We've helped a number of Pipecat users hook into a variety of content moderation systems or use LLMs as judges. The most common approach is to use a `ParallelP

We've helped a number of Pipecat users hook into a variety of content moderation systems or use LLMs as judges. The most common approach is to use a `ParallelPipeline` to evaluate the output of the LLM at the same time as the TTS inference is running, then to cancel the output and call a function if a moderation condition is triggered. Other people have written custom frame processors to make use of the content moderation scoring in the Google and Azure APIs. If you're interested in building a Pipecat integration for your employer's tech, happy to support that. Feel free to DM me on Twitter.