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"""Unit tests for ResearchFlow classes."""
from unittest.mock import AsyncMock, MagicMock, patch
import pytest
from src.orchestrator.research_flow import DeepResearchFlow, IterativeResearchFlow
from src.utils.models import (
AgentSelectionPlan,
AgentTask,
KnowledgeGapOutput,
ReportPlan,
ReportPlanSection,
ToolAgentOutput,
)
class TestIterativeResearchFlow:
"""Tests for IterativeResearchFlow."""
@pytest.fixture
def mock_agents(self):
"""Create mock agents for the flow."""
return {
"knowledge_gap": AsyncMock(),
"tool_selector": AsyncMock(),
"thinking": AsyncMock(),
"writer": AsyncMock(),
}
@pytest.fixture
def flow(self, mock_agents):
"""Create an IterativeResearchFlow with mocked agents."""
from src.utils.models import JudgeAssessment, AssessmentDetails
mock_judge = MagicMock()
# Mock judge assessment - default to insufficient so loops continue
default_assessment = JudgeAssessment(
details=AssessmentDetails(
mechanism_score=5,
mechanism_reasoning="Test reasoning for mechanism assessment",
clinical_evidence_score=5,
clinical_reasoning="Test reasoning for clinical evidence assessment",
drug_candidates=[],
key_findings=[],
),
sufficient=False,
confidence=0.5,
recommendation="continue",
next_search_queries=[],
reasoning="Test assessment for research flow testing purposes",
)
mock_judge.assess = AsyncMock(return_value=default_assessment)
with (
patch("src.orchestrator.research_flow.create_knowledge_gap_agent") as mock_kg,
patch("src.orchestrator.research_flow.create_tool_selector_agent") as mock_ts,
patch("src.orchestrator.research_flow.create_thinking_agent") as mock_thinking,
patch("src.orchestrator.research_flow.create_writer_agent") as mock_writer,
patch("src.orchestrator.research_flow.execute_tool_tasks") as mock_execute,
patch("src.orchestrator.research_flow.get_rag_service") as mock_rag,
patch("src.orchestrator.research_flow.create_judge_handler", return_value=mock_judge),
):
mock_kg.return_value = mock_agents["knowledge_gap"]
mock_ts.return_value = mock_agents["tool_selector"]
mock_thinking.return_value = mock_agents["thinking"]
mock_writer.return_value = mock_agents["writer"]
# execute_tool_tasks is async, so make the mock async
async def mock_execute_async(*args, **kwargs):
return {
"task_1": ToolAgentOutput(output="Finding 1", sources=["url1"]),
}
mock_execute.side_effect = mock_execute_async
# Mock RAG service to return None to avoid ChromaDB initialization
mock_rag.return_value = None
yield IterativeResearchFlow(max_iterations=2, max_time_minutes=5)
@pytest.mark.asyncio
async def test_iterative_flow_completes_when_research_complete(self, flow, mock_agents):
"""IterativeResearchFlow should complete when research is marked complete."""
from src.utils.models import JudgeAssessment, AssessmentDetails
# Mock judge to return sufficient=True so loop completes
sufficient_assessment = JudgeAssessment(
details=AssessmentDetails(
mechanism_score=8,
mechanism_reasoning="Strong evidence for mechanism of action",
clinical_evidence_score=7,
clinical_reasoning="Good support from clinical studies",
drug_candidates=["TestDrug"],
key_findings=["Finding 1"],
),
sufficient=True,
confidence=0.9,
recommendation="synthesize",
next_search_queries=[],
reasoning="Evidence is sufficient",
)
flow.judge_handler.assess = AsyncMock(return_value=sufficient_assessment)
# Mock knowledge gap agent to return complete
mock_agents["knowledge_gap"].evaluate = AsyncMock(
return_value=KnowledgeGapOutput(
research_complete=True,
outstanding_gaps=[],
)
)
# Mock thinking agent
mock_agents["thinking"].generate_observations = AsyncMock(return_value="Initial thoughts")
# Mock writer agent
mock_agents["writer"].write_report = AsyncMock(
return_value="# Final Report\n\nContent here."
)
result = await flow.run("Test query")
assert isinstance(result, str)
assert "Final Report" in result
assert flow.iteration == 1 # Should complete after first iteration
@pytest.mark.asyncio
async def test_iterative_flow_loops_when_research_incomplete(self, flow, mock_agents):
"""IterativeResearchFlow should loop when research is incomplete."""
# Mock knowledge gap agent to return incomplete, then complete
call_count = {"count": 0}
def mock_evaluate(*args, **kwargs):
call_count["count"] += 1
if call_count["count"] == 1:
return KnowledgeGapOutput(
research_complete=False,
outstanding_gaps=["Need more info"],
)
return KnowledgeGapOutput(
research_complete=True,
outstanding_gaps=[],
)
mock_agents["knowledge_gap"].evaluate = AsyncMock(side_effect=mock_evaluate)
# Mock thinking agent
mock_agents["thinking"].generate_observations = AsyncMock(return_value="Thoughts")
# Mock tool selector
mock_agents["tool_selector"].select_tools = AsyncMock(
return_value=AgentSelectionPlan(
tasks=[
AgentTask(
gap="Need more info",
agent="WebSearchAgent",
query="test query",
)
]
)
)
# Mock writer
mock_agents["writer"].write_report = AsyncMock(return_value="# Report\n\nContent")
result = await flow.run("Test query")
assert isinstance(result, str)
assert flow.iteration >= 1
@pytest.mark.asyncio
async def test_iterative_flow_respects_max_iterations(self, flow, mock_agents):
"""IterativeResearchFlow should stop at max_iterations."""
# Always return incomplete
mock_agents["knowledge_gap"].evaluate = AsyncMock(
return_value=KnowledgeGapOutput(
research_complete=False,
outstanding_gaps=["Gap 1"],
)
)
mock_agents["thinking"].generate_observations = AsyncMock(return_value="Thoughts")
mock_agents["tool_selector"].select_tools = AsyncMock(
return_value=AgentSelectionPlan(
tasks=[
AgentTask(
gap="Gap 1",
agent="WebSearchAgent",
query="test",
)
]
)
)
mock_agents["writer"].write_report = AsyncMock(return_value="# Report\n\nContent")
await flow.run("Test query")
# Should stop at max_iterations (2)
assert flow.iteration <= flow.max_iterations
@pytest.mark.asyncio
async def test_iterative_flow_handles_tool_execution_error(self, flow, mock_agents):
"""IterativeResearchFlow should handle tool execution errors gracefully."""
mock_agents["knowledge_gap"].evaluate = AsyncMock(
return_value=KnowledgeGapOutput(
research_complete=False,
outstanding_gaps=["Gap 1"],
)
)
mock_agents["thinking"].generate_observations = AsyncMock(return_value="Thoughts")
mock_agents["tool_selector"].select_tools = AsyncMock(
return_value=AgentSelectionPlan(
tasks=[
AgentTask(
gap="Gap 1",
agent="WebSearchAgent",
query="test",
)
]
)
)
# Mock tool execution to fail
with patch("src.orchestrator.research_flow.execute_tool_tasks") as mock_execute:
mock_execute.side_effect = Exception("Tool execution failed")
mock_agents["writer"].write_report = AsyncMock(return_value="# Report\n\nContent")
# Should not raise, should complete with report
result = await flow.run("Test query")
assert isinstance(result, str)
class TestDeepResearchFlow:
"""Tests for DeepResearchFlow."""
@pytest.fixture
def mock_agents(self):
"""Create mock agents for the flow."""
return {
"planner": AsyncMock(),
"long_writer": AsyncMock(),
"proofreader": AsyncMock(),
}
@pytest.fixture
def flow(self, mock_agents):
"""Create a DeepResearchFlow with mocked agents."""
from src.utils.models import JudgeAssessment, AssessmentDetails
mock_judge = MagicMock()
# Mock judge assessment - default to insufficient so loops continue
default_assessment = JudgeAssessment(
details=AssessmentDetails(
mechanism_score=5,
mechanism_reasoning="Test reasoning for mechanism assessment",
clinical_evidence_score=5,
clinical_reasoning="Test reasoning for clinical evidence assessment",
drug_candidates=[],
key_findings=[],
),
sufficient=False,
confidence=0.5,
recommendation="continue",
next_search_queries=[],
reasoning="Test assessment for research flow testing purposes",
)
mock_judge.assess = AsyncMock(return_value=default_assessment)
with (
patch("src.orchestrator.research_flow.create_planner_agent") as mock_planner,
patch("src.orchestrator.research_flow.create_long_writer_agent") as mock_long_writer,
patch("src.orchestrator.research_flow.create_proofreader_agent") as mock_proofreader,
patch("src.orchestrator.research_flow.create_judge_handler", return_value=mock_judge),
):
mock_planner.return_value = mock_agents["planner"]
mock_long_writer.return_value = mock_agents["long_writer"]
mock_proofreader.return_value = mock_agents["proofreader"]
yield DeepResearchFlow(max_iterations=2, max_time_minutes=5)
@pytest.mark.asyncio
async def test_deep_flow_creates_report_plan(self, flow, mock_agents):
"""DeepResearchFlow should create a report plan."""
mock_plan = ReportPlan(
background_context="Context",
report_outline=[
ReportPlanSection(title="Section 1", key_question="Question 1?"),
ReportPlanSection(title="Section 2", key_question="Question 2?"),
],
report_title="Test Report",
)
mock_agents["planner"].run = AsyncMock(return_value=mock_plan)
# Mock iterative flow results
with patch("src.orchestrator.research_flow.IterativeResearchFlow") as mock_iterative:
mock_iterative_instance = AsyncMock()
mock_iterative_instance.run = AsyncMock(
side_effect=["Section 1 content", "Section 2 content"]
)
mock_iterative.return_value = mock_iterative_instance
mock_agents["long_writer"].write_report = AsyncMock(
return_value="# Final Report\n\nContent"
)
result = await flow.run("Test query")
assert isinstance(result, str)
assert "Final Report" in result
mock_agents["planner"].run.assert_called_once_with("Test query")
@pytest.mark.asyncio
async def test_deep_flow_runs_parallel_research_loops(self, flow, mock_agents):
"""DeepResearchFlow should run parallel research loops for each section."""
mock_plan = ReportPlan(
background_context="Context",
report_outline=[
ReportPlanSection(title="Section 1", key_question="Q1?"),
ReportPlanSection(title="Section 2", key_question="Q2?"),
ReportPlanSection(title="Section 3", key_question="Q3?"),
],
report_title="Test Report",
)
mock_agents["planner"].run = AsyncMock(return_value=mock_plan)
# Track calls to iterative flow
iterative_calls = []
def create_iterative_flow(*args, **kwargs):
flow_instance = AsyncMock()
flow_instance.run = AsyncMock(
side_effect=lambda query, **kw: iterative_calls.append(query)
or f"Content for {query}"
)
return flow_instance
with patch(
"src.orchestrator.research_flow.IterativeResearchFlow",
side_effect=create_iterative_flow,
):
mock_agents["long_writer"].write_report = AsyncMock(
return_value="# Final Report\n\nContent"
)
await flow.run("Test query")
# Should have called iterative flow for each section
assert len(iterative_calls) == 3
assert "Q1?" in iterative_calls
assert "Q2?" in iterative_calls
assert "Q3?" in iterative_calls
@pytest.mark.asyncio
async def test_deep_flow_uses_proofreader_when_specified(self, flow, mock_agents):
"""DeepResearchFlow should use proofreader when use_long_writer=False."""
flow.use_long_writer = False
mock_plan = ReportPlan(
background_context="Context",
report_outline=[
ReportPlanSection(title="Section 1", key_question="Q1?"),
],
report_title="Test Report",
)
mock_agents["planner"].run = AsyncMock(return_value=mock_plan)
with patch("src.orchestrator.research_flow.IterativeResearchFlow") as mock_iterative:
mock_iterative_instance = AsyncMock()
mock_iterative_instance.run = AsyncMock(return_value="Section content")
mock_iterative.return_value = mock_iterative_instance
mock_agents["proofreader"].proofread = AsyncMock(
return_value="# Final Report\n\nContent"
)
result = await flow.run("Test query")
assert isinstance(result, str)
mock_agents["proofreader"].proofread.assert_called_once()
mock_agents["long_writer"].write_report.assert_not_called()
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