add notebook for sql query (#8442)

docs/extras/use_cases/tabular/sql_query.ipynb

@@ -0,0 +1,125 @@
+{
+ "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": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}