RHDH Model Catalog Bridge

This repository provides various containers that faciiltate theseamless export of AI model records from various AI Model Registres and imports them into Red Hat Developer Hub (Backstage) as catalog entities.

Current status: early POC stage.

• We have some docker files in place for the container imaages, but more work is needed there
• This repository collaborates with Backstage catalog entensions currently hosted in our fork of the RHDH plugins repository.
• Until those plugins have assoicated images and can be added to OCP RHDH, we have to run those plugins, and by extension backstage, from our laptops.
• By extension, the rhoai-normalizer and storage-reset containers have to run on one's laptop as well. The location container can run as an OCP deployment, but it is just as easy to run it out of your laptop as well.
• This simple Gitops repo has the means of setting up Open Data Hub plus dev patches for Kubelow Model Registry that facilitate getting the URLs for running Models deployed into RHOAI/ODH by the Model Registry.

Contributing

All contributions are welcome. The Apache 2 license is used and does not require any contributor agreement to submit patches. That said, the preference at this time for issue tracking is not GitHub issues in this repository.

Rather, visit the team's RHDHPAI Jira project and the 'model-registry-bridge' component.

Prerequisites

• An OpenShift cluster with 3x worker nodes, with at least 8 CPU, and 32GB memory each.
  • on AWS m6i.2xlarge or g5.2xlarge (if GPUs are needed) work well
  • For other options, see https://aws.amazon.com/ec2/instance-types/

Usage

Either via the command line, or from your favorite Golang editor, set the following environment variables as follows

rhoai-normalizer

1. K8S_TOKEN - the login/bearer token of your kubeadmin user for the OCP cluster you are testing on
2. KUBECONFIG - the path to the local kubeconfig file corresponding to your OCP cluster
3. MR_ROUTE - the name of the Model Registry route in the istio-system namespace. For now, use odh-model-registries-modelregistry-public-rest.
4. NAMESPACE - the name of the namespace you create for deploying AI models from ODH
5. STORAGE_URL - for now, just use http://localhost:7070; this will be updated when we can run this container in OCP as part of the RHDH plugin running in RHDH

storage-rest

1. RHDH_TOKEN - the static token you create in backstage to allows for authenticated access to the Backstage catalog API. See (https://github.com/redhat-ai-dev/rhdh-plugins/blob/main/workspaces/rhdh-ai/app-config.yaml#L19)[https://github.com/redhat-ai-dev/rhdh-plugins/blob/main/workspaces/rhdh-ai/app-config.yaml#L19]
2. BKSTG_URL - for now, just use http://localhost:7007; this will be updated when we can run this container in OCP as part of the RHDH plugin running in RHDH
3. BRIDGE_URL - for now, just use http://locahost:9090; this is the REST endpoint of our location container
4. STORAGE_TYPE - for now, only the development mode ConfigMap is supported; we'll add GitHub soon
5. K8S_TOKEN, KUBECONFIG, and NAMESPACE are the same as above

location

1. None of the above env vars are needed at this time.