Merging the first draft of the Kserve template

[mholder6]

Description of your changes:
This PR introduces a Kubeflow Pipelines (KFP) template for deploying a model to KServe on OpenShift AI. The template automates the model deployment process by leveraging OpenShift AI’s Data Science Pipelines, ensuring seamless integration with KServe, Authorino, OpenShift Service Mesh, and OpenShift Serverless.

Key Features:

Provides a ready-to-use pipeline template for deploying models via KServe.
Automates the creation of InferenceService and AuthConfig resources.
Uses Kustomize to configure and deploy necessary Kubernetes resources.
Supports integration with Authorino for authentication.
Allows parameterization for model selection and configuration.

How to Use:

Deploy the necessary manifests using Kustomize.
Install required Python dependencies.
Compile the pipeline using kfp dsl compile.
Upload and execute the pipeline in OpenShift AI.
Verify the model deployment by checking the running pods and InferenceService.

[google-oss-prow]

Hi @mholder6. Thanks for your PR.

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[google-oss-prow]

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[terrytangyuan]

This should ideally replace the existing https://github.com/kubeflow/pipelines/tree/master/components/kserve

cc @hbelmiro to provide some guidance here

[hbelmiro]

/hold

[dandawg]

"predictor"