import pytest from audita.corrections import apply_corrections from audita.errors import AuditaValidationError from audita.schemas import CorrectionCandidate, parse_transcript_json def _transcript(): return parse_transcript_json( """ [ {"id": 1, "speaker": "Eric", "start": 10.0, "end": 11.0, "text": "I ask Chontia for help."}, {"id": 2, "speaker": "Mike", "start": 0.0, "end": 1.0, "text": "Then Lyra."} ] """ ) def test_apply_corrections_uses_threshold_and_preserves_id_order(): transcript = _transcript() corrections = [ CorrectionCandidate( id=1, original_text="Chontia", corrected_text="Chauntea", confidence=0.8, ) ] result = apply_corrections(transcript, corrections, confidence_threshold=0.8) assert [segment.speaker for segment in result.transcript] == ["Eric", "Mike"] assert result.transcript[0].text == "I ask Chauntea for help." assert result.skipped == [] def test_apply_corrections_ignores_below_threshold(): transcript = _transcript() corrections = [ CorrectionCandidate( id=1, original_text="Chontia", corrected_text="Chauntea", confidence=0.79, ) ] result = apply_corrections(transcript, corrections, confidence_threshold=0.8) assert result.transcript[0].text == "I ask Chontia for help." assert result.skipped == [] def test_apply_corrections_allows_multiple_distinct_spans_in_one_segment(): transcript = _transcript() first = CorrectionCandidate( id=1, original_text="Chontia", corrected_text="Chauntea", confidence=0.8, ) second = CorrectionCandidate( id=1, original_text="help", corrected_text="guidance", confidence=0.9, ) result = apply_corrections(transcript, [first, second], confidence_threshold=0.8) assert result.transcript[0].text == "I ask Chauntea for guidance." assert result.skipped == [] def test_apply_corrections_skips_missing_substring(): transcript = _transcript() correction = CorrectionCandidate( id=1, original_text="Different text.", corrected_text="Chauntea", confidence=0.8, ) result = apply_corrections(transcript, [correction], confidence_threshold=0.8) assert result.transcript[0].text == "I ask Chontia for help." assert len(result.skipped) == 1 assert result.skipped[0].id == 1 assert result.skipped[0].actual_text == "I ask Chontia for help." assert "does not match any substring" in result.skipped[0].reason def test_apply_corrections_skips_missing_id(): transcript = _transcript() correction = CorrectionCandidate( id=99, original_text="Missing.", corrected_text="Still missing.", confidence=0.8, ) result = apply_corrections(transcript, [correction], confidence_threshold=0.8) assert [segment.text for segment in result.transcript] == ["I ask Chontia for help.", "Then Lyra."] assert len(result.skipped) == 1 assert result.skipped[0].id == 99 assert "does not exist" in result.skipped[0].reason def test_apply_corrections_skips_no_op(): transcript = _transcript() correction = CorrectionCandidate( id=1, original_text="Chontia", corrected_text="Chontia", confidence=0.8, ) result = apply_corrections(transcript, [correction], confidence_threshold=0.8) assert result.transcript[0].text == "I ask Chontia for help." assert len(result.skipped) == 1 assert "identical" in result.skipped[0].reason def test_apply_corrections_replaces_all_repeated_substrings(): transcript = parse_transcript_json( """ [ {"id": 1, "speaker": "Eric", "start": 0.0, "end": 1.0, "text": "Bane met Bane."} ] """ ) correction = CorrectionCandidate( id=1, original_text="Bane", corrected_text="Bain", confidence=0.8, ) result = apply_corrections(transcript, [correction], confidence_threshold=0.8) assert result.transcript[0].text == "Bain met Bain." assert result.skipped == [] def test_apply_corrections_skips_empty_original_text(): transcript = _transcript() correction = CorrectionCandidate( id=1, original_text="", corrected_text="Chauntea", confidence=0.8, ) result = apply_corrections(transcript, [correction], confidence_threshold=0.8) assert result.transcript[0].text == "I ask Chontia for help." assert len(result.skipped) == 1 assert "empty" in result.skipped[0].reason def test_apply_corrections_rejects_invalid_threshold(): with pytest.raises(AuditaValidationError): apply_corrections(_transcript(), [], confidence_threshold=1.1)