code: def main():
      # Load LLM inference endpoints from an env variable or a file
      # See https://microsoft.github.io/autogen/docs/FAQ#set-your-api-endpoints
      # and OAI_CONFIG_LIST_sample.
      # For example, if you have created a OAI_CONFIG_LIST file in the current working directory, that file will be used.
      config_list = config_list_from_json(env_or_file="OAI_CONFIG_LIST")
  
      # Create the agent that uses the LLM.
      assistant = ConversableAgent(
          "agent", llm_config={"config_list": config_list}
      )
  
      # Create the agent that represents the user in the conversation.
      user_proxy = UserProxyAgent("user", code_execution_config=False)
  
      # Let the assistant start the conversation.  It will end when the user types exit.
      assistant.initiate_chat(
          user_proxy, message="How can I help you today?"
      )
  
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types