Source code for langchain.agents.initialize

"""Load agent."""
from typing import Any, Optional, Sequence

from langchain.agents.agent import AgentExecutor
from langchain.agents.agent_types import AgentType
from langchain.agents.loading import AGENT_TO_CLASS, load_agent
from langchain.callbacks.base import BaseCallbackManager
from langchain.schema import BaseLanguageModel
from langchain.tools.base import BaseTool


[docs]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, **kwargs: Any, ) -> AgentExecutor: """Load an agent executor given tools and LLM. Args: tools: List of tools this agent has access to. llm: Language model to use as the agent. agent: Agent type to use. If None and agent_path is also None, will default to AgentType.ZERO_SHOT_REACT_DESCRIPTION. callback_manager: CallbackManager to use. Global callback manager is used if not provided. Defaults to None. agent_path: Path to serialized agent to use. agent_kwargs: Additional key word arguments to pass to the underlying agent **kwargs: Additional key word arguments passed to the agent executor Returns: An agent executor """ 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()}." ) 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 ) 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, **kwargs, )