Improvements to DeepgramSageMakerTTSService.

src/pipecat/services/deepgram/sagemaker/tts.py

@@ -20,18 +20,13 @@ from typing import Any, AsyncGenerator, Optional
 from loguru import logger
 
 from pipecat.frames.frames import (
-    BotStoppedSpeakingFrame,
     CancelFrame,
     EndFrame,
     ErrorFrame,
     Frame,
-    InterruptionFrame,
-    LLMFullResponseEndFrame,
     StartFrame,
     TTSAudioRawFrame,
-    TTSStartedFrame,
 )
-from pipecat.processors.frame_processor import FrameDirection
 from pipecat.services.aws.sagemaker.bidi_client import SageMakerBidiClient
 from pipecat.services.settings import TTSSettings
 from pipecat.services.tts_service import TTSService
@@ -115,6 +110,7 @@ class DeepgramSageMakerTTSService(TTSService):
 
         super().__init__(
             sample_rate=sample_rate,
+            push_start_frame=True,
             push_stop_frames=True,
             pause_frame_processing=True,
             append_trailing_space=True,
@@ -128,8 +124,6 @@ class DeepgramSageMakerTTSService(TTSService):
 
         self._client: Optional[SageMakerBidiClient] = None
         self._response_task: Optional[asyncio.Task] = None
-        self._context_id: Optional[str] = None
-        self._ttfb_started: bool = False
 
     def can_generate_metrics(self) -> bool:
         """Check if this service can generate processing metrics.
@@ -166,20 +160,6 @@ class DeepgramSageMakerTTSService(TTSService):
         await super().cancel(frame)
         await self._disconnect()
 
-    async def process_frame(self, frame: Frame, direction: FrameDirection):
-        """Process frames with special handling for LLM response end.
-
-        Args:
-            frame: The frame to process.
-            direction: The direction of frame processing.
-        """
-        await super().process_frame(frame, direction)
-
-        if isinstance(frame, (LLMFullResponseEndFrame, EndFrame)):
-            await self.flush_audio()
-        elif isinstance(frame, BotStoppedSpeakingFrame):
-            self._ttfb_started = False
-
     async def _connect(self):
         """Connect to the SageMaker endpoint and start the BiDi session.
 
@@ -305,7 +285,7 @@ class DeepgramSageMakerTTSService(TTSService):
                                 payload,
                                 self.sample_rate,
                                 1,
-                                context_id=self._context_id,
+                                context_id=self.get_active_audio_context_id(),
                             )
                             await self.push_frame(frame)
 
@@ -316,15 +296,13 @@ class DeepgramSageMakerTTSService(TTSService):
         finally:
             logger.debug("TTS response processor stopped")
 
-    async def _handle_interruption(self, frame: InterruptionFrame, direction: FrameDirection):
+    async def on_audio_context_interrupted(self, context_id: str):
-        """Handle interruption by sending Clear message to Deepgram.
+        """Called when an audio context is cancelled due to an interruption.
 
-        The Clear message will clear Deepgram's internal text buffer and stop
+        Args:
-        sending audio, allowing for a new response to be generated.
+            context_id: The ID of the audio context that was interrupted, or
+                ``None`` if no context was active at the time.
         """
-        await super()._handle_interruption(frame, direction)
-        self._ttfb_started = False
-
         if self._client and self._client.is_active:
             try:
                 await self._client.send_json({"type": "Clear"})
@@ -356,19 +334,8 @@ class DeepgramSageMakerTTSService(TTSService):
             the response processor).
         """
         logger.debug(f"{self}: Generating TTS [{text}]")
-
         try:
-            if not self.audio_context_available(context_id):
-                await self.create_audio_context(context_id)
-                if not self._ttfb_started:
-                    await self.start_ttfb_metrics()
-                    self._ttfb_started = True
-                yield TTSStartedFrame(context_id=context_id)
-            self._context_id = context_id
-
             await self._client.send_json({"type": "Speak", "text": text})
-
             yield None
-
         except Exception as e:
             yield ErrorFrame(error=f"Unknown error occurred: {e}")