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987099cfcd
Added missed docstrings. Formatted docstrings to the consistent form. --------- Co-authored-by: ccurme <chester.curme@gmail.com>
94 lines
3.4 KiB
Python
94 lines
3.4 KiB
Python
"""Spark SQL agent."""
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from __future__ import annotations
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from typing import TYPE_CHECKING, Any, Dict, List, Optional
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from langchain_core.callbacks import BaseCallbackManager, Callbacks
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from langchain_core.language_models import BaseLanguageModel
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from langchain_community.agent_toolkits.spark_sql.prompt import SQL_PREFIX, SQL_SUFFIX
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from langchain_community.agent_toolkits.spark_sql.toolkit import SparkSQLToolkit
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if TYPE_CHECKING:
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from langchain.agents.agent import AgentExecutor
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def create_spark_sql_agent(
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llm: BaseLanguageModel,
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toolkit: SparkSQLToolkit,
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callback_manager: Optional[BaseCallbackManager] = None,
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callbacks: Callbacks = None,
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prefix: str = SQL_PREFIX,
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suffix: str = SQL_SUFFIX,
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format_instructions: Optional[str] = None,
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input_variables: Optional[List[str]] = None,
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top_k: int = 10,
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max_iterations: Optional[int] = 15,
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max_execution_time: Optional[float] = None,
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early_stopping_method: str = "force",
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verbose: bool = False,
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agent_executor_kwargs: Optional[Dict[str, Any]] = None,
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**kwargs: Any,
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) -> AgentExecutor:
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"""Construct a Spark SQL agent from an LLM and tools.
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Args:
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llm: The language model to use.
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toolkit: The Spark SQL toolkit.
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callback_manager: Optional. The callback manager. Default is None.
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callbacks: Optional. The callbacks. Default is None.
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prefix: Optional. The prefix for the prompt. Default is SQL_PREFIX.
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suffix: Optional. The suffix for the prompt. Default is SQL_SUFFIX.
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format_instructions: Optional. The format instructions for the prompt.
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Default is None.
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input_variables: Optional. The input variables for the prompt. Default is None.
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top_k: Optional. The top k for the prompt. Default is 10.
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max_iterations: Optional. The maximum iterations to run. Default is 15.
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max_execution_time: Optional. The maximum execution time. Default is None.
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early_stopping_method: Optional. The early stopping method. Default is "force".
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verbose: Optional. Whether to print verbose output. Default is False.
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agent_executor_kwargs: Optional. The agent executor kwargs. Default is None.
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kwargs: Any. Additional keyword arguments.
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Returns:
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The agent executor.
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"""
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from langchain.agents.agent import AgentExecutor
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from langchain.agents.mrkl.base import ZeroShotAgent
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from langchain.chains.llm import LLMChain
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tools = toolkit.get_tools()
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prefix = prefix.format(top_k=top_k)
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prompt_params = (
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{"format_instructions": format_instructions}
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if format_instructions is not None
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else {}
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)
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prompt = ZeroShotAgent.create_prompt(
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tools,
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prefix=prefix,
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suffix=suffix,
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input_variables=input_variables,
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**prompt_params,
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)
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llm_chain = LLMChain(
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llm=llm,
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prompt=prompt,
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callback_manager=callback_manager,
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callbacks=callbacks,
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)
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tool_names = [tool.name for tool in tools]
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agent = ZeroShotAgent(llm_chain=llm_chain, allowed_tools=tool_names, **kwargs)
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return AgentExecutor.from_agent_and_tools(
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agent=agent,
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tools=tools,
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callback_manager=callback_manager,
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callbacks=callbacks,
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verbose=verbose,
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max_iterations=max_iterations,
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max_execution_time=max_execution_time,
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early_stopping_method=early_stopping_method,
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**(agent_executor_kwargs or {}),
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)
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