feat(diarization): добавлено разделение транскрипта по говорящим
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.
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Dmitriy Dementiev committed
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commit
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@@ -12,15 +12,26 @@ from local_transcriber.formatter import (
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LANGUAGE_FROM_MODEL,
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LANGUAGE_UNKNOWN,
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)
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from local_transcriber.transcriber import Segment, TranscribeFileResult, TranscribeResult
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from local_transcriber.types import UNKNOWN_LANGUAGE
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from local_transcriber.transcriber import (
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Segment,
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TranscribeFileResult,
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TranscribeResult,
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)
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from local_transcriber.types import (
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UNKNOWN_LANGUAGE,
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DiarizationRun,
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SpeakerInterval,
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Word,
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)
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runner = CliRunner()
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def _make_result(segments=None, language="ru", device_used="cpu", duration=60.0):
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return TranscribeResult(
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segments=[Segment(start=0.0, end=2.0, text="Hello")] if segments is None else segments,
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segments=[Segment(start=0.0, end=2.0, text="Hello")]
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if segments is None
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else segments,
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language=language,
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language_probability=0.95,
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duration=duration,
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@@ -36,7 +47,13 @@ def _make_backend():
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return MagicMock(name="Backend")
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def _make_tfr(result=None, model=None, actual_device="cpu", backend=None, model_path="/models/medium"):
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def _make_tfr(
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result=None,
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model=None,
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actual_device="cpu",
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backend=None,
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model_path="/models/medium",
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):
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if result is None:
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result = _make_result()
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if model is None:
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@@ -44,8 +61,11 @@ def _make_tfr(result=None, model=None, actual_device="cpu", backend=None, model_
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if backend is None:
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backend = _make_backend()
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return TranscribeFileResult(
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result=result, model=model, actual_device=actual_device,
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backend=backend, model_path=model_path,
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result=result,
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model=model,
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actual_device=actual_device,
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backend=backend,
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model_path=model_path,
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)
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@@ -58,9 +78,7 @@ def _make_tfr(result=None, model=None, actual_device="cpu", backend=None, model_
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("auto", UNKNOWN_LANGUAGE, 0.0, LANGUAGE_UNKNOWN),
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],
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)
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def test_format_language_mode(
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requested_language, language, probability, expected
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):
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def test_format_language_mode(requested_language, language, probability, expected):
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result = _make_result(language=language)
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result.language_probability = probability
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@@ -73,12 +91,17 @@ def _single_patches(result=None, tmp_file=None, actual_device="cpu"):
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result = _make_result(device_used=actual_device)
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model = _make_model()
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backend = _make_backend()
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tfr = _make_tfr(result=result, model=model, actual_device=actual_device, backend=backend)
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tfr = _make_tfr(
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result=result, model=model, actual_device=actual_device, backend=backend
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)
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return [
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patch("local_transcriber.cli.load_config", return_value={}),
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patch("local_transcriber.cli.validate_input_file", return_value=tmp_file),
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patch("local_transcriber.cli.detect_device", return_value=actual_device),
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patch("local_transcriber.cli.load_model", return_value=(model, actual_device, backend, "/models/medium")),
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patch(
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"local_transcriber.cli.load_model",
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return_value=(model, actual_device, backend, "/models/medium"),
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),
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patch("local_transcriber.cli._transcribe_file", return_value=tfr),
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patch("local_transcriber.cli.write_transcript"),
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]
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@@ -139,18 +162,28 @@ def test_cli_custom_options(tmp_path):
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patch("local_transcriber.cli.load_config", return_value={}),
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patch("local_transcriber.cli.validate_input_file", return_value=audio),
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patch("local_transcriber.cli.detect_device", return_value="cuda"),
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patch("local_transcriber.cli.load_model", return_value=(model, "cuda", backend, "/models/small")),
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patch(
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"local_transcriber.cli.load_model",
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return_value=(model, "cuda", backend, "/models/small"),
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),
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patch("local_transcriber.cli._transcribe_file", mock_transcribe_file),
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patch("local_transcriber.cli.write_transcript"),
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patch("local_transcriber.cli.get_gpu_name", return_value="RTX 3060"),
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):
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runner.invoke(app, [
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str(audio),
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"--model", "small",
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"--language", "ru",
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"--device", "cuda",
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"--compute-type", "float16",
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])
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runner.invoke(
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app,
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[
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str(audio),
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"--model",
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"small",
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"--language",
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"ru",
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"--device",
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"cuda",
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"--compute-type",
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"float16",
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],
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)
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call_kwargs = mock_transcribe_file.call_args[1]
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assert call_kwargs["model_name"] == "small"
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@@ -158,6 +191,266 @@ def test_cli_custom_options(tmp_path):
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assert call_kwargs["compute_type"] == "float16"
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def test_cli_speakers_enables_diarization_and_writes_speaker_markdown(tmp_path):
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audio = tmp_path / "meeting.mp3"
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audio.write_bytes(b"fake")
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result = _make_result(
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segments=[Segment(0.0, 1.3, "Первый. Второй. Неясно.")],
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duration=10.0,
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)
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result.words = [
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Word(0.0, 0.5, "Первый."),
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Word(0.5, 1.0, "Второй."),
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Word(1.1, 1.3, "Неясно."),
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]
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model = _make_model()
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backend = _make_backend()
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backend.word_timestamps_available = True
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tfr = _make_tfr(result=result, model=model, backend=backend)
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diarizer = MagicMock()
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diarizer.process.return_value = DiarizationRun(
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intervals=[
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SpeakerInterval(0.0, 0.5, 10),
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SpeakerInterval(0.5, 1.0, 20),
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],
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elapsed_seconds=0.2,
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)
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write = MagicMock()
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with (
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patch("local_transcriber.cli.load_config", return_value={}),
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patch("local_transcriber.cli.validate_input_file", return_value=audio),
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patch("local_transcriber.cli.detect_device", return_value="cpu"),
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patch(
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"local_transcriber.cli.load_model",
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return_value=(model, "cpu", backend, "/models/medium"),
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),
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patch("local_transcriber.cli._transcribe_file", return_value=tfr),
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patch(
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"local_transcriber.cli.load_speaker_diarizer",
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return_value=diarizer,
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) as load_diarizer,
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patch("local_transcriber.cli.write_transcript", write),
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):
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out = runner.invoke(
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app,
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[str(audio), "--speakers", "2", "--threads", "3"],
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)
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assert out.exit_code == 0
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load_diarizer.assert_called_once()
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assert load_diarizer.call_args.kwargs["speakers"] == 2
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assert load_diarizer.call_args.kwargs["threads"] == 3
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diarizer.process.assert_called_once()
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assert "Speaker 1: Первый." in write.call_args.args[0]
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assert "Speaker 2: Второй." in write.call_args.args[0]
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assert "Speaker ?: Неясно." in write.call_args.args[0]
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assert "1 слов без назначенного говорящего" in out.output
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assert "малый кластер Speaker 1: 0.5 с" in out.output
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def test_cli_diarization_error_writes_plain_transcript_and_exits_nonzero(tmp_path):
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audio = tmp_path / "meeting.mp3"
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audio.write_bytes(b"fake")
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result = _make_result(
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segments=[Segment(0.0, 1.0, "Полезный текст.")],
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duration=10.0,
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)
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result.words = [Word(0.0, 1.0, "Полезный текст.")]
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model = _make_model()
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backend = _make_backend()
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backend.word_timestamps_available = True
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tfr = _make_tfr(result=result, model=model, backend=backend)
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diarizer = MagicMock()
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diarizer.process.side_effect = RuntimeError("boom")
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write = MagicMock()
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with (
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patch("local_transcriber.cli.load_config", return_value={}),
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patch("local_transcriber.cli.validate_input_file", return_value=audio),
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patch("local_transcriber.cli.detect_device", return_value="cpu"),
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patch(
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"local_transcriber.cli.load_model",
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return_value=(model, "cpu", backend, "/models/medium"),
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),
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patch("local_transcriber.cli._transcribe_file", return_value=tfr),
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patch(
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"local_transcriber.cli.load_speaker_diarizer",
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return_value=diarizer,
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),
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patch("local_transcriber.cli.write_transcript", write),
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):
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out = runner.invoke(app, [str(audio), "--diarize"])
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assert out.exit_code == 1
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assert write.call_count == 1
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assert "Полезный текст." in write.call_args.args[0]
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assert "Диаризация завершилась с ошибкой: boom" in write.call_args.args[0]
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def test_cli_verbose_reports_diarization_counts_and_duration(tmp_path):
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audio = tmp_path / "meeting.mp3"
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audio.write_bytes(b"fake")
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result = _make_result(
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segments=[Segment(0.0, 1.0, "Раз два")],
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duration=10.0,
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)
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result.words = [Word(0.0, 0.5, "Раз"), Word(0.5, 1.0, "два")]
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model = _make_model()
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backend = _make_backend()
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backend.word_timestamps_available = True
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tfr = _make_tfr(result=result, model=model, backend=backend)
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diarizer = MagicMock()
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diarizer.process.return_value = DiarizationRun(
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intervals=[
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SpeakerInterval(0.0, 0.5, 1),
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SpeakerInterval(0.5, 1.0, 2),
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],
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elapsed_seconds=0.2,
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)
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with (
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patch("local_transcriber.cli.load_config", return_value={}),
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patch("local_transcriber.cli.validate_input_file", return_value=audio),
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patch("local_transcriber.cli.detect_device", return_value="cpu"),
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patch(
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"local_transcriber.cli.load_model",
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return_value=(model, "cpu", backend, "/models/medium"),
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),
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patch("local_transcriber.cli._transcribe_file", return_value=tfr),
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patch(
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"local_transcriber.cli.load_speaker_diarizer",
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return_value=diarizer,
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),
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patch("local_transcriber.cli.write_transcript"),
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):
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out = runner.invoke(app, [str(audio), "--diarize", "--verbose"])
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assert out.exit_code == 0
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assert "2 кластеров, 2 интервалов" in out.output
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assert "0.2 с" in out.output
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def test_cli_empty_asr_skips_diarizer_and_reports_it(tmp_path):
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audio = tmp_path / "silence.wav"
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audio.write_bytes(b"fake")
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result = _make_result(segments=[])
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model = _make_model()
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backend = _make_backend()
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backend.word_timestamps_available = True
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tfr = _make_tfr(result=result, model=model, backend=backend)
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diarizer = MagicMock()
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with (
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patch("local_transcriber.cli.load_config", return_value={}),
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patch("local_transcriber.cli.validate_input_file", return_value=audio),
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patch("local_transcriber.cli.detect_device", return_value="cpu"),
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patch(
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"local_transcriber.cli.load_model",
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return_value=(model, "cpu", backend, "/models/medium"),
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),
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patch("local_transcriber.cli._transcribe_file", return_value=tfr),
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patch(
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"local_transcriber.cli.load_speaker_diarizer",
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return_value=diarizer,
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),
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patch("local_transcriber.cli.write_transcript"),
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):
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out = runner.invoke(app, [str(audio), "--diarize"])
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assert out.exit_code == 0
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diarizer.process.assert_not_called()
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assert "диаризация не запускалась" in out.output
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def test_cli_diarizer_preflight_failure_does_not_start_asr_or_write(tmp_path):
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audio = tmp_path / "meeting.mp3"
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audio.write_bytes(b"fake")
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model = _make_model()
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backend = _make_backend()
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backend.word_timestamps_available = True
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transcribe_file = MagicMock()
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write = MagicMock()
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with (
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patch("local_transcriber.cli.load_config", return_value={}),
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patch("local_transcriber.cli.validate_input_file", return_value=audio),
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patch("local_transcriber.cli.detect_device", return_value="cpu"),
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patch(
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"local_transcriber.cli.load_model",
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return_value=(model, "cpu", backend, "/models/medium"),
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),
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patch("local_transcriber.cli._transcribe_file", transcribe_file),
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patch(
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"local_transcriber.cli.load_speaker_diarizer",
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side_effect=RuntimeError("модель повреждена"),
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),
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patch("local_transcriber.cli.write_transcript", write),
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):
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out = runner.invoke(app, [str(audio), "--diarize"])
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assert out.exit_code == 1
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transcribe_file.assert_not_called()
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write.assert_not_called()
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@pytest.mark.parametrize(
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("intervals", "warning"),
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[
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([SpeakerInterval(0.0, 1.0, 1)], "только один голосовой кластер"),
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([], "не нашёл интервалов"),
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],
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)
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def test_cli_unsuccessful_diarization_shape_writes_plain_text_and_exits_nonzero(
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tmp_path, intervals, warning
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):
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audio = tmp_path / "meeting.mp3"
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audio.write_bytes(b"fake")
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result = _make_result(
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segments=[Segment(0.0, 1.0, "Раз два")],
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duration=10.0,
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)
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result.words = [Word(0.0, 0.5, "Раз"), Word(0.5, 1.0, "два")]
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model = _make_model()
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backend = _make_backend()
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backend.word_timestamps_available = True
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tfr = _make_tfr(result=result, model=model, backend=backend)
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diarizer = MagicMock()
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diarizer.process.return_value = DiarizationRun(intervals, elapsed_seconds=0.1)
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write = MagicMock()
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with (
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patch("local_transcriber.cli.load_config", return_value={}),
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patch("local_transcriber.cli.validate_input_file", return_value=audio),
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patch("local_transcriber.cli.detect_device", return_value="cpu"),
|
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patch(
|
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"local_transcriber.cli.load_model",
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return_value=(model, "cpu", backend, "/models/medium"),
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),
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patch("local_transcriber.cli._transcribe_file", return_value=tfr),
|
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patch(
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"local_transcriber.cli.load_speaker_diarizer",
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return_value=diarizer,
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),
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patch("local_transcriber.cli.write_transcript", write),
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):
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out = runner.invoke(app, [str(audio), "--diarize"])
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assert out.exit_code == 1
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content = write.call_args.args[0]
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assert warning in content
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assert "[00:00.00 - 00:01.00] Раз два" in content
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def test_cli_rejects_nonpositive_speaker_count(tmp_path):
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audio = tmp_path / "meeting.mp3"
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audio.write_bytes(b"fake")
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|
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out = runner.invoke(app, [str(audio), "--speakers", "0"])
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assert out.exit_code == 2
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def test_cli_verbose_passes_on_segment_callback(tmp_path):
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audio = tmp_path / "test.mp3"
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audio.write_bytes(b"fake")
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@@ -171,7 +464,10 @@ def test_cli_verbose_passes_on_segment_callback(tmp_path):
|
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patch("local_transcriber.cli.load_config", return_value={}),
|
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patch("local_transcriber.cli.validate_input_file", return_value=audio),
|
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patch("local_transcriber.cli.detect_device", return_value="cpu"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "cpu", backend, "/models/medium")),
|
||||
patch(
|
||||
"local_transcriber.cli.load_model",
|
||||
return_value=(model, "cpu", backend, "/models/medium"),
|
||||
),
|
||||
patch("local_transcriber.cli._transcribe_file", mock_transcribe_file),
|
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patch("local_transcriber.cli.write_transcript"),
|
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):
|
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@@ -209,7 +505,10 @@ def test_cli_default_output_path(tmp_path):
|
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patch("local_transcriber.cli.load_config", return_value={}),
|
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patch("local_transcriber.cli.validate_input_file", return_value=audio),
|
||||
patch("local_transcriber.cli.detect_device", return_value="cpu"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "cpu", backend, "/models/medium")),
|
||||
patch(
|
||||
"local_transcriber.cli.load_model",
|
||||
return_value=(model, "cpu", backend, "/models/medium"),
|
||||
),
|
||||
patch("local_transcriber.cli._transcribe_file", return_value=tfr),
|
||||
patch("local_transcriber.cli.write_transcript", mock_write),
|
||||
):
|
||||
@@ -234,7 +533,10 @@ def test_cli_custom_output_path(tmp_path):
|
||||
patch("local_transcriber.cli.load_config", return_value={}),
|
||||
patch("local_transcriber.cli.validate_input_file", return_value=audio),
|
||||
patch("local_transcriber.cli.detect_device", return_value="cpu"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "cpu", backend, "/models/medium")),
|
||||
patch(
|
||||
"local_transcriber.cli.load_model",
|
||||
return_value=(model, "cpu", backend, "/models/medium"),
|
||||
),
|
||||
patch("local_transcriber.cli._transcribe_file", return_value=tfr),
|
||||
patch("local_transcriber.cli.write_transcript", mock_write),
|
||||
):
|
||||
@@ -257,7 +559,10 @@ def test_cli_passes_status_callback_to_transcribe(tmp_path):
|
||||
patch("local_transcriber.cli.load_config", return_value={}),
|
||||
patch("local_transcriber.cli.validate_input_file", return_value=audio),
|
||||
patch("local_transcriber.cli.detect_device", return_value="cpu"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "cpu", backend, "/models/medium")),
|
||||
patch(
|
||||
"local_transcriber.cli.load_model",
|
||||
return_value=(model, "cpu", backend, "/models/medium"),
|
||||
),
|
||||
patch("local_transcriber.cli._transcribe_file", mock_transcribe_file),
|
||||
patch("local_transcriber.cli.write_transcript"),
|
||||
):
|
||||
@@ -276,7 +581,9 @@ def test_cli_load_model_called_with_model_name(tmp_path):
|
||||
model = _make_model()
|
||||
backend = _make_backend()
|
||||
tfr = _make_tfr(result=result, model=model, backend=backend)
|
||||
mock_load_model = MagicMock(return_value=(model, "cpu", backend, "/models/large-v3"))
|
||||
mock_load_model = MagicMock(
|
||||
return_value=(model, "cpu", backend, "/models/large-v3")
|
||||
)
|
||||
|
||||
with (
|
||||
patch("local_transcriber.cli.load_config", return_value={}),
|
||||
@@ -302,8 +609,14 @@ def test_cli_windows_cuda_diagnostic(tmp_path):
|
||||
patch("local_transcriber.cli.load_config", return_value={}),
|
||||
patch("local_transcriber.cli.validate_input_file", return_value=audio),
|
||||
patch("local_transcriber.cli.detect_device", return_value="cuda"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "cuda", backend, "/models/medium")),
|
||||
patch("local_transcriber.cli._transcribe_file", side_effect=RuntimeError("CUDA error: no device")),
|
||||
patch(
|
||||
"local_transcriber.cli.load_model",
|
||||
return_value=(model, "cuda", backend, "/models/medium"),
|
||||
),
|
||||
patch(
|
||||
"local_transcriber.cli._transcribe_file",
|
||||
side_effect=RuntimeError("CUDA error: no device"),
|
||||
),
|
||||
patch("local_transcriber.cli.sys") as mock_sys,
|
||||
):
|
||||
mock_sys.platform = "win32"
|
||||
@@ -325,8 +638,14 @@ def test_cli_linux_cuda_error_no_windows_hint(tmp_path):
|
||||
patch("local_transcriber.cli.load_config", return_value={}),
|
||||
patch("local_transcriber.cli.validate_input_file", return_value=audio),
|
||||
patch("local_transcriber.cli.detect_device", return_value="cuda"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "cuda", backend, "/models/medium")),
|
||||
patch("local_transcriber.cli._transcribe_file", side_effect=RuntimeError("CUDA error: no device")),
|
||||
patch(
|
||||
"local_transcriber.cli.load_model",
|
||||
return_value=(model, "cuda", backend, "/models/medium"),
|
||||
),
|
||||
patch(
|
||||
"local_transcriber.cli._transcribe_file",
|
||||
side_effect=RuntimeError("CUDA error: no device"),
|
||||
),
|
||||
patch("local_transcriber.cli.sys") as mock_sys,
|
||||
):
|
||||
mock_sys.platform = "linux"
|
||||
@@ -349,7 +668,10 @@ def test_cli_device_fallback_warning(tmp_path):
|
||||
patch("local_transcriber.cli.load_config", return_value={}),
|
||||
patch("local_transcriber.cli.validate_input_file", return_value=audio),
|
||||
patch("local_transcriber.cli.detect_device", return_value="cuda"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "cuda", backend, "/models/medium")),
|
||||
patch(
|
||||
"local_transcriber.cli.load_model",
|
||||
return_value=(model, "cuda", backend, "/models/medium"),
|
||||
),
|
||||
patch("local_transcriber.cli._transcribe_file", return_value=tfr),
|
||||
patch("local_transcriber.cli.write_transcript"),
|
||||
):
|
||||
@@ -372,7 +694,10 @@ def test_cli_strict_device_passed_to_transcribe(tmp_path):
|
||||
patch("local_transcriber.cli.load_config", return_value={}),
|
||||
patch("local_transcriber.cli.validate_input_file", return_value=audio),
|
||||
patch("local_transcriber.cli.detect_device", return_value="cuda"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "cuda", backend, "/models/medium")),
|
||||
patch(
|
||||
"local_transcriber.cli.load_model",
|
||||
return_value=(model, "cuda", backend, "/models/medium"),
|
||||
),
|
||||
patch("local_transcriber.cli._transcribe_file", mock_transcribe_file),
|
||||
patch("local_transcriber.cli.write_transcript"),
|
||||
patch("local_transcriber.cli.get_gpu_name", return_value="RTX 3060"),
|
||||
@@ -390,7 +715,10 @@ def test_cli_strict_device_passed_to_transcribe(tmp_path):
|
||||
patch("local_transcriber.cli.load_config", return_value={}),
|
||||
patch("local_transcriber.cli.validate_input_file", return_value=audio),
|
||||
patch("local_transcriber.cli.detect_device", return_value="cpu"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "cpu", backend, "/models/medium")),
|
||||
patch(
|
||||
"local_transcriber.cli.load_model",
|
||||
return_value=(model, "cpu", backend, "/models/medium"),
|
||||
),
|
||||
patch("local_transcriber.cli._transcribe_file", mock_transcribe_file),
|
||||
patch("local_transcriber.cli.write_transcript"),
|
||||
):
|
||||
@@ -410,7 +738,10 @@ def test_cli_keyboard_interrupt(tmp_path):
|
||||
patch("local_transcriber.cli.load_config", return_value={}),
|
||||
patch("local_transcriber.cli.validate_input_file", return_value=audio),
|
||||
patch("local_transcriber.cli.detect_device", return_value="cpu"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "cpu", backend, "/models/medium")),
|
||||
patch(
|
||||
"local_transcriber.cli.load_model",
|
||||
return_value=(model, "cpu", backend, "/models/medium"),
|
||||
),
|
||||
patch("local_transcriber.cli._transcribe_file", side_effect=KeyboardInterrupt),
|
||||
patch("local_transcriber.cli.write_transcript"),
|
||||
):
|
||||
@@ -443,8 +774,14 @@ def test_cli_unexpected_error_verbose_traceback(tmp_path):
|
||||
patch("local_transcriber.cli.load_config", return_value={}),
|
||||
patch("local_transcriber.cli.validate_input_file", return_value=audio),
|
||||
patch("local_transcriber.cli.detect_device", return_value="cpu"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "cpu", backend, "/models/medium")),
|
||||
patch("local_transcriber.cli._transcribe_file", side_effect=RuntimeError("unexpected boom")),
|
||||
patch(
|
||||
"local_transcriber.cli.load_model",
|
||||
return_value=(model, "cpu", backend, "/models/medium"),
|
||||
),
|
||||
patch(
|
||||
"local_transcriber.cli._transcribe_file",
|
||||
side_effect=RuntimeError("unexpected boom"),
|
||||
),
|
||||
patch("local_transcriber.cli.write_transcript"),
|
||||
):
|
||||
out = runner.invoke(app, [str(audio), "--verbose"])
|
||||
@@ -464,8 +801,14 @@ def test_cli_unexpected_error_no_verbose_hint(tmp_path):
|
||||
patch("local_transcriber.cli.load_config", return_value={}),
|
||||
patch("local_transcriber.cli.validate_input_file", return_value=audio),
|
||||
patch("local_transcriber.cli.detect_device", return_value="cpu"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "cpu", backend, "/models/medium")),
|
||||
patch("local_transcriber.cli._transcribe_file", side_effect=RuntimeError("unexpected boom")),
|
||||
patch(
|
||||
"local_transcriber.cli.load_model",
|
||||
return_value=(model, "cpu", backend, "/models/medium"),
|
||||
),
|
||||
patch(
|
||||
"local_transcriber.cli._transcribe_file",
|
||||
side_effect=RuntimeError("unexpected boom"),
|
||||
),
|
||||
patch("local_transcriber.cli.write_transcript"),
|
||||
):
|
||||
out = runner.invoke(app, [str(audio)])
|
||||
@@ -493,7 +836,10 @@ def test_cli_batch_two_files(tmp_path):
|
||||
patch("local_transcriber.cli.load_config", return_value={}),
|
||||
patch("local_transcriber.cli.validate_input_file", side_effect=lambda p: p),
|
||||
patch("local_transcriber.cli.detect_device", return_value="cpu"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "cpu", backend, "/models/medium")),
|
||||
patch(
|
||||
"local_transcriber.cli.load_model",
|
||||
return_value=(model, "cpu", backend, "/models/medium"),
|
||||
),
|
||||
patch("local_transcriber.cli._transcribe_file", return_value=tfr),
|
||||
patch("local_transcriber.cli.write_transcript"),
|
||||
):
|
||||
@@ -503,6 +849,111 @@ def test_cli_batch_two_files(tmp_path):
|
||||
assert "2 обработано" in out.output
|
||||
|
||||
|
||||
def test_cli_batch_reuses_one_diarizer_for_all_nonempty_files(tmp_path):
|
||||
first = tmp_path / "first.mp3"
|
||||
second = tmp_path / "second.mp3"
|
||||
first.write_bytes(b"fake")
|
||||
second.write_bytes(b"fake")
|
||||
result = _make_result(
|
||||
segments=[Segment(0.0, 1.0, "Раз два")],
|
||||
duration=10.0,
|
||||
)
|
||||
result.words = [Word(0.0, 0.5, "Раз"), Word(0.5, 1.0, "два")]
|
||||
model = _make_model()
|
||||
backend = _make_backend()
|
||||
backend.word_timestamps_available = True
|
||||
tfr = _make_tfr(result=result, model=model, backend=backend)
|
||||
diarizer = MagicMock()
|
||||
diarizer.process.return_value = DiarizationRun(
|
||||
intervals=[
|
||||
SpeakerInterval(0.0, 0.5, 1),
|
||||
SpeakerInterval(0.5, 1.0, 2),
|
||||
],
|
||||
elapsed_seconds=0.1,
|
||||
)
|
||||
|
||||
with (
|
||||
patch("local_transcriber.cli.load_config", return_value={}),
|
||||
patch(
|
||||
"local_transcriber.cli.validate_input_file",
|
||||
side_effect=lambda path: path,
|
||||
),
|
||||
patch("local_transcriber.cli.detect_device", return_value="cpu"),
|
||||
patch(
|
||||
"local_transcriber.cli.load_model",
|
||||
return_value=(model, "cpu", backend, "/models/medium"),
|
||||
),
|
||||
patch("local_transcriber.cli._transcribe_file", return_value=tfr),
|
||||
patch(
|
||||
"local_transcriber.cli.load_speaker_diarizer",
|
||||
return_value=diarizer,
|
||||
) as load_diarizer,
|
||||
patch("local_transcriber.cli.write_transcript") as write,
|
||||
):
|
||||
out = runner.invoke(app, [str(first), str(second), "--diarize"])
|
||||
|
||||
assert out.exit_code == 0
|
||||
load_diarizer.assert_called_once()
|
||||
assert [call.args[0] for call in diarizer.process.call_args_list] == [
|
||||
first,
|
||||
second,
|
||||
]
|
||||
assert write.call_count == 2
|
||||
|
||||
|
||||
def test_cli_batch_continues_after_diarization_error_and_exits_nonzero(tmp_path):
|
||||
first = tmp_path / "first.mp3"
|
||||
second = tmp_path / "second.mp3"
|
||||
first.write_bytes(b"fake")
|
||||
second.write_bytes(b"fake")
|
||||
result = _make_result(
|
||||
segments=[Segment(0.0, 1.0, "Раз два")],
|
||||
duration=10.0,
|
||||
)
|
||||
result.words = [Word(0.0, 0.5, "Раз"), Word(0.5, 1.0, "два")]
|
||||
model = _make_model()
|
||||
backend = _make_backend()
|
||||
backend.word_timestamps_available = True
|
||||
tfr = _make_tfr(result=result, model=model, backend=backend)
|
||||
diarizer = MagicMock()
|
||||
diarizer.process.side_effect = [
|
||||
RuntimeError("boom"),
|
||||
DiarizationRun(
|
||||
[
|
||||
SpeakerInterval(0.0, 0.5, 1),
|
||||
SpeakerInterval(0.5, 1.0, 2),
|
||||
],
|
||||
elapsed_seconds=0.1,
|
||||
),
|
||||
]
|
||||
|
||||
with (
|
||||
patch("local_transcriber.cli.load_config", return_value={}),
|
||||
patch(
|
||||
"local_transcriber.cli.validate_input_file",
|
||||
side_effect=lambda path: path,
|
||||
),
|
||||
patch("local_transcriber.cli.detect_device", return_value="cpu"),
|
||||
patch(
|
||||
"local_transcriber.cli.load_model",
|
||||
return_value=(model, "cpu", backend, "/models/medium"),
|
||||
),
|
||||
patch("local_transcriber.cli._transcribe_file", return_value=tfr),
|
||||
patch(
|
||||
"local_transcriber.cli.load_speaker_diarizer",
|
||||
return_value=diarizer,
|
||||
),
|
||||
patch("local_transcriber.cli.write_transcript") as write,
|
||||
):
|
||||
out = runner.invoke(app, [str(first), str(second), "--diarize"])
|
||||
|
||||
assert out.exit_code == 1
|
||||
assert write.call_count == 2
|
||||
assert "Диаризация завершилась с ошибкой: boom" in write.call_args_list[0].args[0]
|
||||
assert "Speaker 1" in write.call_args_list[1].args[0]
|
||||
assert "1 с деградацией" in out.output
|
||||
|
||||
|
||||
def test_cli_batch_skips_existing(tmp_path):
|
||||
a = tmp_path / "a.mp3"
|
||||
b = tmp_path / "b.mp3"
|
||||
@@ -519,7 +970,10 @@ def test_cli_batch_skips_existing(tmp_path):
|
||||
patch("local_transcriber.cli.load_config", return_value={}),
|
||||
patch("local_transcriber.cli.validate_input_file", side_effect=lambda p: p),
|
||||
patch("local_transcriber.cli.detect_device", return_value="cpu"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "cpu", backend, "/models/medium")),
|
||||
patch(
|
||||
"local_transcriber.cli.load_model",
|
||||
return_value=(model, "cpu", backend, "/models/medium"),
|
||||
),
|
||||
patch("local_transcriber.cli._transcribe_file", return_value=tfr),
|
||||
patch("local_transcriber.cli.write_transcript"),
|
||||
):
|
||||
@@ -540,16 +994,22 @@ def test_cli_batch_all_skipped_no_model_load(tmp_path):
|
||||
(tmp_path / "b-transcript.md").write_text("existing")
|
||||
|
||||
mock_load_model = MagicMock()
|
||||
mock_load_diarizer = MagicMock()
|
||||
|
||||
with (
|
||||
patch("local_transcriber.cli.load_config", return_value={}),
|
||||
patch("local_transcriber.cli.validate_input_file", side_effect=lambda p: p),
|
||||
patch("local_transcriber.cli.load_model", mock_load_model),
|
||||
patch(
|
||||
"local_transcriber.cli.load_speaker_diarizer",
|
||||
mock_load_diarizer,
|
||||
),
|
||||
):
|
||||
out = runner.invoke(app, [str(a), str(b)])
|
||||
out = runner.invoke(app, [str(a), str(b), "--diarize"])
|
||||
|
||||
assert out.exit_code == 0
|
||||
mock_load_model.assert_not_called()
|
||||
mock_load_diarizer.assert_not_called()
|
||||
|
||||
|
||||
def test_cli_batch_force_overwrites(tmp_path):
|
||||
@@ -568,7 +1028,10 @@ def test_cli_batch_force_overwrites(tmp_path):
|
||||
patch("local_transcriber.cli.load_config", return_value={}),
|
||||
patch("local_transcriber.cli.validate_input_file", side_effect=lambda p: p),
|
||||
patch("local_transcriber.cli.detect_device", return_value="cpu"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "cpu", backend, "/models/medium")),
|
||||
patch(
|
||||
"local_transcriber.cli.load_model",
|
||||
return_value=(model, "cpu", backend, "/models/medium"),
|
||||
),
|
||||
patch("local_transcriber.cli._transcribe_file", return_value=tfr),
|
||||
patch("local_transcriber.cli.write_transcript"),
|
||||
):
|
||||
@@ -602,8 +1065,13 @@ def test_cli_batch_per_file_error(tmp_path):
|
||||
patch("local_transcriber.cli.load_config", return_value={}),
|
||||
patch("local_transcriber.cli.validate_input_file", side_effect=lambda p: p),
|
||||
patch("local_transcriber.cli.detect_device", return_value="cpu"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "cpu", backend, "/models/medium")),
|
||||
patch("local_transcriber.cli._transcribe_file", side_effect=transcribe_side_effect),
|
||||
patch(
|
||||
"local_transcriber.cli.load_model",
|
||||
return_value=(model, "cpu", backend, "/models/medium"),
|
||||
),
|
||||
patch(
|
||||
"local_transcriber.cli._transcribe_file", side_effect=transcribe_side_effect
|
||||
),
|
||||
patch("local_transcriber.cli.write_transcript"),
|
||||
):
|
||||
out = runner.invoke(app, [str(a), str(b)])
|
||||
@@ -631,9 +1099,15 @@ def test_cli_batch_invalid_in_prescan(tmp_path):
|
||||
|
||||
with (
|
||||
patch("local_transcriber.cli.load_config", return_value={}),
|
||||
patch("local_transcriber.cli.validate_input_file", side_effect=validate_side_effect),
|
||||
patch(
|
||||
"local_transcriber.cli.validate_input_file",
|
||||
side_effect=validate_side_effect,
|
||||
),
|
||||
patch("local_transcriber.cli.detect_device", return_value="cpu"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "cpu", backend, "/models/medium")),
|
||||
patch(
|
||||
"local_transcriber.cli.load_model",
|
||||
return_value=(model, "cpu", backend, "/models/medium"),
|
||||
),
|
||||
patch("local_transcriber.cli._transcribe_file", return_value=tfr),
|
||||
patch("local_transcriber.cli.write_transcript"),
|
||||
):
|
||||
@@ -768,7 +1242,10 @@ def test_cli_batch_fallback_warning(tmp_path):
|
||||
patch("local_transcriber.cli.load_config", return_value={}),
|
||||
patch("local_transcriber.cli.validate_input_file", side_effect=lambda p: p),
|
||||
patch("local_transcriber.cli.detect_device", return_value="cuda"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "cpu", backend, "/models/medium")),
|
||||
patch(
|
||||
"local_transcriber.cli.load_model",
|
||||
return_value=(model, "cpu", backend, "/models/medium"),
|
||||
),
|
||||
patch("local_transcriber.cli._transcribe_file", return_value=tfr),
|
||||
patch("local_transcriber.cli.write_transcript"),
|
||||
):
|
||||
@@ -795,8 +1272,13 @@ def test_cli_batch_empty_speech_warning(tmp_path):
|
||||
patch("local_transcriber.cli.load_config", return_value={}),
|
||||
patch("local_transcriber.cli.validate_input_file", side_effect=lambda p: p),
|
||||
patch("local_transcriber.cli.detect_device", return_value="cpu"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "cpu", backend, "/models/medium")),
|
||||
patch("local_transcriber.cli._transcribe_file", side_effect=[tfr_empty, tfr_ok]),
|
||||
patch(
|
||||
"local_transcriber.cli.load_model",
|
||||
return_value=(model, "cpu", backend, "/models/medium"),
|
||||
),
|
||||
patch(
|
||||
"local_transcriber.cli._transcribe_file", side_effect=[tfr_empty, tfr_ok]
|
||||
),
|
||||
patch("local_transcriber.cli.write_transcript"),
|
||||
):
|
||||
out = runner.invoke(app, [str(a), str(b)])
|
||||
@@ -817,15 +1299,24 @@ def test_cli_batch_midstream_fallback_warning(tmp_path):
|
||||
model_cpu = _make_model()
|
||||
backend = _make_backend()
|
||||
result = _make_result(device_used="cpu")
|
||||
tfr_fallback = _make_tfr(result=result, model=model_cpu, actual_device="cpu", backend=backend)
|
||||
tfr_ok = _make_tfr(result=result, model=model_cpu, actual_device="cpu", backend=backend)
|
||||
tfr_fallback = _make_tfr(
|
||||
result=result, model=model_cpu, actual_device="cpu", backend=backend
|
||||
)
|
||||
tfr_ok = _make_tfr(
|
||||
result=result, model=model_cpu, actual_device="cpu", backend=backend
|
||||
)
|
||||
|
||||
with (
|
||||
patch("local_transcriber.cli.load_config", return_value={}),
|
||||
patch("local_transcriber.cli.validate_input_file", side_effect=lambda p: p),
|
||||
patch("local_transcriber.cli.detect_device", return_value="cuda"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model_gpu, "cuda", backend, "/models/medium")),
|
||||
patch("local_transcriber.cli._transcribe_file", side_effect=[tfr_fallback, tfr_ok]),
|
||||
patch(
|
||||
"local_transcriber.cli.load_model",
|
||||
return_value=(model_gpu, "cuda", backend, "/models/medium"),
|
||||
),
|
||||
patch(
|
||||
"local_transcriber.cli._transcribe_file", side_effect=[tfr_fallback, tfr_ok]
|
||||
),
|
||||
patch("local_transcriber.cli.write_transcript"),
|
||||
):
|
||||
out = runner.invoke(app, [str(a), str(b)])
|
||||
@@ -864,8 +1355,14 @@ def test_cli_batch_model_loaded_once(tmp_path):
|
||||
|
||||
|
||||
def test_format_device_info_openvino_gpu():
|
||||
with patch("local_transcriber.cli.get_intel_gpu_name", return_value="Intel(R) Arc(TM) 140T GPU"):
|
||||
assert _format_device_info("openvino-gpu") == "OpenVINO (Intel(R) Arc(TM) 140T GPU)"
|
||||
with patch(
|
||||
"local_transcriber.cli.get_intel_gpu_name",
|
||||
return_value="Intel(R) Arc(TM) 140T GPU",
|
||||
):
|
||||
assert (
|
||||
_format_device_info("openvino-gpu")
|
||||
== "OpenVINO (Intel(R) Arc(TM) 140T GPU)"
|
||||
)
|
||||
|
||||
|
||||
def test_format_device_info_openvino_gpu_no_name():
|
||||
@@ -900,9 +1397,13 @@ def test_cli_openvino_gpu_happy_path(tmp_path):
|
||||
audio.write_bytes(b"fake")
|
||||
result = _make_result(device_used="openvino-gpu")
|
||||
|
||||
patches = _single_patches(result=result, tmp_file=audio, actual_device="openvino-gpu")
|
||||
patches = _single_patches(
|
||||
result=result, tmp_file=audio, actual_device="openvino-gpu"
|
||||
)
|
||||
with patches[0], patches[1], patches[2], patches[3], patches[4], patches[5]:
|
||||
with patch("local_transcriber.cli.get_intel_gpu_name", return_value="Intel Arc 140T"):
|
||||
with patch(
|
||||
"local_transcriber.cli.get_intel_gpu_name", return_value="Intel Arc 140T"
|
||||
):
|
||||
out = runner.invoke(app, [str(audio), "--device", "openvino-gpu"])
|
||||
|
||||
assert out.exit_code == 0
|
||||
@@ -915,8 +1416,12 @@ def test_cli_openvino_alias_resolves_to_gpu(tmp_path):
|
||||
result = _make_result(device_used="openvino-gpu")
|
||||
model = _make_model()
|
||||
backend = _make_backend()
|
||||
tfr = _make_tfr(result=result, model=model, actual_device="openvino-gpu", backend=backend)
|
||||
mock_load_model = MagicMock(return_value=(model, "openvino-gpu", backend, "/models/medium"))
|
||||
tfr = _make_tfr(
|
||||
result=result, model=model, actual_device="openvino-gpu", backend=backend
|
||||
)
|
||||
mock_load_model = MagicMock(
|
||||
return_value=(model, "openvino-gpu", backend, "/models/medium")
|
||||
)
|
||||
|
||||
with (
|
||||
patch("local_transcriber.cli.load_config", return_value={}),
|
||||
@@ -925,7 +1430,9 @@ def test_cli_openvino_alias_resolves_to_gpu(tmp_path):
|
||||
patch("local_transcriber.cli.load_model", mock_load_model),
|
||||
patch("local_transcriber.cli._transcribe_file", return_value=tfr),
|
||||
patch("local_transcriber.cli.write_transcript"),
|
||||
patch("local_transcriber.cli.get_intel_gpu_name", return_value="Intel Arc 140T"),
|
||||
patch(
|
||||
"local_transcriber.cli.get_intel_gpu_name", return_value="Intel Arc 140T"
|
||||
),
|
||||
):
|
||||
out = runner.invoke(app, [str(audio), "--device", "openvino"])
|
||||
|
||||
@@ -1000,7 +1507,9 @@ def test_cli_install_menu_success(tmp_path):
|
||||
cmd_path = tmp_path / "Transcribe.cmd"
|
||||
|
||||
with (
|
||||
patch("local_transcriber.cli.install_context_menu", return_value=cmd_path) as mock_install,
|
||||
patch(
|
||||
"local_transcriber.cli.install_context_menu", return_value=cmd_path
|
||||
) as mock_install,
|
||||
patch("local_transcriber.cli.load_config") as mock_load_config,
|
||||
patch("local_transcriber.cli.sys") as mock_sys,
|
||||
):
|
||||
@@ -1018,7 +1527,9 @@ def test_cli_uninstall_menu_success(tmp_path):
|
||||
cmd_path = tmp_path / "Transcribe.cmd"
|
||||
|
||||
with (
|
||||
patch("local_transcriber.cli.uninstall_context_menu", return_value=cmd_path) as mock_uninstall,
|
||||
patch(
|
||||
"local_transcriber.cli.uninstall_context_menu", return_value=cmd_path
|
||||
) as mock_uninstall,
|
||||
patch("local_transcriber.cli.load_config") as mock_load_config,
|
||||
patch("local_transcriber.cli.sys") as mock_sys,
|
||||
):
|
||||
@@ -1079,7 +1590,10 @@ def test_cli_menu_flags_available_only_on_windows():
|
||||
|
||||
def test_cli_menu_runtime_error_has_no_verbose_hint():
|
||||
with (
|
||||
patch("local_transcriber.cli.install_context_menu", side_effect=RuntimeError("нет APPDATA")),
|
||||
patch(
|
||||
"local_transcriber.cli.install_context_menu",
|
||||
side_effect=RuntimeError("нет APPDATA"),
|
||||
),
|
||||
patch("local_transcriber.cli.sys") as mock_sys,
|
||||
):
|
||||
mock_sys.platform = "win32"
|
||||
@@ -1169,7 +1683,10 @@ def test_cli_quality_warning_batch_includes_file_name(tmp_path):
|
||||
patch("local_transcriber.cli.load_config", return_value={}),
|
||||
patch("local_transcriber.cli.validate_input_file", side_effect=lambda p: p),
|
||||
patch("local_transcriber.cli.detect_device", return_value="cpu"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "cpu", backend, "/models/medium")),
|
||||
patch(
|
||||
"local_transcriber.cli.load_model",
|
||||
return_value=(model, "cpu", backend, "/models/medium"),
|
||||
),
|
||||
patch("local_transcriber.cli._transcribe_file", side_effect=[tfr_warn, tfr_ok]),
|
||||
patch("local_transcriber.cli.write_transcript"),
|
||||
patch("local_transcriber.cli.console", Console(stderr=True, width=1000)),
|
||||
@@ -1178,8 +1695,7 @@ def test_cli_quality_warning_batch_includes_file_name(tmp_path):
|
||||
|
||||
assert out.exit_code == 0
|
||||
assert (
|
||||
" a.mp3: транскрипт покрывает 01:00 из 10:00 — "
|
||||
"возможна потеря хвоста записи"
|
||||
" a.mp3: транскрипт покрывает 01:00 из 10:00 — возможна потеря хвоста записи"
|
||||
) in out.output
|
||||
|
||||
|
||||
|
||||
Reference in new issue
Block a user