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audita/tests/test_corrections.py

89 lines
2.4 KiB
Python

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(
"""
[
{"speaker": "Eric", "start": 10.0, "end": 11.0, "text": "I ask Chontia."},
{"speaker": "Mike", "start": 0.0, "end": 1.0, "text": "Then Lyra."}
]
"""
)
def test_apply_corrections_uses_threshold_and_sorts_chronologically():
transcript = _transcript()
corrections = [
CorrectionCandidate(
segment_index=0,
speaker="Eric",
start=10.0,
end=11.0,
original_text="I ask Chontia.",
corrected_text="I ask Chauntea.",
confidence=0.8,
)
]
revised = apply_corrections(transcript, corrections, confidence_threshold=0.8)
assert [segment.speaker for segment in revised] == ["Mike", "Eric"]
assert revised[1].text == "I ask Chauntea."
def test_apply_corrections_ignores_below_threshold():
transcript = _transcript()
corrections = [
CorrectionCandidate(
segment_index=0,
speaker="Eric",
start=10.0,
end=11.0,
original_text="I ask Chontia.",
corrected_text="I ask Chauntea.",
confidence=0.79,
)
]
revised = apply_corrections(transcript, corrections, confidence_threshold=0.8)
assert revised[1].text == "I ask Chontia."
def test_apply_corrections_rejects_duplicate_targets():
transcript = _transcript()
correction = CorrectionCandidate(
segment_index=0,
speaker="Eric",
start=10.0,
end=11.0,
original_text="I ask Chontia.",
corrected_text="I ask Chauntea.",
confidence=0.8,
)
with pytest.raises(AuditaValidationError):
apply_corrections(transcript, [correction, correction], confidence_threshold=0.8)
def test_apply_corrections_rejects_mismatched_original_text():
transcript = _transcript()
correction = CorrectionCandidate(
segment_index=0,
speaker="Eric",
start=10.0,
end=11.0,
original_text="Different text.",
corrected_text="I ask Chauntea.",
confidence=0.8,
)
with pytest.raises(AuditaValidationError):
apply_corrections(transcript, [correction], confidence_threshold=0.8)