some comments

src/dailyai/pipeline/frame_processor.py

@@ -3,6 +3,19 @@ from typing import AsyncGenerator
 
 from dailyai.pipeline.frames import ControlQueueFrame, QueueFrame
 
+"""
+This is the base class for all frame processors. Frame processors consume a frame
+and yield 0 or more frames. Generally frame processors are used as part of a pipeline,
+where frames come from a source queue, are processed by a series of frame processors,
+then placed on a sink queue.
+
+By convention, FrameProcessors should immediately yield any frames they don't process.
+
+Stateful FrameProcessors should watch for the EndStreamQueueFrame and finalize their
+output, eg. yielding an unfinished sentence if they're aggregating LLM output to full
+sentences. EndStreamQueueFrame is also a chance to clean up any services that need to
+be closed, del'd, etc.
+"""
 
 class FrameProcessor:
     @abstractmethod

src/dailyai/pipeline/pipeline.py

@@ -4,6 +4,12 @@ from dailyai.pipeline.frame_processor import FrameProcessor
 
 from dailyai.pipeline.frames import EndParallelPipeQueueFrame, EndStreamQueueFrame, QueueFrame
 
+"""
+This class manages a pipe of FrameProcessors, and runs them in sequence. The "source"
+and "sink" queues are managed by the caller. You can use this class stand-alone to
+perform specialized processing, or you can use the Transport's run_pipeline method to
+instantiate and run a pipeline with the Transport's sink and source queues.
+"""
 
 class Pipeline:
     def __init__(

src/dailyai/services/ai_services.py

@@ -7,7 +7,6 @@ from dailyai.pipeline.frame_processor import FrameProcessor
 
 from dailyai.pipeline.frames import (
     AudioQueueFrame,
-    ControlQueueFrame,
     EndStreamQueueFrame,
     ImageQueueFrame,
     LLMMessagesQueueFrame,