Agent

An entity that can send messages, receive messages and generate a reply using models, tools, human inputs or a mixture of them

• Can be built on top of LLMs
• Has code executors that enables to execute code
• Human element: humans can be in the loop
• Example
• Features
  • Conversable: Agents can send and receive messages
  • Customizable: Agents can integrate with AI models, tools, humans, or a combination of all

Some Built-In Agents in AutoGen

• ConversableAgent
  • The main agent that can integrate AI models (tools and human input)
  • You can pass in certain settings (human_input_mode, code_execution_config, DEFAULT_SYSTEM_MESSAGE)
• AssistantAgent
  • Assistant agent, designed to solve a task with LLM (that you can attach).
  • A subclass of ConversableAgent 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.
• UserProxyAgent
  • A proxy agent for the user, that can execute code and provide feedback to the other agents.
  • A subclass of ConversableAgent configured with human_input_mode to ALWAYS and llm_config to False.
  • Triggers when human_input_mode="ALWAYS"
• GroupChatManager
  • A chat manager agent that can manage a group chat of multiple agents.

• is_terminate_msg
  • This condition can trigger termination if the received message satisfies a particular condition, e.g., it contains the word “TERMINATE”. You can customize this condition using the is_terminate_msg argument in the constructor of the ConversableAgent class.
  • https://microsoft.github.io/autogen/docs/tutorial/chat-termination/
  • Example: is_terminate_msg = lambda msg: "elephant" in msg["content"].lower()