langchain/templates/rag-vectara/rag_vectara.ipynb

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{
"cells": [
{
"attachments": {},
"cell_type": "markdown",
"id": "8692a430",
"metadata": {},
"source": [
"# Run Template\n",
"\n",
"In `server.py`, set -\n",
"```\n",
"add_routes(app, chain_ext, path=\"/rag-vectara\")\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "41db5e30",
"metadata": {},
"outputs": [],
"source": [
"from langserve.client import RemoteRunnable\n",
"\n",
"rag_app_vectara = RemoteRunnable(\"http://localhost:8000/rag-vectara\")\n",
"rag_app_vectara.invoke(\"How does agent memory work?\")"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3.11.6 64-bit",
"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": "3.11.6"
},
"vscode": {
"interpreter": {
"hash": "aee8b7b246df8f9039afb4144a1f6fd8d2ca17a180786b69acc140d282b71a49"
}
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},
"nbformat": 4,
"nbformat_minor": 5
}