class_docstr: (Experimental) Retrieve Assistant agent, designed to solve a task with LLM.
  
  RetrieveAssistantAgent is a subclass of AssistantAgent configured with a default system message.
  The default system message is designed to solve a task with LLM,
  including suggesting python code blocks and debugging.
  `human_input_mode` is default to "NEVER"
  and `code_execution_config` is default to False.
  This agent doesn't execute code by default, and expects the user to execute the code.
class_docstr_tok: ["(","Experimental",")","Retrieve","Assistant","agent",",","designed","to","solve","a","task","with","LLM",".","RetrieveAssistantAgent","is","a","subclass","of","AssistantAgent","configured","with","a","default","system","message",".","The","default","system","message","is","designed","to","solve","a","task","with","LLM",",","including","suggesting","python","code","blocks","and","debugging",".","`","human_input_mode","`","is","default","to","``","NEVER","''","and","`","code_execution_config","`","is","default","to","False",".","This","agent","does","n't","execute","code","by","default",",","and","expects","the","user","to","execute","the","code","."]
code: def __init__(self, *args, **kwargs):
      super().__init__(*args, **kwargs)
      self.register_reply(
          Agent,
          RetrieveAssistantAgent._generate_retrieve_assistant_reply,
      )
  
imports: from autogen.agentchat.agent import Agent
  from autogen.agentchat.assistant_agent import AssistantAgent
  from typing import Dict, Optional, Union, List, Tuple, Any
label_desc: Use image node_id 1 to create a new RetrieveAssistantAgent object from inherited base classes: AssistantAgent with example: obj = RetrieveAssistantAgent()