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    "## Run Template\n",
    "\n",
    "In `server.py`, set -\n",
    "```\n",
    "from fastapi import FastAPI\n",
    "from langserve import add_routes\n",
    "from propositional_retrieval import chain\n",
    "\n",
    "app = FastAPI(\n",
    "    title=\"LangChain Server\",\n",
    "    version=\"1.0\",\n",
    "    description=\"Retriever and Generator for RAG Chroma Dense Retrieval\",\n",
    ")\n",
    "\n",
    "add_routes(app, chain, path=\"/propositional-retrieval\")\n",
    "\n",
    "if __name__ == \"__main__\":\n",
    "    import uvicorn\n",
    "\n",
    "    uvicorn.run(app, host=\"localhost\", port=8000)\n",
    "\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d774be2a",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langserve.client import RemoteRunnable\n",
    "\n",
    "rag_app = RemoteRunnable(\"http://localhost:8001/propositional-retrieval\")\n",
    "rag_app.invoke(\"How are transformers related to convolutional neural networks?\")"
   ]
  }
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