259 lines
8.6 KiB
Python
259 lines
8.6 KiB
Python
from __future__ import annotations
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import asyncio
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import json
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import math
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import wave
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from pathlib import Path
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from app.tools.local_stresstest.audio import (
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AudioSample,
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audio_metrics,
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build_variations,
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read_wav_mono16,
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vad_proxy_metrics,
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write_wav,
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)
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from app.tools.local_stresstest.report import render_markdown_report, write_csv, write_mermaid_files
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from app.tools.local_stresstest.runner import StressConfig, wait_for_local_services
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from app.tools.local_stresstest.scenarios import scenario_description
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from app.tools.local_stresstest.text import compare_text, normalize_text, word_error_rate
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from app.tools.local_stresstest.timeline import excerpt_timeline, read_timeline, timeline_has_error
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def _tone_pcm(*, sample_rate: int = 16_000, duration_ms: int = 300, hz: float = 440.0) -> bytes:
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samples = round(sample_rate * duration_ms / 1000)
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out = bytearray()
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for idx in range(samples):
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value = round(math.sin(2 * math.pi * hz * idx / sample_rate) * 9000)
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out.extend(int(value).to_bytes(2, byteorder="little", signed=True))
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return bytes(out)
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def test_normalize_text_removes_accents_case_and_punctuation() -> None:
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assert normalize_text(" Teste UNITÁRIO, Sofya! ") == "teste unitario sofya"
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def test_word_error_rate_counts_insertions_deletions_and_substitutions() -> None:
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wer, substitutions, deletions, insertions = word_error_rate(
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"teste unitario do stt sofya",
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"teste unitario stt sofia agora",
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)
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assert round(wer, 2) == 0.6
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assert substitutions == 1
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assert deletions == 1
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assert insertions == 1
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def test_compare_text_reports_missing_critical_terms() -> None:
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comparison = compare_text(
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expected="Teste unitario do STT Sofya",
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actual="Teste unitario do STT",
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critical_terms=["teste", "sofya"],
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)
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assert comparison.terms_ok is False
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assert comparison.missing_terms == ("sofya",)
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def test_audio_variations_keep_expected_names_and_are_nonempty() -> None:
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sample = AudioSample(name="base", pcm=_tone_pcm())
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variations = build_variations(sample)
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assert [item.name for item in variations] == [
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"clean",
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"low_volume",
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"very_low_volume",
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"high_volume",
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"clipped_high_volume",
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"leading_trailing_silence",
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"short_leading_silence",
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"long_leading_silence",
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"noise_snr_20",
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"noise_snr_15",
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"noise_snr_10",
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"pre_noise_300ms",
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"pre_noise_800ms",
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"telephony_profile",
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"telephony_low_volume",
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"initial_fade_in_250ms",
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"initial_fade_in_500ms",
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"initial_fade_in_900ms",
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"initial_dip_300ms",
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"initial_dip_700ms",
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"prefix_300ms_15pct",
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"prefix_600ms_20pct",
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"prefix_900ms_25pct",
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"low_prefix_noise_600ms",
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"low_prefix_telephony_700ms",
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]
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assert all(item.pcm for item in variations)
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assert len(variations[5].pcm) > len(sample.pcm)
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assert len(variations) == 25
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def test_audio_metrics_detects_audible_tone_and_duration() -> None:
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metrics = audio_metrics(_tone_pcm(duration_ms=500))
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assert metrics.duration_ms == 500
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assert metrics.audible is True
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assert metrics.clipping_ratio == 0.0
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def test_vad_proxy_metrics_flags_soft_start_risk() -> None:
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sample = AudioSample(name="base", pcm=(b"\x00" * 1600) + _tone_pcm(duration_ms=300))
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metrics = vad_proxy_metrics(sample, threshold_dbfs=-45.0, prefix_padding_ms=20)
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assert metrics.first_voice_ms > 0
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assert metrics.unrecovered_prefix_ms > 0
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assert metrics.low_start_risk is True
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def test_wav_read_converts_to_16k_mono(tmp_path: Path) -> None:
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stereo_path = tmp_path / "stereo.wav"
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left = _tone_pcm(sample_rate=8_000, duration_ms=100)
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stereo = bytearray()
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for idx in range(0, len(left), 2):
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stereo.extend(left[idx : idx + 2])
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stereo.extend(left[idx : idx + 2])
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with wave.open(str(stereo_path), "wb") as handle:
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handle.setnchannels(2)
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handle.setsampwidth(2)
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handle.setframerate(8_000)
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handle.writeframes(bytes(stereo))
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sample = read_wav_mono16(stereo_path)
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assert sample.sample_rate == 16_000
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assert sample.channels == 1
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assert audio_metrics(sample.pcm).duration_ms == 100
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def test_write_wav_creates_parent_directory(tmp_path: Path) -> None:
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out = write_wav(tmp_path / "nested" / "tone.wav", AudioSample(name="tone", pcm=_tone_pcm()))
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assert out.exists()
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assert read_wav_mono16(out).pcm
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def test_render_markdown_report_contains_tables_and_mermaid() -> None:
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report = render_markdown_report(
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{
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"passed": True,
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"started_at": "2026-06-16T00:00:00Z",
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"duration_ms": 123,
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"expected_text": "Teste",
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"baseline": {"path": "baseline.wav", "synthetic": True},
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"stt_results": [{"scenario": "clean", "passed": True, "wer": 0.0}],
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"tts_results": [{"scenario": "short", "passed": True, "duration_ms": 1000}],
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"e2e_results": [{"scenario": "clean", "passed": True, "ready_received": True}],
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"startup_checks": {
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"bridge": {
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"service": "bridge",
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"url": "http://127.0.0.1:8000/health",
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"status": "ready",
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"attempts": 1,
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"detail": "HTTP 200",
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}
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},
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"artifacts": {"summary_json": "summary.json"},
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}
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)
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assert "Aviso: esta execucao usou um audio base sintetico" in report
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assert "## Prontidao Local" in report
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assert "Versao textual:" in report
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assert "" in report
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assert "Codigo Mermaid:" in report
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assert "```mermaid" in report
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assert "| cenario | descricao | status | prefixo_ok |" in report
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assert "Audio base sem degradacao" in report
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def test_scenario_description_ignores_repeat_suffix() -> None:
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assert scenario_description("noise_snr_20_r2").startswith("Audio com ruido leve")
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def test_write_mermaid_files_creates_standalone_diagrams(tmp_path: Path) -> None:
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files = write_mermaid_files(tmp_path)
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assert Path(files["stt_mermaid"]).read_text(encoding="utf-8").startswith("flowchart LR")
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assert "sequenceDiagram" in Path(files["e2e_mermaid"]).read_text(encoding="utf-8")
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assert Path(files["stt_svg"]).read_text(encoding="utf-8").startswith("<svg")
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def _stress_config(tmp_path: Path) -> StressConfig:
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return StressConfig(
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env_file=Path(".env.dev"),
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report_dir=tmp_path,
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expected_text="Teste",
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synthesis_text="Teste",
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critical_terms=("teste",),
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stt_wer_threshold=0.2,
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bridge_url="ws://127.0.0.1:8000/ws/agent",
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bridge_health_url="http://bridge.local/health",
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agent_health_url="http://agent.local/",
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startup_wait_s=5.0,
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startup_poll_s=0.01,
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skip_local_wait=False,
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repeat=1,
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concurrency=1,
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e2e_turns=1,
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e2e_timeout_s=5.0,
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stress_audio=None,
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prefix_text="Teste",
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prefix_words=1,
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vad_proxy_threshold_dbfs=-45.0,
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vad_proxy_prefix_padding_ms=1000,
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vad_proxy_min_speech_ms=100,
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)
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def test_wait_for_local_services_retries_until_agent_is_ready(tmp_path: Path) -> None:
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config = _stress_config(tmp_path)
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attempts: dict[str, int] = {}
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async def probe(url: str) -> tuple[bool, str]:
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attempts[url] = attempts.get(url, 0) + 1
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if "agent" in url and attempts[url] < 3:
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return False, "connection refused"
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return True, "HTTP 200"
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async def no_sleep(_: float) -> None:
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return None
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states = asyncio.run(wait_for_local_services(config, probe=probe, sleep=no_sleep))
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assert states["bridge"]["ok"] is True
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assert states["bridge"]["attempts"] == 1
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assert states["agent_runtime"]["ok"] is True
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assert states["agent_runtime"]["attempts"] == 3
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def test_write_csv_handles_empty_rows(tmp_path: Path) -> None:
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out = write_csv(tmp_path / "empty.csv", [])
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assert out.read_text(encoding="utf-8").strip() == ""
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def test_timeline_helpers_parse_excerpt_and_errors(tmp_path: Path) -> None:
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path = tmp_path / "timeline.jsonl"
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records = [
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{"event": "ready_sent"},
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{"event": "noise"},
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{"event": "user_transcript_final", "text": "ola"},
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{"event": "bridge_failed"},
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]
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path.write_text("\n".join(json.dumps(item) for item in records), encoding="utf-8")
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parsed = read_timeline(path)
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assert parsed == records
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assert [item["event"] for item in excerpt_timeline(parsed)] == [
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"ready_sent",
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"user_transcript_final",
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"bridge_failed",
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]
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assert timeline_has_error(parsed) is True
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