Update foundation examples 22b, 22c, and 22d to be ready for function calling
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@@ -20,6 +20,8 @@ from pipecat.frames.frames import (
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CancelFrame,
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EndFrame,
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Frame,
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FunctionCallInProgressFrame,
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FunctionCallResultFrame,
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InputAudioRawFrame,
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LLMFullResponseEndFrame,
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LLMFullResponseStartFrame,
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@@ -575,6 +577,11 @@ class OutputGate(FrameProcessor):
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await self.push_frame(frame, direction)
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return
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# Don't block function call frames
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if isinstance(frame, (FunctionCallInProgressFrame, FunctionCallResultFrame)):
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await self.push_frame(frame, direction)
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return
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# Ignore frames that are not following the direction of this gate.
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if direction != FrameDirection.DOWNSTREAM:
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await self.push_frame(frame, direction)
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@@ -672,12 +679,6 @@ async def main():
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context = OpenAILLMContext()
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context_aggregator = conversation_llm.create_context_aggregator(context)
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# We have instructed the LLM to return 'True' if it thinks the user
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# completed a sentence. So, if it's 'True' we will return true in this
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# predicate which will wake up the notifier.
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async def wake_check_filter(frame):
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return frame.text == "True"
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# This is a notifier that we use to synchronize the two LLMs.
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notifier = EventNotifier()
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@@ -694,14 +695,6 @@ async def main():
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async def block_user_stopped_speaking(frame):
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return not isinstance(frame, UserStoppedSpeakingFrame)
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async def pass_only_llm_trigger_frames(frame):
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return (
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isinstance(frame, OpenAILLMContextFrame)
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or isinstance(frame, LLMMessagesFrame)
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or isinstance(frame, StartInterruptionFrame)
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or isinstance(frame, StopInterruptionFrame)
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)
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conversation_audio_context_assembler = ConversationAudioContextAssembler(context=context)
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user_aggregator_buffer = UserAggregatorBuffer()
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