[唤醒应答与快速端点]：完成唤醒后我在播报和本地VAD端点优化，包含缓冲清理、配置项和测试覆盖

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,