langchain.agents.initialize — 🦜🔗 LangChain 0.2.0

"""加载代理。"""
from typing import Any, Optional, Sequence

from langchain_core._api import deprecated
from langchain_core.callbacks import BaseCallbackManager
from langchain_core.language_models import BaseLanguageModel
from langchain_core.tools import BaseTool

from langchain.agents.agent import AgentExecutor
from langchain.agents.agent_types import AgentType
from langchain.agents.loading import AGENT_TO_CLASS, load_agent


[docs]@deprecated(
    "0.1.0",
    alternative=(
        "Use new agent constructor methods like create_react_agent, create_json_agent, "
        "create_structured_chat_agent, etc."
    ),
    removal="0.3.0",
)
def initialize_agent(
    tools: Sequence[BaseTool],
    llm: BaseLanguageModel,
    agent: Optional[AgentType] = None,
    callback_manager: Optional[BaseCallbackManager] = None,
    agent_path: Optional[str] = None,
    agent_kwargs: Optional[dict] = None,
    *,
    tags: Optional[Sequence[str]] = None,
    **kwargs: Any,
) -> AgentExecutor:
    """加载给定工具和LLM的代理执行器。

参数：
    tools：代理可以访问的工具列表。
    llm：用作代理的语言模型。
    agent：要使用的代理类型。如果为None且agent_path也为None，则默认为AgentType.ZERO_SHOT_REACT_DESCRIPTION。
    callback_manager：要使用的CallbackManager。如果未提供，则使用全局回调管理器。默认为None。
    agent_path：要使用的序列化代理的路径。
    agent_kwargs：传递给底层代理的额外关键字参数。
    tags：要应用于跟踪运行的标记。
    **kwargs：传递给代理执行器的额外关键字参数。

返回：
    一个代理执行器。
"""
    tags_ = list(tags) if tags else []
    if agent is None and agent_path is None:
        agent = AgentType.ZERO_SHOT_REACT_DESCRIPTION
    if agent is not None and agent_path is not None:
        raise ValueError(
            "Both `agent` and `agent_path` are specified, "
            "but at most only one should be."
        )
    if agent is not None:
        if agent not in AGENT_TO_CLASS:
            raise ValueError(
                f"Got unknown agent type: {agent}. "
                f"Valid types are: {AGENT_TO_CLASS.keys()}."
            )
        tags_.append(agent.value if isinstance(agent, AgentType) else agent)
        agent_cls = AGENT_TO_CLASS[agent]
        agent_kwargs = agent_kwargs or {}
        agent_obj = agent_cls.from_llm_and_tools(
            llm, tools, callback_manager=callback_manager, **agent_kwargs
        )
    elif agent_path is not None:
        agent_obj = load_agent(
            agent_path, llm=llm, tools=tools, callback_manager=callback_manager
        )
        try:
            # TODO: Add tags from the serialized object directly.
            tags_.append(agent_obj._agent_type)
        except NotImplementedError:
            pass
    else:
        raise ValueError(
            "Somehow both `agent` and `agent_path` are None, "
            "this should never happen."
        )
    return AgentExecutor.from_agent_and_tools(
        agent=agent_obj,
        tools=tools,
        callback_manager=callback_manager,
        tags=tags_,
        **kwargs,
    )
Source code for langchain.agents.initialize
