langchain/docs/examples/chains/sqlite.ipynb

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   "source": [
    "# SQLite example\n",
    "\n",
    "This example showcases hooking up an LLM to answer questions over a database."
   ]
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    "This uses the example Chinook database.\n",
    "To set it up follow the instructions on https://database.guide/2-sample-databases-sqlite/, placing the `.db` file in a notebooks folder at the root of this repository."
   ]
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   "source": [
    "from langchain import OpenAI, SQLDatabase, SQLDatabaseChain"
   ]
  },
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   "cell_type": "code",
   "execution_count": 2,
   "id": "72ede462",
   "metadata": {
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   "source": [
    "db = SQLDatabase.from_uri(\"sqlite:///../../../notebooks/Chinook.db\")\n",
    "llm = OpenAI(temperature=0)\n",
    "db_chain = SQLDatabaseChain(llm=llm, database=db, verbose=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "15ff81df",
   "metadata": {
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "\u001b[1m> Entering new chain...\u001b[0m\n",
      "How many employees are there?\n",
      "SQLQuery:\u001b[102m SELECT COUNT(*) FROM Employee\u001b[0m\n",
      "SQLResult: \u001b[103m[(8,)]\u001b[0m\n",
      "Answer:\u001b[102m 8\u001b[0m\n",
      "\u001b[1m> Finished chain.\u001b[0m\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "' 8'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "db_chain.run(\"How many employees are there?\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "61d91b85",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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