Dmitriy Dementiev
726718197f
Зачем: - локальным транскриптам нужна структура реплик для конспектов и протоколов. Что: - добавлены пословные таймкоды для всех ASR-бэкендов и сведение с Sherpa-ONNX. - реализованы CLI-флаги, деградация без потери ASR и speaker Markdown. - добавлены проверяемый кеш моделей, тесты и документация. Проверка: - `pytest` — 283 passed, 1 skipped. - `pyright` — 0 errors. - Ruff и `git diff --check` — без ошибок. - выполнены три контрольных прогона на реальных записях.
454 lines
15 KiB
Python
454 lines
15 KiB
Python
from datetime import datetime
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from local_transcriber.formatter import (
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LANGUAGE_DETECTED,
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LANGUAGE_FORCED,
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LANGUAGE_UNKNOWN,
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_group_segments,
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format_timestamp,
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format_transcript,
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write_transcript,
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)
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from local_transcriber.transcriber import Segment, TranscribeResult
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from local_transcriber.types import (
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UNKNOWN_LANGUAGE,
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SmallSpeakerCluster,
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SpeakerTranscript,
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SpeakerTurn,
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)
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def test_format_timestamp_minutes():
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assert format_timestamp(0.0) == "00:00.00"
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assert format_timestamp(83.45) == "01:23.45"
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assert format_timestamp(9.1) == "00:09.10"
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assert format_timestamp(599.99) == "09:59.99"
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assert format_timestamp(0.995) == "00:01.00" # carry-over: не даёт .100
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def test_format_timestamp_hours():
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assert format_timestamp(3723.45, use_hours=True) == "01:02:03.45"
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assert format_timestamp(0.0, use_hours=True) == "00:00:00.00"
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assert format_timestamp(7261.0, use_hours=True) == "02:01:01.00"
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def test_format_transcript_basic():
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result = TranscribeResult(
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segments=[
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Segment(start=0.0, end=4.82, text=" Добрый день, коллеги."),
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Segment(start=4.82, end=9.15, text=" Первый вопрос."),
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],
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language="ru",
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language_probability=0.97,
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duration=120.0,
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device_used="cuda",
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)
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content = format_transcript(
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result,
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source_filename="meeting.mp4",
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model_name="large-v3",
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device_info="CUDA (NVIDIA GeForce RTX 3060)",
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language_mode=LANGUAGE_DETECTED,
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transcription_date=datetime(2026, 3, 17, 14, 30, 5),
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)
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assert "# Транскрипт: meeting.mp4" in content
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assert "**Дата транскрипции**: 2026-03-17 14:30:05" in content
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assert "**Модель**: large-v3" in content
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assert "**Язык**: ru (определён автоматически)" in content
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assert "**Длительность**: 02:00" in content
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assert "**Устройство**: CUDA (NVIDIA GeForce RTX 3060)" in content
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assert "---" in content
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# Соседние сегменты без паузы объединяются в один абзац
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assert "[00:00.00 - 00:09.15] Добрый день, коллеги. Первый вопрос." in content
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def test_format_transcript_speaker_turns_use_truncated_start_timestamps():
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result = TranscribeResult(
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segments=[Segment(start=547.96, end=560.0, text=" Обычный текст")],
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language="ru",
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language_probability=0.97,
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duration=700.0,
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device_used="cpu",
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)
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speakers = SpeakerTranscript(
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turns=[
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SpeakerTurn(547.96, 550.0, "Первая реплика.", 1),
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SpeakerTurn(558.4, 560.0, "Ответ.", 2),
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],
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cluster_count=2,
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unassigned_word_count=0,
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small_clusters=[],
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)
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content = format_transcript(
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result,
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source_filename="meeting.mp4",
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model_name="medium",
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device_info="CPU",
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language_mode=LANGUAGE_DETECTED,
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speaker_transcript=speakers,
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)
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assert "- **Голосовых кластеров**: 2" in content
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assert "[09:07] Speaker 1: Первая реплика." in content
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assert "[09:18] Speaker 2: Ответ." in content
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assert "[09:07.96 -" not in content
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def test_format_transcript_speaker_turns_use_hours_after_one_hour():
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result = TranscribeResult(
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segments=[Segment(start=3661.9, end=3663.0, text=" Длинная встреча")],
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language="ru",
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language_probability=1.0,
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duration=3700.0,
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device_used="cpu",
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)
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speakers = SpeakerTranscript(
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turns=[SpeakerTurn(3661.9, 3663.0, "Длинная встреча", 1)],
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cluster_count=2,
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unassigned_word_count=0,
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small_clusters=[],
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)
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content = format_transcript(
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result,
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source_filename="meeting.mp4",
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model_name="medium",
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device_info="CPU",
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language_mode=LANGUAGE_FORCED,
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speaker_transcript=speakers,
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)
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assert "[01:01:01] Speaker 1: Длинная встреча" in content
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def test_format_transcript_reports_unknown_words_and_small_clusters():
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result = TranscribeResult(
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segments=[Segment(start=0.0, end=8.0, text=" Текст")],
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language="ru",
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language_probability=1.0,
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duration=20.0,
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device_used="cpu",
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)
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speakers = SpeakerTranscript(
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turns=[SpeakerTurn(1.2, 2.0, "Неясная реплика.", None)],
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cluster_count=2,
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unassigned_word_count=3,
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small_clusters=[SmallSpeakerCluster(speaker=2, duration=4.2)],
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)
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content = format_transcript(
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result,
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source_filename="meeting.mp4",
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model_name="medium",
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device_info="CPU",
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language_mode=LANGUAGE_FORCED,
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speaker_transcript=speakers,
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)
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assert "[00:01] Speaker ?: Неясная реплика." in content
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assert "3 слов без назначенного говорящего" in content
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assert "малый кластер Speaker 2: 4.2 с" in content
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def test_format_transcript_keeps_plain_body_with_diarization_warning():
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result = TranscribeResult(
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segments=[Segment(start=0.0, end=2.0, text=" Полезный текст.")],
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language="ru",
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language_probability=1.0,
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duration=5.0,
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device_used="cpu",
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)
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content = format_transcript(
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result,
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source_filename="meeting.mp4",
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model_name="medium",
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device_info="CPU",
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language_mode=LANGUAGE_FORCED,
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diarization_warning="Диаризация завершилась с ошибкой: boom",
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)
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assert "**Внимание**: Диаризация завершилась с ошибкой: boom" in content
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assert "[00:00.00 - 00:02.00] Полезный текст." in content
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assert "Speaker" not in content
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def test_format_transcript_unknown_language_without_placeholder():
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"""Неизвестный язык печатается одной строкой, без служебного значения."""
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result = TranscribeResult(
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segments=[Segment(start=0.0, end=4.0, text=" Добрый день.")],
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language=UNKNOWN_LANGUAGE,
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language_probability=0.0,
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duration=120.0,
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device_used="openvino-cpu",
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)
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content = format_transcript(
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result,
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source_filename="meeting.mp4",
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model_name="medium",
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device_info="OpenVINO (CPU)",
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language_mode=LANGUAGE_UNKNOWN,
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)
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assert "**Язык**: не определён" in content
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assert UNKNOWN_LANGUAGE not in content
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def test_format_transcript_segment_no_leading_space():
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"""Сегменты без ведущего пробела должны форматироваться корректно."""
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result = TranscribeResult(
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segments=[Segment(start=0.0, end=2.0, text="Hello")],
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language="en",
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language_probability=0.99,
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duration=5.0,
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device_used="cpu",
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)
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content = format_transcript(
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result,
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source_filename="f.mp3",
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model_name="tiny",
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device_info="CPU",
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language_mode=LANGUAGE_DETECTED,
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transcription_date=datetime(2026, 1, 1, 0, 0, 0),
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)
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assert "[00:00.00 - 00:02.00] Hello" in content
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def test_format_transcript_empty():
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result = TranscribeResult(
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segments=[],
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language="ru",
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language_probability=0.5,
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duration=30.0,
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device_used="cpu",
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)
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content = format_transcript(
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result,
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source_filename="silence.wav",
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model_name="tiny",
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device_info="CPU",
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language_mode=LANGUAGE_DETECTED,
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transcription_date=datetime(2026, 1, 1, 0, 0, 0),
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)
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assert "# Транскрипт: silence.wav" in content
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assert "*Речь не обнаружена.*" in content
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assert "**Модель**: tiny" in content
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def test_format_transcript_long():
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result = TranscribeResult(
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segments=[
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Segment(start=0.0, end=10.5, text=" Начало."),
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Segment(start=3700.0, end=3710.25, text=" Конец."),
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],
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language="en",
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language_probability=0.99,
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duration=3800.0,
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device_used="cuda",
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)
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content = format_transcript(
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result,
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source_filename="long.mp4",
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model_name="large-v3",
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device_info="CUDA",
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language_mode=LANGUAGE_FORCED,
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transcription_date=datetime(2026, 3, 17, 10, 0, 0),
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)
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assert "**Длительность**: 01:03:20" in content
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assert "**Язык**: en (задан явно)" in content
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# Timestamps should use hours format
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assert "[00:00:00.00 - 00:00:10.50] Начало." in content
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assert "[01:01:40.00 - 01:01:50.25] Конец." in content
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def test_group_segments_merges_adjacent():
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"""Соседние сегменты без паузы объединяются."""
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segments = [
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Segment(start=0.0, end=3.0, text=" Первый."),
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Segment(start=3.0, end=6.0, text=" Второй."),
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Segment(start=6.0, end=9.0, text=" Третий."),
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]
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groups = _group_segments(segments)
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assert len(groups) == 1
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assert groups[0].start == 0.0
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assert groups[0].end == 9.0
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assert groups[0].text == "Первый. Второй. Третий."
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def test_group_segments_splits_on_pause():
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"""Пауза > 2с разбивает на отдельные абзацы."""
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segments = [
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Segment(start=0.0, end=3.0, text=" Первый."),
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Segment(start=3.0, end=6.0, text=" Второй."),
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Segment(start=9.0, end=12.0, text=" После паузы."),
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]
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groups = _group_segments(segments)
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assert len(groups) == 2
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assert groups[0].text == "Первый. Второй."
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assert groups[1].text == "После паузы."
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def test_group_segments_splits_on_max_duration():
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"""Абзац разбивается при превышении макс. длительности."""
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segments = [
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Segment(start=0.0, end=30.0, text=" Длинный."),
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Segment(start=30.0, end=55.0, text=" Ещё."),
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Segment(start=55.0, end=80.0, text=" Перелив."),
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]
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groups = _group_segments(segments)
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assert len(groups) == 2
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assert groups[0].text == "Длинный. Ещё."
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assert groups[1].text == "Перелив."
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def test_group_segments_empty():
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assert _group_segments([]) == []
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def test_write_transcript(tmp_path):
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out = tmp_path / "output.md"
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write_transcript("# Test content\n", out)
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assert out.read_text(encoding="utf-8") == "# Test content\n"
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def test_format_transcript_tail_gap_warning():
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result = TranscribeResult(
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segments=[Segment(start=0.0, end=60.0, text=" Фраза.")],
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language="ru",
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language_probability=0.95,
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duration=600.0,
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device_used="cpu",
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)
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content = format_transcript(
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result,
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source_filename="tail.mp3",
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model_name="medium",
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device_info="CPU",
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language_mode=LANGUAGE_FORCED,
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transcription_date=datetime(2026, 1, 1, 0, 0, 0),
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)
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assert "возможна потеря хвоста" in content
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assert "транскрипт покрывает 01:00 из 10:00" in content
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def test_format_transcript_no_tail_gap_warning_for_small_gap():
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result = TranscribeResult(
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segments=[Segment(start=0.0, end=60.0, text=" Фраза.")],
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language="ru",
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language_probability=0.95,
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duration=179.99,
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device_used="cpu",
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)
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content = format_transcript(
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result,
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source_filename="ok.mp3",
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model_name="medium",
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device_info="CPU",
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language_mode=LANGUAGE_FORCED,
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transcription_date=datetime(2026, 1, 1, 0, 0, 0),
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)
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assert "потеря хвоста" not in content
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def test_format_transcript_no_tail_gap_warning_for_exact_threshold():
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result = TranscribeResult(
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segments=[Segment(start=0.0, end=60.0, text=" Фраза.")],
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language="ru",
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language_probability=0.95,
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duration=180.0,
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device_used="cpu",
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)
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content = format_transcript(
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result,
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source_filename="ok.mp3",
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model_name="medium",
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device_info="CPU",
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language_mode=LANGUAGE_FORCED,
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transcription_date=datetime(2026, 1, 1, 0, 0, 0),
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)
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assert "потеря хвоста" not in content
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def test_format_transcript_repetition_warning():
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result = TranscribeResult(
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segments=[
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Segment(start=10.0, end=11.0, text=" Повторяемая фраза."),
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Segment(start=11.0, end=12.0, text=" повторяемая фраза"),
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Segment(start=12.0, end=13.0, text=" «Повторяемая фраза»"),
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Segment(start=13.0, end=14.0, text=" повторяемая фраза…"),
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],
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language="ru",
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language_probability=0.95,
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duration=60.0,
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device_used="cpu",
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)
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content = format_transcript(
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result,
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source_filename="repeat.mp3",
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model_name="medium",
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device_info="CPU",
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language_mode=LANGUAGE_FORCED,
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transcription_date=datetime(2026, 1, 1, 0, 0, 0),
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)
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assert "повторы в [00:10.00 - 00:14.00] (4×)" in content
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assert "возможны галлюцинации" in content
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def test_format_transcript_repetition_warning_uses_hours():
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result = TranscribeResult(
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segments=[
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Segment(start=3600.0, end=3601.0, text=" Повтор."),
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Segment(start=3601.0, end=3602.0, text=" повтор"),
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Segment(start=3602.0, end=3603.0, text=" повтор"),
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Segment(start=3603.0, end=3604.0, text=" повтор"),
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],
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language="ru",
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language_probability=0.95,
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duration=3700.0,
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device_used="cpu",
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)
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content = format_transcript(
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result,
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source_filename="long-repeat.mp3",
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model_name="medium",
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device_info="CPU",
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language_mode=LANGUAGE_FORCED,
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transcription_date=datetime(2026, 1, 1, 0, 0, 0),
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)
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assert "повторы в [01:00:00.00 - 01:00:04.00] (4×)" in content
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def test_format_transcript_without_anomalies_has_no_warning_lines():
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result = TranscribeResult(
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segments=[Segment(start=0.0, end=60.0, text=" Обычная запись.")],
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language="ru",
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language_probability=0.95,
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duration=120.0,
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device_used="cpu",
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)
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content = format_transcript(
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result,
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source_filename="ok.mp3",
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model_name="medium",
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device_info="CPU",
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language_mode=LANGUAGE_FORCED,
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transcription_date=datetime(2026, 1, 1, 0, 0, 0),
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)
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assert "Внимание" not in content
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