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Simplified universal context aggregators, _handle_text() to only check frame.append_to_context instead of also checking self._started

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filipi87
2026-02-10 11:27:30 -03:00
parent 1dccbe7c0b
commit 9bb712a47b
1 changed files with 6 additions and 15 deletions
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21
src/pipecat/processors/aggregators/llm_response_universal.py
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@@ -52,6 +52,7 @@ from pipecat.frames.frames import (
StartFrame,
TextFrame,
TranscriptionFrame,
TranslationFrame,
UserImageRawFrame,
UserMuteStartedFrame,
UserMuteStoppedFrame,
@@ -795,7 +796,6 @@ class LLMAssistantAggregator(LLMContextAggregator):
DeprecationWarning,
)
self._started = 0
self._function_calls_in_progress: Dict[str, Optional[FunctionCallInProgressFrame]] = {}
self._function_calls_image_results: Dict[str, UserImageRawFrame] = {}
self._context_updated_tasks: Set[asyncio.Task] = set()
@@ -917,12 +917,10 @@ class LLMAssistantAggregator(LLMContextAggregator):
async def _handle_interruptions(self, frame: InterruptionFrame):
await self._trigger_assistant_turn_stopped()
self._started = 0
await self.reset()
async def _handle_end_or_cancel(self, frame: Frame):
await self._trigger_assistant_turn_stopped()
self._started = 0
async def _handle_function_calls_started(self, frame: FunctionCallsStartedFrame):
function_names = [f"{f.function_name}:{f.tool_call_id}" for f in frame.function_calls]
@@ -1067,15 +1065,17 @@ class LLMAssistantAggregator(LLMContextAggregator):
)
async def _handle_llm_start(self, _: LLMFullResponseStartFrame):
self._started += 1
await self._trigger_assistant_turn_started()
async def _handle_llm_end(self, _: LLMFullResponseEndFrame):
self._started -= 1
await self._trigger_assistant_turn_stopped()
async def _handle_text(self, frame: TextFrame):
if not self._started or not frame.append_to_context:
# Skip TextFrame types not intended to build the assistant context
if isinstance(frame, (TranscriptionFrame, TranslationFrame, InterimTranscriptionFrame)):
return
if not frame.append_to_context:
return
# Make sure we really have text (spaces count, too!)
@@ -1089,18 +1089,12 @@ class LLMAssistantAggregator(LLMContextAggregator):
)
async def _handle_thought_start(self, frame: LLMThoughtStartFrame):
if not self._started:
return
await self._reset_thought_aggregation()
self._thought_append_to_context = frame.append_to_context
self._thought_llm = frame.llm
self._thought_start_time = time_now_iso8601()
async def _handle_thought_text(self, frame: LLMThoughtTextFrame):
if not self._started:
return
# Make sure we really have text (spaces count, too!)
if len(frame.text) == 0:
return
@@ -1112,9 +1106,6 @@ class LLMAssistantAggregator(LLMContextAggregator):
)
async def _handle_thought_end(self, frame: LLMThoughtEndFrame):
if not self._started:
return
thought = concatenate_aggregated_text(self._thought_aggregation)
if self._thought_append_to_context: