2026-02-26 15:53:09 -08:00
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"""Tests for transcription service."""
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from voice_to_notes.services.transcribe import (
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SegmentResult,
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TranscriptionResult,
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WordResult,
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result_to_payload,
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)
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def test_result_to_payload():
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"""Test converting TranscriptionResult to IPC payload."""
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result = TranscriptionResult(
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segments=[
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SegmentResult(
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text="hello world",
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start_ms=0,
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end_ms=2000,
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words=[
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WordResult(word="hello", start_ms=0, end_ms=500, confidence=0.95),
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WordResult(word="world", start_ms=600, end_ms=2000, confidence=0.92),
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],
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),
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],
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language="en",
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language_probability=0.98,
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duration_ms=2000,
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)
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payload = result_to_payload(result)
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assert payload["language"] == "en"
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assert payload["duration_ms"] == 2000
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assert len(payload["segments"]) == 1
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seg = payload["segments"][0]
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assert seg["text"] == "hello world"
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assert seg["start_ms"] == 0
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assert seg["end_ms"] == 2000
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assert len(seg["words"]) == 2
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assert seg["words"][0]["word"] == "hello"
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assert seg["words"][0]["confidence"] == 0.95
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def test_result_to_payload_empty():
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"""Test empty transcription result."""
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result = TranscriptionResult()
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payload = result_to_payload(result)
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assert payload["segments"] == []
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assert payload["language"] == ""
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assert payload["duration_ms"] == 0
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2026-03-20 13:49:20 -07:00
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def test_chunk_report_size_progress():
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"""Test CHUNK_REPORT_SIZE progress emission."""
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from voice_to_notes.services.transcribe import CHUNK_REPORT_SIZE
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assert CHUNK_REPORT_SIZE == 10
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def test_transcribe_chunked_with_mocked_ffmpeg(monkeypatch):
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"""Test transcribe_chunked with mocked ffmpeg/ffprobe and mocked WhisperModel."""
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from unittest.mock import MagicMock, patch
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from voice_to_notes.services.transcribe import TranscribeService, SegmentResult, WordResult
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# Mock subprocess.run for ffprobe (returns duration of 700s = ~2 chunks at 300s each)
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original_run = __import__("subprocess").run
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def mock_subprocess_run(cmd, **kwargs):
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if "ffprobe" in cmd:
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result = MagicMock()
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result.stdout = "700.0\n"
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result.returncode = 0
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return result
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elif "ffmpeg" in cmd:
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# Create an empty temp file (simulate chunk extraction)
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# The output file is the last argument
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import pathlib
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output_file = cmd[-1]
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pathlib.Path(output_file).touch()
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result = MagicMock()
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result.returncode = 0
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return result
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return original_run(cmd, **kwargs)
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# Mock WhisperModel
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mock_model = MagicMock()
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def mock_transcribe_call(file_path, **kwargs):
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mock_segments = []
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for i in range(3):
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seg = MagicMock()
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seg.start = i * 1.0
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seg.end = (i + 1) * 1.0
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seg.text = f"Segment {i}"
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seg.words = []
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mock_segments.append(seg)
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mock_info = MagicMock()
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mock_info.language = "en"
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mock_info.language_probability = 0.99
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mock_info.duration = 300.0
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return iter(mock_segments), mock_info
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mock_model.transcribe = mock_transcribe_call
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service = TranscribeService()
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service._model = mock_model
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service._current_model_name = "base"
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service._current_device = "cpu"
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service._current_compute_type = "int8"
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written_messages = []
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def mock_write(msg):
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written_messages.append(msg)
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with patch("subprocess.run", mock_subprocess_run), \
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patch("voice_to_notes.services.transcribe.write_message", mock_write):
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result = service.transcribe_chunked("req-1", "/fake/long_audio.wav")
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# Should have segments from multiple chunks
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assert len(result.segments) > 0
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# Verify timestamp offsets — segments from chunk 1 should start at 0,
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# segments from chunk 2 should be offset by 300000ms
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if len(result.segments) > 3:
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# Chunk 2 segments should have offset timestamps
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assert result.segments[3].start_ms >= 300000
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assert result.duration_ms == 700000
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assert result.language == "en"
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