IdentityFilter

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.

Constructor Parameters

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

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).

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

Usage Example

from pipecat.pipeline.pipeline import Pipeline
from pipecat.processors.filters.identity_filter import IdentityFilter

# Create an identity filter
pass_through = IdentityFilter()

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

Frame Flow

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

Get Started

Standards

Pipecat Server

Client SDKs

Pipecat Flows

Pipecat Cloud

CLI

Pipecat Context Hub

Overview

Constructor Parameters

Functionality

Use Cases

Usage Example

Frame Flow

Notes

​Overview

​Constructor Parameters

​Functionality

​Use Cases

​Usage Example

​Frame Flow

​Notes

Overview

Constructor Parameters

Functionality

Use Cases

Usage Example

Frame Flow

Notes