Update docs in favor the 2023b release

docs/developer-guide.md

@@ -8,7 +8,7 @@ These release branches follow a specific naming format: YYYYx, where "YYYY" repr
 The structure of the notebook's build chain is derived from the parent image. To better comprehend this concept, refer to the following graph.
 
 <p align="center">
-<img src="https://github.com/opendatahub-io/notebooks/assets/42587738/9e5df03f-01f4-4bba-9792-3b56e9b5b912" data-canonical-src="https://github.com/opendatahub-io/notebooks/assets/42587738/9e5df03f-01f4-4bba-9792-3b56e9b5b912" width="820" height="520" />
+<img src="https://github.com/opendatahub-io/notebooks/assets/42587738/9e5df03f-01f4-4bba-9792-3b56e9b5b912" data-canonical-src="https://github.com/opendatahub-io/notebooks/assets/42587738/9e5df03f-01f4-4bba-9792-3b56e9b5b912" width="820" height="450" />
 </p>
 
 
@@ -62,7 +62,7 @@ spec:
 
 ### **ImageStream definitions for the supported out-of-the-box images in ODH**  
 
-The ImageStream definitions of the out-of-the-box workbench images for ODH can be found [here](https://github.com/opendatahub-io/odh-manifests/tree/master/notebook-images).
+The ImageStream definitions of the out-of-the-box workbench images for ODH can be found [here](https://github.com/opendatahub-io/notebooks/tree/2023b/manifests).
 
 ### **Example ImageStream object definition**  
 
@@ -140,19 +140,19 @@ tests:
 ## GitHub Actions
 This section provides an overview of the automation functionalities.
 
-**Piplock Renewal** [[Link](https://github.com/opendatahub-io/notebooks/blob/main/.github/workflows/piplock-renewal-2023a.yml)]
+### **Piplock Renewal** [[Link](https://github.com/opendatahub-io/notebooks/blob/main/.github/workflows/piplock-renewal-2023a.yml)]
 
 This GitHub action is configured to be triggered on a weekly basis, specifically every Monday at 22:00 PM UTC. Its main objective is to automatically update the Pipfile.lock files by fetching the most recent minor versions available. Additionally, it also updates the hashes for the downloaded files of Python dependencies, including any sub-dependencies. Once the updated files are pushed, the CI pipeline is triggered to generate new updated images based on these changes.
 
-**Sync the downstream release branch with the upstream** [[Link](https://github.com/red-hat-data-services/notebooks/blob/main/.github/workflows/sync-release-branch-2023a.yml)]
+### **Sync the downstream release branch with the upstream** [[Link](https://github.com/red-hat-data-services/notebooks/blob/main/.github/workflows/sync-release-branch-2023a.yml)]
 
 This GitHub action is configured to be triggered on a weekly basis, specifically every Tuesday at 08:00 AM UTC. Its main objective is to automatically update the downstream release branch with the upstream branch. 
 
-**Digest Updater workflow on the manifests** [[Link](https://github.com/opendatahub-io/odh-manifests/blob/master/.github/workflows/notebooks-digest-updater-upstream.yaml)]
+### **Digest Updater workflow on the manifests** [[Link](https://github.com/opendatahub-io/odh-manifests/blob/master/.github/workflows/notebooks-digest-updater-upstream.yaml)]
  
 This GitHub action is designed to be triggered on a weekly basis, specifically every Friday at 12:00 AM UTC. Its primary purpose is to automate the process of updating the SHA digest of the notebooks. It achieves this by fetching the new SHA values from the quay.io registry and updating the [param.env](https://github.com/opendatahub-io/odh-manifests/blob/master/notebook-images/base/params.env) file, which is hosted on the odh-manifest repository. By automatically updating the SHA digest, this action ensures that the notebooks remain synchronized with the latest changes.
 
-**Digest Updater workflow on the live-builder** [[Link](https://gitlab.cee.redhat.com/data-hub/rhods-live-builder/-/blob/main/.gitlab/notebook-sha-digest-updater.yml)]
+### **Digest Updater workflow on the live-builder** [[Link](https://gitlab.cee.redhat.com/data-hub/rhods-live-builder/-/blob/main/.gitlab/notebook-sha-digest-updater.yml)]
 
 This GitHub action works with the same logic as the above and is designed to be triggered on a weekly basis, specifically every Friday. It is also update the SHA digest of the images into the [CSV](https://gitlab.cee.redhat.com/data-hub/rhods-live-builder/-/blob/main/rhods-operator-live/bundle/template/manifests/clusterserviceversion.yml.j2#L725) file on the live-builder repo. 
   

docs/user-guide.md

@@ -6,7 +6,7 @@ There are two options for launching a workbench image: either through the Enable
 In the ODH dashboard, you can navigate to Applications -> Enabled -> Launch Application from the Jupyter tile. The notebook server spawner page displays a list of available container images you can run as a single user."
 
 <p align="center">
-<img src="https://github.com/opendatahub-io/notebooks/assets/42587738/8ff97ee4-4c47-4b87-b476-fe5adec4462d" data-canonical-src="https://github.com/opendatahub-io/notebooks/assets/42587738/8ff97ee4-4c47-4b87-b476-fe5adec4462d" width="700" height="950" />
+<img src="https://github.com/opendatahub-io/notebooks/assets/42587738/8ff97ee4-4c47-4b87-b476-fe5adec4462d" data-canonical-src="https://github.com/opendatahub-io/notebooks/assets/42587738/8ff97ee4-4c47-4b87-b476-fe5adec4462d" width="700" height="920" />
 </p>
 
 
@@ -15,7 +15,7 @@ In the ODH dashboard, you can navigate to Applications -> Enabled -> Launch Appl
 A user can navigate to the Data Science Project menu and create a project like the following:
 
 <p align="center">
-<img src="https://github.com/opendatahub-io/notebooks/assets/42587738/487b99b0-01a4-4fb6-8f68-17b558c3808f" data-canonical-src="https://github.com/opendatahub-io/notebooks/assets/42587738/487b99b0-01a4-4fb6-8f68-17b558c3808f" width="950" height="920" />
+<img src="https://github.com/opendatahub-io/notebooks/assets/42587738/487b99b0-01a4-4fb6-8f68-17b558c3808f" data-canonical-src="https://github.com/opendatahub-io/notebooks/assets/42587738/487b99b0-01a4-4fb6-8f68-17b558c3808f" width="950" height="820" />
 </p>
 
 ## Updates
@@ -26,12 +26,12 @@ This section provides an overview of the rebuilding plan. There are two types of
 1. Patch updates - These updates will be carried out weekly and will focus on incorporating security updates to the notebook images.
 
 
-**Scope and frequency of the updates**
+### **Scope and frequency of the updates**
 
 When performing major updates to the notebook images, all components are reviewed for updates, including the base OS image, OS packages, Python version, and Python packages and libraries. A major update, which will be named “YYYYx” release (where YYYY is the year and x is an increased letter), will fix the set of components that are included, as well as their MAJOR and MINOR versions.
 During the release lifecycle, which is the period during which the update is supported, the only updates that will be made are patches to allow for security updates and fixes while maintaining compatibility. These weekly updates will only modify the PATCH version, leaving the major and minor versions unchanged.
 
-**Support**
+### **Support**
 
 Our goal is to ensure that notebook images are supported for a minimum of one year, meaning that typically two supported images will be available at any given time. This provides sufficient time for users to update their code to use components from the latest notebook images. We will continue to make older images available in the registry for users to add as custom notebook images, even if they are no longer supported. This way, users can still access the older images if needed.
 Example lifecycle (not actual dates):

docs/workbench-imagestreams.md

@@ -1,12 +1,12 @@
-# Workbench ImageStreams
+## Workbench ImageStreams
 
 ODH supports multiple out-of-the-box pre-built workbench images ([provided in this repository](https://github.com/opendatahub-io/notebooks)). For each of those workbench images, there is a dedicated ImageStream object definition. This ImageStream object references the actual image tag(s) and contains additional metadata that describe the workbench image.
-
-## Annotations
+  
+### **Annotations**
 
 Aside from the general ImageStream config values, there are additional annotations that can be provided in the workbench ImageStream definition. This additional data is leveraged further by the [odh-dashboard](https://github.com/opendatahub-io/odh-dashboard/).
 
-### ImageStream-specific annotations
+### **ImageStream-specific annotations**  
 The following labels and annotations are specific to the particular workbench image. They are provided in their respective sections in the `metadata` section. 
 ```yaml
 metadata:
@@ -15,17 +15,16 @@ metadata:
   annotations:
     ...
 ```
-#### Available labels
+### **Available labels**  
 -  **`opendatahub.io/notebook-image:`** - a flag that determines whether the ImageStream references a workbench image that is meant be shown in the UI
-#### Available annotations
+### **Available annotations**
 - **`opendatahub.io/notebook-image-url:`** - a URL reference to the source of the particular workbench image
 - **`opendatahub.io/notebook-image-name:`** - a desired display name string for the particular workbench image (used in the UI)
 - **`opendatahub.io/notebook-image-desc:`** - a desired description string of the of the particular workbench image (used in the UI) 
 - **`opendatahub.io/notebook-image-order:`** - an index value for the particular workbench ImageStream (used by the UI to list available workbench images in a specific order)
+- **`opendatahub.io/recommended-accelerators`** - a string that represents the list of recommended hardware accelerators for the particular workbench ImageStream (used in the UI)
 
-- **`opendatahub.io/recommended-accelerators`** - a string that represents the list of recommended hardware accelerators for the particular workbench ImageStream. This is used by the ODH dashboard component to correctly assign accelerators and tolerations to the workbench. Ex: `'["nvidia.com/gpu", "habana.com/gen1"]'`
-Note: The annotation is not required for non-accelerator recommended images i.e. you do not need to include an empty array.
-### Tag-specific annotations
+### **Tag-specific annotations**  
 One ImageStream can reference multiple image tags. The following annotations are specific to a particular workbench image tag and are provided in its `annotations:` section.
 ```yaml
 spec:
@@ -37,17 +36,17 @@ spec:
         name: image-repository/tag
       name: tag-name
 ```
-#### Available annotations
+### **Available annotations**  
   - **`opendatahub.io/notebook-software:`** - a string that represents the technology stack included within the workbench image. Each technology in the list is described by its name and the version used (e.g. `'[{"name":"CUDA","version":"11.8"},{"name":"Python","version":"v3.9"}]`')
   - **`opendatahub.io/notebook-python-dependencies:`** -  a string that represents the list of Python libraries included within the workbench image. Each library is described by its name and currently used version (e.g. `'[{"name":"Numpy","version":"1.24"},{"name":"Pandas","version":"1.5"}]'`)
   - **`openshift.io/imported-from:`** - a reference to the image repository where the workbench image was obtained (e.g. `quay.io/repository/opendatahub/workbench-images`)
   - **`opendatahub.io/workbench-image-recommended:`** - a flag that allows the ImageStream tag to be marked as Recommended (used by the UI to distinguish which tags are recommended for use, e.g., when the workbench image offers multiple tags to choose from)
 
-## ImageStream definitions for the supported out-of-the-box images in ODH
+### **ImageStream definitions for the supported out-of-the-box images in ODH**  
 
-The ImageStream definitions of the out-of-the-box workbench images for ODH can be found [here](https://github.com/opendatahub-io/odh-manifests/tree/master/notebook-images).
+The ImageStream definitions of the out-of-the-box workbench images for ODH can be found [here](https://github.com/opendatahub-io/notebooks/tree/2023b/manifests).
 
-## Example ImageStream object definition
+### **Example ImageStream object definition**  
 
 An exemplary, non-functioning ImageStream object definition that uses all the aforementioned annotations is provided below.
 
@@ -62,14 +61,14 @@ metadata:
     opendatahub.io/notebook-image-name: "Example Jupyter Notebook"
     opendatahub.io/notebook-image-desc: "Exemplary Jupyter notebook image just for demonstrative purposes"
     opendatahub.io/notebook-image-order: "1"
-    opendatahub.io/recommended-accelerators: '["nvidia.com/gpu"]'
+    opendatahub.io/recommended-accelerators: '["nvidia.com/gpu", "habana.com/gen1"]'
   name: example-jupyter-notebook
 spec:
   lookupPolicy:
     local: true
   tags:
   - annotations:
-      opendatahub.io/notebook-software: '[{"name":"CUDA","version":"11.8"},{"name":"Python","version":"v3.9"}]'
+      opendatahub.io/notebook-software: '[{"name":"Python","version":"v3.9"}]'
       opendatahub.io/notebook-python-dependencies: '[{"name":"Boto3","version":"1.26"},{"name":"Kafka-Python","version":"2.0"},{"name":"Kfp-tekton","version":"1.5"},{"name":"Matplotlib","version":"3.6"},{"name":"Numpy","version":"1.24"},{"name":"Pandas","version":"1.5"},{"name":"Scikit-learn","version":"1.2"},{"name":"Scipy","version":"1.10"}]'
       openshift.io/imported-from: quay.io/opendatahub/workbench-images
       opendatahub.io/workbench-image-recommended: 'true'