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libs/langchain/tests/integration_tests/evaluation/hallucination/test_detector.py

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# import os
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# import pytest
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# from unittest.mock import patch
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# from langchain.evaluation.hallucination.detector import HallucinationDetector
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# # -----------------------------
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# # Integration Tests (Real HF model)
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# # -----------------------------
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# skip_if_no_hf = pytest.mark.skipif(
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# "HF_TOKEN" not in os.environ, reason="Hugging Face token not available"
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# )
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# @pytest.fixture(scope="module")
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# @skip_if_no_hf
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# @pytest.mark.requires("integration")
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# def detector_real():
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# # Only runs locally if HF token is available
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# return HallucinationDetector(model_name="facebook/bart-large-mnli")
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# @skip_if_no_hf
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# @pytest.mark.requires("integration")
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# def test_extract_claims_integration(detector_real):
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# text = "Barack Obama was the 44th President of the United States. He was born in Kenya."
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# claims = detector_real.extract_claims(text)
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# assert isinstance(claims, list)
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# assert len(claims) == 2
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# assert "Barack Obama was the 44th President of the United States" in claims
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# @skip_if_no_hf
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# @pytest.mark.requires("integration")
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# def test_compute_hallucination_rate_integration(detector_real):
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# text = "Barack Obama was the 44th President of the United States. He was born in Kenya."
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# evidence = [
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# "Barack Obama served as the 44th President of the United States from 2009 to 2017.",
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# "Barack Obama was born in Hawaii, not Kenya."
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# ]
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# result = detector_real.compute_hallucination_rate(text, evidence)
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# unsupported = result["unsupported_claims"]
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# total = result["total_claims"]
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# hallucination_rate = result["hallucination_rate"]
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# assert "total_claims" in result
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# assert "unsupported_claims" in result
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# assert "hallucination_rate" in result
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# assert result["total_claims"] == 2
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# assert unsupported in [1, 2] # Accepts both possible outputs
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# assert 0 <= hallucination_rate <= 1 # Just check it’s a valid rate
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# # -----------------------------
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# # Unit Tests (Mocked)
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# # -----------------------------
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# # Unit test fixture
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# @pytest.fixture(scope="module")
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# def detector_mock():
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# with patch("langchain.evaluation.hallucination.detector.pipeline") as mock_pipeline:
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# # mock NLI results
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# mock_pipeline.return_value = lambda text: [
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# {"label": "ENTAILMENT", "score": 0.9} if "President" in text else {"label": "CONTRADICTION", "score": 0.9}
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# ]
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# # Now constructor won't load HF model
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# detector = HallucinationDetector(model_name="any")
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# yield detector
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# def test_extract_claims_mock(detector_mock):
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# text = "Barack Obama was the 44th President of the United States. He was born in Kenya."
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# claims = detector_mock.extract_claims(text)
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# assert isinstance(claims, list)
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# assert len(claims) == 2
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# def test_verify_claim_supported_mock(detector_mock):
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# claim = "Barack Obama was the 44th President of the United States"
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# evidence = "Barack Obama served as the 44th President of the United States from 2009 to 2017."
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# result = detector_mock.verify_claim(claim, evidence)
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# assert result is True
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# def test_verify_claim_unsupported_mock(detector_mock):
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# claim = "Barack Obama was born in Kenya"
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# evidence = "Barack Obama was born in Hawaii, not Kenya."
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# result = detector_mock.verify_claim(claim, evidence)
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# assert result is False
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# def test_compute_hallucination_rate_mock(detector_mock):
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# text = "Barack Obama was the 44th President of the United States. He was born in Kenya."
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# evidence = [
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# "Barack Obama served as the 44th President of the United States from 2009 to 2017.",
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# "Barack Obama was born in Hawaii, not Kenya."
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# ]
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# result = detector_mock.compute_hallucination_rate(text, evidence)
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# assert "total_claims" in result
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# assert "unsupported_claims" in result
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# assert "hallucination_rate" in result
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import os
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import pytest
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from unittest.mock import patch

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