Revert "docs: add new documentation and fix existing docs"

This reverts commit 9288016.

Author: KPostOffice

README.md

@@ -11,7 +11,7 @@ For guided demos and basics walkthroughs, check out the following links:
 - these demos can be copied into your current working directory when using the `codeflare-sdk` by using the `codeflare_sdk.copy_demo_nbs()` function
 - Additionally, we have a [video walkthrough](https://www.youtube.com/watch?v=U76iIfd9EmE) of these basic demos from June, 2023
 
-Full documentation can be found [here](https://project-codeflare.github.io/codeflare-sdk/index.html)
+Full documentation can be found [here](https://project-codeflare.github.io/codeflare-sdk/detailed-documentation)
 
 ## Installation
 
@@ -32,10 +32,11 @@ It is possible to use the Release Github workflow to do the release. This is gen
 The following instructions apply when doing release manually. This may be required in instances where the automation is failing.
 
 - Check and update the version in "pyproject.toml" file.
+- Generate new documentation.
+`pdoc --html -o docs src/codeflare_sdk && pushd docs && rm -rf cluster job utils && mv codeflare_sdk/* . && rm -rf codeflare_sdk && popd && find docs -type f -name "*.html" -exec bash -c "echo '' >> {}" \;` (it is possible to install **pdoc** using the following command `poetry install --with docs`)
 - Commit all the changes to the repository.
 - Create Github release (<https://docs.github.com/en/repositories/releasing-projects-on-github/managing-releases-in-a-repository#creating-a-release>).
 - Build the Python package. `poetry build`
 - If not present already, add the API token to Poetry.
 `poetry config pypi-token.pypi API_TOKEN`
 - Publish the Python package. `poetry publish`
-- Trigger the [Publish Documentation](https://github.com/project-codeflare/codeflare-sdk/actions/workflows/publish-documentation.yaml) workflow

docs/sphinx/index.rst

@@ -16,16 +16,14 @@ The CodeFlare SDK is an intuitive, easy-to-use python interface for batch resour
    modules
 
 .. toctree::
-   :maxdepth: 1
+   :maxdepth: 2
    :caption: User Documentation:
 
    user-docs/authentication
    user-docs/cluster-configuration
-   user-docs/ray-cluster-interaction
    user-docs/e2e
    user-docs/s3-compatible-storage
    user-docs/setup-kueue
-   user-docs/ui-widgets
 
 Quick Links
 ===========

docs/sphinx/user-docs/authentication.rst

@@ -39,7 +39,7 @@ a login command like ``oc login --token=<token> --server=<server>``
 their kubernetes config file should have updated. If the user has not
 specifically authenticated through the SDK by other means such as
 ``TokenAuthentication`` then the SDK will try to use their default
-Kubernetes config file located at ``"$HOME/.kube/config"``.
+Kubernetes config file located at ``"/HOME/.kube/config"``.
 
 Method 3 Specifying a Kubernetes Config File
 --------------------------------------------
@@ -62,5 +62,5 @@ Method 4 In-Cluster Authentication
 ----------------------------------
 
 If a user does not authenticate by any of the means detailed above and
-does not have a config file at ``"$HOME/.kube/config"`` the SDK will try
+does not have a config file at ``"/HOME/.kube/config"`` the SDK will try
 to authenticate with the in-cluster configuration file.

docs/sphinx/user-docs/cluster-configuration.rst

@@ -29,14 +29,13 @@ requirements for creating the Ray Cluster.
        labels={"exampleLabel": "example", "secondLabel": "example"},
    ))
 
-.. note::
-  `quay.io/modh/ray:2.35.0-py39-cu121` is the default image used by
-  the CodeFlare SDK for creating a RayCluster resource. If you have your
-  own Ray image which suits your purposes, specify it in image field to
-  override the default image. If you are using ROCm compatible GPUs you
-  can use `quay.io/modh/ray:2.35.0-py39-rocm61`. You can also find
-  documentation on building a custom image
-  `here <https://github.com/opendatahub-io/distributed-workloads/tree/main/images/runtime/examples>`__.
+Note: ‘quay.io/modh/ray:2.35.0-py39-cu121’ is the default image used by
+the CodeFlare SDK for creating a RayCluster resource. If you have your
+own Ray image which suits your purposes, specify it in image field to
+override the default image. If you are using ROCm compatible GPUs you
+can use ‘quay.io/modh/ray:2.35.0-py39-rocm61’. You can also find
+documentation on building a custom image
+`here <https://github.com/opendatahub-io/distributed-workloads/tree/main/images/runtime/examples>`__.
 
 The ``labels={"exampleLabel": "example"}`` parameter can be used to
 apply additional labels to the RayCluster resource.
@@ -47,8 +46,7 @@ After creating their ``cluster``, a user can call ``cluster.up()`` and
 Deprecating Parameters
 ----------------------
 
-The following parameters of the ``ClusterConfiguration`` are being
-deprecated.
+The following parameters of the ``ClusterConfiguration`` are being deprecated.
 
 .. list-table::
    :header-rows: 1

docs/sphinx/user-docs/e2e.rst

@@ -11,7 +11,7 @@ On KinD clusters
 
 Pre-requisite for KinD clusters: please add in your local ``/etc/hosts``
 file ``127.0.0.1 kind``. This will map your localhost IP address to the
-KinD cluster's hostname. This is already performed on `GitHub
+KinD cluster’s hostname. This is already performed on `GitHub
 Actions <https://github.com/project-codeflare/codeflare-common/blob/1edd775e2d4088a5a0bfddafb06ff3a773231c08/github-actions/kind/action.yml#L70-L72>`__
 
 If the system you run on contains NVidia GPU then you can enable the GPU
@@ -91,7 +91,7 @@ instructions <https://www.substratus.ai/blog/kind-with-gpus>`__.
       poetry install --with test,docs
       poetry run pytest -v -s ./tests/e2e/mnist_raycluster_sdk_kind_test.py
 
-   -  If the cluster doesn't have NVidia GPU support then we need to
+   -  If the cluster doesn’t have NVidia GPU support then we need to
       disable NVidia GPU tests by providing proper marker:
 
    ::
@@ -124,8 +124,8 @@ If the system you run on contains NVidia GPU then you can enable the GPU
 support on OpenShift, this will allow you to run also GPU tests. To
 enable GPU on OpenShift follow `these
 instructions <https://docs.nvidia.com/datacenter/cloud-native/openshift/latest/introduction.html>`__.
-Currently the SDK doesn't support tolerations, so e2e tests can't be
-executed on nodes with taint (i.e. GPU taint).
+Currently the SDK doesn’t support tolerations, so e2e tests can’t be
+executed on nodes with taint (i.e. GPU taint).
 
 -  Test Phase:
 
@@ -203,9 +203,8 @@ On OpenShift Disconnected clusters
             AWS_STORAGE_BUCKET=<storage-bucket-name>
             AWS_STORAGE_BUCKET_MNIST_DIR=<storage-bucket-MNIST-datasets-directory>
 
-         .. note::
-            When using the Python Minio client to connect to a minio
-            storage bucket, the ``AWS_DEFAULT_ENDPOINT`` environment
-            variable by default expects secure endpoint where user can use
-            endpoint url with https/http prefix for autodetection of
-            secure/insecure endpoint.
+         Note : When using the Python Minio client to connect to a minio
+         storage bucket, the ``AWS_DEFAULT_ENDPOINT`` environment
+         variable by default expects secure endpoint where user can use
+         endpoint url with https/http prefix for autodetection of
+         secure/insecure endpoint.

docs/sphinx/user-docs/images/ui-buttons.png

@@ -82,5 +82,5 @@ Lastly the new ``run_config`` must be added to the Trainer:
 To find more information on creating a Minio Bucket compatible with
 RHOAI you can refer to this
 `documentation <https://ai-on-openshift.io/tools-and-applications/minio/minio/>`__.
-Note: You must have ``s3fs`` and ``pyarrow`` installed in your
+Note: You must have ``sf3s`` and ``pyarrow`` installed in your
 environment for this method.

docs/sphinx/user-docs/images/ui-view-clusters.png

@@ -11,9 +11,10 @@ Kueue resources, namely Cluster Queue, Resource Flavor, and Local Queue.
 1. Resource Flavor:
 -------------------
 
-Resource Flavors allow the cluster admin to reflect differing resource capabilities
-of nodes within a clusters, such as CPU, memory, GPU, etc. These can then be assigned
-to workloads to ensure they are executed on nodes with appropriate resources.
+Resource Flavors allow the cluster admin to define different types of
+resources with specific characteristics, such as CPU, memory, GPU, etc.
+These can then be assigned to workloads to ensure they are executed on
+appropriate resources.
 
 The YAML configuration provided below creates an empty Resource Flavor
 named default-flavor. It serves as a starting point and does not specify