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Test end-to-end integration flows.
Tests cover:
- EpisodeService → EventBus → LearningEngine flow
- MementoEngine full lifecycle
- AlphaEvolverEngine full lifecycle
- EvolutionEngine monitoring and optimization
- FitnessService + AdvisorService integration
"""
import pytest
from unittest.mock import AsyncMock, MagicMock
from core.auto_dev.event_hooks import EventBus, TaskEvent, SkillExecutionEvent
class TestIntegrationEventFlow:
"""Test EpisodeService → EventBus → LearningEngine flow."""
@pytest.mark.asyncio
async def test_full_event_chain(self, sample_task_event):
"""Test full event chain from emit to handler."""
bus = EventBus()
handler_called = []
async def handler(event):
handler_called.append(event.episode_id)
bus.on_task_fail(handler)
await bus.emit_task_fail(sample_task_event)
assert len(handler_called) == 1
assert handler_called[0] == sample_task_event.episode_id
class TestIntegrationMementoEngineLifecycle:
"""Test MementoEngine full lifecycle (episode → skill)."""
@pytest.mark.asyncio
async def test_analyzes_failed_episode(self, mock_auto_dev_llm, auto_dev_db_session, sample_episode):
"""Test analyzes failed episode."""
from core.auto_dev.memento_engine import MementoEngine
engine = MementoEngine(db=auto_dev_db_session, llm_service=mock_auto_dev_llm)
result = await engine.analyze_episode(sample_episode.id)
assert "episode_id" in result
@pytest.mark.asyncio
async def test_proposes_skill_code(self, mock_auto_dev_llm, auto_dev_db_session):
"""Test proposes skill code."""
from core.auto_dev.memento_engine import MementoEngine
engine = MementoEngine(db=auto_dev_db_session, llm_service=mock_auto_dev_llm)
code = await engine.propose_code_change(
context={"task_description": "Test task", "error_trace": "Error"}
)
assert isinstance(code, str)
assert len(code) > 0
@pytest.mark.asyncio
async def test_validates_in_sandbox(self, mock_sandbox, auto_dev_db_session):
"""Test validates in sandbox."""
from core.auto_dev.memento_engine import MementoEngine
engine = MementoEngine(db=auto_dev_db_session, sandbox=mock_sandbox)
result = await engine.validate_change(
code="print('test')",
test_inputs=[{}],
tenant_id="tenant-001",
)
assert "passed" in result
@pytest.mark.asyncio
async def test_promotes_to_community_skill(self, mock_auto_dev_llm, mock_sandbox, auto_dev_db_session, sample_tenant_id, sample_agent_id):
"""Test promotes to CommunitySkill."""
from core.auto_dev.memento_engine import MementoEngine
from core.auto_dev.models import SkillCandidate
engine = MementoEngine(db=auto_dev_db_session, llm_service=mock_auto_dev_llm, sandbox=mock_sandbox)
# Create validated candidate
candidate = SkillCandidate(
tenant_id=sample_tenant_id,
agent_id=sample_agent_id,
skill_name="test_skill",
generated_code="def test(): pass",
validation_status="validated",
)
auto_dev_db_session.add(candidate)
auto_dev_db_session.commit()
# Note: This will fail to promote due to missing SkillBuilderService
# but we can test the method exists
assert hasattr(engine, "promote_skill")
class TestIntegrationAlphaEvolverEngineLifecycle:
"""Test AlphaEvolverEngine full lifecycle (episode → variant)."""
@pytest.mark.asyncio
async def test_analyzes_successful_episode(self, mock_auto_dev_llm, auto_dev_db_session, sample_episode):
"""Test analyzes successful episode."""
from core.auto_dev.alpha_evolver_engine import AlphaEvolverEngine
engine = AlphaEvolverEngine(db=auto_dev_db_session, llm_service=mock_auto_dev_llm)
result = await engine.analyze_episode(sample_episode.id)
assert "episode_id" in result
@pytest.mark.asyncio
async def test_generates_mutations(self, mock_auto_dev_llm, auto_dev_db_session, sample_tenant_id):
"""Test generates mutations."""
from core.auto_dev.alpha_evolver_engine import AlphaEvolverEngine
engine = AlphaEvolverEngine(db=auto_dev_db_session, llm_service=mock_auto_dev_llm)
mutation = await engine.generate_tool_mutation(
tenant_id=sample_tenant_id,
tool_name="test_tool",
parent_tool_id=None,
base_code="def test(): pass",
mutation_prompt="Optimize",
)
assert mutation.id is not None
@pytest.mark.asyncio
async def test_validates_variants(self, mock_sandbox, auto_dev_db_session, sample_tenant_id):
"""Test validates variants."""
from core.auto_dev.alpha_evolver_engine import AlphaEvolverEngine
from core.auto_dev.models import ToolMutation
engine = AlphaEvolverEngine(db=auto_dev_db_session, sandbox=mock_sandbox)
mutation = ToolMutation(
tenant_id=sample_tenant_id,
tool_name="test",
mutated_code="x = 1",
sandbox_status="pending",
)
auto_dev_db_session.add(mutation)
auto_dev_db_session.commit()
result = await engine.sandbox_execute_mutation(
mutation_id=mutation.id,
tenant_id=sample_tenant_id,
inputs={},
)
assert "success" in result
@pytest.mark.asyncio
async def test_spawns_workflow_variant(self, auto_dev_db_session, sample_tenant_id, sample_agent_id):
"""Test spawns WorkflowVariant."""
from core.auto_dev.alpha_evolver_engine import AlphaEvolverEngine
engine = AlphaEvolverEngine(db=auto_dev_db_session)
variant = engine.spawn_workflow_variant(
tenant_id=sample_tenant_id,
agent_id=sample_agent_id,
workflow_def={"steps": []},
parent_variant_id=None,
)
assert variant.id is not None
class TestIntegrationEvolutionEngineMonitoring:
"""Test EvolutionEngine monitoring and optimization."""
def test_monitors_variant_performance(self, auto_dev_db_session, sample_workflow_variant):
"""Test monitors WorkflowVariant performance."""
from core.auto_dev.evolution_engine import EvolutionEngine
engine = EvolutionEngine(db=auto_dev_db_session)
# Should initialize
assert engine.db == auto_dev_db_session
@pytest.mark.asyncio
async def test_detects_trigger_conditions(self, auto_dev_db_session, monkeypatch):
"""Test detects trigger conditions."""
from core.auto_dev.evolution_engine import EvolutionEngine
engine = EvolutionEngine(db=auto_dev_db_session)
# Mock capability gate to return True (bypass AUTONOMOUS check)
monkeypatch.setattr(engine, "_should_optimize", lambda agent_id, tenant_id: True)
# Mock _get_skill_code to return test code
monkeypatch.setattr(engine, "_get_skill_code", lambda skill_id, tenant_id: "def test_skill():\n pass")
# Mock AlphaEvolverEngine
mock_evolver = MagicMock()
mock_mutation = MagicMock()
mock_mutation.id = "mutation-001"
mock_evolver.generate_tool_mutation = AsyncMock(return_value=mock_mutation)
mock_evolver.sandbox_execute_mutation = AsyncMock(return_value={"success": True})
import sys
original_module = sys.modules.get("core.auto_dev.alpha_evolver_engine")
class MockAlphaEvolverEngine:
def __init__(self, db):
pass
sys.modules["core.auto_dev.alpha_evolver_engine"] = MockAlphaEvolverEngine
sys.modules["core.auto_dev.alpha_evolver_engine"].AlphaEvolverEngine = lambda db: mock_evolver
try:
event = SkillExecutionEvent(
execution_id="exec-001",
agent_id="agent-001",
tenant_id="tenant-001",
skill_id="skill-001",
skill_name="test_skill",
execution_seconds=10.0, # High latency > 5s threshold
token_usage=1000,
success=True,
)
await engine.process_execution(event)
# Should detect and trigger
assert mock_evolver.generate_tool_mutation.called
finally:
if original_module:
sys.modules["core.auto_dev.alpha_evolver_engine"] = original_module
else:
sys.modules.pop("core.auto_dev.alpha_evolver_engine", None)
class TestIntegrationServiceIntegration:
"""Test FitnessService + AdvisorService integration."""
def test_fitness_evaluates_variants(self, auto_dev_db_session, sample_workflow_variant):
"""Test FitnessService evaluates variants."""
from core.auto_dev.fitness_service import FitnessService
service = FitnessService(auto_dev_db_session)
proxy_signals = {
"syntax_error": False,
"execution_success": True,
}
score = service.evaluate_initial_proxy(
sample_workflow_variant.id,
sample_workflow_variant.tenant_id,
proxy_signals,
)
assert 0.0 <= score <= 1.0
@pytest.mark.asyncio
async def test_advisor_generates_guidance(self, mock_auto_dev_llm, auto_dev_db_session, sample_tenant_id):
"""Test AdvisorService generates guidance."""
from core.auto_dev.advisor_service import AdvisorService
service = AdvisorService(db=auto_dev_db_session, llm_service=mock_auto_dev_llm)
result = await service.generate_guidance(tenant_id=sample_tenant_id)
assert "status" in result
assert result["status"] == "success"
@pytest.mark.asyncio
async def test_end_to_end_optimization_flow(self, mock_auto_dev_llm, mock_sandbox, auto_dev_db_session, sample_tenant_id, sample_agent_id):
"""Test end-to-end optimization flow."""
from core.auto_dev.alpha_evolver_engine import AlphaEvolverEngine
from core.auto_dev.fitness_service import FitnessService
from core.auto_dev.advisor_service import AdvisorService
# Step 1: Generate mutation
evolver = AlphaEvolverEngine(
db=auto_dev_db_session,
llm_service=mock_auto_dev_llm,
sandbox=mock_sandbox,
)
mutation = await evolver.generate_tool_mutation(
tenant_id=sample_tenant_id,
tool_name="test_tool",
parent_tool_id=None,
base_code="def test(): pass",
mutation_prompt="Optimize",
)
# Step 2: Create variant
variant = evolver.spawn_workflow_variant(
tenant_id=sample_tenant_id,
agent_id=sample_agent_id,
workflow_def={"optimized": True},
parent_variant_id=None,
)
# Step 3: Evaluate fitness
fitness_service = FitnessService(auto_dev_db_session)
proxy_signals = {
"syntax_error": False,
"execution_success": True,
}
score = fitness_service.evaluate_initial_proxy(
variant.id,
variant.tenant_id,
proxy_signals,
)
# Step 4: Generate guidance
advisor = AdvisorService(db=auto_dev_db_session, llm_service=mock_auto_dev_llm)
guidance = await advisor.generate_guidance(tenant_id=sample_tenant_id)
# Verify full pipeline worked
assert mutation.id is not None
assert variant.id is not None
assert 0.0 <= score <= 1.0
assert guidance["status"] == "success"
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