Updated 1_langchain_basic_deploy.ipynb markdown section to add content related to build. This example will be used to refer to annoucemnt for support of deploying lanchain app on manged online endpoint. Micky Lu and team will update the example with add quick start image (#3197)

sdk/python/endpoints/online/llm/langchain/1_langchain_basic_deploy.ipynb

@@ -4,7 +4,18 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Langchain Integration into Azure Machine Learning (AzureML)\n",
+    "# Unleashing the new possibilities: Deploy your LangChain application on managed online endpoint \n",
+    "\n",
+    "In rapidly evolving AI landscape, the need for swift and scalable AI application deployment is essential. Recognizing this, we are excited to unveil a new capability that supports LangChain applications- the leading tool for building LLM apps to be deployed quickly and effortlessly on managed online endpoints and enjoy the perks of managed online endpoints.\n",
+    "\n",
+    "In this notebook, you will learn how to deploy rapidly your LangChain app to a managed online endpoint for use in real-time inference. You can follow below steps to easily deploy your LangCahin app on managed online endpoints. We’re providing you with a QuickStart image that you can reuse for your development purpose along with example below to follow along."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Langchain Integration into Azure Machine Learning (AzureML)\n",
     "\n",
     "**Requirements** - In order to benefit from this tutorial, you will need:\n",
     "* A basic understanding of Machine Learning and Large Language Models\n",