mirror of
https://github.com/hwchase17/langchain
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76 lines
2.9 KiB
Python
76 lines
2.9 KiB
Python
"""Toolkit for interacting with an SQL database."""
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from typing import List
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from langchain_core.language_models import BaseLanguageModel
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from langchain_core.pydantic_v1 import Field
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from langchain_community.agent_toolkits.base import BaseToolkit
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from langchain_community.tools import BaseTool
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from langchain_community.tools.sql_database.tool import (
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InfoSQLDatabaseTool,
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ListSQLDatabaseTool,
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QuerySQLCheckerTool,
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QuerySQLDataBaseTool,
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)
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from langchain_community.utilities.sql_database import SQLDatabase
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class SQLDatabaseToolkit(BaseToolkit):
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"""Toolkit for interacting with SQL databases."""
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db: SQLDatabase = Field(exclude=True)
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llm: BaseLanguageModel = Field(exclude=True)
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@property
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def dialect(self) -> str:
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"""Return string representation of SQL dialect to use."""
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return self.db.dialect
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class Config:
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"""Configuration for this pydantic object."""
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arbitrary_types_allowed = True
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def get_tools(self) -> List[BaseTool]:
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"""Get the tools in the toolkit."""
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list_sql_database_tool = ListSQLDatabaseTool(db=self.db)
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info_sql_database_tool_description = (
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"Input to this tool is a comma-separated list of tables, output is the "
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"schema and sample rows for those tables. "
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"Be sure that the tables actually exist by calling "
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f"{list_sql_database_tool.name} first! "
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"Example Input: table1, table2, table3"
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)
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info_sql_database_tool = InfoSQLDatabaseTool(
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db=self.db, description=info_sql_database_tool_description
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)
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query_sql_database_tool_description = (
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"Input to this tool is a detailed and correct SQL query, output is a "
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"result from the database. If the query is not correct, an error message "
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"will be returned. If an error is returned, rewrite the query, check the "
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"query, and try again. If you encounter an issue with Unknown column "
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f"'xxxx' in 'field list', use {info_sql_database_tool.name} "
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"to query the correct table fields."
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)
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query_sql_database_tool = QuerySQLDataBaseTool(
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db=self.db, description=query_sql_database_tool_description
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)
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query_sql_checker_tool_description = (
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"Use this tool to double check if your query is correct before executing "
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"it. Always use this tool before executing a query with "
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f"{query_sql_database_tool.name}!"
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)
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query_sql_checker_tool = QuerySQLCheckerTool(
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db=self.db, llm=self.llm, description=query_sql_checker_tool_description
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)
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return [
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query_sql_database_tool,
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info_sql_database_tool,
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list_sql_database_tool,
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query_sql_checker_tool,
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]
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def get_context(self) -> dict:
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"""Return db context that you may want in agent prompt."""
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return self.db.get_context()
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