feat(cli): реализован шаг 5 — CLI-связка всех модулей с исправлениями из ревью
- Зачем:
- шаг 5 плана: нужен рабочий CLI-happy path, связывающий utils / transcriber / formatter.
- ревью этапов 4–5 выявило два medium-бага в formatter и отсутствие тестов для CLI.
- Что:
- cli.py: все опции по PRD 3.2 (--model, --language, --output, --device, --compute-type, --verbose),
rich Status + stderr-консоль, предупреждение на пустую речь, статистика времени.
- transcriber.py: добавлена ensure_model_available() с проверкой кэша HF и валидацией
локальной директории; on_status callback для передачи прогресса в CLI; обработка
ImportError при отсутствии socksio через SOCKS proxy.
- formatter.py: исправлен overflow в format_timestamp (0.995 → 00:01.00 вместо 00:00.100);
сегменты теперь пишутся с явным пробелом и strip() независимо от whisper-формата текста.
- deps: добавлен socksio>=1.0.0 для поддержки SOCKS proxy при загрузке модели.
- tests: test_cli.py (8 тестов на CLI-контракт), расширены test_formatter.py и test_transcriber.py.
- Проверка:
- uv run pytest — 42 passed.
- uv run transcribe --help показывает все опции.
This commit is contained in:
@@ -0,0 +1,236 @@
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from pathlib import Path
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from unittest.mock import MagicMock, patch
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from typer.testing import CliRunner
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from local_transcriber.cli import app
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from local_transcriber.transcriber import Segment, TranscribeResult
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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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language=language,
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language_probability=0.95,
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duration=duration,
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device_used=device_used,
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)
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def _patches(result=None, tmp_file=None):
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"""Context managers for a standard CLI happy path."""
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if result is None:
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result = _make_result()
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return [
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patch("local_transcriber.cli.check_ffmpeg"),
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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="cpu"),
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patch("local_transcriber.cli.transcribe", return_value=result),
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patch("local_transcriber.cli.write_transcript"),
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]
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def test_cli_happy_path_exit_code_zero(tmp_path):
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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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with (
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patch("local_transcriber.cli.check_ffmpeg"),
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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"),
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patch("local_transcriber.cli.transcribe", return_value=result),
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patch("local_transcriber.cli.write_transcript"),
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):
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out = runner.invoke(app, [str(audio)])
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assert out.exit_code == 0
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def test_cli_default_options_passed_to_transcribe(tmp_path):
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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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mock_transcribe = MagicMock(return_value=result)
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with (
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patch("local_transcriber.cli.check_ffmpeg"),
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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"),
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patch("local_transcriber.cli.transcribe", mock_transcribe),
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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.call_args[1]
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assert call_kwargs["model_name"] == "/models/large-v3"
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assert call_kwargs["device"] == "cpu"
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assert call_kwargs["compute_type"] == "int8"
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assert call_kwargs["language"] is None # "auto" → None passed to transcribe
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assert call_kwargs["on_segment"] is None # verbose=False
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def test_cli_custom_options(tmp_path):
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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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mock_transcribe = MagicMock(return_value=result)
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with (
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patch("local_transcriber.cli.check_ffmpeg"),
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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.transcribe", mock_transcribe),
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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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call_kwargs = mock_transcribe.call_args[1]
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assert call_kwargs["model_name"] == "/models/small"
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assert call_kwargs["language"] == "ru" # explicit language passed through
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assert call_kwargs["compute_type"] == "float16"
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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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result = _make_result()
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mock_transcribe = MagicMock(return_value=result)
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with (
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patch("local_transcriber.cli.check_ffmpeg"),
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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"),
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patch("local_transcriber.cli.transcribe", mock_transcribe),
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patch("local_transcriber.cli.write_transcript"),
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):
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runner.invoke(app, [str(audio), "--verbose"])
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call_kwargs = mock_transcribe.call_args[1]
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assert call_kwargs["on_segment"] is not None
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assert callable(call_kwargs["on_segment"])
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def test_cli_empty_speech_warning(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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with (
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patch("local_transcriber.cli.check_ffmpeg"),
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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"),
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patch("local_transcriber.cli.transcribe", return_value=result),
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patch("local_transcriber.cli.write_transcript"),
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):
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out = runner.invoke(app, [str(audio)])
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assert out.exit_code == 0
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assert "Речь не обнаружена" in out.output
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def test_cli_default_output_path(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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mock_write = MagicMock()
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with (
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patch("local_transcriber.cli.check_ffmpeg"),
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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"),
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patch("local_transcriber.cli.transcribe", return_value=result),
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patch("local_transcriber.cli.write_transcript", mock_write),
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):
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runner.invoke(app, [str(audio)])
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written_path: Path = mock_write.call_args[0][1]
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assert written_path.name == "meeting-transcript.md"
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def test_cli_custom_output_path(tmp_path):
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audio = tmp_path / "meeting.mp3"
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audio.write_bytes(b"fake")
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out_file = tmp_path / "custom.md"
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result = _make_result()
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mock_write = MagicMock()
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with (
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patch("local_transcriber.cli.check_ffmpeg"),
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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"),
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patch("local_transcriber.cli.transcribe", return_value=result),
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patch("local_transcriber.cli.write_transcript", mock_write),
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):
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runner.invoke(app, [str(audio), "--output", str(out_file)])
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written_path: Path = mock_write.call_args[0][1]
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assert written_path == out_file
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def test_cli_error_exit_code_one(tmp_path):
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audio = tmp_path / "test.mp3"
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audio.write_bytes(b"fake")
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with patch("local_transcriber.cli.check_ffmpeg", side_effect=SystemExit(1)):
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out = runner.invoke(app, [str(audio)])
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assert out.exit_code == 1
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def test_cli_passes_status_callback_to_transcribe(tmp_path):
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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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mock_transcribe = MagicMock(return_value=result)
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with (
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patch("local_transcriber.cli.check_ffmpeg"),
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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"),
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patch("local_transcriber.cli.transcribe", mock_transcribe),
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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.call_args[1]
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assert call_kwargs["on_status"] is not None
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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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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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mock_transcribe = MagicMock(return_value=result)
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with (
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patch("local_transcriber.cli.check_ffmpeg"),
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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_model,
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patch("local_transcriber.cli.transcribe", mock_transcribe),
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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_model.assert_called_once()
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call_kwargs = mock_transcribe.call_args[1]
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assert call_kwargs["model_name"] == "/models/large-v3"
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@@ -14,6 +14,7 @@ def test_format_timestamp_minutes():
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assert format_timestamp(83.45) == "01:23.45"
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assert format_timestamp(9.1) == "00:09.10"
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assert format_timestamp(599.99) == "09:59.99"
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assert format_timestamp(0.995) == "00:01.00" # carry-over: не даёт .100
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def test_format_timestamp_hours():
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@@ -49,10 +50,31 @@ def test_format_transcript_basic():
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assert "**Длительность**: 02:00" in content
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assert "**Устройство**: CUDA (NVIDIA GeForce RTX 3060)" in content
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assert "---" in content
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# Проверяем пробел между ] и текстом независимо от ведущих пробелов в seg.text
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assert "[00:00.00 - 00:04.82] Добрый день, коллеги." in content
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assert "[00:04.82 - 00:09.15] Первый вопрос." in content
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def test_format_transcript_segment_no_leading_space():
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"""Сегменты без ведущего пробела должны форматироваться корректно."""
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result = TranscribeResult(
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segments=[Segment(start=0.0, end=2.0, text="Hello")],
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language="en",
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language_probability=0.99,
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duration=5.0,
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device_used="cpu",
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)
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content = format_transcript(
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result,
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source_filename="f.mp3",
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model_name="tiny",
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device_info="CPU",
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language_mode="detected",
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transcription_date=datetime(2026, 1, 1, 0, 0, 0),
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)
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assert "[00:00.00 - 00:02.00] Hello" in content
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def test_format_transcript_empty():
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result = TranscribeResult(
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segments=[],
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+155
-1
@@ -3,8 +3,9 @@ from pathlib import Path
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from unittest.mock import MagicMock, patch
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import pytest
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from huggingface_hub.errors import LocalEntryNotFoundError
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from local_transcriber.transcriber import Segment, TranscribeResult, transcribe
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from local_transcriber.transcriber import Segment, TranscribeResult, ensure_model_available, transcribe
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def _make_raw_segments(count: int) -> list:
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@@ -27,6 +28,16 @@ def _make_info(language: str = "ru", probability: float = 0.95, duration: float
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return info
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def _create_model_dir(path: Path) -> Path:
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path.mkdir(parents=True, exist_ok=True)
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(path / "config.json").write_text("{}")
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(path / "preprocessor_config.json").write_text("{}")
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(path / "tokenizer.json").write_text("{}")
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(path / "vocabulary.json").write_text("{}")
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(path / "model.bin").write_bytes(b"ok")
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return path
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@patch("local_transcriber.transcriber.WhisperModel")
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def test_transcribe_collects_segments(mock_model_cls):
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raw_segments = _make_raw_segments(3)
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@@ -201,3 +212,146 @@ def test_transcribe_midstream_fallback_no_duplicate_callbacks(mock_model_cls):
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# This is acceptable — on_segment is a live progress callback.
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# The important thing is that result.segments contains only CPU segments.
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assert all(s.text.startswith(" Segment") for s in result.segments)
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@patch("local_transcriber.transcriber.WhisperModel")
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def test_transcribe_reports_missing_socksio_for_proxy(mock_model_cls):
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mock_model_cls.side_effect = ImportError(
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"Using SOCKS proxy, but the 'socksio' package is not installed."
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)
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with pytest.raises(RuntimeError, match="socksio"):
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transcribe(
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file_path=Path("test.mp3"),
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model_name="tiny",
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device="cpu",
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)
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@patch("local_transcriber.transcriber.WhisperModel")
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def test_transcribe_reports_status_transitions(mock_model_cls):
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raw_segments = _make_raw_segments(1)
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info = _make_info()
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instance = MagicMock()
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instance.transcribe.return_value = (iter(raw_segments), info)
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mock_model_cls.return_value = instance
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statuses: list[str] = []
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transcribe(
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file_path=Path("test.mp3"),
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model_name="tiny",
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device="cpu",
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on_status=statuses.append,
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)
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assert statuses == [
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"Загружаю модель на cpu...",
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"Транскрибирую...",
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]
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@patch("local_transcriber.transcriber.snapshot_download")
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def test_ensure_model_available_uses_cache_first(mock_snapshot_download, tmp_path):
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model_dir = _create_model_dir(tmp_path / "cache-model")
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mock_snapshot_download.return_value = str(model_dir)
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result = ensure_model_available("large-v3")
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assert result == str(model_dir)
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mock_snapshot_download.assert_called_once_with(
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"Systran/faster-whisper-large-v3",
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local_files_only=True,
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allow_patterns=[
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"config.json",
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"preprocessor_config.json",
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"model.bin",
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"tokenizer.json",
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"vocabulary.*",
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],
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)
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@patch("local_transcriber.transcriber._validate_model_dir")
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@patch("local_transcriber.transcriber.snapshot_download")
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def test_ensure_model_available_downloads_on_cache_miss(mock_snapshot_download, mock_validate_model_dir):
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mock_snapshot_download.side_effect = [
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LocalEntryNotFoundError("not cached"),
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"/downloaded/model",
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]
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statuses: list[str] = []
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result = ensure_model_available("large-v3", on_status=statuses.append)
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assert result == "/downloaded/model"
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assert mock_snapshot_download.call_args_list[0].kwargs["local_files_only"] is True
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assert mock_snapshot_download.call_args_list[1].kwargs["local_files_only"] is False
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assert statuses == [
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"Проверяю кэш модели large-v3...",
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"Скачиваю модель large-v3 из Hugging Face...",
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]
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def test_ensure_model_available_accepts_local_directory(tmp_path):
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model_dir = _create_model_dir(tmp_path / "model")
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result = ensure_model_available(str(model_dir))
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assert result == str(model_dir)
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def test_ensure_model_available_accepts_repo_id(tmp_path):
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model_dir = _create_model_dir(tmp_path / "repo-model")
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||||
with patch("local_transcriber.transcriber.snapshot_download", return_value=str(model_dir)) as mock_snapshot_download:
|
||||
result = ensure_model_available("org/model")
|
||||
|
||||
assert result == str(model_dir)
|
||||
assert mock_snapshot_download.call_args.kwargs["local_files_only"] is True
|
||||
|
||||
|
||||
def test_ensure_model_available_rejects_unsupported_alias():
|
||||
with pytest.raises(ValueError, match="Неподдерживаемая модель"):
|
||||
ensure_model_available("distil-large-v3")
|
||||
|
||||
|
||||
@patch("local_transcriber.transcriber.snapshot_download")
|
||||
def test_ensure_model_available_redownloads_incomplete_cache(mock_snapshot_download, tmp_path):
|
||||
incomplete = tmp_path / "incomplete"
|
||||
incomplete.mkdir()
|
||||
(incomplete / "config.json").write_text("{}")
|
||||
(incomplete / "preprocessor_config.json").write_text("{}")
|
||||
(incomplete / "tokenizer.json").write_text("{}")
|
||||
(incomplete / "vocabulary.json").write_text("{}")
|
||||
|
||||
complete = tmp_path / "complete"
|
||||
complete.mkdir()
|
||||
(complete / "config.json").write_text("{}")
|
||||
(complete / "preprocessor_config.json").write_text("{}")
|
||||
(complete / "tokenizer.json").write_text("{}")
|
||||
(complete / "vocabulary.json").write_text("{}")
|
||||
(complete / "model.bin").write_bytes(b"ok")
|
||||
|
||||
mock_snapshot_download.side_effect = [
|
||||
str(incomplete),
|
||||
str(complete),
|
||||
]
|
||||
statuses: list[str] = []
|
||||
|
||||
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...",
|
||||
]
|
||||
|
||||
|
||||
def test_ensure_model_available_rejects_incomplete_local_directory(tmp_path):
|
||||
model_dir = tmp_path / "model"
|
||||
model_dir.mkdir()
|
||||
(model_dir / "config.json").write_text("{}")
|
||||
|
||||
with pytest.raises(ValueError, match="Неполная локальная модель"):
|
||||
ensure_model_available(str(model_dir))
|
||||
|
||||
Reference in New Issue
Block a user