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| """Exercise the complete risk rules offline, with translation and model scores mocked.""" | |
| import importlib.util | |
| import sys | |
| from pathlib import Path | |
| from types import SimpleNamespace | |
| import pytest | |
| import torch | |
| def analyzer(monkeypatch): | |
| service_dir = Path(__file__).resolve().parents[1] | |
| monkeypatch.syspath_prepend(str(service_dir)) | |
| classifier = SimpleNamespace( | |
| tokenizer=lambda *args, **kwargs: {"attention_mask": torch.ones((1, 1))}, | |
| model=SimpleNamespace( | |
| base_model=lambda **kwargs: SimpleNamespace( | |
| last_hidden_state=torch.zeros((1, 1, 768)) | |
| ) | |
| ), | |
| ) | |
| # Stub the lazy Transformers module itself so import-time model loading | |
| # cannot make a network request, even on the first import. | |
| monkeypatch.setitem(sys.modules, "transformers", SimpleNamespace( | |
| pipeline=lambda *args, **kwargs: classifier | |
| )) | |
| monkeypatch.setattr("nltk.data.find", lambda *args, **kwargs: True) | |
| # Deliberately omit the crisis wording from the translation: the raw Tagalog | |
| # must be enough to trigger the safety rules despite a low model score. | |
| monkeypatch.setattr("deep_translator.GoogleTranslator.translate", lambda *args: "I am sad.") | |
| spec = importlib.util.spec_from_file_location("risk_rules_under_test", service_dir / "main.py") | |
| module = importlib.util.module_from_spec(spec) | |
| spec.loader.exec_module(module) | |
| monkeypatch.setattr(module, "get_risk_components", lambda *args: (0.0, 0.0)) | |
| return module.analyze_text_sync | |
| def test_explicit_self_harm_is_critical_despite_low_scores(analyzer, text): | |
| result = analyzer(text) | |
| assert result["risk_level"] == "CRITICAL" | |
| assert 86 <= result["risk_score"] <= 100 | |
| def test_other_directed_harm_and_ordinary_sadness_are_not_critical(analyzer, text): | |
| assert analyzer(text)["risk_level"] != "CRITICAL" | |