Merge pull request #3074 from pipecat-ai/pk/tweak-moondream-example

Update Moondream example so that Moondream service output makes it in…
This commit is contained in:
kompfner
2025-11-17 16:52:18 -05:00
committed by GitHub

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@@ -15,14 +15,21 @@ from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
from pipecat.frames.frames import LLMRunFrame, UserImageRequestFrame
from pipecat.frames.frames import (
Frame,
LLMFullResponseEndFrame,
LLMFullResponseStartFrame,
LLMRunFrame,
TextFrame,
UserImageRequestFrame,
)
from pipecat.pipeline.parallel_pipeline import ParallelPipeline
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
from pipecat.processors.frame_processor import FrameDirection
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import (
create_transport,
@@ -66,6 +73,27 @@ async def fetch_user_image(params: FunctionCallParams):
# await params.result_callback({"result": "Image is being captured."})
class MoondreamTextFrameWrapper(FrameProcessor):
"""Wraps Moondream-provided TextFrames with LLM response start/end frames.
This processor detects TextFrames and automatically wraps them with
LLMFullResponseStartFrame and LLMFullResponseEndFrame to provide proper
response boundaries for downstream processors.
"""
async def process_frame(self, frame: Frame, direction: FrameDirection):
await super().process_frame(frame, direction)
# If we receive a TextFrame, wrap it with response start/end frames
if isinstance(frame, TextFrame):
await self.push_frame(LLMFullResponseStartFrame(), direction)
await self.push_frame(frame, direction)
await self.push_frame(LLMFullResponseEndFrame(), direction)
else:
# For all other frames, just pass them through
await self.push_frame(frame, direction)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
@@ -130,6 +158,12 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
# If you run into weird description, try with use_cpu=True
moondream = MoondreamService()
# Wrap TextFrames with LLM response start/end frames, which makes Moondream
# output be treated like LLM responses for the purpose of context
# aggregation. Without this, the assistant context aggregator would ignore
# Moondream output (if the TTS service is disabled).
moondream_text_wrapper = MoondreamTextFrameWrapper()
pipeline = Pipeline(
[
transport.input(), # Transport user input
@@ -137,7 +171,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
context_aggregator.user(), # User responses
ParallelPipeline(
[llm], # LLM
[moondream],
[moondream, moondream_text_wrapper],
),
tts, # TTS
transport.output(), # Transport bot output