQueenSystemsPerformance(unittest.TestCase):
    def setUp(self):
        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_performance(self):
        num_items = 10000
        for i in range(num_items):
            self.memory.store(f"key_{i}", f"value_{i}")

        start_time = time.time()
        for i in range(num_items):
            self.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, 1.0, "Memory recall performance is too slow.")  # Adjust threshold as needed

    def test_consciousness_loop_performance(self):
        num_iterations = 1000
        start_time = time.time()
        for _ in range(num_iterations):
            self.consciousness.process("test data")
        end_time = time.time()
        elapsed_time = end_time - start_time
        print(f"Consciousness loop performance: {elapsed_time:.4f} seconds for {num_iterations} iterations")
        self.assertLess(elapsed_time, 2.0, "Consciousness loop performance is too slow.") # Adjust threshold


# Stress Tests
class TestQueenSystemsStress(unittest.TestCase):
    def setUp(self):
        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_stress(self):
        num_items = 100000
        for i in range(num_items):
            self.memory.store(f"key_{i}", f"value_{i}")
        # Attempt to recall a large number of items to ensure no memory errors
        for i in range(num_items):
            self.memory.recall(f"key_{i}")

        self.assertIsNotNone(self.memory.recall("key_50000"), "Failed to retrieve after high memory usage")  # Basic check after stress

    def test_concurrent_consciousness_loops(self):
      num_threads = 20
      num_iterations = 50

      def process_data(loop):
        for i in range(num_iterations):
          loop.process(f"data_{i}")

      threads = []
      for _ in range(num_threads):
        thread = threading.Thread(target=process_data, args=(self.consciousness,))
        threads.append(thread)
        thread.start()

      for thread in threads:
        thread.join()

      self.assertEqual(self.consciousness.state, "idle")


# Failure Mode Tests
class TestQueenSystemsFailureModes(unittest.TestCase):
    def setUp(self):
        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_failure(self):
        # Simulate a memory corruption scenario
        with patch.object(self.memory, 'recall', side_effect=Exception("Memory Error")):
            with self.assertRaises(Exception):
                self.orchestrator.make_decision("analyze data")

    def test_validation_gate_failure(self):
      # Simulate validation gate failing unexpectedly.
      with patch.object(self.validation, 'validate', side_effect=Exception("Validation Error")):
        with self.assertRaises(Exception):
          self.orchestrator.make_decision("analyze data")

    def test_constitutional_compliance_exception(self):
        with patch.object(self.compliance, 'check_compliance', side_effect=Exception("Compliance Check Failed")):
            with self.assertRaises(Exception):
                self.orchestrator.make_decision("analyze data")


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