agentchat
agentchat.user_proxy_agent
UserProxyAgent
(In preview) A proxy agent for the user, that can execute code and provide feedback to the other agents.
UserProxyAgent is a subclass of ConversableAgent configured with human_input_mode
to ALWAYS
and llm_config
to False. By default, the agent will prompt for human input every time a message is received.
Code execution is enabled by default. LLM-based auto reply is disabled by default.
To modify auto reply, register a method with register_reply
.
To modify the way to get human input, override get_human_input
method.
To modify the way to execute code blocks, single code block, or function call, override execute_code_blocks
,
run_code
, and execute_function
methods respectively.
__init__
Arguments:
name
str - name of the agent.is_termination_msg
function - a function that takes a message in the form of a dictionary and returns a boolean value indicating if this received message is a termination message. The dict can contain the following keys: “content”, “role”, “name”, “function_call”.max_consecutive_auto_reply
int - the maximum number of consecutive auto replies. default to None (no limit provided, class attribute MAX_CONSECUTIVE_AUTO_REPLY will be used as the limit in this case). The limit only plays a role when human_input_mode is not “ALWAYS”.human_input_mode
str - whether to ask for human inputs every time a message is received. Possible values are “ALWAYS”, “TERMINATE”, “NEVER”. (1) When “ALWAYS”, the agent prompts for human input every time a message is received. Under this mode, the conversation stops when the human input is “exit”, or when is_termination_msg is True and there is no human input. (2) When “TERMINATE”, the agent only prompts for human input only when a termination message is received or the number of auto reply reaches the max_consecutive_auto_reply. (3) When “NEVER”, the agent will never prompt for human input. Under this mode, the conversation stops when the number of auto reply reaches the max_consecutive_auto_reply or when is_termination_msg is True.function_map
dict[str, callable] - Mapping function names (passed to openai) to callable functions.code_execution_config
dict or False - config for the code execution. To disable code execution, set to False. Otherwise, set to a dictionary with the following keys:- work_dir (Optional, str): The working directory for the code execution. If None, a default working directory will be used. The default working directory is the “extensions” directory under “path_to_autogen”.
- use_docker (Optional, list, str or bool): The docker image to use for code execution. Default is True, which means the code will be executed in a docker container. A default list of images will be used. If a list or a str of image name(s) is provided, the code will be executed in a docker container with the first image successfully pulled. If False, the code will be executed in the current environment. We strongly recommend using docker for code execution.
- timeout (Optional, int): The maximum execution time in seconds.
- last_n_messages (Experimental, Optional, int): The number of messages to look back for code execution. Default to 1.
default_auto_reply
str or dict or None - the default auto reply message when no code execution or llm based reply is generated.llm_config
dict or False or None - llm inference configuration. Please refer to OpenAIWrapper.create for available options. Default to False, which disables llm-based auto reply. When set to None, will use self.DEFAULT_CONFIG, which defaults to False.system_message
str or List - system message for ChatCompletion inference. Only used when llm_config is not False. Use it to reprogram the agent.description
str - a short description of the agent. This description is used by other agents (e.g. the GroupChatManager) to decide when to call upon this agent. (Default: system_message)**kwargs
dict - Please refer to other kwargs in ConversableAgent.