a dg3@sdZddlmZddlZddlmZmZmZmZddl m Z ddl m Z ddl mZmZmZddlmZdd lmZdd lmZdd lmZdd lmZdd lmZddlmZmZm Z dZ!dZ"dZ#Gddde Z$Gddde Z%dS)z(Chain for interacting with SQL Database.) annotationsN)AnyDictListOptional)Chain)LLMChain)DECIDER_PROMPTPROMPT SQL_PROMPTS)BasePromptTemplate) QUERY_CHECKER) SQLDatabase)CallbackManagerForChainRun)BaseLanguageModel)PromptTemplate) ConfigDictFieldmodel_validatorintermediate_stepsz SQLQuery:z SQLResult:c@s4eZdZUdZded<dZded<eddZd ed <dZd ed <d Z ded<dZ ded<dZ ded<dZ ded<dZ ded<dZded<dZded<dZd ed<edddZedded d!d"d#d$Zed%d&d'd(Zed%d&d)d*Zd6d+d,d+d-d.d/Zedd&d0d1Zed7d2d d d!dd3d4d5ZdS)8SQLDatabaseChainaChain for interacting with SQL Database. Example: .. code-block:: python from langchain_experimental.sql import SQLDatabaseChain from langchain_community.llms import OpenAI, SQLDatabase db = SQLDatabase(...) db_chain = SQLDatabaseChain.from_llm(OpenAI(), db) *Security note*: Make sure that the database connection uses credentials that are narrowly-scoped to only include the permissions this chain needs. Failure to do so may result in data corruption or loss, since this chain may attempt commands like `DROP TABLE` or `INSERT` if appropriately prompted. The best way to guard against such negative outcomes is to (as appropriate) limit the permissions granted to the credentials used with this chain. This issue shows an example negative outcome if these steps are not taken: https://github.com/langchain-ai/langchain/issues/5923 r llm_chainNzOptional[BaseLanguageModel]llmT)excluderdatabasezOptional[BasePromptTemplate]promptinttop_kquerystr input_keyresult output_keyFbool return_sqlreturn_intermediate_steps return_directuse_query_checkerquery_checker_promptZforbid)Zarbitrary_types_allowedextrabefore)moderr)valuesreturncCs^d|vrZtdd|vrZ|ddurZ|d}|dpDt|jt}t|d|d|d<|S)NrzDirectly instantiating an SQLDatabaseChain with an llm is deprecated. 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