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Overview

The Producer and Consumer processors work as a pair to route frames between different parts of a pipeline, particularly useful when working with ParallelPipeline. They allow you to selectively capture frames from one pipeline branch and inject them into another.

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ProducerProcessor

ProducerProcessor examines frames flowing through the pipeline, applies a filter to decide which frames to share, and optionally transforms these frames before sending them to connected consumers.

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Constructor Parameters

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filter
Callable[[Frame], Awaitable[bool]]
required

An async function that determines which frames should be sent to consumers. Should return True for frames to be shared.

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transformer
Callable[[Frame], Awaitable[Frame]]
default:"identity_transformer"

Optional async function that transforms frames before sending to consumers. By default, passes frames unchanged.

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passthrough
bool
default:"True"

When True, passes all frames through the normal pipeline flow. When False, only passes through frames that don’t match the filter.

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ConsumerProcessor

ConsumerProcessor receives frames from a ProducerProcessor and injects them into its pipeline branch.

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Constructor Parameters

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producer
ProducerProcessor
required

The producer processor that will send frames to this consumer.

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transformer
Callable[[Frame], Awaitable[Frame]]
default:"identity_transformer"

Optional async function that transforms frames before injecting them into the pipeline.

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direction
FrameDirection
default:"FrameDirection.DOWNSTREAM"

The direction in which to push received frames. Usually DOWNSTREAM to send frames forward in the pipeline.

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Usage Examples

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Basic Usage: Moving TTS Audio Between Branches

# Create a producer that captures TTS audio frames
async def is_tts_audio(frame: Frame) -> bool:
    return isinstance(frame, TTSAudioRawFrame)

# Define an async transformer function
async def tts_to_input_audio_transformer(frame: Frame) -> Frame:
    if isinstance(frame, TTSAudioRawFrame):
        # Convert TTS audio to input audio format
        return InputAudioRawFrame(
            audio=frame.audio,
            sample_rate=frame.sample_rate,
            num_channels=frame.num_channels
        )
    return frame

producer = ProducerProcessor(
    filter=is_tts_audio,
    transformer=tts_to_input_audio_transformer
    passthrough=True  # Keep these frames in original pipeline
)

# Create a consumer to receive the frames
consumer = ConsumerProcessor(
    producer=producer,
    direction=FrameDirection.DOWNSTREAM
)

# Use in a ParallelPipeline
pipeline = Pipeline([
    transport.input(),
    ParallelPipeline(
        # Branch 1: LLM for bot responses
        [
            llm,
            tts,
            producer,  # Capture TTS audio here
        ],
        # Branch 2: Audio processing branch
        [
            consumer,  # Receive TTS audio here
            llm, # Speech-to-Speech LLM (audio in)
        ]
    ),
    transport.output(),
])