langchain/docs/extras/use_cases/tabular/sql_query.ipynb

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 "cells": [
  {
   "cell_type": "markdown",
   "id": "c04293ac",
   "metadata": {},
   "source": [
    "# SQL Query\n",
    "\n",
    "This notebook walks through how to load and run a chain that constructs SQL queries that can be run against your database to answer a question. Note that this ONLY constructs the query and does not run it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e9063a93",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.chains import create_sql_query_chain\n",
    "\n",
    "from langchain.chat_models import ChatOpenAI\n",
    "from langchain.utilities import SQLDatabase"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a1ff5cee",
   "metadata": {},
   "outputs": [],
   "source": [
    "db = SQLDatabase.from_uri(\"sqlite:///../../../../notebooks/Chinook.db\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "cb04579f",
   "metadata": {},
   "outputs": [],
   "source": [
    "chain = create_sql_query_chain(ChatOpenAI(temperature=0), db)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "744e6210",
   "metadata": {},
   "outputs": [],
   "source": [
    "response = chain.invoke({\"question\":\"How many employees are there\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "28f984f1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SELECT COUNT(*) FROM Employee\n"
     ]
    }
   ],
   "source": [
    "print(response)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "08de511c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'[(8,)]'"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "db.run(response)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e3a006a7",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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