Merge pull request #1710 from pipecat-ai/mb/openai-context-aggregation
fix: OpenAIRealtimeBetaLLMService writes two assistant messages to th…
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@@ -87,6 +87,9 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
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### Fixed
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- Fixed an issue where `OpenAIRealtimeBetaLLMService` would add two assistant
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messages to the context.
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- Fixed an issue with `GeminiMultimodalLiveLLMService` where the context
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contained tokens instead of words.
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@@ -12,9 +12,11 @@ from loguru import logger
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from pipecat.frames.frames import (
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Frame,
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FunctionCallResultFrame,
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InterimTranscriptionFrame,
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LLMMessagesUpdateFrame,
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LLMSetToolsFrame,
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LLMTextFrame,
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TranscriptionFrame,
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)
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from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
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from pipecat.processors.frame_processor import FrameDirection
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@@ -137,15 +139,6 @@ class OpenAIRealtimeLLMContext(OpenAILLMContext):
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}
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self.add_message(message)
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def add_assistant_content_item_as_message(self, item):
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message = {"role": "assistant", "content": []}
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for content in item.content:
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if content.type == "audio":
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message["content"].append({"type": "text", "text": content.transcript})
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else:
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logger.error(f"Unhandled content type in assistant item: {content.type} - {item}")
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self.add_message(message)
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class OpenAIRealtimeUserContextAggregator(OpenAIUserContextAggregator):
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async def process_frame(
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@@ -175,8 +168,10 @@ class OpenAIRealtimeAssistantContextAggregator(OpenAIAssistantContextAggregator)
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# but the OpenAIRealtimeLLMService pushes LLMTextFrames and TTSTextFrames. We
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# need to override this proces_frame for LLMTextFrame, so that only the TTSTextFrames
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# are process. This ensures that the context gets only one set of messages.
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# OpenAIRealtimeLLMService also pushes TranscriptionFrames and InterimTranscriptionFrames,
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# so we need to ignore pushing those as well, as they're also TextFrames.
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async def process_frame(self, frame: Frame, direction: FrameDirection):
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if not isinstance(frame, LLMTextFrame):
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if not isinstance(frame, (LLMTextFrame, TranscriptionFrame, InterimTranscriptionFrame)):
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await super().process_frame(frame, direction)
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async def handle_function_call_result(self, frame: FunctionCallResultFrame):
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@@ -562,13 +562,11 @@ class OpenAIRealtimeBetaLLMService(LLMService):
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await self.push_error(ErrorFrame(error=f"Error: {evt}", fatal=True))
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async def _handle_assistant_output(self, output):
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# logger.debug(f"!!! HANDLE Assistant output: {output}")
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# We haven't seen intermixed audio and function_call items in the same response. But let's
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# try to write logic that handles that, if it does happen.
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messages = [item for item in output if item.type == "message"]
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# Also, the assistant output is pushed as LLMTextFrame and TTSTextFrame to be handled by
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# the assistant context aggregator.
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function_calls = [item for item in output if item.type == "function_call"]
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for item in messages:
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self._context.add_assistant_content_item_as_message(item)
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await self._handle_function_call_items(function_calls)
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async def _handle_function_call_items(self, items):
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