refactor: remove redundant comments from task pipeline

Clean up code by removing unnecessary comments that were added during previous refactoring iterations. The code is now self-documenting and these comments were redundant.

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

api/core/app/apps/advanced_chat/generate_task_pipeline.py

@@ -166,7 +166,6 @@ class AdvancedChatAppGenerateTaskPipeline:
         Process generate task pipeline.
         :return:
         """
-        # start generate conversation name thread
         self._conversation_name_generate_thread = self._message_cycle_manager.generate_conversation_name(
             conversation_id=self._conversation_id, query=self._application_generate_entity.query
         )
@@ -258,15 +257,12 @@ class AdvancedChatAppGenerateTaskPipeline:
             yield response
 
         start_listener_time = time.time()
-        # timeout
         while (time.time() - start_listener_time) < TTS_AUTO_PLAY_TIMEOUT:
             try:
                 if not tts_publisher:
                     break
                 audio_trunk = tts_publisher.check_and_get_audio()
                 if audio_trunk is None:
-                    # release cpu
-                    # sleep 20 ms ( 40ms => 1280 byte audio file,20ms => 640 byte audio file)
                     time.sleep(TTS_AUTO_PLAY_YIELD_CPU_TIME)
                     continue
                 if audio_trunk.status == "finish":
@@ -848,20 +844,16 @@ class AdvancedChatAppGenerateTaskPipeline:
         for queue_message in self._base_task_pipeline._queue_manager.listen():
             event = queue_message.event
 
-            # Use elegant pattern matching for event dispatch
             match event:
-                # Handle QueueWorkflowStartedEvent specially - it has a side effect
                 case QueueWorkflowStartedEvent():
-                    graph_runtime_state = event.graph_runtime_state  # Side effect!
+                    graph_runtime_state = event.graph_runtime_state
                     yield from self._handle_workflow_started_event(event)
 
-                # Handle QueueTextChunkEvent specially - needs queue_message
                 case QueueTextChunkEvent():
                     yield from self._handle_text_chunk_event(
                         event, tts_publisher=tts_publisher, queue_message=queue_message
                     )
 
-                # Handle events that cause loop breaks
                 case QueueErrorEvent():
                     yield from self._handle_error_event(event)
                     break
@@ -890,9 +882,7 @@ class AdvancedChatAppGenerateTaskPipeline:
                         )
                     ):
                         yield from responses
-                    # Continue with next event (elegant fallthrough)
 
-        # Cleanup - publish None when task finished
         if tts_publisher:
             tts_publisher.publish(None)
 
@@ -964,7 +954,6 @@ class AdvancedChatAppGenerateTaskPipeline:
         """
         if self._base_task_pipeline._output_moderation_handler:
             if self._base_task_pipeline._output_moderation_handler.should_direct_output():
-                # stop subscribe new token when output moderation should direct output
                 self._task_state.answer = self._base_task_pipeline._output_moderation_handler.get_final_output()
                 self._base_task_pipeline._queue_manager.publish(
                     QueueTextChunkEvent(text=self._task_state.answer), PublishFrom.TASK_PIPELINE

api/core/app/apps/workflow/generate_task_pipeline.py

@@ -711,20 +711,16 @@ class WorkflowAppGenerateTaskPipeline:
         for queue_message in self._base_task_pipeline._queue_manager.listen():
             event = queue_message.event
 
-            # Use elegant pattern matching for event dispatch
             match event:
-                # Handle QueueWorkflowStartedEvent specially - it has a side effect
                 case QueueWorkflowStartedEvent():
-                    graph_runtime_state = event.graph_runtime_state  # Side effect!
+                    graph_runtime_state = event.graph_runtime_state
                     yield from self._handle_workflow_started_event(event)
 
-                # Handle QueueTextChunkEvent specially - needs queue_message
                 case QueueTextChunkEvent():
                     yield from self._handle_text_chunk_event(
                         event, tts_publisher=tts_publisher, queue_message=queue_message
                     )
 
-                # Handle events that cause loop breaks
                 case QueueErrorEvent():
                     yield from self._handle_error_event(event)
                     break
@@ -741,9 +737,7 @@ class WorkflowAppGenerateTaskPipeline:
                         )
                     ):
                         yield from responses
-                    # Continue with next event (elegant fallthrough)
 
-        # Cleanup - publish None when task finished
         if tts_publisher:
             tts_publisher.publish(None)