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"""
Advanced orchestration tests for multi-agent system.
Tests complex coordination patterns, failure handling, and performance.
"""
import pytest
import asyncio
from datetime import datetime, timedelta
from unittest.mock import AsyncMock, MagicMock, patch
from uuid import uuid4
import numpy as np
from src.agents import (
MasterAgent,
ZumbiAgent,
AnitaAgent,
TiradentesAgent,
BonifacioAgent,
MariaQuiteriaAgent,
AgentContext,
AgentMessage,
AgentResponse
)
from src.services.agent_orchestrator import AgentOrchestrator
from src.models.agent import AgentStatus
@pytest.fixture
async def orchestrator():
"""Create agent orchestrator for tests."""
orch = AgentOrchestrator()
await orch.initialize()
return orch
@pytest.fixture
def orchestration_context():
"""Create orchestration context."""
return AgentContext(
investigation_id=str(uuid4()),
user_id="orchestration-tester",
session_id=str(uuid4()),
metadata={
"test_type": "orchestration",
"timestamp": datetime.utcnow().isoformat()
}
)
class TestAdvancedOrchestration:
"""Test advanced orchestration patterns."""
@pytest.mark.asyncio
@pytest.mark.integration
async def test_dynamic_agent_selection(self, orchestrator, orchestration_context):
"""Test dynamic agent selection based on task requirements."""
# Define tasks with different requirements
tasks = [
{
"type": "anomaly_detection",
"data": {"contract_value": 1_000_000},
"required_capabilities": ["anomaly_detection", "pattern_analysis"]
},
{
"type": "security_audit",
"data": {"system_name": "Portal"},
"required_capabilities": ["security_audit", "threat_detection"]
},
{
"type": "policy_analysis",
"data": {"policy_name": "Digital Gov"},
"required_capabilities": ["policy_analysis", "governance"]
}
]
# Execute dynamic routing
results = []
for task in tasks:
agent = await orchestrator.select_best_agent(
task["required_capabilities"]
)
assert agent is not None
message = AgentMessage(
type=task["type"],
data=task["data"],
sender="orchestrator",
metadata={"dynamic_routing": True}
)
response = await agent.process(message, orchestration_context)
results.append({
"task": task["type"],
"agent": agent.name,
"success": response.success
})
# Verify correct agent selection
assert results[0]["agent"] in ["InvestigatorAgent", "AnalystAgent"] # Anomaly detection
assert results[1]["agent"] == "MariaQuiteriaAgent" # Security audit
assert results[2]["agent"] == "BonifacioAgent" # Policy analysis
@pytest.mark.asyncio
@pytest.mark.integration
async def test_adaptive_retry_with_fallback(self, orchestrator, orchestration_context):
"""Test adaptive retry mechanism with agent fallback."""
primary_agent = MariaQuiteriaAgent()
fallback_agent = ZumbiAgent()
# Mock primary agent to fail initially
call_count = 0
original_process = primary_agent.process
async def failing_process(message, context):
nonlocal call_count
call_count += 1
if call_count < 3:
raise Exception("Temporary failure")
return await original_process(message, context)
primary_agent.process = failing_process
# Configure orchestrator with retry and fallback
orchestrator.configure_retry_policy({
"max_retries": 2,
"backoff_multiplier": 1.5,
"fallback_agents": {
"MariaQuiteriaAgent": "InvestigatorAgent"
}
})
message = AgentMessage(
type="security_audit",
data={"system_name": "Test System"},
sender="orchestrator",
metadata={}
)
# Execute with retry logic
result = await orchestrator.execute_with_retry(
primary_agent,
message,
orchestration_context,
fallback_agent=fallback_agent
)
# Should succeed after retries
assert result.success is True
assert call_count == 3 # Failed twice, succeeded on third
@pytest.mark.asyncio
@pytest.mark.integration
async def test_conditional_workflow_branching(self, orchestrator, orchestration_context):
"""Test conditional workflow branching based on intermediate results."""
# Define workflow with conditions
workflow = {
"start": "anomaly_detection",
"steps": {
"anomaly_detection": {
"agent": "zumbi",
"next": {
"condition": "anomalies_found",
"true": "security_audit",
"false": "generate_report"
}
},
"security_audit": {
"agent": "maria_quiteria",
"next": {
"condition": "high_risk",
"true": "policy_review",
"false": "generate_report"
}
},
"policy_review": {
"agent": "bonifacio",
"next": "generate_report"
},
"generate_report": {
"agent": "tiradentes",
"next": None
}
}
}
# Execute conditional workflow
initial_data = {
"contract_id": "test-123",
"value": 10_000_000
}
execution_path = await orchestrator.execute_conditional_workflow(
workflow,
initial_data,
orchestration_context
)
# Verify execution followed correct path
assert len(execution_path) >= 2 # At least start and report
assert execution_path[0]["step"] == "anomaly_detection"
assert execution_path[-1]["step"] == "generate_report"
@pytest.mark.asyncio
@pytest.mark.integration
async def test_parallel_map_reduce_pattern(self, orchestrator, orchestration_context):
"""Test map-reduce pattern for parallel data processing."""
# Data to process in parallel
contracts = [
{"id": f"contract-{i}", "value": np.random.randint(100_000, 10_000_000)}
for i in range(5)
]
# Map phase: Process each contract with appropriate agent
async def process_contract(contract):
agent = ZumbiAgent()
message = AgentMessage(
type="analyze",
data={"contract_data": contract},
sender="mapper",
metadata={"map_task": True}
)
return await agent.process(message, orchestration_context)
# Execute map phase in parallel
map_results = await asyncio.gather(
*[process_contract(c) for c in contracts]
)
# Reduce phase: Aggregate results
aggregator = AnitaAgent()
reduce_message = AgentMessage(
type="aggregate_analysis",
data={
"individual_results": [r.data for r in map_results],
"aggregation_type": "anomaly_summary"
},
sender="reducer",
metadata={"reduce_task": True}
)
final_result = await aggregator.process(reduce_message, orchestration_context)
# Verify map-reduce completed
assert all(r.success for r in map_results)
assert final_result.success is True
assert len(map_results) == len(contracts)
@pytest.mark.asyncio
@pytest.mark.integration
async def test_agent_capability_discovery(self, orchestrator):
"""Test dynamic agent capability discovery and registration."""
# Get all registered agents
available_agents = await orchestrator.discover_agents()
# Verify core agents are discovered
agent_names = [a["name"] for a in available_agents]
assert "InvestigatorAgent" in agent_names or "zumbi" in agent_names
assert "MariaQuiteriaAgent" in agent_names or "maria_quiteria" in agent_names
assert "BonifacioAgent" in agent_names or "bonifacio" in agent_names
# Test capability search
security_agents = await orchestrator.find_agents_with_capability("security_audit")
assert len(security_agents) >= 1
assert any("maria" in a["name"].lower() for a in security_agents)
policy_agents = await orchestrator.find_agents_with_capability("policy_analysis")
assert len(policy_agents) >= 1
assert any("bonifacio" in a["name"].lower() for a in policy_agents)
@pytest.mark.asyncio
@pytest.mark.integration
async def test_circuit_breaker_pattern(self, orchestrator, orchestration_context):
"""Test circuit breaker pattern for failing agents."""
agent = MariaQuiteriaAgent()
# Configure circuit breaker
orchestrator.configure_circuit_breaker({
"failure_threshold": 3,
"recovery_timeout": 5,
"half_open_requests": 1
})
# Mock agent to fail consistently
agent.process = AsyncMock(side_effect=Exception("Service unavailable"))
message = AgentMessage(
type="security_audit",
data={"test": True},
sender="test",
metadata={}
)
# Attempt multiple requests
results = []
for i in range(5):
try:
result = await orchestrator.execute_with_circuit_breaker(
agent, message, orchestration_context
)
results.append(("success", result))
except Exception as e:
results.append(("failure", str(e)))
await asyncio.sleep(0.1)
# Circuit should open after threshold
failures = [r for r in results if r[0] == "failure"]
assert len(failures) >= 3
# Later requests should fail fast
assert any("Circuit breaker open" in r[1] for r in failures[3:])
@pytest.mark.asyncio
@pytest.mark.integration
async def test_agent_performance_monitoring(self, orchestrator, orchestration_context):
"""Test agent performance monitoring and optimization."""
agents = [
ZumbiAgent(),
AnitaAgent(),
MariaQuiteriaAgent(),
BonifacioAgent()
]
# Execute multiple requests and monitor performance
performance_stats = {}
for agent in agents:
stats = {
"response_times": [],
"success_rate": 0,
"total_requests": 10
}
success_count = 0
for i in range(stats["total_requests"]):
message = AgentMessage(
type="test_performance",
data={"iteration": i},
sender="performance_monitor",
metadata={}
)
start_time = datetime.utcnow()
try:
response = await agent.process(message, orchestration_context)
if response.success:
success_count += 1
except:
pass
elapsed = (datetime.utcnow() - start_time).total_seconds()
stats["response_times"].append(elapsed)
stats["success_rate"] = success_count / stats["total_requests"]
stats["avg_response_time"] = np.mean(stats["response_times"])
stats["p95_response_time"] = np.percentile(stats["response_times"], 95)
performance_stats[agent.name] = stats
# Verify performance metrics
for agent_name, stats in performance_stats.items():
assert stats["success_rate"] >= 0.9 # 90% success rate
assert stats["avg_response_time"] < 5 # Under 5 seconds average
assert stats["p95_response_time"] < 10 # P95 under 10 seconds
@pytest.mark.asyncio
@pytest.mark.integration
async def test_distributed_transaction_pattern(self, orchestrator, orchestration_context):
"""Test distributed transaction pattern with compensation."""
# Define transaction steps
transaction_steps = [
{
"agent": ZumbiAgent(),
"action": "reserve_analysis_slot",
"compensation": "release_analysis_slot"
},
{
"agent": MariaQuiteriaAgent(),
"action": "allocate_security_resources",
"compensation": "deallocate_security_resources"
},
{
"agent": BonifacioAgent(),
"action": "lock_policy_review",
"compensation": "unlock_policy_review"
}
]
completed_steps = []
try:
# Execute transaction steps
for step in transaction_steps:
message = AgentMessage(
type=step["action"],
data={"transaction_id": "tx-123"},
sender="transaction_manager",
metadata={"transaction": True}
)
response = await step["agent"].process(message, orchestration_context)
if not response.success:
raise Exception(f"Transaction step failed: {step['action']}")
completed_steps.append(step)
# Simulate failure on third step
if len(completed_steps) == 2:
raise Exception("Simulated transaction failure")
# Commit transaction (not reached in this test)
await orchestrator.commit_transaction("tx-123")
except Exception as e:
# Compensate completed steps in reverse order
for step in reversed(completed_steps):
compensation_message = AgentMessage(
type=step["compensation"],
data={"transaction_id": "tx-123"},
sender="transaction_manager",
metadata={"compensation": True}
)
await step["agent"].process(compensation_message, orchestration_context)
# Verify compensation occurred
assert len(completed_steps) == 2 # Two steps completed before failure
class TestOrchestrationPatterns:
"""Test specific orchestration patterns."""
@pytest.mark.asyncio
@pytest.mark.integration
async def test_saga_pattern(self, orchestrator, orchestration_context):
"""Test saga pattern for long-running transactions."""
saga_definition = {
"name": "investigation_saga",
"steps": [
{"service": "anomaly_detection", "agent": "zumbi"},
{"service": "pattern_analysis", "agent": "anita"},
{"service": "security_check", "agent": "maria_quiteria"},
{"service": "policy_review", "agent": "bonifacio"},
{"service": "report_generation", "agent": "tiradentes"}
]
}
saga_state = await orchestrator.start_saga(
saga_definition,
{"investigation_id": "saga-123"},
orchestration_context
)
# Process saga steps
while not saga_state["completed"]:
next_step = saga_state["current_step"]
if next_step >= len(saga_definition["steps"]):
break
step = saga_definition["steps"][next_step]
saga_state = await orchestrator.execute_saga_step(
saga_state,
step,
orchestration_context
)
# Verify saga completed
assert saga_state["completed"] is True
assert len(saga_state["completed_steps"]) == len(saga_definition["steps"])
@pytest.mark.asyncio
@pytest.mark.integration
async def test_event_driven_choreography(self, orchestrator, orchestration_context):
"""Test event-driven agent choreography."""
# Setup event bus
event_bus = orchestrator.get_event_bus()
# Register agent event handlers
agents_triggered = []
async def on_anomaly_detected(event):
agents_triggered.append("security_audit")
await event_bus.emit("security_audit_required", event.data)
async def on_security_audit_required(event):
agents_triggered.append("policy_review")
await event_bus.emit("policy_review_required", event.data)
async def on_policy_review_required(event):
agents_triggered.append("report_generation")
await event_bus.emit("report_ready", event.data)
event_bus.on("anomaly_detected", on_anomaly_detected)
event_bus.on("security_audit_required", on_security_audit_required)
event_bus.on("policy_review_required", on_policy_review_required)
# Trigger initial event
await event_bus.emit("anomaly_detected", {
"severity": "high",
"contract_id": "test-123"
})
# Allow events to propagate
await asyncio.sleep(0.5)
# Verify choreography executed
assert "security_audit" in agents_triggered
assert "policy_review" in agents_triggered
assert "report_generation" in agents_triggered
assert len(agents_triggered) == 3 |