Merge pull request #4231 from pipecat-ai/pk/llm-messages-transform-frame

Add a `LLMMessagesTransformFrame` to facilitate programmatically edit…
This commit is contained in:
kompfner
2026-04-03 11:54:34 -04:00
committed by GitHub
6 changed files with 268 additions and 4 deletions

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@@ -38,7 +38,7 @@ from pipecat.utils.time import nanoseconds_to_str
from pipecat.utils.utils import obj_count, obj_id
if TYPE_CHECKING:
from pipecat.processors.aggregators.llm_context import LLMContext, NotGiven
from pipecat.processors.aggregators.llm_context import LLMContext, LLMContextMessage, NotGiven
from pipecat.processors.frame_processor import FrameProcessor
from pipecat.services.settings import ServiceSettings
from pipecat.utils.context.llm_context_summarization import LLMContextSummaryConfig
@@ -587,6 +587,23 @@ class LLMMessagesUpdateFrame(DataFrame):
run_llm: Optional[bool] = None
@dataclass
class LLMMessagesTransformFrame(DataFrame):
"""Frame containing a transform function to modify the current context's LLM messages.
A frame containing a transform function that takes the context's current list
of LLM messages and returns a modified list.
Parameters:
transform: A function that takes a list of messages and returns a
modified list.
run_llm: Whether the context update should be sent to the LLM.
"""
transform: Callable[[List["LLMContextMessage"]], List["LLMContextMessage"]]
run_llm: Optional[bool] = None
@dataclass
class LLMSetToolsFrame(DataFrame):
"""Frame containing tools for LLM function calling.

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@@ -19,7 +19,7 @@ import base64
import io
import wave
from dataclasses import dataclass
from typing import Any, List, Optional, TypeAlias, Union
from typing import Any, Callable, List, Optional, TypeAlias, Union
from loguru import logger
from openai._types import NOT_GIVEN as OPEN_AI_NOT_GIVEN
@@ -266,6 +266,17 @@ class LLMContext:
"""
self._messages[:] = messages
def transform_messages(
self, transform: Callable[[List[LLMContextMessage]], List[LLMContextMessage]]
):
"""Transform the current messages using the provided function.
Args:
transform: A function that takes the current list of messages and returns
a modified list of messages to set in the context.
"""
self.set_messages(transform(self._messages))
def set_tools(self, tools: ToolsSchema | NotGiven = NOT_GIVEN):
"""Set the available tools for the LLM.

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@@ -16,7 +16,7 @@ import json
import warnings
from abc import abstractmethod
from dataclasses import dataclass, field
from typing import Any, Dict, List, Literal, Optional, Set, Type
from typing import Any, Callable, Dict, List, Literal, Optional, Set, Type
from loguru import logger
@@ -42,6 +42,7 @@ from pipecat.frames.frames import (
LLMFullResponseEndFrame,
LLMFullResponseStartFrame,
LLMMessagesAppendFrame,
LLMMessagesTransformFrame,
LLMMessagesUpdateFrame,
LLMRunFrame,
LLMSetToolChoiceFrame,
@@ -315,6 +316,17 @@ class LLMContextAggregator(FrameProcessor):
"""
self._context.set_messages(messages)
def transform_messages(
self, transform: Callable[[List[LLMContextMessage]], List[LLMContextMessage]]
):
"""Transform the context messages using a provided function.
Args:
transform: A function that takes the current list of messages and returns
a modified list of messages to set in the context.
"""
self._context.transform_messages(transform)
def set_tools(self, tools: ToolsSchema | NotGiven):
"""Set tools in the context.
@@ -512,6 +524,8 @@ class LLMUserAggregator(LLMContextAggregator):
await self._handle_llm_messages_append(frame)
elif isinstance(frame, LLMMessagesUpdateFrame):
await self._handle_llm_messages_update(frame)
elif isinstance(frame, LLMMessagesTransformFrame):
await self._handle_llm_messages_transform(frame)
elif isinstance(frame, LLMSetToolsFrame):
self.set_tools(frame.tools)
# Push the LLMSetToolsFrame as well, since speech-to-speech LLM
@@ -635,6 +649,11 @@ class LLMUserAggregator(LLMContextAggregator):
if frame.run_llm:
await self.push_context_frame()
async def _handle_llm_messages_transform(self, frame: LLMMessagesTransformFrame):
self.transform_messages(frame.transform)
if frame.run_llm:
await self.push_context_frame()
async def _handle_transcription(self, frame: TranscriptionFrame):
text = frame.text
@@ -923,6 +942,8 @@ class LLMAssistantAggregator(LLMContextAggregator):
await self._handle_llm_messages_append(frame)
elif isinstance(frame, LLMMessagesUpdateFrame):
await self._handle_llm_messages_update(frame)
elif isinstance(frame, LLMMessagesTransformFrame):
await self._handle_llm_messages_transform(frame)
elif isinstance(frame, LLMSetToolsFrame):
self.set_tools(frame.tools)
elif isinstance(frame, LLMSetToolChoiceFrame):
@@ -982,6 +1003,11 @@ class LLMAssistantAggregator(LLMContextAggregator):
if frame.run_llm:
await self.push_context_frame(FrameDirection.UPSTREAM)
async def _handle_llm_messages_transform(self, frame: LLMMessagesTransformFrame):
self.transform_messages(frame.transform)
if frame.run_llm:
await self.push_context_frame(FrameDirection.UPSTREAM)
async def _handle_interruptions(self, frame: InterruptionFrame):
await self._trigger_assistant_turn_stopped()
await self.reset()

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@@ -127,6 +127,7 @@ async def run_test(
expected_down_frames: Optional[Sequence[type]] = None,
expected_up_frames: Optional[Sequence[type]] = None,
frames_to_send: Sequence[Frame],
frames_to_send_direction: FrameDirection = FrameDirection.DOWNSTREAM,
ignore_start: bool = True,
observers: Optional[List[BaseObserver]] = None,
pipeline_params: Optional[PipelineParams] = None,
@@ -144,6 +145,9 @@ async def run_test(
expected_down_frames: Expected frame types flowing downstream (optional).
expected_up_frames: Expected frame types flowing upstream (optional).
frames_to_send: Sequence of frames to send through the processor.
frames_to_send_direction: Direction to send frames_to_send. Downstream
frames are pushed from the beginning of the pipeline, upstream frames
from the end. Defaults to DOWNSTREAM.
ignore_start: Whether to ignore StartFrames in frame validation.
observers: Optional list of observers to attach to the pipeline.
pipeline_params: Optional pipeline parameters.
@@ -188,7 +192,7 @@ async def run_test(
if isinstance(frame, SleepFrame):
await asyncio.sleep(frame.sleep)
else:
await task.queue_frame(frame)
await task.queue_frame(frame, frames_to_send_direction)
if send_end_frame:
await task.queue_frame(EndFrame())