diff --git a/docs/docs/integrations/tools/nvidia_riva.ipynb b/docs/docs/integrations/tools/nvidia_riva.ipynb
index a4cf2f299ae..1cc5b9c964b 100644
--- a/docs/docs/integrations/tools/nvidia_riva.ipynb
+++ b/docs/docs/integrations/tools/nvidia_riva.ipynb
@@ -527,9 +527,54 @@
     "## 6. Create Additional Chain Components\n",
     "As usual, declare the other parts of the chain. In this case, it's just a prompt template and an LLM.\n",
     "\n",
+    "You can use any [LangChain compatible LLM](https://python.langchain.com/v0.1/docs/integrations/llms/) in the chain. In this example, we use a [Mixtral8x7b NIM from NVIDIA](https://python.langchain.com/v0.2/docs/integrations/chat/nvidia_ai_endpoints/). NVIDIA NIMs are supported in LangChain via the `langchain-nvidia-ai-endpoints` package, so you can easily build applications with best in class throughput and latency. \n",
+    "\n",
     "LangChain compatible NVIDIA LLMs from [NVIDIA AI Foundation Endpoints](https://www.nvidia.com/en-us/ai-data-science/foundation-models/) can also be used by following these [instructions](https://python.langchain.com/docs/integrations/chat/nvidia_ai_endpoints). "
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7fb27b941602401d91542211134fc71a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%pip install --upgrade --quiet langchain-nvidia-ai-endpoints"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1744eec9",
+   "metadata": {},
+   "source": [
+    "Follow the [instructions for LangChain](https://python.langchain.com/v0.2/docs/integrations/chat/nvidia_ai_endpoints/) to use NVIDIA NIM in your speech-enabled LangChain application. \n",
+    "\n",
+    "Set your key for NVIDIA API catalog, where NIMs are hosted for you to try."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0e37bdab",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import getpass\n",
+    "import os\n",
+    "\n",
+    "nvapi_key = getpass.getpass(\"NVAPI Key (starts with nvapi-): \")\n",
+    "assert nvapi_key.startswith(\"nvapi-\"), f\"{nvapi_key[:5]}... is not a valid key\"\n",
+    "os.environ[\"NVIDIA_API_KEY\"] = nvapi_key"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c754acb0",
+   "metadata": {},
+   "source": [
+    "Instantiate LLM."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 7,
@@ -538,10 +583,11 @@
    "outputs": [],
    "source": [
     "from langchain_core.prompts import PromptTemplate\n",
-    "from langchain_openai import OpenAI\n",
+    "from langchain_nvidia_ai_endpoints import ChatNVIDIA\n",
     "\n",
     "prompt = PromptTemplate.from_template(\"{user_input}\")\n",
-    "llm = OpenAI(openai_api_key=\"sk-xxx\")"
+    "\n",
+    "llm = ChatNVIDIA(model=\"mistralai/mixtral-8x7b-instruct-v0.1\")"
    ]
   },
   {