Source code for autogen_agentchat.agents._base_chat_agent

from abc import ABC, abstractmethod
from typing import Any, AsyncGenerator, List, Mapping, Sequence, Tuple

from autogen_core import CancellationToken

from ..base import ChatAgent, Response, TaskResult
from ..messages import (
    AgentEvent,
    BaseChatMessage,
    ChatMessage,
    TextMessage,
)
from ..state import BaseState


[docs] class BaseChatAgent(ChatAgent, ABC): """Base class for a chat agent.""" def __init__(self, name: str, description: str) -> None: self._name = name if self._name.isidentifier() is False: raise ValueError("The agent name must be a valid Python identifier.") self._description = description @property def name(self) -> str: """The name of the agent. This is used by team to uniquely identify the agent. It should be unique within the team.""" return self._name @property def description(self) -> str: """The description of the agent. This is used by team to make decisions about which agents to use. The description should describe the agent's capabilities and how to interact with it.""" return self._description @property @abstractmethod def produced_message_types(self) -> Tuple[type[ChatMessage], ...]: """The types of messages that the agent produces in the :attr:`Response.chat_message` field. They must be :class:`ChatMessage` types.""" ...
[docs] @abstractmethod async def on_messages(self, messages: Sequence[ChatMessage], cancellation_token: CancellationToken) -> Response: """Handles incoming messages and returns a response. .. note:: Agents are stateful and the messages passed to this method should be the new messages since the last call to this method. The agent should maintain its state between calls to this method. For example, if the agent needs to remember the previous messages to respond to the current message, it should store the previous messages in the agent state. """ ...
[docs] async def on_messages_stream( self, messages: Sequence[ChatMessage], cancellation_token: CancellationToken ) -> AsyncGenerator[AgentEvent | ChatMessage | Response, None]: """Handles incoming messages and returns a stream of messages and and the final item is the response. The base implementation in :class:`BaseChatAgent` simply calls :meth:`on_messages` and yields the messages in the response. .. note:: Agents are stateful and the messages passed to this method should be the new messages since the last call to this method. The agent should maintain its state between calls to this method. For example, if the agent needs to remember the previous messages to respond to the current message, it should store the previous messages in the agent state. """ response = await self.on_messages(messages, cancellation_token) for inner_message in response.inner_messages or []: yield inner_message yield response
[docs] async def run( self, *, task: str | ChatMessage | Sequence[ChatMessage] | None = None, cancellation_token: CancellationToken | None = None, ) -> TaskResult: """Run the agent with the given task and return the result.""" if cancellation_token is None: cancellation_token = CancellationToken() input_messages: List[ChatMessage] = [] output_messages: List[AgentEvent | ChatMessage] = [] if task is None: pass elif isinstance(task, str): text_msg = TextMessage(content=task, source="user") input_messages.append(text_msg) output_messages.append(text_msg) elif isinstance(task, BaseChatMessage): input_messages.append(task) output_messages.append(task) else: if not task: raise ValueError("Task list cannot be empty.") # Task is a sequence of messages. for msg in task: if isinstance(msg, BaseChatMessage): input_messages.append(msg) output_messages.append(msg) else: raise ValueError(f"Invalid message type in sequence: {type(msg)}") response = await self.on_messages(input_messages, cancellation_token) if response.inner_messages is not None: output_messages += response.inner_messages output_messages.append(response.chat_message) return TaskResult(messages=output_messages)
[docs] async def run_stream( self, *, task: str | ChatMessage | Sequence[ChatMessage] | None = None, cancellation_token: CancellationToken | None = None, ) -> AsyncGenerator[AgentEvent | ChatMessage | TaskResult, None]: """Run the agent with the given task and return a stream of messages and the final task result as the last item in the stream.""" if cancellation_token is None: cancellation_token = CancellationToken() input_messages: List[ChatMessage] = [] output_messages: List[AgentEvent | ChatMessage] = [] if task is None: pass elif isinstance(task, str): text_msg = TextMessage(content=task, source="user") input_messages.append(text_msg) output_messages.append(text_msg) yield text_msg elif isinstance(task, BaseChatMessage): input_messages.append(task) output_messages.append(task) yield task else: if not task: raise ValueError("Task list cannot be empty.") for msg in task: if isinstance(msg, BaseChatMessage): input_messages.append(msg) output_messages.append(msg) yield msg else: raise ValueError(f"Invalid message type in sequence: {type(msg)}") async for message in self.on_messages_stream(input_messages, cancellation_token): if isinstance(message, Response): yield message.chat_message output_messages.append(message.chat_message) yield TaskResult(messages=output_messages) else: output_messages.append(message) yield message
[docs] @abstractmethod async def on_reset(self, cancellation_token: CancellationToken) -> None: """Resets the agent to its initialization state.""" ...
[docs] async def save_state(self) -> Mapping[str, Any]: """Export state. Default implementation for stateless agents.""" return BaseState().model_dump()
[docs] async def load_state(self, state: Mapping[str, Any]) -> None: """Restore agent from saved state. Default implementation for stateless agents.""" BaseState.model_validate(state)