# Copyright (c) 2023 - 2025, AG2ai, Inc., AG2ai open-source projects maintainers and core contributors # # SPDX-License-Identifier: Apache-2.0 # # Portions derived from https://github.com/microsoft/autogen are under the MIT License. # SPDX-License-Identifier: MIT from typing import Any, Callable, Literal, Optional, Union from ..doc_utils import export_module from ..llm_config import LLMConfig from ..runtime_logging import log_new_agent, logging_enabled from .conversable_agent import ConversableAgent @export_module("autogen") class UserProxyAgent(ConversableAgent): """(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`](../ConversableAgent#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. """ # Default UserProxyAgent.description values, based on human_input_mode DEFAULT_USER_PROXY_AGENT_DESCRIPTIONS = { "ALWAYS": "An attentive HUMAN user who can answer questions about the task, and can perform tasks such as running Python code or inputting command line commands at a Linux terminal and reporting back the execution results.", "TERMINATE": "A user that can run Python code or input command line commands at a Linux terminal and report back the execution results.", "NEVER": "A computer terminal that performs no other action than running Python scripts (provided to it quoted in ```python code blocks), or sh shell scripts (provided to it quoted in ```sh code blocks).", } def __init__( self, name: str, is_termination_msg: Optional[Callable[[dict[str, Any]], bool]] = None, max_consecutive_auto_reply: Optional[int] = None, human_input_mode: Literal["ALWAYS", "TERMINATE", "NEVER"] = "ALWAYS", function_map: Optional[dict[str, Callable[..., Any]]] = None, code_execution_config: Union[dict[str, Any], Literal[False]] = {}, default_auto_reply: Optional[Union[str, dict[str, Any]]] = "", llm_config: Optional[Union[LLMConfig, dict[str, Any], Literal[False]]] = False, system_message: Optional[Union[str, list[str]]] = "", description: Optional[str] = None, **kwargs: Any, ): """Args: 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 (LLMConfig or dict or False or None): llm inference configuration. Please refer to [OpenAIWrapper.create](https://docs.ag2.ai/latest/docs/api-reference/autogen/OpenAIWrapper/#autogen.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](https://docs.ag2.ai/latest/docs/api-reference/autogen/ConversableAgent). """ super().__init__( name=name, system_message=system_message, is_termination_msg=is_termination_msg, max_consecutive_auto_reply=max_consecutive_auto_reply, human_input_mode=human_input_mode, function_map=function_map, code_execution_config=code_execution_config, llm_config=llm_config, default_auto_reply=default_auto_reply, description=( description if description is not None else self.DEFAULT_USER_PROXY_AGENT_DESCRIPTIONS[human_input_mode] ), **kwargs, ) if logging_enabled(): log_new_agent(self, locals())