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Overview

IdentityFilter is a simple pass-through processor that forwards all frames without any modification or filtering. It acts as a transparent layer in your pipeline, allowing all frames to flow through unchanged.

Check out Observers for an option that delivers similar functionality but doesn’t require a processor to reside in the Pipeline.

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Constructor Parameters

The IdentityFilter constructor accepts no specific parameters beyond those inherited from FrameProcessor.

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Functionality

When a frame passes through the processor, it is immediately forwarded in the same direction with no changes. This applies to all frame types and both directions (upstream and downstream).

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Use Cases

While functionally equivalent to having no filter at all, IdentityFilter can be useful in several scenarios:

  • Testing ParallelPipeline configurations to ensure frames aren’t duplicated
  • Acting as a placeholder where a more complex filter might be added later
  • Monitoring frame flow in pipelines by adding logging in subclasses
  • Creating a base class for more complex conditional filters

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Usage Example

from pipecat.processors.filters import IdentityFilter

# Create an identity filter
pass_through = IdentityFilter()

# Add to pipeline
pipeline = Pipeline([
    source,
    pass_through,  # All frames pass through unchanged
    destination
])

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Frame Flow

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Notes

  • Simplest possible filter implementation
  • Passes all frames through without modification
  • Useful in testing parallel pipelines
  • Can serve as a placeholder or base class
  • Zero overhead in normal operation