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Incorporated Gabe's comments
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modules/openshift-ai-connector-for-rhdh/proc-setting-up-openshift-ai-connector-for-rhdh-with-rhoai.adoc

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.{rhoai-short} Prerequisites
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* To have Model Cards from the Model Catalog imported as Tech Docs, you must use {rhoai-short} version 2.25 or later, and the Model Catalog dashboard and a Model Registry need to be enabled (they are both off by default).
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* To have Model Cards from the Model Catalog imported as TechDocs, you must use {rhoai-short} version 2.25 or later, and the *Model Catalog* dashboard and a Model Registry need to be enabled (they are both disabled by default).
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* If you employed Model Catalog at earlier versions of {rhoai-short}, Tech Doc propagation does not work for any models you registered into the Model Registry while at those earlier versions; only models registered into Model Registry from a 2.25 (or later) Model Catalog have their Model Cards transferred to {product-very-short} as TechDocs.
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* For the rest of the features, version 2.20 or later suffices. Enabling Model Registry and its associated dashboard allows for a user experience that more directly allows for customizing AI Model metadata.
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package: oci://ghcr.io/redhat-developer/rhdh-plugin-export-overlays/red-hat-developer-hub-backstage-plugin-catalog-techdoc-url-reader-backend:bs_1.42.5__0.3.0!red-hat-developer-hub-backstage-plugin-catalog-techdoc-url-reader-backend
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----
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. Add Connector sidecar containers to the {product-very-short} Pod.
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The system relies on three sidecar containers (Model Catalog Bridge) running alongside the `backstage-backend` container. These sidecar containers must be added to your {product-very-short} deployment specification, referencing the `rhdh-rhoai-bridge-token` Secret:
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** `location`: Provides the REST API for RHDH plugins to fetch model metadata.
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. Add `Connector` sidecar containers to the {product-very-short} Pod.
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** If {product-very-short} was installed using the Operator, modify your {product-very-short} custom resource (CR) instance.
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** If {product-very-short} was installed using the Helm charts, modify the *Deployment* specification.
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. The system relies on three sidecar containers (Model Catalog Bridge) running alongside the `backstage-backend` container. Add these sidecar containers to your configuration referencing the `rhdh-rhoai-bridge-token` Secret:
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** `location`: Provides the REST API for {product-very-short} plugins to fetch model metadata.
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** `storage-rest`: Maintains a cache of AI Model metadata in a ConfigMap called `bac-import-model`.
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** `rhoai-normalizer`: Acts as a Kubernetes controller and RHOAI client, normalizing RHOAI metadata for the connector. The following code block is an example:
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** `rhoai-normalizer`: Acts as a Kubernetes controller and {rhoai-short} client, normalizing {rhoai-short} metadata for the connector. The following code block is an example:
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[source,yaml]
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modules/openshift-ai-connector-for-rhdh/proc-troubleshooting-connector-functionality.adoc

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The Model Catalog Bridge sidecars manage the data fetching and storage:
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[IMPORTANT]
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====
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{openshift-ai-connector-name} collects feedback from users who engage with the feedback feature. If a user submits feedback, the feedback score (thumbs up or down), text feedback (if entered), the user query, and the LLM provider response are stored locally in the file system of the Pod. {company-name} does not have access to the collected feedback data.
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====
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. Check Cached Data (ConfigMap): The processed AI Model metadata is stored in a `ConfigMap`.
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[source,bash]

modules/openshift-ai-connector-for-rhdh/ref-enrich-ai-model-metadata.adoc

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|`TechDocs`
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|TechDocs
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|URL pointing to a Git repository that follows {product-very-short} TechDocs conventions for the Model Card.
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|URL pointing to a Git repository that follows {product-very-short} TechDocs conventions for the Model Card. Use this setting only if the *Model Card to TechDocs* mapping is not active.
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|`Homepage URL`
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|Links

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