fix: resolve CI lint and test failures
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126
app/local-ai-commit-reviewer/tests/conftest.py
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126
app/local-ai-commit-reviewer/tests/conftest.py
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@@ -0,0 +1,126 @@
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import subprocess
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import tempfile
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from pathlib import Path
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import pytest
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from src.config import Config
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from src.llm.provider import LLMProvider, LLMResponse, ModelInfo
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@pytest.fixture
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def temp_git_repo():
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"""Create a temporary Git repository for testing."""
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with tempfile.TemporaryDirectory() as tmpdir:
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repo_path = Path(tmpdir)
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subprocess.run(["git", "init"], cwd=repo_path, capture_output=True, check=False)
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subprocess.run(["git", "config", "user.email", "test@test.com"], cwd=repo_path, capture_output=True, check=False)
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subprocess.run(["git", "config", "user.name", "Test"], cwd=repo_path, capture_output=True, check=False)
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yield repo_path
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@pytest.fixture
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def sample_python_file(temp_git_repo):
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"""Create a sample Python file in the temp repo."""
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test_file = temp_git_repo / "test.py"
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test_file.write_text('def hello():\n print("Hello, World!")\n return True\n')
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subprocess.run(["git", "add", "test.py"], cwd=temp_git_repo, capture_output=True, check=False)
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return test_file
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@pytest.fixture
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def sample_js_file(temp_git_repo):
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"""Create a sample JavaScript file."""
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test_file = temp_git_repo / "test.js"
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test_file.write_text('function hello() {\n console.log("Hello, World!");\n}\n')
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subprocess.run(["git", "add", "test.js"], cwd=temp_git_repo, capture_output=True, check=False)
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return test_file
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@pytest.fixture
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def sample_diff():
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"""Return a sample diff for testing."""
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return """diff --git a/test.py b/test.py
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--- a/test.py
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+++ b/test.py
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@@ -1,3 +1,4 @@
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def hello():
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+ print("hello")
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return True
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- return False
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"""
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@pytest.fixture
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def mock_config():
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"""Return a default Config instance."""
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return Config()
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class MockLLMProvider(LLMProvider):
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"""Mock LLM provider for testing."""
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def __init__(self, available: bool = True, response_text: str | None = None):
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self._available = available
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self._response_text = response_text or '{"issues": [], "summary": {"critical_count": 0, "warning_count": 0, "info_count": 0, "overall_assessment": "No issues"}}'
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def is_available(self) -> bool:
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return self._available
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def generate(self, _prompt: str, **_kwargs) -> LLMResponse:
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return LLMResponse(
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text=self._response_text,
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model="mock-model",
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tokens_used=50,
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finish_reason="stop"
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)
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async def agenerate(self, _prompt: str, **_kwargs) -> LLMResponse:
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return self.generate(_prompt, **_kwargs)
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def stream_generate(self, _prompt: str, **_kwargs):
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yield "Mock"
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def list_models(self) -> list[ModelInfo]:
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return [
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ModelInfo(name="mock-model", size="4GB", modified="2024-01-01", digest="abc123")
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]
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def health_check(self) -> bool:
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return self._available
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@pytest.fixture
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def mock_llm_provider():
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"""Return a mock LLM provider."""
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return MockLLMProvider(available=True)
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@pytest.fixture
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def mock_llm_unavailable():
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"""Return a mock LLM provider that's not available."""
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return MockLLMProvider(available=False)
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@pytest.fixture
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def mock_llm_with_issues():
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"""Return a mock LLM provider that returns issues."""
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response = '''{
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"issues": [
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{
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"file": "test.py",
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"line": 2,
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"severity": "warning",
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"category": "style",
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"message": "Missing docstring for function",
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"suggestion": "Add a docstring above the function definition"
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}
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],
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"summary": {
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"critical_count": 0,
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"warning_count": 1,
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"info_count": 0,
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"overall_assessment": "Minor style issues found"
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}
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}'''
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return MockLLMProvider(available=True, response_text=response)
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