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refactor: convert isinstance chains to match/case in easy_ui_based_generate_task_pipeline.py (#36222)
This commit is contained in:
EvanYao
GitHub
parent
27b084c4d4
commit
c0bdd6792f
@ -140,42 +140,43 @@ class EasyUIBasedGenerateTaskPipeline(BasedGenerateTaskPipeline):
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:return:
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:return:
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"""
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"""
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for stream_response in generator:
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for stream_response in generator:
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if isinstance(stream_response, ErrorStreamResponse):
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match stream_response:
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raise stream_response.err
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case ErrorStreamResponse():
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elif isinstance(stream_response, MessageEndStreamResponse):
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raise stream_response.err
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extras = {"usage": self._task_state.llm_result.usage.model_dump()}
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case MessageEndStreamResponse():
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if self._task_state.metadata:
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extras = {"usage": self._task_state.llm_result.usage.model_dump()}
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extras["metadata"] = self._task_state.metadata.model_dump()
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if self._task_state.metadata:
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response: ChatbotAppBlockingResponse | CompletionAppBlockingResponse
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extras["metadata"] = self._task_state.metadata.model_dump()
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if self._conversation_mode == AppMode.COMPLETION:
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response: ChatbotAppBlockingResponse | CompletionAppBlockingResponse
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response = CompletionAppBlockingResponse(
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if self._conversation_mode == AppMode.COMPLETION:
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task_id=self._application_generate_entity.task_id,
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response = CompletionAppBlockingResponse(
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data=CompletionAppBlockingResponse.Data(
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task_id=self._application_generate_entity.task_id,
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id=self._message_id,
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data=CompletionAppBlockingResponse.Data(
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mode=self._conversation_mode,
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id=self._message_id,
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message_id=self._message_id,
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mode=self._conversation_mode,
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answer=self._task_state.llm_result.message.get_text_content(),
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message_id=self._message_id,
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created_at=self._message_created_at,
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answer=self._task_state.llm_result.message.get_text_content(),
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**extras,
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created_at=self._message_created_at,
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),
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**extras,
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)
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),
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else:
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)
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response = ChatbotAppBlockingResponse(
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else:
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task_id=self._application_generate_entity.task_id,
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response = ChatbotAppBlockingResponse(
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data=ChatbotAppBlockingResponse.Data(
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task_id=self._application_generate_entity.task_id,
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id=self._message_id,
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data=ChatbotAppBlockingResponse.Data(
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mode=self._conversation_mode,
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id=self._message_id,
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conversation_id=self._conversation_id,
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mode=self._conversation_mode,
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message_id=self._message_id,
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conversation_id=self._conversation_id,
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answer=self._task_state.llm_result.message.get_text_content(),
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message_id=self._message_id,
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created_at=self._message_created_at,
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answer=self._task_state.llm_result.message.get_text_content(),
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**extras,
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created_at=self._message_created_at,
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),
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**extras,
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)
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),
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)
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return response
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return response
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else:
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case _:
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continue
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continue
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raise RuntimeError("queue listening stopped unexpectedly.")
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raise RuntimeError("queue listening stopped unexpectedly.")
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@ -265,104 +266,107 @@ class EasyUIBasedGenerateTaskPipeline(BasedGenerateTaskPipeline):
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publisher.publish(message)
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publisher.publish(message)
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event = message.event
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event = message.event
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if isinstance(event, QueueErrorEvent):
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match event:
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with sessionmaker(bind=db.engine).begin() as session:
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case QueueErrorEvent():
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err = self.handle_error(event=event, session=session, message_id=self._message_id)
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with sessionmaker(bind=db.engine).begin() as session:
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yield self.error_to_stream_response(err)
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err = self.handle_error(event=event, session=session, message_id=self._message_id)
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break
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yield self.error_to_stream_response(err)
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elif isinstance(event, QueueStopEvent | QueueMessageEndEvent):
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break
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if isinstance(event, QueueMessageEndEvent):
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case QueueStopEvent() | QueueMessageEndEvent():
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if event.llm_result:
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if isinstance(event, QueueMessageEndEvent):
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self._task_state.llm_result = event.llm_result
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if event.llm_result:
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else:
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self._task_state.llm_result = event.llm_result
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self._handle_stop(event)
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else:
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self._handle_stop(event)
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# handle output moderation
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# handle output moderation
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output_moderation_answer = self.handle_output_moderation_when_task_finished(
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output_moderation_answer = self.handle_output_moderation_when_task_finished(
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self._task_state.llm_result.message.get_text_content()
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self._task_state.llm_result.message.get_text_content()
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)
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if output_moderation_answer:
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self._task_state.llm_result.message.content = output_moderation_answer
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yield self._message_cycle_manager.message_replace_to_stream_response(
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answer=output_moderation_answer
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)
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)
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if output_moderation_answer:
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with sessionmaker(bind=db.engine).begin() as session:
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self._task_state.llm_result.message.content = output_moderation_answer
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# Save message
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yield self._message_cycle_manager.message_replace_to_stream_response(
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self._save_message(session=session, trace_manager=trace_manager)
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answer=output_moderation_answer
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message_end_resp = self._message_end_to_stream_response()
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yield message_end_resp
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elif isinstance(event, QueueRetrieverResourcesEvent):
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self._message_cycle_manager.handle_retriever_resources(event)
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elif isinstance(event, QueueAnnotationReplyEvent):
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annotation = self._message_cycle_manager.handle_annotation_reply(event)
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if annotation:
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self._task_state.llm_result.message.content = annotation.content
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elif isinstance(event, QueueAgentThoughtEvent):
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agent_thought_response = self._agent_thought_to_stream_response(event)
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if agent_thought_response is not None:
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yield agent_thought_response
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elif isinstance(event, QueueMessageFileEvent):
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response = self._message_cycle_manager.message_file_to_stream_response(event)
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if response:
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yield response
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elif isinstance(event, QueueLLMChunkEvent | QueueAgentMessageEvent):
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chunk = event.chunk
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delta_text = chunk.delta.message.content
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if delta_text is None:
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continue
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if isinstance(chunk.delta.message.content, list):
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delta_text = ""
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for content in chunk.delta.message.content:
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logger.debug(
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"The content type %s in LLM chunk delta message content.: %r", type(content), content
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)
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)
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if isinstance(content, TextPromptMessageContent):
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delta_text += content.data
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with sessionmaker(bind=db.engine).begin() as session:
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elif isinstance(content, str):
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# Save message
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delta_text += content # failback to str
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self._save_message(session=session, trace_manager=trace_manager)
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else:
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message_end_resp = self._message_end_to_stream_response()
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logger.warning(
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yield message_end_resp
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"Unsupported content type %s in LLM chunk delta message content.: %r",
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case QueueRetrieverResourcesEvent():
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type(content),
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self._message_cycle_manager.handle_retriever_resources(event)
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content,
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case QueueAnnotationReplyEvent():
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annotation = self._message_cycle_manager.handle_annotation_reply(event)
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if annotation:
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self._task_state.llm_result.message.content = annotation.content
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case QueueAgentThoughtEvent():
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agent_thought_response = self._agent_thought_to_stream_response(event)
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if agent_thought_response is not None:
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yield agent_thought_response
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case QueueMessageFileEvent():
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response = self._message_cycle_manager.message_file_to_stream_response(event)
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if response:
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yield response
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case QueueLLMChunkEvent() | QueueAgentMessageEvent():
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chunk = event.chunk
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delta_text = chunk.delta.message.content
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if delta_text is None:
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continue
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if isinstance(chunk.delta.message.content, list):
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delta_text = ""
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for content in chunk.delta.message.content:
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logger.debug(
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"The content type %s in LLM chunk delta message content.: %r", type(content), content
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)
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)
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continue
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match content:
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case TextPromptMessageContent():
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delta_text += content.data
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case str():
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delta_text += content # failback to str
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case _:
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logger.warning(
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"Unsupported content type %s in LLM chunk delta message content.: %r",
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type(content),
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content,
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)
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continue
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if not self._task_state.llm_result.prompt_messages:
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if not self._task_state.llm_result.prompt_messages:
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self._task_state.llm_result.prompt_messages = chunk.prompt_messages
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self._task_state.llm_result.prompt_messages = chunk.prompt_messages
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# handle output moderation chunk
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# handle output moderation chunk
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should_direct_answer = self._handle_output_moderation_chunk(cast(str, delta_text))
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should_direct_answer = self._handle_output_moderation_chunk(cast(str, delta_text))
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if should_direct_answer:
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if should_direct_answer:
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continue
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current_content = cast(str, self._task_state.llm_result.message.content)
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current_content += cast(str, delta_text)
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self._task_state.llm_result.message.content = current_content
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match event:
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case QueueLLMChunkEvent():
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# Determine the event type once, on first LLM chunk, and reuse for subsequent chunks
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if not hasattr(self, "_precomputed_event_type") or self._precomputed_event_type is None:
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self._precomputed_event_type = self._message_cycle_manager.get_message_event_type(
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message_id=self._message_id
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)
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yield self._message_cycle_manager.message_to_stream_response(
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answer=cast(str, delta_text),
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message_id=self._message_id,
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event_type=self._precomputed_event_type,
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)
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case _:
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yield self._agent_message_to_stream_response(
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answer=cast(str, delta_text),
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message_id=self._message_id,
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)
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case QueueMessageReplaceEvent():
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yield self._message_cycle_manager.message_replace_to_stream_response(answer=event.text)
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case QueuePingEvent():
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yield self.ping_stream_response()
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case _:
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continue
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continue
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current_content = cast(str, self._task_state.llm_result.message.content)
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current_content += cast(str, delta_text)
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self._task_state.llm_result.message.content = current_content
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if isinstance(event, QueueLLMChunkEvent):
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# Determine the event type once, on first LLM chunk, and reuse for subsequent chunks
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if not hasattr(self, "_precomputed_event_type") or self._precomputed_event_type is None:
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self._precomputed_event_type = self._message_cycle_manager.get_message_event_type(
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message_id=self._message_id
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)
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yield self._message_cycle_manager.message_to_stream_response(
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answer=cast(str, delta_text),
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message_id=self._message_id,
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event_type=self._precomputed_event_type,
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)
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else:
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yield self._agent_message_to_stream_response(
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answer=cast(str, delta_text),
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message_id=self._message_id,
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)
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elif isinstance(event, QueueMessageReplaceEvent):
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yield self._message_cycle_manager.message_replace_to_stream_response(answer=event.text)
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elif isinstance(event, QueuePingEvent):
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yield self.ping_stream_response()
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else:
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continue
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if publisher:
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if publisher:
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publisher.publish(None)
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publisher.publish(None)
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if self._conversation_name_generate_thread:
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if self._conversation_name_generate_thread:
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