fix old notebook

applications/rag/example_notebooks/rag-kaggle-ray-sql-latest.ipynb

@@ -1,5 +1,15 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "afb6fda4-ffde-4831-88a5-ae41144492b2",
+   "metadata": {},
+   "source": [
+    "# RAG-on-GKE Application\n",
+    "\n",
+    "This is a Python notebook for generating the vector embeddings used by the RAG on GKE application. For full information, please checkout the GitHub documentation [here](https://github.com/GoogleCloudPlatform/ai-on-gke/blob/main/applications/rag/README.md).\n"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -10,7 +20,7 @@
     "# Replace these with your settings\n",
     "# Navigate to https://www.kaggle.com/settings/account and generate an API token to be used to setup the env variable. See https://www.kaggle.com/docs/api#authentication how to create one.\n",
     "KAGGLE_USERNAME = \"<username>\"\n",
-    "KAGGLE_KEY = \"<token>\"\n"
+    "KAGGLE_KEY = \"<token>\""
    ]
   },
   {
@@ -36,8 +46,8 @@
     "\n",
     "# Download the zip file to local storage and then extract the desired contents directly to the GKE GCS CSI mounted bucket. The bucket is mounted at the \"/persist-data\" path in the jupyter pod.\n",
     "!kaggle datasets download -d shivamb/netflix-shows -p ~/data --force\n",
-    "!mkdir /persist-data/netflix-shows -p\n",
-    "!unzip -o ~/data/netflix-shows.zip -d /persist-data/netflix-shows"
+    "!mkdir /data/netflix-shows -p\n",
+    "!unzip -o ~/data/netflix-shows.zip -d /data/netflix-shows"
    ]
   },
   {