Skip to main content
`Ctrl`+`K`

#

# Source code for langchain.agents.agent_toolkits.pandas.base

    """Agent for working with pandas objects."""
    from typing import Any, List, Optional

    from langchain.agents.agent import AgentExecutor
    from langchain.agents.agent_toolkits.pandas.prompt import PREFIX, SUFFIX
    from langchain.agents.mrkl.base import ZeroShotAgent
    from langchain.callbacks.base import BaseCallbackManager
    from langchain.chains.llm import LLMChain
    from langchain.llms.base import BaseLLM
    from langchain.tools.python.tool import PythonAstREPLTool

    def create_pandas_dataframe_agent(
        llm: BaseLLM,
        df: Any,
        callback_manager: Optional[BaseCallbackManager] = None,
        prefix: str = PREFIX,
        suffix: str = SUFFIX,
        input_variables: Optional[List[str]] = None,
        verbose: bool = False,
        return_intermediate_steps: bool = False,
        max_iterations: Optional[int] = 15,
        max_execution_time: Optional[float] = None,
        early_stopping_method: str = "force",
        **kwargs: Any,
    ) -> AgentExecutor:
        """Construct a pandas agent from an LLM and dataframe."""
        import pandas as pd

        if not isinstance(df, pd.DataFrame):
            raise ValueError(f"Expected pandas object, got {type(df)}")
        if input_variables is None:
            input_variables = ["df", "input", "agent_scratchpad"]
        tools = [PythonAstREPLTool(locals={"df": df})]
        prompt = ZeroShotAgent.create_prompt(
            tools, prefix=prefix, suffix=suffix, input_variables=input_variables
        )
        partial_prompt = prompt.partial(df=str(df.head()))
        llm_chain = LLMChain(
            llm=llm,
            prompt=partial_prompt,
            callback_manager=callback_manager,
        )
        tool_names = [tool.name for tool in tools]
        agent = ZeroShotAgent(llm_chain=llm_chain, allowed_tools=tool_names, **kwargs)
        return AgentExecutor.from_agent_and_tools(
            agent=agent,
            tools=tools,
            verbose=verbose,
            return_intermediate_steps=return_intermediate_steps,
            max_iterations=max_iterations,
            max_execution_time=max_execution_time,
            early_stopping_method=early_stopping_method,
        )