[Search] Update notebooks & search_notebooks readme (#180630)

x-pack/plugins/search_notebooks/README.mdx

@@ -1,3 +1,15 @@
 # Search Notebooks plugin
 
 This plugin contains endpoints and components for rendering search python notebooks in the persistent dev console.
+
+### Cached Notebooks
+
+There is a limited set of search notebooks that we cache in `/server/data` directory to be served from this plugin. These should be available in all environments.
+
+To update the cached notebooks, run the following command:
+
+```shell
+./scripts/download-notebooks.sh
+```
+
+This script reads the `scripts/notebooks.txt` file and downloads each notebook from the url in the file and then saves it in the `server/data` directory with a snake_case filename and `.json` extension. The `.json` extension is just to make loading the files with node.js easier using an `async require()` instead of writing custom loading code with `fs` and implementing in-memory caching with the same loading code.

x-pack/plugins/search_notebooks/server/data/00_quick_start.json

@@ -9,7 +9,7 @@
    "source": [
     "# Semantic search quick start\n",
     "\n",
-    "<a target=\"_blank\" href=\"https://colab.research.google.com/github/elastic/elasticsearch-labs/blob/main/notebooks/search/00-quick-start.ipynb\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>\n",
+    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/elastic/elasticsearch-labs/blob/main/notebooks/search/00-quick-start.ipynb)\n",
     "\n",
     "This interactive notebook will introduce you to some basic operations with Elasticsearch, using the official [Elasticsearch Python client](https://www.elastic.co/guide/en/elasticsearch/client/python-api/current/connecting.html).\n",
     "You'll perform semantic search using [Sentence Transformers](https://www.sbert.net) for text embedding. Learn how to integrate traditional text-based search with semantic search, for a hybrid search system."

x-pack/plugins/search_notebooks/server/data/01_keyword_querying_filtering.json

@@ -8,7 +8,7 @@
    "source": [
     "# Keyword querying and filtering\n",
     "\n",
-    "<a target=\"_blank\" href=\"https://colab.research.google.com/github/elasticsearch-labs/blob/main/search/01-keyword-querying-filtering.ipynb\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>\n",
+    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/elasticsearch-labs/blob/main/search/01-keyword-querying-filtering.ipynb)\n",
     "\n",
     "This interactive notebook will introduce you to the basic Elasticsearch queries, using the official Elasticsearch Python client. Before getting started on this section you should work through our [quick start](https://github.com/elastic/elasticsearch-labs/blob/main/notebooks/search/00-quick-start.ipynb), as you will be using the same dataset."
    ]