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https://git.mirrors.martin98.com/https://github.com/bytedance/deer-flow
synced 2025-08-18 00:55:54 +08:00
feat(ut): add ut coverage check (#170)
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parent
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commit
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20
.github/workflows/unittest.yaml
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20
.github/workflows/unittest.yaml
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@ -23,7 +23,23 @@ jobs:
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uv pip install -e ".[dev]"
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uv pip install -e ".[test]"
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- name: Run test cases
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- name: Run test cases with coverage
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run: |
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source .venv/bin/activate
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TAVILY_API_KEY=mock-key make test
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TAVILY_API_KEY=mock-key make coverage
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- name: Generate HTML Coverage Report
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run: |
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source .venv/bin/activate
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python -m coverage html -d coverage_html
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- name: Upload Coverage Report
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uses: actions/upload-artifact@v4
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with:
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name: coverage-report
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path: coverage_html/
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- name: Display Coverage Summary
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run: |
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source .venv/bin/activate
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python -m coverage report
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3
.gitignore
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3
.gitignore
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@ -21,3 +21,6 @@ conf.yaml
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.idea/
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.langgraph_api/
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# coverage report
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coverage.xml
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coverage/
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2
Makefile
2
Makefile
@ -19,4 +19,4 @@ langgraph-dev:
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uvx --refresh --from "langgraph-cli[inmem]" --with-editable . --python 3.12 langgraph dev --allow-blocking
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coverage:
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uv run pytest --cov=src tests/ --cov-report=term-missing
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uv run pytest --cov=src tests/ --cov-report=term-missing --cov-report=xml
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@ -2,7 +2,7 @@
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[](https://www.python.org/downloads/)
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[](https://opensource.org/licenses/MIT)
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[](https://deepwiki.com/bytedance/deer-flow)
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[](https://deepwiki.com/bytedance/deer-flow)
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<!-- DeepWiki badge generated by https://deepwiki.ryoppippi.com/ -->
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@ -52,6 +52,9 @@ filterwarnings = [
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"ignore::UserWarning",
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]
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[tool.coverage.report]
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fail_under = 25
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[tool.hatch.build.targets.wheel]
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packages = ["src"]
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24
test_fix.py
Normal file
24
test_fix.py
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@ -0,0 +1,24 @@
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#!/usr/bin/env python3
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"""
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This script manually patches sys.modules to fix the LLM import issue
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so that tests can run without requiring LLM configuration.
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"""
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import sys
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from unittest.mock import MagicMock
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# Create mocks
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mock_llm = MagicMock()
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mock_llm.invoke.return_value = "Mock LLM response"
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# Create a mock module for llm.py
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mock_llm_module = MagicMock()
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mock_llm_module.get_llm_by_type = lambda llm_type: mock_llm
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mock_llm_module.basic_llm = mock_llm
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mock_llm_module._create_llm_use_conf = lambda llm_type, conf: mock_llm
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# Set the mock module
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sys.modules["src.llms.llm"] = mock_llm_module
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print("Successfully patched LLM module. You can now run your tests.")
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print("Example: uv run pytest tests/test_types.py -v")
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131
tests/test_state.py
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131
tests/test_state.py
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@ -0,0 +1,131 @@
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import pytest
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import sys
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import os
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from typing import Annotated, List, Optional
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# Import MessagesState directly from langgraph rather than through our application
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from langgraph.graph import MessagesState
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# Create stub versions of Plan/Step/StepType to avoid dependencies
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class StepType:
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RESEARCH = "research"
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PROCESSING = "processing"
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class Step:
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def __init__(self, need_web_search, title, description, step_type):
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self.need_web_search = need_web_search
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self.title = title
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self.description = description
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self.step_type = step_type
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class Plan:
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def __init__(self, locale, has_enough_context, thought, title, steps):
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self.locale = locale
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self.has_enough_context = has_enough_context
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self.thought = thought
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self.title = title
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self.steps = steps
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# Import the actual State class by loading the module directly
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# This avoids the cascade of imports that would normally happen
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def load_state_class():
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# Get the absolute path to the types.py file
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src_dir = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "src"))
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types_path = os.path.join(src_dir, "graph", "types.py")
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# Create a namespace for the module
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import types
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module_name = "src.graph.types_direct"
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spec = types.ModuleType(module_name)
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# Add the module to sys.modules to avoid import loops
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sys.modules[module_name] = spec
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# Set up the namespace with required imports
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spec.__dict__["operator"] = __import__("operator")
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spec.__dict__["Annotated"] = Annotated
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spec.__dict__["MessagesState"] = MessagesState
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spec.__dict__["Plan"] = Plan
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# Execute the module code
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with open(types_path, "r") as f:
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module_code = f.read()
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exec(module_code, spec.__dict__)
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# Return the State class
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return spec.State
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# Load the actual State class
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State = load_state_class()
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def test_state_initialization():
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"""Test that State class has correct default attribute definitions."""
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# Test that the class has the expected attribute definitions
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assert State.locale == "en-US"
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assert State.observations == []
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assert State.plan_iterations == 0
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assert State.current_plan is None
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assert State.final_report == ""
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assert State.auto_accepted_plan is False
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assert State.enable_background_investigation is True
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assert State.background_investigation_results is None
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# Verify state initialization
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state = State(messages=[])
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assert "messages" in state
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# Without explicitly passing attributes, they're not in the state
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assert "locale" not in state
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assert "observations" not in state
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def test_state_with_custom_values():
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"""Test that State can be initialized with custom values."""
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test_step = Step(
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need_web_search=True,
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title="Test Step",
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description="Step description",
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step_type=StepType.RESEARCH,
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)
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test_plan = Plan(
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locale="en-US",
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has_enough_context=False,
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thought="Test thought",
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title="Test Plan",
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steps=[test_step],
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)
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# Initialize state with custom values and required messages field
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state = State(
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messages=[],
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locale="fr-FR",
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observations=["Observation 1"],
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plan_iterations=2,
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current_plan=test_plan,
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final_report="Test report",
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auto_accepted_plan=True,
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enable_background_investigation=False,
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background_investigation_results="Test results",
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)
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# Access state keys - these are explicitly initialized
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assert state["locale"] == "fr-FR"
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assert state["observations"] == ["Observation 1"]
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assert state["plan_iterations"] == 2
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assert state["current_plan"].title == "Test Plan"
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assert state["current_plan"].thought == "Test thought"
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assert len(state["current_plan"].steps) == 1
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assert state["current_plan"].steps[0].title == "Test Step"
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assert state["final_report"] == "Test report"
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assert state["auto_accepted_plan"] is True
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assert state["enable_background_investigation"] is False
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assert state["background_investigation_results"] == "Test results"
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