From 44f708a3dc4f5dc9d4213bcfd69b6fca394c54ae Mon Sep 17 00:00:00 2001 From: mkbk Date: Wed, 17 Jun 2026 20:51:14 +0800 Subject: [PATCH] =?UTF-8?q?[=E5=94=A4=E9=86=92=E5=BA=94=E7=AD=94=E4=B8=8E?= =?UTF-8?q?=E5=BF=AB=E9=80=9F=E7=AB=AF=E7=82=B9]=EF=BC=9A=E5=AE=8C?= =?UTF-8?q?=E6=88=90=E5=94=A4=E9=86=92=E5=90=8E=E6=88=91=E5=9C=A8=E6=92=AD?= =?UTF-8?q?=E6=8A=A5=E5=92=8C=E6=9C=AC=E5=9C=B0VAD=E7=AB=AF=E7=82=B9?= =?UTF-8?q?=E4=BC=98=E5=8C=96=EF=BC=8C=E5=8C=85=E5=90=AB=E7=BC=93=E5=86=B2?= =?UTF-8?q?=E6=B8=85=E7=90=86=E3=80=81=E9=85=8D=E7=BD=AE=E9=A1=B9=E5=92=8C?= =?UTF-8?q?=E6=B5=8B=E8=AF=95=E8=A6=86=E7=9B=96?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .env.example | 8 +++ README.md | 14 ++++- .../specs/voice-pet-pipeline/spec.md | 24 ++++++- .../tasks.md | 7 +++ src/owner_voice_pet/cli.py | 16 +++++ src/owner_voice_pet/config.py | 62 +++++++++++++++++++ src/owner_voice_pet/protocols.py | 3 + src/owner_voice_pet/runtime.py | 50 ++++++++++++++- src/owner_voice_pet/transport.py | 15 +++++ tests/test_live_runtime.py | 5 +- tests/test_models_config.py | 13 ++++ tests/test_transport.py | 14 +++++ 12 files changed, 224 insertions(+), 7 deletions(-) diff --git a/.env.example b/.env.example index 899c044..ec86249 100644 --- a/.env.example +++ b/.env.example @@ -10,6 +10,14 @@ OWNER_WAKE_PROVIDER=local_kws OWNER_WAKE_KEYWORDS_FILE= OWNER_WAKE_KWS_THRESHOLD=0.25 OWNER_WAKE_KWS_SCORE=1.0 +OWNER_WAKE_ACK_TEXT=我在 +OWNER_POST_PLAYBACK_DRAIN_MS=250 +OWNER_VAD_PROVIDER=local +OWNER_VAD_THRESHOLD=0.5 +OWNER_VAD_MIN_DURATION_MS=250 +OWNER_VAD_END_SILENCE_MS=350 +OWNER_VAD_NO_SPEECH_TIMEOUT_MS=5000 +OWNER_VAD_MAX_RECORDING_MS=12000 OWNER_SPEECH_PROVIDER=cloud OWNER_ASR_MODEL=mimo-v2.5-asr OWNER_TTS_MODEL=mimo-v2.5-tts diff --git a/README.md b/README.md index e2bb2f0..15c9212 100644 --- a/README.md +++ b/README.md @@ -13,7 +13,7 @@ - `OWNER_SPEECH_PROVIDER=cloud|local`：选择云端语音模型或本地语音模型。 - 默认云端语音模型：`mimo-v2.5-asr`、`mimo-v2.5-tts`。 - 本地设备：`sounddevice` 读取麦克风，扬声器或 `afplay` 播放。 -- 本地模型：`models/` 存放 `sherpa-onnx` VAD/STT 模型，目录不提交 Git。 +- 本地模型：`models/` 存放 `sherpa-onnx` wake/VAD/STT 模型，目录不提交 Git。 - 临时上下文：同一次 `run-live` 进程内携带最近 user/assistant 历史，退出即清空。 ## 首次准备 @@ -36,13 +36,21 @@ OWNER_WAKE_PROVIDER=local_kws OWNER_WAKE_KEYWORDS_FILE= OWNER_WAKE_KWS_THRESHOLD=0.25 OWNER_WAKE_KWS_SCORE=1.0 +OWNER_WAKE_ACK_TEXT=我在 +OWNER_POST_PLAYBACK_DRAIN_MS=250 +OWNER_VAD_PROVIDER=local +OWNER_VAD_THRESHOLD=0.5 +OWNER_VAD_MIN_DURATION_MS=250 +OWNER_VAD_END_SILENCE_MS=350 +OWNER_VAD_NO_SPEECH_TIMEOUT_MS=5000 +OWNER_VAD_MAX_RECORDING_MS=12000 OWNER_SPEECH_PROVIDER=cloud OWNER_ASR_MODEL=mimo-v2.5-asr OWNER_TTS_MODEL=mimo-v2.5-tts OWNER_TTS_VOICE=mimo_default ``` -`OWNER_WAKE_PROVIDER=local_kws` 表示唤醒词“小杰小杰”由本地模型检测。`OWNER_SPEECH_PROVIDER=cloud` 只影响唤醒后的正式问题 ASR/TTS：它会把 VAD 切出来的用户问题片段发送到云端 ASR，不会上传连续麦克风流，也不会用云端判断唤醒。改成 `local` 时使用项目 `models/` 下的本地语音模型路径。 +`OWNER_WAKE_PROVIDER=local_kws` 表示唤醒词“小杰小杰”由本地模型检测。唤醒命中后会先本地播报 `OWNER_WAKE_ACK_TEXT=我在`，再开始听取问题。`OWNER_SPEECH_PROVIDER=cloud` 只影响唤醒后的正式问题 ASR/TTS：它会把 VAD 切出来的用户问题片段发送到云端 ASR，不会上传连续麦克风流，也不会用云端判断唤醒。改成 `local` 时使用项目 `models/` 下的本地语音模型路径。 ## 本地模型 @@ -57,6 +65,8 @@ python3.11 scripts/download_speech_models.py --dir models 本地唤醒关键词文件位于 `models/wake/keywords.txt`。如果真人唤醒不灵敏，可以先把 `.env` 中 `OWNER_WAKE_KWS_THRESHOLD` 调低，例如 `0.15`，再重新运行。 +如果唤醒后你已经停说但还长时间显示“录音中”，优先调小 `OWNER_VAD_END_SILENCE_MS`，例如 `250`；如果房间噪声较大，再略调高 `OWNER_VAD_THRESHOLD`，例如 `0.6`。 + ## 设备检查 ```bash diff --git a/openspec/changes/separate-wake-and-realtime-transcript/specs/voice-pet-pipeline/spec.md b/openspec/changes/separate-wake-and-realtime-transcript/specs/voice-pet-pipeline/spec.md index 1093053..bae59a3 100644 --- a/openspec/changes/separate-wake-and-realtime-transcript/specs/voice-pet-pipeline/spec.md +++ b/openspec/changes/separate-wake-and-realtime-transcript/specs/voice-pet-pipeline/spec.md @@ -11,6 +11,28 @@ The live runtime SHALL display the recognized user utterance text in the termina - **WHEN** STT returns empty text, punctuation-only text, or an invalid transcript - **THEN** the runtime SHALL NOT emit a misleading transcript as valid user input and SHALL recover to standby without invoking the LLM +### Requirement: Wake acknowledgement before recording +The live runtime SHALL provide an audible local acknowledgement after local wake detection and before it starts recording the user's formal question. + +#### Scenario: Wake is detected +- **WHEN** the local wakeword provider detects “小杰小杰” +- **THEN** the runtime SHALL play a short acknowledgement such as “我在” before entering the user utterance recording state + +#### Scenario: Acknowledgement playback finishes +- **WHEN** the acknowledgement playback completes +- **THEN** the runtime SHALL clear buffered microphone input captured during acknowledgement playback before starting VAD recording for the user's question + +### Requirement: Fast user utterance endpointing +The live runtime SHALL use the project-local VAD model by default for user utterance endpoint detection and SHALL expose configurable silence timing so the recording stops promptly after the user stops speaking. + +#### Scenario: User stops speaking after wake +- **WHEN** VAD observes the configured continuous silence duration after a started utterance +- **THEN** the runtime SHALL close the utterance segment and proceed to STT without waiting for the maximum recording duration + +#### Scenario: Local VAD model is available +- **WHEN** `OWNER_VAD_PROVIDER=local` +- **THEN** the runtime SHALL use the project-local `sherpa-onnx` VAD model rather than a raw energy threshold for live user utterance endpointing + ## MODIFIED Requirements ### Requirement: Wake word detection @@ -56,7 +78,7 @@ The system SHALL provide a `run-live` command that performs real repeated voice #### Scenario: Live runtime completes two turns - **WHEN** the user wakes the system with “小杰小杰”, asks a question, hears the reply, then wakes it again and asks another question -- **THEN** the system SHALL complete local wake, recording, STT, transcript display, LLM, TTS, playback for both turns and SHALL return to standby after each turn +- **THEN** the system SHALL complete local wake, audible acknowledgement, recording, STT, transcript display, LLM, TTS, playback for both turns and SHALL return to standby after each turn #### Scenario: Once mode completes one turn - **WHEN** the user runs `PYTHONPATH=src python3.11 -m owner_voice_pet run-live --once` diff --git a/openspec/changes/separate-wake-and-realtime-transcript/tasks.md b/openspec/changes/separate-wake-and-realtime-transcript/tasks.md index 8f1ee3b..8e7766f 100644 --- a/openspec/changes/separate-wake-and-realtime-transcript/tasks.md +++ b/openspec/changes/separate-wake-and-realtime-transcript/tasks.md @@ -31,3 +31,10 @@ - [ ] 4.3 执行真实 run-live 验收；前置条件：模型、设备、.env 齐全；验收标准：唤醒命中使用本地模型，终端显示转写结果；测试要点：单轮或两轮状态输出；优先级：P0；预计：60 分钟。 - [x] 4.4 最终门禁；前置条件：全部实现完成；验收标准：compileall、unittest、security-check、model-check、device-check、OpenSpec strict 全通过；优先级：P0；预计：30 分钟。 - [ ] 4.5 归档变更并提交；前置条件：4.4 通过；验收标准：主 spec 更新，archive 完成，最终 commit，`git status --short` 为空；测试要点：中文提交信息；优先级：P0；预计：20 分钟。 + +## 5. 唤醒应答与快速端点修正 + +- [x] 5.1 增加唤醒后本地语音应答；前置条件：本地 KWS 已可唤醒；验收标准：wake 命中后播放“我在”再进入录音；测试要点：fake runtime 播放顺序；优先级：P0；预计：45 分钟。 +- [x] 5.2 清理应答播放期间的麦克风缓冲；前置条件：5.1 完成；验收标准：应答音频不进入正式问题 VAD/STT；测试要点：transport flush 测试；优先级：P0；预计：45 分钟。 +- [x] 5.3 live 默认改用本地 `sherpa-onnx` VAD 并缩短静音端点；前置条件：模型已下载；验收标准：`.env` 可配置 VAD provider、静音结束时间和最大录音时长；测试要点：配置和 runtime 构造测试；优先级：P0；预计：45 分钟。 +- [x] 5.4 验证并提交“唤醒应答与快速端点”模块；前置条件：5.1 至 5.3 完成；验收标准：compileall、unittest、security-check、model-check、OpenSpec strict 通过后 commit；优先级：P0；预计：20 分钟。 diff --git a/src/owner_voice_pet/cli.py b/src/owner_voice_pet/cli.py index 6358604..4916406 100644 --- a/src/owner_voice_pet/cli.py +++ b/src/owner_voice_pet/cli.py @@ -57,6 +57,14 @@ def main(argv: list[str] | None = None) -> int: "wake_keywords_file": str(config.wake_keywords_file) if config.wake_keywords_file else "", "wake_kws_threshold": config.wake_kws_threshold, "wake_kws_score": config.wake_kws_score, + "wake_ack_text": config.wake_ack_text, + "post_playback_drain_ms": config.post_playback_drain_ms, + "vad_provider": config.vad_provider, + "vad_threshold": config.vad_threshold, + "vad_min_duration_ms": config.vad_min_duration_ms, + "vad_end_silence_ms": config.vad_end_silence_ms, + "vad_no_speech_timeout_ms": config.vad_no_speech_timeout_ms, + "vad_max_recording_ms": config.vad_max_recording_ms, "speech_provider": config.speech_provider, "asr_model": config.asr_model, "tts_model": config.tts_model, @@ -144,6 +152,14 @@ def main(argv: list[str] | None = None) -> int: wake_keywords_file=config.wake_keywords_file, wake_kws_threshold=config.wake_kws_threshold, wake_kws_score=config.wake_kws_score, + wake_ack_text=config.wake_ack_text, + post_playback_drain_ms=config.post_playback_drain_ms, + vad_provider=config.vad_provider, + vad_threshold=config.vad_threshold, + vad_min_duration_ms=config.vad_min_duration_ms, + vad_end_silence_ms=config.vad_end_silence_ms, + vad_no_speech_timeout_ms=config.vad_no_speech_timeout_ms, + vad_max_recording_ms=config.vad_max_recording_ms, speech_provider=config.speech_provider, asr_model=config.asr_model, tts_model=config.tts_model, diff --git a/src/owner_voice_pet/config.py b/src/owner_voice_pet/config.py index 60a8c6b..5c694fd 100644 --- a/src/owner_voice_pet/config.py +++ b/src/owner_voice_pet/config.py @@ -24,6 +24,14 @@ class AppConfig: wake_keywords_file: Path | None = None wake_kws_threshold: float = 0.25 wake_kws_score: float = 1.0 + wake_ack_text: str = "我在" + post_playback_drain_ms: int = 250 + vad_provider: str = "local" + vad_threshold: float = 0.5 + vad_min_duration_ms: int = 250 + vad_end_silence_ms: int = 350 + vad_no_speech_timeout_ms: int = 5000 + vad_max_recording_ms: int = 12000 speech_provider: str = "cloud" asr_model: str = "mimo-v2.5-asr" tts_model: str = "mimo-v2.5-tts" @@ -57,6 +65,14 @@ class AppConfig: wake_keywords_file=Path(value) if (value := get("WAKE_KEYWORDS_FILE")) else None, wake_kws_threshold=float(get("WAKE_KWS_THRESHOLD", "0.25") or "0.25"), wake_kws_score=float(get("WAKE_KWS_SCORE", "1.0") or "1.0"), + wake_ack_text=get("WAKE_ACK_TEXT", "我在") or "我在", + post_playback_drain_ms=int(get("POST_PLAYBACK_DRAIN_MS", "250") or "250"), + vad_provider=(get("VAD_PROVIDER", "local") or "local").lower(), + vad_threshold=float(get("VAD_THRESHOLD", "0.5") or "0.5"), + vad_min_duration_ms=int(get("VAD_MIN_DURATION_MS", "250") or "250"), + vad_end_silence_ms=int(get("VAD_END_SILENCE_MS", "350") or "350"), + vad_no_speech_timeout_ms=int(get("VAD_NO_SPEECH_TIMEOUT_MS", "5000") or "5000"), + vad_max_recording_ms=int(get("VAD_MAX_RECORDING_MS", "12000") or "12000"), speech_provider=(get("SPEECH_PROVIDER", "cloud") or "cloud").lower(), asr_model=get("ASR_MODEL", "mimo-v2.5-asr") or "mimo-v2.5-asr", tts_model=get("TTS_MODEL", "mimo-v2.5-tts") or "mimo-v2.5-tts", @@ -152,6 +168,52 @@ class AppConfig: "startup", ) ) + if self.post_playback_drain_ms < 0: + errors.append( + ProviderError( + ErrorCode.CONFIG_MISSING_VALUE, + "OWNER_POST_PLAYBACK_DRAIN_MS must be non-negative", + False, + "config", + "startup", + ) + ) + if self.vad_provider not in {"local", "energy"}: + errors.append( + ProviderError( + ErrorCode.CONFIG_MISSING_VALUE, + "OWNER_VAD_PROVIDER must be local or energy", + False, + "config", + "startup", + ) + ) + if self.vad_threshold <= 0: + errors.append( + ProviderError( + ErrorCode.CONFIG_MISSING_VALUE, + "OWNER_VAD_THRESHOLD must be positive", + False, + "config", + "startup", + ) + ) + for name, value in { + "OWNER_VAD_MIN_DURATION_MS": self.vad_min_duration_ms, + "OWNER_VAD_END_SILENCE_MS": self.vad_end_silence_ms, + "OWNER_VAD_NO_SPEECH_TIMEOUT_MS": self.vad_no_speech_timeout_ms, + "OWNER_VAD_MAX_RECORDING_MS": self.vad_max_recording_ms, + }.items(): + if value <= 0: + errors.append( + ProviderError( + ErrorCode.CONFIG_MISSING_VALUE, + f"{name} must be positive", + False, + "config", + "startup", + ) + ) if not self.llm_base_url.startswith(("http://", "https://")): errors.append( ProviderError( diff --git a/src/owner_voice_pet/protocols.py b/src/owner_voice_pet/protocols.py index 6efd425..a5758b9 100644 --- a/src/owner_voice_pet/protocols.py +++ b/src/owner_voice_pet/protocols.py @@ -28,6 +28,9 @@ class AudioTransport(Protocol): def play_pcm(self, segment: AudioSegment, interrupt: bool = False) -> PlaybackResult: ... + def flush_input(self) -> int: + ... + def stop(self) -> None: ... diff --git a/src/owner_voice_pet/runtime.py b/src/owner_voice_pet/runtime.py index 524c913..9aa8038 100644 --- a/src/owner_voice_pet/runtime.py +++ b/src/owner_voice_pet/runtime.py @@ -12,7 +12,7 @@ from .protocols import AudioTransport, LlmProvider, SttProvider, TtsProvider, Wa from .stt import CloudAsrSttProvider, SherpaOnnxSttProvider, is_valid_transcript_text from .transport import SoundDeviceAudioTransport from .tts import CloudTtsProvider, MacSayTtsProvider, SentenceBuffer -from .vad import EnergyVadProvider, VadRecorder +from .vad import EnergyVadProvider, SherpaOnnxVadProvider, VadRecorder from .wakeword import SherpaOnnxKeywordWakeWordProvider @@ -71,6 +71,7 @@ class LiveVoiceRuntime: llm: LlmProvider, tts: TtsProvider, context: ConversationContext, + ack_tts: TtsProvider | None = None, reporter: RuntimeReporter | None = None, sentence_buffer: SentenceBuffer | None = None, ) -> None: @@ -81,6 +82,7 @@ class LiveVoiceRuntime: self.stt = stt self.llm = llm self.tts = tts + self.ack_tts = ack_tts or tts self.context = context self.reporter = reporter or TerminalRuntimeReporter() self.sentence_buffer = sentence_buffer or SentenceBuffer() @@ -91,6 +93,8 @@ class LiveVoiceRuntime: self.vad_recorder.provider.load() self.stt.load() self.tts.load() + if self.ack_tts is not self.tts: + self.ack_tts.load() def run(self, *, once: bool = False, max_turns: int | None = None) -> RuntimeSummary: completed = 0 @@ -142,6 +146,9 @@ class LiveVoiceRuntime: if wake_error is not None: return wake_error self._state(PipelineState.SPEECH_DETECTING, "唤醒命中：请说出问题", turn_id=turn_id) + ack_error = self._acknowledge_wake(turn_id) + if ack_error is not None: + return ack_error user_segment = self._capture_segment(turn_id, state_message="录音中：正在听取问题") if isinstance(user_segment, ProviderError): return user_segment @@ -186,6 +193,33 @@ class LiveVoiceRuntime: if isinstance(result, AudioSegment): return result + def _acknowledge_wake(self, turn_id: int) -> ProviderError | None: + text = self.config.wake_ack_text.strip() + if not text: + self._drain_input_after_playback() + return None + try: + self._state(PipelineState.SPEAKING, f"应答中：{text}", turn_id=turn_id) + segment = self.ack_tts.synthesize(text) + playback = self.transport.play_pcm(segment) + if playback.error: + return playback.error + self._drain_input_after_playback() + return None + except ProviderError as exc: + return exc + + def _drain_input_after_playback(self) -> None: + if self.config.post_playback_drain_ms <= 0: + return + self.transport.flush_input() + remaining_ms = self.config.post_playback_drain_ms + while remaining_ms > 0: + timeout_ms = min(50, remaining_ms) + self.transport.read_frames(timeout_ms=timeout_ms) + remaining_ms -= timeout_ms + self.transport.flush_input() + def _reply_to_user(self, user_text: str, turn_id: int) -> TurnResult: self.context.append_user(user_text) self._state(PipelineState.THINKING, "思考中：正在生成回复", turn_id=turn_id) @@ -220,6 +254,7 @@ class LiveVoiceRuntime: playback = self.transport.play_pcm(segment) if playback.error: raise playback.error + self._drain_input_after_playback() def _recover(self, error: ProviderError, turn_id: int) -> TurnResult: self.reporter.error(error.stage, error.code.value, error.message, turn_id=turn_id) @@ -242,6 +277,10 @@ def build_live_runtime(config: AppConfig, reporter: RuntimeReporter | None = Non else: stt = SherpaOnnxSttProvider(str(config.speech_models_dir)) tts = MacSayTtsProvider() + if config.vad_provider == "local": + vad_provider = SherpaOnnxVadProvider(config.speech_models_dir, threshold=config.vad_threshold) + else: + vad_provider = EnergyVadProvider() return LiveVoiceRuntime( config=config, transport=SoundDeviceAudioTransport(output_device=config.audio_output_device), @@ -252,10 +291,17 @@ def build_live_runtime(config: AppConfig, reporter: RuntimeReporter | None = Non threshold=config.wake_kws_threshold, score=config.wake_kws_score, ), - vad_recorder=VadRecorder(EnergyVadProvider(), min_duration_ms=300, end_silence_ms=500, no_speech_timeout_ms=8000), + vad_recorder=VadRecorder( + vad_provider, + min_duration_ms=config.vad_min_duration_ms, + end_silence_ms=config.vad_end_silence_ms, + no_speech_timeout_ms=config.vad_no_speech_timeout_ms, + max_recording_ms=config.vad_max_recording_ms, + ), stt=stt, llm=OpenAICompatibleLlmProvider(config), tts=tts, + ack_tts=MacSayTtsProvider(), context=ConversationContext( max_messages=config.context_max_messages, max_chars=config.context_max_chars, diff --git a/src/owner_voice_pet/transport.py b/src/owner_voice_pet/transport.py index 50a3dc8..2f31b6b 100644 --- a/src/owner_voice_pet/transport.py +++ b/src/owner_voice_pet/transport.py @@ -103,6 +103,11 @@ class MemoryAudioTransport: self.played_segments.append(segment) return PlaybackResult(True, segment.duration_ms) + def flush_input(self) -> int: + count = len(self._frames) + self._frames.clear() + return count + def stop(self) -> None: self.started = False @@ -290,6 +295,16 @@ class SoundDeviceAudioTransport: break return None + def flush_input(self) -> int: + count = 0 + while not self._queue.empty(): + try: + self._queue.get_nowait() + count += 1 + except queue.Empty: + break + return count + def health(self) -> TransportHealth: if self._sd is None: return TransportHealth(False, False, "sounddevice unavailable") diff --git a/tests/test_live_runtime.py b/tests/test_live_runtime.py index 5ad9e92..d75540a 100644 --- a/tests/test_live_runtime.py +++ b/tests/test_live_runtime.py @@ -80,7 +80,7 @@ def make_runtime(texts: list[str], context: ConversationContext | None = None) - tts = SineTtsProvider() reporter = RecordingReporter() runtime = LiveVoiceRuntime( - config=AppConfig(llm_api_key="secret", speech_provider="cloud"), + config=AppConfig(llm_api_key="secret", speech_provider="cloud", post_playback_drain_ms=0), transport=transport, wakeword=KeywordWakeWordProvider(), vad_recorder=VadRecorder(EnergyVadProvider(), min_duration_ms=40, end_silence_ms=40), @@ -101,8 +101,9 @@ class LiveRuntimeTests(unittest.TestCase): self.assertEqual(summary.completed_turns, 2) self.assertEqual(len(stt.calls), 2) self.assertEqual(len(llm.calls), 2) - self.assertEqual(len(transport.played_segments), 2) + self.assertEqual(len(transport.played_segments), 4) self.assertEqual(reporter.transcripts, ["第一问", "第二问"]) + self.assertIn("应答中：我在", reporter.statuses) self.assertIn("恢复待机：可继续唤醒", reporter.statuses[-1]) def test_temporary_context_is_sent_to_second_llm_call(self) -> None: diff --git a/tests/test_models_config.py b/tests/test_models_config.py index 537480a..6c0ff01 100644 --- a/tests/test_models_config.py +++ b/tests/test_models_config.py @@ -72,6 +72,14 @@ class ModelsConfigTests(unittest.TestCase): self.assertEqual(config.wake_provider, "local_kws") self.assertEqual(config.wake_kws_threshold, 0.25) self.assertEqual(config.wake_kws_score, 1.0) + self.assertEqual(config.wake_ack_text, "我在") + self.assertEqual(config.post_playback_drain_ms, 250) + self.assertEqual(config.vad_provider, "local") + self.assertEqual(config.vad_threshold, 0.5) + self.assertEqual(config.vad_min_duration_ms, 250) + self.assertEqual(config.vad_end_silence_ms, 350) + self.assertEqual(config.vad_no_speech_timeout_ms, 5000) + self.assertEqual(config.vad_max_recording_ms, 12000) self.assertEqual(config.speech_provider, "cloud") self.assertEqual(config.asr_model, "mimo-v2.5-asr") self.assertEqual(config.tts_model, "mimo-v2.5-tts") @@ -90,6 +98,11 @@ class ModelsConfigTests(unittest.TestCase): errors = config.validate_basic() self.assertTrue(any("OWNER_WAKE_PROVIDER" in error.message for error in errors)) + def test_vad_provider_must_be_local_or_energy(self) -> None: + config = AppConfig(vad_provider="invalid") + errors = config.validate_basic() + self.assertTrue(any("OWNER_VAD_PROVIDER" in error.message for error in errors)) + def test_missing_dotenv_uses_non_secret_defaults(self) -> None: config = AppConfig.from_dotenv("/tmp/owner-voice-pet-missing.env") self.assertEqual(config.llm_base_url, "https://token-plan-cn.xiaomimimo.com/v1") diff --git a/tests/test_transport.py b/tests/test_transport.py index e0672cb..7407bd5 100644 --- a/tests/test_transport.py +++ b/tests/test_transport.py @@ -42,6 +42,12 @@ class TransportTests(unittest.TestCase): self.assertFalse(result.played) self.assertEqual(result.error.code, ErrorCode.AUDIO_OUTPUT_DEVICE_MISSING) + def test_memory_transport_flushes_input_frames(self) -> None: + transport = MemoryAudioTransport([frame(1, 0), frame(2, 20)]) + transport.start_input() + self.assertEqual(transport.flush_input(), 2) + self.assertEqual(transport.read_frames(10), []) + def test_file_replay_roundtrip(self) -> None: frames = [frame(1, 0, {"wake": True}), frame(2, 20, {"speech": True})] with tempfile.TemporaryDirectory() as tmp: @@ -76,6 +82,14 @@ class TransportTests(unittest.TestCase): self.assertEqual(frames[0].pcm, b"\x01\x00\x02\x00") self.assertEqual(frames[0].sample_rate, 16000) + def test_sounddevice_transport_flushes_queued_input(self) -> None: + fake = FakeSoundDevice() + transport = SoundDeviceAudioTransport(sounddevice_module=fake) + transport.start_input(sample_rate=16000, channels=1) + self.assertEqual(transport.flush_input(), 1) + self.assertEqual(transport.read_frames(0), []) + transport.stop() + def test_sounddevice_transport_plays_pcm_to_raw_output_stream(self) -> None: fake = FakeSoundDevice() transport = SoundDeviceAudioTransport(sounddevice_module=fake)