João HenriqueandClaude Opus 5
ffaebb3f72
Eram 882 linhas de seis papéis sem relação, sob um nome que só dizia
"compartilhado" — o depósito onde tudo que servia a mais de um handler
acabava caindo.
media 316 transcrição em cache, corte por fala, relatório
paths 206 sandbox, limites, caminho de saída
project 116 abrir projeto, preparar modifier/generator
captions 112 SRT, VTT, listas com timestamp
detection 99 flash frames, buracos, duplicados
formatting 86 tabelas e relatórios dos handlers
O __init__ reexporta os 46 nomes, então os treze pontos que importam daqui
não mudaram.
_transcript_cut_report saiu de formatting para media: ele precisa do hint de
instalação e do _text_result, ou seja, é relatório de transcrição e não
formatação genérica — mover foi mais honesto que cruzar imports entre os
dois módulos.
Quatro testes patchavam `server_tools._shared.transcribe`; o nome agora é
ligado por _shared/media.py, então o patch passou a apontar para lá — mesmo
padrão da experiência #23.
Lint zerado, 1454 testes passando.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
112 lines
4.2 KiB
Python
112 lines
4.2 KiB
Python
"""Tests for the build_voice_timeline MCP tool."""
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import json
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import pytest
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from tests.test_voice_features_tool import _write_silent_wav
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_TRANSCRIPT = {
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"language": "pt",
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"duration": 4.0,
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"text": "isso e seguranca total",
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"segments": [
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{"text": "isso e", "start": 0.0, "end": 1.0},
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{"text": "seguranca total", "start": 2.0, "end": 4.0},
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],
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"words": [
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{"word": "isso", "start": 0.0, "end": 0.4, "confidence": 0.9},
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{"word": "e", "start": 0.5, "end": 0.7, "confidence": 0.9},
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{"word": "seguranca", "start": 2.0, "end": 2.9, "confidence": 0.9},
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{"word": "total", "start": 3.0, "end": 3.5, "confidence": 0.9},
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],
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}
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@pytest.fixture
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def wav(tmp_path):
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path = tmp_path / "clip.wav"
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_write_silent_wav(str(path))
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return path
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@pytest.fixture
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def patched(monkeypatch):
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"""Deterministic transcription + acoustics, no optional extras needed."""
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import fcpxml.voice_timeline as vt
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import server_tools._shared.media as _shared_mod
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monkeypatch.setattr(_shared_mod, "transcribe", lambda *a, **k: _TRANSCRIPT)
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monkeypatch.setattr(vt, "extract_pitch", lambda *a, **k: [(2.4, 260.0), (0.2, 120.0)])
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monkeypatch.setattr(vt, "extract_energy", lambda *a, **k: [(2.4, 0.95), (0.2, 0.10)])
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class TestBuildVoiceTimelineHandler:
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async def test_writes_timeline_json(self, wav, patched):
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from server import handle_build_voice_timeline
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result = await handle_build_voice_timeline({"media_path": str(wav)})
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text = result[0].text
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json_path = wav.parent / "clip_voice_timeline.json"
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assert str(json_path) in text
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data = json.loads(json_path.read_text(encoding="utf-8"))
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assert data["summary"]["word_count"] == 4
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assert len(data["segments"]) == 2
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async def test_reports_which_layers_ran(self, wav, patched):
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from server import handle_build_voice_timeline
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result = await handle_build_voice_timeline({"media_path": str(wav)})
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text = result[0].text
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assert "Analysis Layers" in text
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assert "Transcript" in text
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async def test_rejects_disallowed_extension(self, tmp_path):
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from server import handle_build_voice_timeline
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bad = tmp_path / "clip.txt"
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bad.write_text("not audio")
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with pytest.raises(ValueError):
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await handle_build_voice_timeline({"media_path": str(bad)})
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async def test_untranscribable_media_reports_hint(self, wav, monkeypatch):
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import server_tools._shared.media as _shared_mod
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from server import handle_build_voice_timeline
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monkeypatch.setattr(_shared_mod, "transcribe", lambda *a, **k: None)
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result = await handle_build_voice_timeline({"media_path": str(wav)})
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assert "faster-whisper" in result[0].text
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async def test_uses_persisted_peak_settings(self, wav, patched, monkeypatch):
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"""A wider percentile must surface more peak moments."""
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import server_tools.voice as server_mod
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from server import handle_build_voice_timeline
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def config(percentile):
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return {
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"energy_threshold": 0.5,
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"peak_percentile": percentile,
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"emphasis_floor": 0.0,
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"emphasis_weights": {
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"energy": 0.30, "pitch_variation": 0.25, "rate_variation": 0.20,
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"pause_before": 0.15, "duration": 0.10,
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},
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"emotion_enabled": False,
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"emotion_sensitivity": 0.5,
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"zoom_scale": 1.3,
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"zoom_mode": "in_out",
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"zoom_ease_in": 0.25,
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"zoom_ease_out": 0.04,
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}
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monkeypatch.setattr(server_mod, "load_voice_analysis_config", lambda: config(0.01))
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await handle_build_voice_timeline({"media_path": str(wav)})
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strict = json.loads((wav.parent / "clip_voice_timeline.json").read_text())
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monkeypatch.setattr(server_mod, "load_voice_analysis_config", lambda: config(1.0))
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await handle_build_voice_timeline({"media_path": str(wav)})
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loose = json.loads((wav.parent / "clip_voice_timeline.json").read_text())
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assert loose["summary"]["peak_count"] > strict["summary"]["peak_count"]
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