Source code for langchain_community.agent_toolkits.spark_sql.base

"""Spark SQL agent."""

from __future__ import annotations

from typing import TYPE_CHECKING, Any, Dict, List, Optional

from langchain_core.callbacks import BaseCallbackManager, Callbacks
from langchain_core.language_models import BaseLanguageModel

from langchain_community.agent_toolkits.spark_sql.prompt import SQL_PREFIX, SQL_SUFFIX
from langchain_community.agent_toolkits.spark_sql.toolkit import SparkSQLToolkit

if TYPE_CHECKING:
    from langchain.agents.agent import AgentExecutor


[docs]def create_spark_sql_agent( llm: BaseLanguageModel, toolkit: SparkSQLToolkit, callback_manager: Optional[BaseCallbackManager] = None, callbacks: Callbacks = None, prefix: str = SQL_PREFIX, suffix: str = SQL_SUFFIX, format_instructions: Optional[str] = None, input_variables: Optional[List[str]] = None, top_k: int = 10, max_iterations: Optional[int] = 15, max_execution_time: Optional[float] = None, early_stopping_method: str = "force", verbose: bool = False, agent_executor_kwargs: Optional[Dict[str, Any]] = None, **kwargs: Any, ) -> AgentExecutor: """Construct a Spark SQL agent from an LLM and tools. Args: llm: The language model to use. toolkit: The Spark SQL toolkit. callback_manager: Optional. The callback manager. Default is None. callbacks: Optional. The callbacks. Default is None. prefix: Optional. The prefix for the prompt. Default is SQL_PREFIX. suffix: Optional. The suffix for the prompt. Default is SQL_SUFFIX. format_instructions: Optional. The format instructions for the prompt. Default is None. input_variables: Optional. The input variables for the prompt. Default is None. top_k: Optional. The top k for the prompt. Default is 10. max_iterations: Optional. The maximum iterations to run. Default is 15. max_execution_time: Optional. The maximum execution time. Default is None. early_stopping_method: Optional. The early stopping method. Default is "force". verbose: Optional. Whether to print verbose output. Default is False. agent_executor_kwargs: Optional. The agent executor kwargs. Default is None. kwargs: Any. Additional keyword arguments. Returns: The agent executor. """ from langchain.agents.agent import AgentExecutor from langchain.agents.mrkl.base import ZeroShotAgent from langchain.chains.llm import LLMChain tools = toolkit.get_tools() prefix = prefix.format(top_k=top_k) prompt_params = ( {"format_instructions": format_instructions} if format_instructions is not None else {} ) prompt = ZeroShotAgent.create_prompt( tools, prefix=prefix, suffix=suffix, input_variables=input_variables, **prompt_params, ) llm_chain = LLMChain( llm=llm, prompt=prompt, callback_manager=callback_manager, callbacks=callbacks, ) 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, callback_manager=callback_manager, callbacks=callbacks, verbose=verbose, max_iterations=max_iterations, max_execution_time=max_execution_time, early_stopping_method=early_stopping_method, **(agent_executor_kwargs or {}), )