notebooks/langchain/_nbtest.teardown.langchain-vector-store-using-elser.ipynb

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   "source": [
    "from elasticsearch import Elasticsearch\n",
    "from getpass import getpass\n",
    "\n",
    "ELASTIC_CLOUD_ID = getpass(\"Elastic Cloud ID: \")\n",
    "ELASTIC_API_KEY = getpass(\"Elastic Api Key: \")\n",
    "\n",
    "client = Elasticsearch(\n",
    "    cloud_id=ELASTIC_CLOUD_ID,\n",
    "    api_key=ELASTIC_API_KEY,\n",
    ")\n",
    "\n",
    "# delete the notebook's index\n",
    "client.indices.delete(index=\"workplace_index\", ignore_unavailable=True)\n",
    "\n",
    "# delete the pipeline\n",
    "try:\n",
    "    client.ingest.delete_pipeline(id=\".elser_model_2_sparse_embedding\")\n",
    "except:\n",
    "    pass\n",
    "\n",
    "# delete the model\n",
    "try:\n",
    "    client.ml.delete_trained_model(model_id=\".elser_model_2\", force=True)\n",
    "except:\n",
    "    pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6dbce06c-fea9-457b-87c4-0a0e5cfcc1b7",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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