Source code for langchain_experimental.agents.agent_toolkits.python.base

"""Python agent."""

from typing import Any, Dict, Optional

from langchain.agents.agent import AgentExecutor, BaseSingleActionAgent
from langchain.agents.mrkl.base import ZeroShotAgent
from langchain.agents.openai_functions_agent.base import OpenAIFunctionsAgent
from langchain.agents.types import AgentType
from langchain.chains.llm import LLMChain
from langchain_core.callbacks.base import BaseCallbackManager
from langchain_core.language_models import BaseLanguageModel
from langchain_core.messages import SystemMessage

from langchain_experimental.agents.agent_toolkits.python.prompt import PREFIX
from langchain_experimental.tools.python.tool import PythonREPLTool


[docs]def create_python_agent( llm: BaseLanguageModel, tool: PythonREPLTool, agent_type: AgentType = AgentType.ZERO_SHOT_REACT_DESCRIPTION, callback_manager: Optional[BaseCallbackManager] = None, verbose: bool = False, prefix: str = PREFIX, agent_executor_kwargs: Optional[Dict[str, Any]] = None, **kwargs: Dict[str, Any], ) -> AgentExecutor: """Construct a python agent from an LLM and tool.""" tools = [tool] agent: BaseSingleActionAgent if agent_type == AgentType.ZERO_SHOT_REACT_DESCRIPTION: prompt = ZeroShotAgent.create_prompt(tools, prefix=prefix) llm_chain = LLMChain( llm=llm, prompt=prompt, callback_manager=callback_manager, ) tool_names = [tool.name for tool in tools] agent = ZeroShotAgent(llm_chain=llm_chain, allowed_tools=tool_names, **kwargs) elif agent_type == AgentType.OPENAI_FUNCTIONS: system_message = SystemMessage(content=prefix) _prompt = OpenAIFunctionsAgent.create_prompt(system_message=system_message) agent = OpenAIFunctionsAgent( llm=llm, prompt=_prompt, tools=tools, callback_manager=callback_manager, **kwargs, ) else: raise ValueError(f"Agent type {agent_type} not supported at the moment.") return AgentExecutor.from_agent_and_tools( agent=agent, tools=tools, callback_manager=callback_manager, verbose=verbose, **(agent_executor_kwargs or {}), )