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"""Load agent."""
from typing import Any, Optional, Sequence
from langchain.agents.agent import AgentExecutor
from langchain.agents.loading import AGENT_TO_CLASS, load_agent
from langchain.callbacks.base import BaseCallbackManager
from langchain.llms.base import BaseLLM
from langchain.tools.base import BaseTool
def initialize_agent(
tools: Sequence[BaseTool],
llm: BaseLLM,
agent: Optional[str] = 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: A string that specified the agent type to use. Valid options are:
`zero-shot-react-description`
`react-docstore`
`self-ask-with-search`
`conversational-react-description`
`chat-zero-shot-react-description`,
`chat-conversational-react-description`,
If None and agent_path is also None, will default to
`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 = "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,
)
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