| | """Integration tests for Modal (requires credentials).""" |
| |
|
| | import pytest |
| |
|
| | from src.utils.config import settings |
| |
|
| | |
| | _llm_available = bool(settings.openai_api_key or settings.anthropic_api_key) |
| |
|
| |
|
| | @pytest.mark.integration |
| | @pytest.mark.skipif(not settings.modal_available, reason="Modal not configured") |
| | class TestModalIntegration: |
| | """Integration tests requiring Modal credentials.""" |
| |
|
| | @pytest.mark.asyncio |
| | async def test_sandbox_executes_code(self) -> None: |
| | """Modal sandbox should execute Python code.""" |
| | import asyncio |
| | from functools import partial |
| |
|
| | from src.tools.code_execution import get_code_executor |
| |
|
| | executor = get_code_executor() |
| | code = "import pandas as pd; print(pd.DataFrame({'a': [1,2,3]})['a'].sum())" |
| |
|
| | loop = asyncio.get_running_loop() |
| | result = await loop.run_in_executor(None, partial(executor.execute, code, timeout=30)) |
| |
|
| | assert result["success"] |
| | assert "6" in result["stdout"] |
| |
|
| | @pytest.mark.asyncio |
| | @pytest.mark.skipif(not _llm_available, reason="LLM API key not configured") |
| | async def test_statistical_analyzer_works(self) -> None: |
| | """StatisticalAnalyzer should work end-to-end (requires Modal + LLM).""" |
| | from src.services.statistical_analyzer import get_statistical_analyzer |
| | from src.utils.models import Citation, Evidence |
| |
|
| | evidence = [ |
| | Evidence( |
| | content="Drug shows 40% improvement in trial.", |
| | citation=Citation( |
| | source="pubmed", |
| | title="Test", |
| | url="https://test.com", |
| | date="2024-01-01", |
| | authors=["Test"], |
| | ), |
| | relevance=0.9, |
| | ) |
| | ] |
| |
|
| | analyzer = get_statistical_analyzer() |
| | result = await analyzer.analyze("test drug efficacy", evidence) |
| |
|
| | assert result.verdict in ["SUPPORTED", "REFUTED", "INCONCLUSIVE"] |
| | assert 0.0 <= result.confidence <= 1.0 |
| |
|
