Story (Required)

As a Platform Engineer, I should be able to model my organization’s AI assets in Red Hat Developer Hub in a consistent and logical manner. I should be able to 

As an Application Developer, I should be able to browse model servers and models that are available to my organization, and be provided with information about each one. 

Background (Required)

As part of DEVAI-10, a way to model AI assets (models, model servers) in a Backstage catalog will be implemented. This issue will focus on modeling the assets as native Backstage types:

• The LLM data files tracked by the customer (e.g. GGUF, safetensor files, etc.), modeled in the RHDH catalog as Resources.
• Model APIs, modeled in RHDH as API entities and readable in the API viewer in RHDH if using compatible specifications (like Swagger, OpenAPI, gRPC, etc).
• Model servers, modeled in the catalog as Components These may be linked to APIs and/or Resources using the entity graph in RHDH.

If these AI assets belong as part of a larger system (e.g. RHDH lightspeed), then it should be possible to link them together under one single System. 

Out of scope

• Any items documented in the Model Catalog API requiring techdocs will be handled in separate issues.

Approach (Required)

• Define a specification that implements every eligible field from the Model Catalog API using Backstage native types (see https://docs.google.com/document/d/1xQy-srzIakk_7fdN5_5AjlbZyXlR035Map8X_VCWYDs/edit#heading=h.kpa7e1df5ov) 
• Documenting an example, and how an AI catalog can be created from it
  • Use team model server as reference for example

Dependencies

<Describes what this story depends on. Dependent Stories and EPICs should be linked to the story.>

Acceptance Criteria (Required)

• Specification provided that implements the Model Catalog API (e.g. Google Doc or Git repo)
• Every, eligible non-techdoc related field in the Model Catalog API is implemented

Done Checklist

Code is completed, reviewed, documented and checked in
Unit and integration test automation have been delivered and running cleanly in continuous integration/staging/canary environment
Continuous Delivery pipeline(s) is able to proceed with new code included
Customer facing documentation, API docs, design docs etc. are produced/updated, reviewed and published
Acceptance criteria are met
If the Grafana dashboard is updated, ensure the corresponding SOP is updated as well