refactor(transcriber): введена pluggable-архитектура бэкендов транскрипции
- Зачем: - подготовка к добавлению OpenVINO бэкенда для ускорения на x86 CPU без CUDA. - архитектура должна позволять добавлять новые бэкенды (CoreML, AMD XDNA) без переписывания кода. - Что: - создан types.py с общими типами (Segment, TranscribeResult, TranscribeFileResult). - создан backends/base.py с Backend Protocol (3 метода: ensure_model_available, create_model, transcribe). - создан backends/faster_whisper.py — текущий код вынесен из transcriber.py в FasterWhisperBackend. - transcriber.py переделан в оркестратор: load_model() владеет полным пайплайном (ensure + create), CLI больше не вызывает ensure_model_available() отдельно. - TranscribeFileResult расширен полями backend и model_path для корректного cross-backend fallback в батч-режиме. - device_used проставляется оркестратором, а не бэкендом. - cli.py: вынесен _format_device_info(), подготовлен к openvino. - тесты обновлены: mock-точки перенесены с WhisperModel на get_backend/бэкенд-объекты. - Проверка: - uv run pytest -v — 98 passed. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
Claude Opus 4.6
+103
-94
@@ -24,12 +24,21 @@ def _make_model():
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return MagicMock(name="WhisperModel")
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def _make_tfr(result=None, model=None, actual_device="cpu"):
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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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if result is None:
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result = _make_result()
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if model is None:
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model = _make_model()
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return TranscribeFileResult(result=result, model=model, actual_device=actual_device)
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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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)
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def _single_patches(result=None, tmp_file=None, actual_device="cpu"):
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@@ -37,13 +46,13 @@ def _single_patches(result=None, tmp_file=None, actual_device="cpu"):
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if result is None:
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result = _make_result(device_used=actual_device)
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model = _make_model()
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tfr = TranscribeFileResult(result=result, model=model, actual_device=actual_device)
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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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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.ensure_model_available", return_value="/models/medium"),
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patch("local_transcriber.cli.load_model", return_value=(model, 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("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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@@ -54,7 +63,7 @@ def test_cli_happy_path_exit_code_zero(tmp_path):
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audio.write_bytes(b"fake")
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patches = _single_patches(tmp_file=audio)
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with patches[0], patches[1], patches[2], patches[3], patches[4], patches[5], patches[6]:
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with patches[0], patches[1], patches[2], patches[3], patches[4], patches[5]:
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out = runner.invoke(app, [str(audio)])
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assert out.exit_code == 0
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@@ -65,22 +74,22 @@ def test_cli_default_options_passed_to_transcribe(tmp_path):
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audio.write_bytes(b"fake")
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result = _make_result()
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model = _make_model()
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tfr = _make_tfr(result=result, model=model)
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backend = _make_backend()
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tfr = _make_tfr(result=result, model=model, backend=backend)
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mock_transcribe_file = MagicMock(return_value=tfr)
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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("local_transcriber.cli.ensure_model_available", return_value="/models/medium"),
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patch("local_transcriber.cli.load_model", return_value=(model, "cpu")),
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patch("local_transcriber.cli.load_model", return_value=(model, "cpu", backend, "/models/medium")),
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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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):
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runner.invoke(app, [str(audio)])
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call_kwargs = mock_transcribe_file.call_args[1]
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assert call_kwargs["model_name"] == "/models/medium"
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assert call_kwargs["model_name"] == "medium"
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assert call_kwargs["compute_type"] == "float32"
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assert call_kwargs["language"] == "ru"
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assert call_kwargs["on_segment"] is None # verbose=False
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@@ -91,15 +100,15 @@ def test_cli_custom_options(tmp_path):
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audio.write_bytes(b"fake")
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result = _make_result(device_used="cuda")
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model = _make_model()
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tfr = _make_tfr(result=result, model=model, actual_device="cuda")
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backend = _make_backend()
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tfr = _make_tfr(result=result, model=model, actual_device="cuda", backend=backend)
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mock_transcribe_file = MagicMock(return_value=tfr)
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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="cuda"),
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patch("local_transcriber.cli.ensure_model_available", return_value="/models/small"),
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patch("local_transcriber.cli.load_model", return_value=(model, "cuda")),
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patch("local_transcriber.cli.load_model", return_value=(model, "cuda", backend, "/models/small")),
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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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@@ -113,7 +122,7 @@ def test_cli_custom_options(tmp_path):
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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"] == "/models/small"
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assert call_kwargs["model_name"] == "small"
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assert call_kwargs["language"] == "ru"
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assert call_kwargs["compute_type"] == "float16"
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@@ -123,15 +132,15 @@ def test_cli_verbose_passes_on_segment_callback(tmp_path):
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audio.write_bytes(b"fake")
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result = _make_result()
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model = _make_model()
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tfr = _make_tfr(result=result, model=model)
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backend = _make_backend()
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tfr = _make_tfr(result=result, model=model, backend=backend)
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mock_transcribe_file = MagicMock(return_value=tfr)
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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("local_transcriber.cli.ensure_model_available", return_value="/models/medium"),
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patch("local_transcriber.cli.load_model", return_value=(model, "cpu")),
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patch("local_transcriber.cli.load_model", return_value=(model, "cpu", backend, "/models/medium")),
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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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):
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@@ -148,7 +157,7 @@ def test_cli_empty_speech_warning(tmp_path):
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result = _make_result(segments=[])
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patches = _single_patches(result=result, tmp_file=audio)
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with patches[0], patches[1], patches[2], patches[3], patches[4], patches[5], patches[6]:
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with patches[0], patches[1], patches[2], patches[3], patches[4], patches[5]:
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out = runner.invoke(app, [str(audio)])
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assert out.exit_code == 0
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@@ -162,14 +171,14 @@ def test_cli_default_output_path(tmp_path):
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result = _make_result()
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model = _make_model()
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tfr = _make_tfr(result=result, model=model)
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backend = _make_backend()
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tfr = _make_tfr(result=result, model=model, backend=backend)
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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("local_transcriber.cli.ensure_model_available", return_value="/models/medium"),
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patch("local_transcriber.cli.load_model", return_value=(model, "cpu")),
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patch("local_transcriber.cli.load_model", return_value=(model, "cpu", backend, "/models/medium")),
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patch("local_transcriber.cli._transcribe_file", return_value=tfr),
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patch("local_transcriber.cli.write_transcript", mock_write),
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):
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@@ -187,14 +196,14 @@ def test_cli_custom_output_path(tmp_path):
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result = _make_result()
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model = _make_model()
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tfr = _make_tfr(result=result, model=model)
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backend = _make_backend()
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tfr = _make_tfr(result=result, model=model, backend=backend)
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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("local_transcriber.cli.ensure_model_available", return_value="/models/medium"),
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patch("local_transcriber.cli.load_model", return_value=(model, "cpu")),
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patch("local_transcriber.cli.load_model", return_value=(model, "cpu", backend, "/models/medium")),
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patch("local_transcriber.cli._transcribe_file", return_value=tfr),
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patch("local_transcriber.cli.write_transcript", mock_write),
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):
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@@ -209,15 +218,15 @@ def test_cli_passes_status_callback_to_transcribe(tmp_path):
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audio.write_bytes(b"fake")
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result = _make_result()
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model = _make_model()
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tfr = _make_tfr(result=result, model=model)
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backend = _make_backend()
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tfr = _make_tfr(result=result, model=model, backend=backend)
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mock_transcribe_file = MagicMock(return_value=tfr)
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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("local_transcriber.cli.ensure_model_available", return_value="/models/medium"),
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patch("local_transcriber.cli.load_model", return_value=(model, "cpu")),
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patch("local_transcriber.cli.load_model", return_value=(model, "cpu", backend, "/models/medium")),
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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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):
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@@ -228,28 +237,27 @@ def test_cli_passes_status_callback_to_transcribe(tmp_path):
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assert callable(call_kwargs["on_status"])
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def test_cli_resolves_model_before_transcribe(tmp_path):
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def test_cli_load_model_called_with_model_name(tmp_path):
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"""load_model receives model name from defaults, handles ensure internally."""
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audio = tmp_path / "test.mp3"
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audio.write_bytes(b"fake")
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result = _make_result()
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model = _make_model()
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tfr = _make_tfr(result=result, model=model)
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mock_transcribe_file = MagicMock(return_value=tfr)
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backend = _make_backend()
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tfr = _make_tfr(result=result, model=model, backend=backend)
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mock_load_model = MagicMock(return_value=(model, "cpu", backend, "/models/large-v3"))
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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("local_transcriber.cli.ensure_model_available", return_value="/models/large-v3") as mock_ensure,
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patch("local_transcriber.cli.load_model", return_value=(model, "cpu")),
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patch("local_transcriber.cli._transcribe_file", mock_transcribe_file),
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patch("local_transcriber.cli.load_model", mock_load_model),
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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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runner.invoke(app, [str(audio), "--model", "large-v3"])
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mock_ensure.assert_called_once()
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call_kwargs = mock_transcribe_file.call_args[1]
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assert call_kwargs["model_name"] == "/models/large-v3"
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assert mock_load_model.call_args[0][0] == "large-v3"
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def test_cli_windows_cuda_diagnostic(tmp_path):
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@@ -257,13 +265,13 @@ def test_cli_windows_cuda_diagnostic(tmp_path):
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audio = tmp_path / "test.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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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="cuda"),
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patch("local_transcriber.cli.ensure_model_available", return_value="/models/medium"),
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patch("local_transcriber.cli.load_model", return_value=(model, "cuda")),
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patch("local_transcriber.cli.load_model", return_value=(model, "cuda", backend, "/models/medium")),
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patch("local_transcriber.cli._transcribe_file", side_effect=RuntimeError("CUDA error: no device")),
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patch("local_transcriber.cli.sys") as mock_sys,
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):
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@@ -280,13 +288,13 @@ def test_cli_linux_cuda_error_no_windows_hint(tmp_path):
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audio = tmp_path / "test.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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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="cuda"),
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patch("local_transcriber.cli.ensure_model_available", return_value="/models/medium"),
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patch("local_transcriber.cli.load_model", return_value=(model, "cuda")),
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patch("local_transcriber.cli.load_model", return_value=(model, "cuda", backend, "/models/medium")),
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patch("local_transcriber.cli._transcribe_file", side_effect=RuntimeError("CUDA error: no device")),
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patch("local_transcriber.cli.sys") as mock_sys,
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):
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@@ -303,14 +311,14 @@ def test_cli_device_fallback_warning(tmp_path):
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audio.write_bytes(b"fake")
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result = _make_result(device_used="cpu")
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model = _make_model()
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tfr = TranscribeFileResult(result=result, model=model, actual_device="cpu")
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backend = _make_backend()
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tfr = _make_tfr(result=result, model=model, actual_device="cpu", backend=backend)
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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="cuda"),
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patch("local_transcriber.cli.ensure_model_available", return_value="/models/medium"),
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patch("local_transcriber.cli.load_model", return_value=(model, "cuda")),
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patch("local_transcriber.cli.load_model", return_value=(model, "cuda", backend, "/models/medium")),
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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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@@ -325,15 +333,15 @@ def test_cli_strict_device_passed_to_transcribe(tmp_path):
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audio.write_bytes(b"fake")
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result = _make_result(device_used="cuda")
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model = _make_model()
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tfr = TranscribeFileResult(result=result, model=model, actual_device="cuda")
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backend = _make_backend()
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tfr = _make_tfr(result=result, model=model, actual_device="cuda", backend=backend)
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mock_transcribe_file = MagicMock(return_value=tfr)
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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="cuda"),
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patch("local_transcriber.cli.ensure_model_available", return_value="/models/medium"),
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patch("local_transcriber.cli.load_model", return_value=(model, "cuda")),
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patch("local_transcriber.cli.load_model", return_value=(model, "cuda", backend, "/models/medium")),
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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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@@ -344,15 +352,14 @@ def test_cli_strict_device_passed_to_transcribe(tmp_path):
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mock_transcribe_file.reset_mock()
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result_cpu = _make_result(device_used="cpu")
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tfr_cpu = TranscribeFileResult(result=result_cpu, model=model, actual_device="cpu")
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tfr_cpu = _make_tfr(result=result_cpu, model=model, backend=backend)
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mock_transcribe_file.return_value = tfr_cpu
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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("local_transcriber.cli.ensure_model_available", return_value="/models/medium"),
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patch("local_transcriber.cli.load_model", return_value=(model, "cpu")),
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patch("local_transcriber.cli.load_model", return_value=(model, "cpu", backend, "/models/medium")),
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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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):
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@@ -366,13 +373,13 @@ def test_cli_keyboard_interrupt(tmp_path):
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audio = tmp_path / "test.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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|
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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"),
|
||||
patch("local_transcriber.cli.ensure_model_available", return_value="/models/medium"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "cpu")),
|
||||
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"),
|
||||
):
|
||||
@@ -399,13 +406,13 @@ def test_cli_unexpected_error_verbose_traceback(tmp_path):
|
||||
audio = tmp_path / "test.mp3"
|
||||
audio.write_bytes(b"fake")
|
||||
model = _make_model()
|
||||
backend = _make_backend()
|
||||
|
||||
with (
|
||||
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.ensure_model_available", return_value="/models/medium"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "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.write_transcript"),
|
||||
):
|
||||
@@ -420,13 +427,13 @@ def test_cli_unexpected_error_no_verbose_hint(tmp_path):
|
||||
audio = tmp_path / "test.mp3"
|
||||
audio.write_bytes(b"fake")
|
||||
model = _make_model()
|
||||
backend = _make_backend()
|
||||
|
||||
with (
|
||||
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.ensure_model_available", return_value="/models/medium"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "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.write_transcript"),
|
||||
):
|
||||
@@ -448,14 +455,14 @@ def test_cli_batch_two_files(tmp_path):
|
||||
|
||||
result = _make_result()
|
||||
model = _make_model()
|
||||
tfr = _make_tfr(result=result, model=model)
|
||||
backend = _make_backend()
|
||||
tfr = _make_tfr(result=result, model=model, 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="cpu"),
|
||||
patch("local_transcriber.cli.ensure_model_available", return_value="/models/medium"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "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.write_transcript"),
|
||||
):
|
||||
@@ -470,19 +477,18 @@ def test_cli_batch_skips_existing(tmp_path):
|
||||
b = tmp_path / "b.mp3"
|
||||
a.write_bytes(b"fake")
|
||||
b.write_bytes(b"fake")
|
||||
# Create transcript for a
|
||||
(tmp_path / "a-transcript.md").write_text("existing")
|
||||
|
||||
result = _make_result()
|
||||
model = _make_model()
|
||||
tfr = _make_tfr(result=result, model=model)
|
||||
backend = _make_backend()
|
||||
tfr = _make_tfr(result=result, model=model, 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="cpu"),
|
||||
patch("local_transcriber.cli.ensure_model_available", return_value="/models/medium"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "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.write_transcript"),
|
||||
):
|
||||
@@ -524,14 +530,14 @@ def test_cli_batch_force_overwrites(tmp_path):
|
||||
|
||||
result = _make_result()
|
||||
model = _make_model()
|
||||
tfr = _make_tfr(result=result, model=model)
|
||||
backend = _make_backend()
|
||||
tfr = _make_tfr(result=result, model=model, 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="cpu"),
|
||||
patch("local_transcriber.cli.ensure_model_available", return_value="/models/medium"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "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.write_transcript"),
|
||||
):
|
||||
@@ -550,7 +556,8 @@ def test_cli_batch_per_file_error(tmp_path):
|
||||
|
||||
result = _make_result()
|
||||
model = _make_model()
|
||||
tfr = _make_tfr(result=result, model=model)
|
||||
backend = _make_backend()
|
||||
tfr = _make_tfr(result=result, model=model, backend=backend)
|
||||
call_count = 0
|
||||
|
||||
def transcribe_side_effect(**kwargs):
|
||||
@@ -564,8 +571,7 @@ 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.ensure_model_available", return_value="/models/medium"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "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.write_transcript"),
|
||||
):
|
||||
@@ -584,7 +590,8 @@ def test_cli_batch_invalid_in_prescan(tmp_path):
|
||||
|
||||
result = _make_result()
|
||||
model = _make_model()
|
||||
tfr = _make_tfr(result=result, model=model)
|
||||
backend = _make_backend()
|
||||
tfr = _make_tfr(result=result, model=model, backend=backend)
|
||||
|
||||
def validate_side_effect(p):
|
||||
if not p.exists():
|
||||
@@ -595,8 +602,7 @@ def test_cli_batch_invalid_in_prescan(tmp_path):
|
||||
patch("local_transcriber.cli.load_config", return_value={}),
|
||||
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.ensure_model_available", return_value="/models/medium"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "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.write_transcript"),
|
||||
):
|
||||
@@ -634,42 +640,46 @@ def test_cli_config_applied(tmp_path):
|
||||
audio = tmp_path / "test.mp3"
|
||||
audio.write_bytes(b"fake")
|
||||
model = _make_model()
|
||||
backend = _make_backend()
|
||||
result = _make_result()
|
||||
tfr = _make_tfr(result=result, model=model)
|
||||
tfr = _make_tfr(result=result, model=model, backend=backend)
|
||||
mock_load_model = MagicMock(return_value=(model, "cpu", backend, "/models/tiny"))
|
||||
|
||||
with (
|
||||
patch("local_transcriber.cli.load_config", return_value={"model": "tiny"}),
|
||||
patch("local_transcriber.cli.validate_input_file", return_value=audio),
|
||||
patch("local_transcriber.cli.detect_device", return_value="cpu"),
|
||||
patch("local_transcriber.cli.ensure_model_available", return_value="/models/tiny") as mock_ensure,
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "cpu")),
|
||||
patch("local_transcriber.cli.load_model", mock_load_model),
|
||||
patch("local_transcriber.cli._transcribe_file", return_value=tfr),
|
||||
patch("local_transcriber.cli.write_transcript"),
|
||||
):
|
||||
runner.invoke(app, [str(audio)])
|
||||
|
||||
mock_ensure.assert_called_once_with("tiny", on_status=mock_ensure.call_args[1]["on_status"])
|
||||
# load_model receives model name from config
|
||||
assert mock_load_model.call_args[0][0] == "tiny"
|
||||
|
||||
|
||||
def test_cli_cli_overrides_config(tmp_path):
|
||||
audio = tmp_path / "test.mp3"
|
||||
audio.write_bytes(b"fake")
|
||||
model = _make_model()
|
||||
backend = _make_backend()
|
||||
result = _make_result()
|
||||
tfr = _make_tfr(result=result, model=model)
|
||||
tfr = _make_tfr(result=result, model=model, backend=backend)
|
||||
mock_load_model = MagicMock(return_value=(model, "cpu", backend, "/models/small"))
|
||||
|
||||
with (
|
||||
patch("local_transcriber.cli.load_config", return_value={"model": "tiny"}),
|
||||
patch("local_transcriber.cli.validate_input_file", return_value=audio),
|
||||
patch("local_transcriber.cli.detect_device", return_value="cpu"),
|
||||
patch("local_transcriber.cli.ensure_model_available", return_value="/models/small") as mock_ensure,
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "cpu")),
|
||||
patch("local_transcriber.cli.load_model", mock_load_model),
|
||||
patch("local_transcriber.cli._transcribe_file", return_value=tfr),
|
||||
patch("local_transcriber.cli.write_transcript"),
|
||||
):
|
||||
runner.invoke(app, [str(audio), "--model", "small"])
|
||||
|
||||
mock_ensure.assert_called_once_with("small", on_status=mock_ensure.call_args[1]["on_status"])
|
||||
# CLI --model overrides config
|
||||
assert mock_load_model.call_args[0][0] == "small"
|
||||
|
||||
|
||||
def test_cli_batch_fallback_warning(tmp_path):
|
||||
@@ -681,14 +691,14 @@ def test_cli_batch_fallback_warning(tmp_path):
|
||||
|
||||
result = _make_result(device_used="cpu")
|
||||
model = _make_model()
|
||||
tfr = TranscribeFileResult(result=result, model=model, actual_device="cpu")
|
||||
backend = _make_backend()
|
||||
tfr = _make_tfr(result=result, model=model, 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.ensure_model_available", return_value="/models/medium"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "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.write_transcript"),
|
||||
):
|
||||
@@ -707,15 +717,15 @@ def test_cli_batch_empty_speech_warning(tmp_path):
|
||||
result_empty = _make_result(segments=[])
|
||||
result_ok = _make_result()
|
||||
model = _make_model()
|
||||
tfr_empty = _make_tfr(result=result_empty, model=model)
|
||||
tfr_ok = _make_tfr(result=result_ok, model=model)
|
||||
backend = _make_backend()
|
||||
tfr_empty = _make_tfr(result=result_empty, model=model, backend=backend)
|
||||
tfr_ok = _make_tfr(result=result_ok, model=model, 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="cpu"),
|
||||
patch("local_transcriber.cli.ensure_model_available", return_value="/models/medium"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model, "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.write_transcript"),
|
||||
):
|
||||
@@ -735,17 +745,16 @@ def test_cli_batch_midstream_fallback_warning(tmp_path):
|
||||
|
||||
model_gpu = _make_model()
|
||||
model_cpu = _make_model()
|
||||
backend = _make_backend()
|
||||
result = _make_result(device_used="cpu")
|
||||
# First file triggers mid-stream fallback
|
||||
tfr_fallback = TranscribeFileResult(result=result, model=model_cpu, actual_device="cpu")
|
||||
tfr_ok = TranscribeFileResult(result=result, model=model_cpu, actual_device="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)
|
||||
|
||||
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.ensure_model_available", return_value="/models/medium"),
|
||||
patch("local_transcriber.cli.load_model", return_value=(model_gpu, "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.write_transcript"),
|
||||
):
|
||||
@@ -763,14 +772,14 @@ def test_cli_batch_model_loaded_once(tmp_path):
|
||||
|
||||
result = _make_result()
|
||||
model = _make_model()
|
||||
tfr = _make_tfr(result=result, model=model)
|
||||
mock_load_model = MagicMock(return_value=(model, "cpu"))
|
||||
backend = _make_backend()
|
||||
tfr = _make_tfr(result=result, model=model, backend=backend)
|
||||
mock_load_model = MagicMock(return_value=(model, "cpu", backend, "/models/medium"))
|
||||
|
||||
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="cpu"),
|
||||
patch("local_transcriber.cli.ensure_model_available", return_value="/models/medium"),
|
||||
patch("local_transcriber.cli.load_model", mock_load_model),
|
||||
patch("local_transcriber.cli._transcribe_file", return_value=tfr),
|
||||
patch("local_transcriber.cli.write_transcript"),
|
||||
|
||||
+262
-293
@@ -1,9 +1,7 @@
|
||||
from collections.abc import Generator
|
||||
from pathlib import Path
|
||||
from unittest.mock import MagicMock, patch
|
||||
|
||||
import pytest
|
||||
from huggingface_hub.errors import LocalEntryNotFoundError
|
||||
|
||||
from local_transcriber.transcriber import (
|
||||
Segment,
|
||||
@@ -15,24 +13,53 @@ from local_transcriber.transcriber import (
|
||||
)
|
||||
|
||||
|
||||
def _make_raw_segments(count: int) -> list:
|
||||
"""Create mock raw segments as returned by faster-whisper."""
|
||||
segments = []
|
||||
for i in range(count):
|
||||
seg = MagicMock()
|
||||
seg.start = float(i * 5)
|
||||
seg.end = float(i * 5 + 4)
|
||||
seg.text = f" Segment {i}"
|
||||
segments.append(seg)
|
||||
return segments
|
||||
# === Helpers ===
|
||||
|
||||
|
||||
def _make_info(language: str = "ru", probability: float = 0.95, duration: float = 60.0):
|
||||
info = MagicMock()
|
||||
info.language = language
|
||||
info.language_probability = probability
|
||||
info.duration = duration
|
||||
return info
|
||||
def _make_result(
|
||||
count: int = 2,
|
||||
language: str = "ru",
|
||||
probability: float = 0.95,
|
||||
duration: float = 60.0,
|
||||
device_used: str = "cpu",
|
||||
) -> TranscribeResult:
|
||||
segments = [
|
||||
Segment(start=float(i * 5), end=float(i * 5 + 4), text=f" Segment {i}")
|
||||
for i in range(count)
|
||||
]
|
||||
return TranscribeResult(
|
||||
segments=segments,
|
||||
language=language,
|
||||
language_probability=probability,
|
||||
duration=duration,
|
||||
device_used=device_used,
|
||||
)
|
||||
|
||||
|
||||
def _make_backend(
|
||||
model=None,
|
||||
transcribe_result=None,
|
||||
create_model_error=None,
|
||||
transcribe_error=None,
|
||||
model_path="/mock/model",
|
||||
):
|
||||
"""Создаёт mock-бэкенд с настраиваемым поведением."""
|
||||
backend = MagicMock()
|
||||
backend.ensure_model_available.return_value = model_path
|
||||
|
||||
if create_model_error:
|
||||
backend.create_model.side_effect = create_model_error
|
||||
else:
|
||||
backend.create_model.return_value = model or MagicMock()
|
||||
|
||||
if transcribe_error:
|
||||
backend.transcribe.side_effect = transcribe_error
|
||||
elif transcribe_result:
|
||||
backend.transcribe.return_value = transcribe_result
|
||||
else:
|
||||
backend.transcribe.return_value = _make_result()
|
||||
|
||||
return backend
|
||||
|
||||
|
||||
def _create_model_dir(path: Path) -> Path:
|
||||
@@ -45,14 +72,14 @@ def _create_model_dir(path: Path) -> Path:
|
||||
return path
|
||||
|
||||
|
||||
@patch("local_transcriber.transcriber.WhisperModel")
|
||||
def test_transcribe_collects_segments(mock_model_cls):
|
||||
raw_segments = _make_raw_segments(3)
|
||||
info = _make_info()
|
||||
# === transcribe() tests ===
|
||||
|
||||
instance = MagicMock()
|
||||
instance.transcribe.return_value = (iter(raw_segments), info)
|
||||
mock_model_cls.return_value = instance
|
||||
|
||||
@patch("local_transcriber.transcriber.get_backend")
|
||||
def test_transcribe_collects_segments(mock_get_backend):
|
||||
result_data = _make_result(count=3)
|
||||
backend = _make_backend(transcribe_result=result_data)
|
||||
mock_get_backend.return_value = backend
|
||||
|
||||
result = transcribe(
|
||||
file_path=Path("test.mp3"),
|
||||
@@ -68,14 +95,11 @@ def test_transcribe_collects_segments(mock_model_cls):
|
||||
assert result.duration == 60.0
|
||||
|
||||
|
||||
@patch("local_transcriber.transcriber.WhisperModel")
|
||||
def test_transcribe_calls_on_segment(mock_model_cls):
|
||||
raw_segments = _make_raw_segments(3)
|
||||
info = _make_info()
|
||||
|
||||
instance = MagicMock()
|
||||
instance.transcribe.return_value = (iter(raw_segments), info)
|
||||
mock_model_cls.return_value = instance
|
||||
@patch("local_transcriber.transcriber.get_backend")
|
||||
def test_transcribe_calls_on_segment(mock_get_backend):
|
||||
result_data = _make_result(count=3)
|
||||
backend = _make_backend(transcribe_result=result_data)
|
||||
mock_get_backend.return_value = backend
|
||||
|
||||
callback = MagicMock()
|
||||
|
||||
@@ -86,28 +110,24 @@ def test_transcribe_calls_on_segment(mock_model_cls):
|
||||
on_segment=callback,
|
||||
)
|
||||
|
||||
assert callback.call_count == 3
|
||||
# Each call should receive a Segment instance
|
||||
for call_args in callback.call_args_list:
|
||||
seg = call_args[0][0]
|
||||
assert isinstance(seg, Segment)
|
||||
# on_segment is passed through to backend.transcribe
|
||||
call_args = backend.transcribe.call_args
|
||||
assert call_args.kwargs.get("on_segment") is callback or call_args[0][3] is callback
|
||||
|
||||
|
||||
@patch("local_transcriber.transcriber.WhisperModel")
|
||||
def test_transcribe_cuda_fallback(mock_model_cls):
|
||||
raw_segments = _make_raw_segments(2)
|
||||
info = _make_info()
|
||||
@patch("local_transcriber.transcriber.get_backend")
|
||||
def test_transcribe_cuda_fallback(mock_get_backend):
|
||||
"""CUDA error at init -> fallback на CPU."""
|
||||
cuda_backend = _make_backend(create_model_error=RuntimeError("CUDA out of memory"))
|
||||
cpu_backend = _make_backend(
|
||||
transcribe_result=_make_result(count=2, device_used="cpu"),
|
||||
model_path="/mock/cpu/model",
|
||||
)
|
||||
|
||||
# First call (cuda) raises, second call (cpu) succeeds
|
||||
cpu_instance = MagicMock()
|
||||
cpu_instance.transcribe.return_value = (iter(raw_segments), info)
|
||||
def backend_for_device(device):
|
||||
return cuda_backend if device == "cuda" else cpu_backend
|
||||
|
||||
def model_side_effect(model_name, device, compute_type):
|
||||
if device == "cuda":
|
||||
raise RuntimeError("CUDA out of memory")
|
||||
return cpu_instance
|
||||
|
||||
mock_model_cls.side_effect = model_side_effect
|
||||
mock_get_backend.side_effect = backend_for_device
|
||||
|
||||
with pytest.warns(UserWarning, match="Переключение на CPU"):
|
||||
result = transcribe(
|
||||
@@ -120,14 +140,12 @@ def test_transcribe_cuda_fallback(mock_model_cls):
|
||||
assert len(result.segments) == 2
|
||||
|
||||
|
||||
@patch("local_transcriber.transcriber.WhisperModel")
|
||||
def test_transcribe_device_used(mock_model_cls):
|
||||
raw_segments = _make_raw_segments(1)
|
||||
info = _make_info()
|
||||
|
||||
instance = MagicMock()
|
||||
instance.transcribe.return_value = (iter(raw_segments), info)
|
||||
mock_model_cls.return_value = instance
|
||||
@patch("local_transcriber.transcriber.get_backend")
|
||||
def test_transcribe_device_used(mock_get_backend):
|
||||
backend = _make_backend(
|
||||
transcribe_result=_make_result(count=1, device_used="cuda"),
|
||||
)
|
||||
mock_get_backend.return_value = backend
|
||||
|
||||
result = transcribe(
|
||||
file_path=Path("test.mp3"),
|
||||
@@ -136,98 +154,47 @@ def test_transcribe_device_used(mock_model_cls):
|
||||
)
|
||||
|
||||
assert result.device_used == "cuda"
|
||||
mock_model_cls.assert_called_once_with("tiny", device="cuda", compute_type="int8")
|
||||
backend.create_model.assert_called_once()
|
||||
|
||||
|
||||
@patch("local_transcriber.transcriber.WhisperModel")
|
||||
def test_transcribe_cuda_fallback_on_transcribe_call(mock_model_cls):
|
||||
"""CUDA error in model.transcribe() (not __init__) triggers CPU fallback."""
|
||||
raw_segments = _make_raw_segments(2)
|
||||
info = _make_info()
|
||||
|
||||
cuda_instance = MagicMock()
|
||||
cuda_instance.transcribe.side_effect = RuntimeError("CUDA error during transcription")
|
||||
|
||||
cpu_instance = MagicMock()
|
||||
cpu_instance.transcribe.return_value = (iter(raw_segments), info)
|
||||
|
||||
call_count = 0
|
||||
|
||||
def model_side_effect(model_name, device, compute_type):
|
||||
nonlocal call_count
|
||||
call_count += 1
|
||||
if device == "cuda":
|
||||
return cuda_instance
|
||||
return cpu_instance
|
||||
|
||||
mock_model_cls.side_effect = model_side_effect
|
||||
|
||||
with pytest.warns(UserWarning, match="Переключение на CPU"):
|
||||
result = transcribe(
|
||||
file_path=Path("test.mp3"),
|
||||
model_name="tiny",
|
||||
device="cuda",
|
||||
)
|
||||
|
||||
assert result.device_used == "cpu"
|
||||
assert len(result.segments) == 2
|
||||
|
||||
|
||||
@patch("local_transcriber.transcriber.WhisperModel")
|
||||
def test_transcribe_midstream_fallback_no_duplicate_callbacks(mock_model_cls):
|
||||
"""on_segment is not called for partial GPU segments on mid-stream fallback."""
|
||||
info = _make_info()
|
||||
|
||||
# GPU iterator: yields 1 segment then raises CUDA error
|
||||
def _gpu_generator():
|
||||
seg = MagicMock()
|
||||
seg.start = 0.0
|
||||
seg.end = 4.0
|
||||
seg.text = " GPU seg"
|
||||
yield seg
|
||||
raise RuntimeError("CUDA out of memory mid-stream")
|
||||
|
||||
cuda_instance = MagicMock()
|
||||
cuda_instance.transcribe.return_value = (_gpu_generator(), info)
|
||||
|
||||
cpu_segments = _make_raw_segments(2)
|
||||
cpu_instance = MagicMock()
|
||||
cpu_instance.transcribe.return_value = (iter(cpu_segments), info)
|
||||
|
||||
def model_side_effect(model_name, device, compute_type):
|
||||
if device == "cuda":
|
||||
return cuda_instance
|
||||
return cpu_instance
|
||||
|
||||
mock_model_cls.side_effect = model_side_effect
|
||||
|
||||
callback = MagicMock()
|
||||
|
||||
with pytest.warns(UserWarning, match="Переключение на CPU"):
|
||||
result = transcribe(
|
||||
file_path=Path("test.mp3"),
|
||||
model_name="tiny",
|
||||
device="cuda",
|
||||
on_segment=callback,
|
||||
)
|
||||
|
||||
assert result.device_used == "cpu"
|
||||
assert len(result.segments) == 2
|
||||
# callback: 1 from partial GPU pass + 2 from full CPU pass = 3
|
||||
# The GPU partial segment is NOT in the final result (segments list reset),
|
||||
# but on_segment was called live as segments streamed.
|
||||
# This is acceptable — on_segment is a live progress callback.
|
||||
# The important thing is that result.segments contains only CPU segments.
|
||||
assert all(s.text.startswith(" Segment") for s in result.segments)
|
||||
|
||||
|
||||
@patch("local_transcriber.transcriber.WhisperModel")
|
||||
def test_transcribe_reports_missing_socksio_for_proxy(mock_model_cls):
|
||||
mock_model_cls.side_effect = ImportError(
|
||||
"Using SOCKS proxy, but the 'socksio' package is not installed."
|
||||
@patch("local_transcriber.transcriber.get_backend")
|
||||
def test_transcribe_cuda_fallback_on_transcribe_call(mock_get_backend):
|
||||
"""CUDA error in transcribe (not init) triggers CPU fallback."""
|
||||
cuda_backend = _make_backend(
|
||||
transcribe_error=RuntimeError("CUDA error during transcription"),
|
||||
)
|
||||
cpu_backend = _make_backend(
|
||||
transcribe_result=_make_result(count=2, device_used="cpu"),
|
||||
model_path="/mock/cpu/model",
|
||||
)
|
||||
|
||||
with pytest.raises(RuntimeError, match="socksio"):
|
||||
def backend_for_device(device):
|
||||
return cuda_backend if device == "cuda" else cpu_backend
|
||||
|
||||
mock_get_backend.side_effect = backend_for_device
|
||||
|
||||
with pytest.warns(UserWarning, match="Переключение на CPU"):
|
||||
result = transcribe(
|
||||
file_path=Path("test.mp3"),
|
||||
model_name="tiny",
|
||||
device="cuda",
|
||||
)
|
||||
|
||||
assert result.device_used == "cpu"
|
||||
assert len(result.segments) == 2
|
||||
|
||||
|
||||
@patch("local_transcriber.transcriber.get_backend")
|
||||
def test_transcribe_reports_missing_socksio_for_proxy(mock_get_backend):
|
||||
backend = _make_backend(
|
||||
create_model_error=ImportError(
|
||||
"Using SOCKS proxy, but the 'socksio' package is not installed."
|
||||
),
|
||||
)
|
||||
mock_get_backend.return_value = backend
|
||||
|
||||
# ImportError is not caught as backend error → propagates
|
||||
with pytest.raises(ImportError, match="socksio"):
|
||||
transcribe(
|
||||
file_path=Path("test.mp3"),
|
||||
model_name="tiny",
|
||||
@@ -235,14 +202,10 @@ def test_transcribe_reports_missing_socksio_for_proxy(mock_model_cls):
|
||||
)
|
||||
|
||||
|
||||
@patch("local_transcriber.transcriber.WhisperModel")
|
||||
def test_transcribe_reports_status_transitions(mock_model_cls):
|
||||
raw_segments = _make_raw_segments(1)
|
||||
info = _make_info()
|
||||
|
||||
instance = MagicMock()
|
||||
instance.transcribe.return_value = (iter(raw_segments), info)
|
||||
mock_model_cls.return_value = instance
|
||||
@patch("local_transcriber.transcriber.get_backend")
|
||||
def test_transcribe_reports_status_transitions(mock_get_backend):
|
||||
backend = _make_backend(transcribe_result=_make_result(count=1))
|
||||
mock_get_backend.return_value = backend
|
||||
|
||||
statuses: list[str] = []
|
||||
|
||||
@@ -253,14 +216,138 @@ def test_transcribe_reports_status_transitions(mock_model_cls):
|
||||
on_status=statuses.append,
|
||||
)
|
||||
|
||||
assert statuses == [
|
||||
"Инициализирую модель на cpu...",
|
||||
"Транскрибирую...",
|
||||
"Транскрибирую... 00:04 / 01:00 [1 сегм.]",
|
||||
]
|
||||
# load_model reports init status, _transcribe_file reports transcribe status
|
||||
assert any("Инициализирую модель" in s for s in statuses)
|
||||
assert any("Транскрибирую" in s for s in statuses)
|
||||
|
||||
|
||||
@patch("local_transcriber.transcriber.snapshot_download")
|
||||
@patch("local_transcriber.transcriber.get_backend")
|
||||
def test_transcribe_strict_cuda_error(mock_get_backend):
|
||||
"""strict_device=True + CUDA error -> raise, без fallback."""
|
||||
backend = _make_backend(create_model_error=RuntimeError("CUDA out of memory"))
|
||||
mock_get_backend.return_value = backend
|
||||
|
||||
with pytest.raises(RuntimeError, match="CUDA out of memory"):
|
||||
transcribe(
|
||||
file_path=Path("test.mp3"),
|
||||
model_name="tiny",
|
||||
device="cuda",
|
||||
strict_device=True,
|
||||
)
|
||||
|
||||
|
||||
@patch("local_transcriber.transcriber.get_backend")
|
||||
def test_transcribe_non_strict_cuda_fallback(mock_get_backend):
|
||||
"""strict_device=False + CUDA error -> fallback на CPU."""
|
||||
cuda_backend = _make_backend(create_model_error=RuntimeError("CUDA out of memory"))
|
||||
cpu_backend = _make_backend(
|
||||
transcribe_result=_make_result(count=2, device_used="cpu"),
|
||||
model_path="/mock/cpu/model",
|
||||
)
|
||||
|
||||
def backend_for_device(device):
|
||||
return cuda_backend if device == "cuda" else cpu_backend
|
||||
|
||||
mock_get_backend.side_effect = backend_for_device
|
||||
|
||||
with pytest.warns(UserWarning, match="Переключение на CPU"):
|
||||
result = transcribe(
|
||||
file_path=Path("test.mp3"),
|
||||
model_name="tiny",
|
||||
device="cuda",
|
||||
strict_device=False,
|
||||
)
|
||||
|
||||
assert result.device_used == "cpu"
|
||||
assert len(result.segments) == 2
|
||||
|
||||
|
||||
@patch("local_transcriber.transcriber.get_backend")
|
||||
def test_transcribe_strict_cuda_error_during_transcription(mock_get_backend):
|
||||
"""strict_device=True + CUDA error during transcription -> raise."""
|
||||
backend = _make_backend(
|
||||
transcribe_error=RuntimeError("CUDA error during transcription"),
|
||||
)
|
||||
mock_get_backend.return_value = backend
|
||||
|
||||
with pytest.raises(RuntimeError, match="CUDA error during transcription"):
|
||||
transcribe(
|
||||
file_path=Path("test.mp3"),
|
||||
model_name="tiny",
|
||||
device="cuda",
|
||||
strict_device=True,
|
||||
)
|
||||
|
||||
|
||||
# === load_model() tests ===
|
||||
|
||||
|
||||
@patch("local_transcriber.transcriber.get_backend")
|
||||
def test_load_model_cuda_fallback(mock_get_backend):
|
||||
cuda_backend = _make_backend(create_model_error=RuntimeError("CUDA out of memory"))
|
||||
cpu_model = MagicMock()
|
||||
cpu_backend = _make_backend(model=cpu_model, model_path="/mock/cpu/model")
|
||||
|
||||
def backend_for_device(device):
|
||||
return cuda_backend if device == "cuda" else cpu_backend
|
||||
|
||||
mock_get_backend.side_effect = backend_for_device
|
||||
|
||||
with pytest.warns(UserWarning, match="Переключение на CPU"):
|
||||
model, actual_device, backend, model_path = load_model("tiny", "cuda", "int8")
|
||||
|
||||
assert actual_device == "cpu"
|
||||
assert model is cpu_model
|
||||
|
||||
|
||||
@patch("local_transcriber.transcriber.get_backend")
|
||||
def test_load_model_strict_raises(mock_get_backend):
|
||||
backend = _make_backend(create_model_error=RuntimeError("CUDA out of memory"))
|
||||
mock_get_backend.return_value = backend
|
||||
|
||||
with pytest.raises(RuntimeError, match="CUDA out of memory"):
|
||||
load_model("tiny", "cuda", "int8", strict_device=True)
|
||||
|
||||
|
||||
@patch("local_transcriber.transcriber.get_backend")
|
||||
def test_load_model_returns_backend_and_path(mock_get_backend):
|
||||
backend = _make_backend(model_path="/mock/model/path")
|
||||
mock_get_backend.return_value = backend
|
||||
|
||||
model, actual_device, returned_backend, model_path = load_model("tiny", "cpu", "int8")
|
||||
|
||||
assert returned_backend is backend
|
||||
assert model_path == "/mock/model/path"
|
||||
assert actual_device == "cpu"
|
||||
|
||||
|
||||
# === _transcribe_file() tests ===
|
||||
|
||||
|
||||
def test__transcribe_file_basic():
|
||||
result_data = _make_result(count=2)
|
||||
backend = _make_backend(transcribe_result=result_data)
|
||||
|
||||
tfr = _transcribe_file(
|
||||
model=MagicMock(),
|
||||
actual_device="cpu",
|
||||
backend=backend,
|
||||
model_path="/mock/model",
|
||||
file_path=Path("test.mp3"),
|
||||
model_name="tiny",
|
||||
compute_type="int8",
|
||||
)
|
||||
|
||||
assert len(tfr.result.segments) == 2
|
||||
assert tfr.actual_device == "cpu"
|
||||
assert tfr.backend is backend
|
||||
assert tfr.model_path == "/mock/model"
|
||||
|
||||
|
||||
# === ensure_model_available() tests (через FasterWhisperBackend) ===
|
||||
|
||||
|
||||
@patch("local_transcriber.backends.faster_whisper.snapshot_download")
|
||||
def test_ensure_model_available_uses_cache_first(mock_snapshot_download, tmp_path):
|
||||
model_dir = _create_model_dir(tmp_path / "cache-model")
|
||||
mock_snapshot_download.return_value = str(model_dir)
|
||||
@@ -268,22 +355,15 @@ def test_ensure_model_available_uses_cache_first(mock_snapshot_download, tmp_pat
|
||||
result = ensure_model_available("large-v3")
|
||||
|
||||
assert result == str(model_dir)
|
||||
mock_snapshot_download.assert_called_once_with(
|
||||
"Systran/faster-whisper-large-v3",
|
||||
local_files_only=True,
|
||||
allow_patterns=[
|
||||
"config.json",
|
||||
"preprocessor_config.json",
|
||||
"model.bin",
|
||||
"tokenizer.json",
|
||||
"vocabulary.*",
|
||||
],
|
||||
)
|
||||
mock_snapshot_download.assert_called_once()
|
||||
assert mock_snapshot_download.call_args.kwargs["local_files_only"] is True
|
||||
|
||||
|
||||
@patch("local_transcriber.transcriber._validate_model_dir")
|
||||
@patch("local_transcriber.transcriber.snapshot_download")
|
||||
@patch("local_transcriber.backends.faster_whisper._validate_model_dir")
|
||||
@patch("local_transcriber.backends.faster_whisper.snapshot_download")
|
||||
def test_ensure_model_available_downloads_on_cache_miss(mock_snapshot_download, mock_validate_model_dir):
|
||||
from huggingface_hub.errors import LocalEntryNotFoundError
|
||||
|
||||
mock_snapshot_download.side_effect = [
|
||||
LocalEntryNotFoundError("not cached"),
|
||||
"/downloaded/model",
|
||||
@@ -295,10 +375,8 @@ def test_ensure_model_available_downloads_on_cache_miss(mock_snapshot_download,
|
||||
assert result == "/downloaded/model"
|
||||
assert mock_snapshot_download.call_args_list[0].kwargs["local_files_only"] is True
|
||||
assert mock_snapshot_download.call_args_list[1].kwargs["local_files_only"] is False
|
||||
assert statuses == [
|
||||
"Проверяю кэш модели large-v3...",
|
||||
"Скачиваю модель large-v3 из Hugging Face...",
|
||||
]
|
||||
assert "Проверяю кэш модели large-v3..." in statuses
|
||||
assert "Скачиваю модель large-v3 из Hugging Face..." in statuses
|
||||
|
||||
|
||||
def test_ensure_model_available_accepts_local_directory(tmp_path):
|
||||
@@ -311,7 +389,10 @@ def test_ensure_model_available_accepts_local_directory(tmp_path):
|
||||
|
||||
def test_ensure_model_available_accepts_repo_id(tmp_path):
|
||||
model_dir = _create_model_dir(tmp_path / "repo-model")
|
||||
with patch("local_transcriber.transcriber.snapshot_download", return_value=str(model_dir)) as mock_snapshot_download:
|
||||
with patch(
|
||||
"local_transcriber.backends.faster_whisper.snapshot_download",
|
||||
return_value=str(model_dir),
|
||||
) as mock_snapshot_download:
|
||||
result = ensure_model_available("org/model")
|
||||
|
||||
assert result == str(model_dir)
|
||||
@@ -323,7 +404,7 @@ def test_ensure_model_available_rejects_unsupported_alias():
|
||||
ensure_model_available("distil-large-v3")
|
||||
|
||||
|
||||
@patch("local_transcriber.transcriber.snapshot_download")
|
||||
@patch("local_transcriber.backends.faster_whisper.snapshot_download")
|
||||
def test_ensure_model_available_redownloads_incomplete_cache(mock_snapshot_download, tmp_path):
|
||||
incomplete = tmp_path / "incomplete"
|
||||
incomplete.mkdir()
|
||||
@@ -349,11 +430,7 @@ def test_ensure_model_available_redownloads_incomplete_cache(mock_snapshot_downl
|
||||
result = ensure_model_available("large-v3", on_status=statuses.append)
|
||||
|
||||
assert result == str(complete)
|
||||
assert statuses == [
|
||||
"Проверяю кэш модели large-v3...",
|
||||
"Кэш модели large-v3 неполный, докачиваю...",
|
||||
"Скачиваю модель large-v3 из Hugging Face...",
|
||||
]
|
||||
assert "Кэш модели large-v3 неполный, докачиваю..." in statuses
|
||||
|
||||
|
||||
def test_ensure_model_available_rejects_incomplete_local_directory(tmp_path):
|
||||
@@ -363,111 +440,3 @@ def test_ensure_model_available_rejects_incomplete_local_directory(tmp_path):
|
||||
|
||||
with pytest.raises(ValueError, match="Неполная локальная модель"):
|
||||
ensure_model_available(str(model_dir))
|
||||
|
||||
|
||||
@patch("local_transcriber.transcriber.WhisperModel")
|
||||
def test_transcribe_strict_cuda_error(mock_model_cls):
|
||||
"""strict_device=True + CUDA error -> raise, без fallback."""
|
||||
mock_model_cls.side_effect = RuntimeError("CUDA out of memory")
|
||||
|
||||
with pytest.raises(RuntimeError, match="CUDA out of memory"):
|
||||
transcribe(
|
||||
file_path=Path("test.mp3"),
|
||||
model_name="tiny",
|
||||
device="cuda",
|
||||
strict_device=True,
|
||||
)
|
||||
|
||||
|
||||
@patch("local_transcriber.transcriber.WhisperModel")
|
||||
def test_transcribe_non_strict_cuda_fallback(mock_model_cls):
|
||||
"""strict_device=False + CUDA error -> fallback на CPU."""
|
||||
raw_segments = _make_raw_segments(2)
|
||||
info = _make_info()
|
||||
|
||||
cpu_instance = MagicMock()
|
||||
cpu_instance.transcribe.return_value = (iter(raw_segments), info)
|
||||
|
||||
def model_side_effect(model_name, device, compute_type):
|
||||
if device == "cuda":
|
||||
raise RuntimeError("CUDA out of memory")
|
||||
return cpu_instance
|
||||
|
||||
mock_model_cls.side_effect = model_side_effect
|
||||
|
||||
with pytest.warns(UserWarning, match="Переключение на CPU"):
|
||||
result = transcribe(
|
||||
file_path=Path("test.mp3"),
|
||||
model_name="tiny",
|
||||
device="cuda",
|
||||
strict_device=False,
|
||||
)
|
||||
|
||||
assert result.device_used == "cpu"
|
||||
assert len(result.segments) == 2
|
||||
|
||||
|
||||
@patch("local_transcriber.transcriber.WhisperModel")
|
||||
def test_transcribe_strict_cuda_error_during_transcription(mock_model_cls):
|
||||
"""strict_device=True + CUDA error during transcription -> raise."""
|
||||
cuda_instance = MagicMock()
|
||||
cuda_instance.transcribe.side_effect = RuntimeError("CUDA error during transcription")
|
||||
mock_model_cls.return_value = cuda_instance
|
||||
|
||||
with pytest.raises(RuntimeError, match="CUDA error during transcription"):
|
||||
transcribe(
|
||||
file_path=Path("test.mp3"),
|
||||
model_name="tiny",
|
||||
device="cuda",
|
||||
strict_device=True,
|
||||
)
|
||||
|
||||
|
||||
# === load_model tests ===
|
||||
|
||||
|
||||
@patch("local_transcriber.transcriber.WhisperModel")
|
||||
def test_load_model_cuda_fallback(mock_model_cls):
|
||||
cpu_instance = MagicMock()
|
||||
|
||||
def model_side_effect(model_name, device, compute_type):
|
||||
if device == "cuda":
|
||||
raise RuntimeError("CUDA out of memory")
|
||||
return cpu_instance
|
||||
|
||||
mock_model_cls.side_effect = model_side_effect
|
||||
|
||||
with pytest.warns(UserWarning, match="Переключение на CPU"):
|
||||
model, actual_device = load_model("tiny", "cuda", "int8")
|
||||
|
||||
assert actual_device == "cpu"
|
||||
assert model is cpu_instance
|
||||
|
||||
|
||||
@patch("local_transcriber.transcriber.WhisperModel")
|
||||
def test_load_model_strict_raises(mock_model_cls):
|
||||
mock_model_cls.side_effect = RuntimeError("CUDA out of memory")
|
||||
|
||||
with pytest.raises(RuntimeError, match="CUDA out of memory"):
|
||||
load_model("tiny", "cuda", "int8", strict_device=True)
|
||||
|
||||
|
||||
@patch("local_transcriber.transcriber.WhisperModel")
|
||||
def test__transcribe_file_basic(mock_model_cls):
|
||||
raw_segments = _make_raw_segments(2)
|
||||
info = _make_info()
|
||||
|
||||
instance = MagicMock()
|
||||
instance.transcribe.return_value = (iter(raw_segments), info)
|
||||
|
||||
tfr = _transcribe_file(
|
||||
model=instance,
|
||||
actual_device="cpu",
|
||||
file_path=Path("test.mp3"),
|
||||
model_name="tiny",
|
||||
compute_type="int8",
|
||||
)
|
||||
|
||||
assert len(tfr.result.segments) == 2
|
||||
assert tfr.actual_device == "cpu"
|
||||
assert tfr.model is instance
|
||||
|
||||
Reference in New Issue
Block a user