Merge pull request #1301 from pipecat-ai/aleix/example-22d-fix-llm-aggregator

examples/foundational/22d-natural-conversation-gemini-audio.py

@@ -23,7 +23,6 @@ from pipecat.frames.frames import (
     FunctionCallInProgressFrame,
     FunctionCallResultFrame,
     InputAudioRawFrame,
-    LLMFullResponseEndFrame,
     LLMFullResponseStartFrame,
     StartFrame,
     StartInterruptionFrame,
@@ -37,7 +36,7 @@ from pipecat.pipeline.parallel_pipeline import ParallelPipeline
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_response import LLMResponseAggregator
+from pipecat.processors.aggregators.llm_response import LLMAssistantResponseAggregator
 from pipecat.processors.aggregators.openai_llm_context import (
     OpenAILLMContext,
     OpenAILLMContextFrame,
@@ -432,7 +431,11 @@ class CompletenessCheck(FrameProcessor):
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)
 
-        if isinstance(frame, UserStartedSpeakingFrame):
+        if isinstance(frame, (EndFrame, CancelFrame)):
+            if self._idle_task:
+                await self.cancel_task(self._idle_task)
+                self._idle_task = None
+        elif isinstance(frame, UserStartedSpeakingFrame):
             if self._idle_task:
                 await self.cancel_task(self._idle_task)
         elif isinstance(frame, TextFrame) and frame.text.startswith("YES"):
@@ -474,19 +477,11 @@ class CompletenessCheck(FrameProcessor):
             self._idle_task = None
 
 
-class UserAggregatorBuffer(LLMResponseAggregator):
+class LLMAggregatorBuffer(LLMAssistantResponseAggregator):
     """Buffers the output of the transcription LLM. Used by the bot output gate."""
 
     def __init__(self, **kwargs):
-        super().__init__(
-            messages=None,
-            role=None,
-            start_frame=LLMFullResponseStartFrame,
-            end_frame=LLMFullResponseEndFrame,
-            accumulator_frame=TextFrame,
-            handle_interruptions=True,
-            expect_stripped_words=False,
-        )
+        super().__init__(expect_stripped_words=False)
         self._transcription = ""
 
     async def process_frame(self, frame: Frame, direction: FrameDirection):
@@ -544,7 +539,7 @@ class OutputGate(FrameProcessor):
         self,
         notifier: BaseNotifier,
         context: OpenAILLMContext,
-        user_transcription_buffer: "UserAggregatorBuffer",
+        llm_transcription_buffer: LLMAggregatorBuffer,
         **kwargs,
     ):
         super().__init__(**kwargs)
@@ -552,7 +547,7 @@ class OutputGate(FrameProcessor):
         self._frames_buffer = []
         self._notifier = notifier
         self._context = context
-        self._transcription_buffer = user_transcription_buffer
+        self._transcription_buffer = llm_transcription_buffer
         self._gate_task = None
 
     def close_gate(self):
@@ -699,10 +694,10 @@ async def main():
 
         conversation_audio_context_assembler = ConversationAudioContextAssembler(context=context)
 
-        user_aggregator_buffer = UserAggregatorBuffer()
+        llm_aggregator_buffer = LLMAggregatorBuffer()
 
         bot_output_gate = OutputGate(
-            notifier=notifier, context=context, user_transcription_buffer=user_aggregator_buffer
+            notifier=notifier, context=context, llm_transcription_buffer=llm_aggregator_buffer
         )
 
         pipeline = Pipeline(
@@ -723,7 +718,7 @@ async def main():
                             ],
                             [
                                 tx_llm,
-                                user_aggregator_buffer,
+                                llm_aggregator_buffer,
                             ],
                         )
                     ],