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langchain/langchain/agents/agent_toolkits/sql/toolkit.py

60 lines
2.2 KiB
Python

"""Toolkit for interacting with a SQL database."""
from typing import List
from pydantic import Field
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.base_language import BaseLanguageModel
from langchain.sql_database import SQLDatabase
from langchain.tools import BaseTool
from langchain.tools.sql_database.tool import (
InfoSQLDatabaseTool,
ListSQLDatabaseTool,
QuerySQLCheckerTool,
QuerySQLDataBaseTool,
)
class SQLDatabaseToolkit(BaseToolkit):
"""Toolkit for interacting with SQL databases."""
db: SQLDatabase = Field(exclude=True)
llm: BaseLanguageModel = Field(exclude=True)
@property
def dialect(self) -> str:
"""Return string representation of dialect to use."""
return self.db.dialect
class Config:
"""Configuration for this pydantic object."""
arbitrary_types_allowed = True
def get_tools(self) -> List[BaseTool]:
"""Get the tools in the toolkit."""
query_sql_database_tool_description = (
"Input to this tool is a detailed and correct SQL query, output is a "
"result from the database. If the query is not correct, an error message "
"will be returned. If an error is returned, rewrite the query, check the "
"query, and try again. If you encounter an issue with Unknown column "
"'xxxx' in 'field list', using schema_sql_db to query the correct table "
"fields."
)
info_sql_database_tool_description = (
"Input to this tool is a comma-separated list of tables, output is the "
"schema and sample rows for those tables. "
"Be sure that the tables actually exist by calling list_tables_sql_db "
"first! Example Input: 'table1, table2, table3'"
)
return [
QuerySQLDataBaseTool(
db=self.db, description=query_sql_database_tool_description
),
InfoSQLDatabaseTool(
db=self.db, description=info_sql_database_tool_description
),
ListSQLDatabaseTool(db=self.db),
QuerySQLCheckerTool(db=self.db, llm=self.llm),
]