add redirectToPlayground to ChatbotConfigurationModal in VectorStoreTableRow.tsx, move computeEmbeddingModelStatus and reuse in Configuration modal, update tests

Author: jharan1

packages/gen-ai/frontend/src/app/AIAssets/components/vectorstores/VectorStoreTableRow.tsx

@@ -16,42 +16,13 @@ import {
   LlamaStackDistributionModel,
   VectorStore,
 } from '~/app/types';
-import { splitLlamaModelId } from '~/app/utilities/utils';
+import { computeEmbeddingModelStatus } from '~/app/utilities/utils';
 import { GenAiContext } from '~/app/context/GenAiContext';
 import { genAiChatPlaygroundRoute } from '~/app/utilities/routes';
 import ChatbotConfigurationModal from '~/app/Chatbot/components/chatbotConfiguration/ChatbotConfigurationModal';
 import VectorStoreTableRowInfo from './VectorStoreTableRowInfo';
 
-export type EmbeddingModelStatus = 'not_available' | 'available' | 'registered';
-
-export const computeEmbeddingModelStatus = (
-  embeddingModel: string,
-  allModels: AIModel[],
-  playgroundModels: LlamaModel[],
-): EmbeddingModelStatus => {
-  const { id: normalizedId } = splitLlamaModelId(embeddingModel);
-
-  // "registered": embedding model is in the LlamaStack playground.
-  // playgroundModels[].modelId is already normalized via splitLlamaModelId.
-  const isRegistered = playgroundModels.some(
-    (m) => m.modelId === embeddingModel || m.modelId === normalizedId,
-  );
-  if (isRegistered) {
-    return 'registered';
-  }
-
-  // "available": embedding model exists in the unified AI Assets models list (AAE + MaaS).
-  // Normalize both sides to handle provider-prefixed vs plain IDs.
-  const isAvailable = allModels.some((m) => {
-    const { id: normalizedModelId } = splitLlamaModelId(m.model_id);
-    return m.model_id === embeddingModel || normalizedModelId === normalizedId;
-  });
-  if (isAvailable) {
-    return 'available';
-  }
-
-  return 'not_available';
-};
+export type { EmbeddingModelStatus } from '~/app/utilities/utils';
 
 interface VectorStoreTableRowProps {
   store: ExternalVectorStoreSummary;
@@ -174,6 +145,7 @@ const VectorStoreTableRow: React.FC<VectorStoreTableRowProps> = ({
           existingCollections={existingCollections}
           extraSelectedCollections={[store]}
           initialStepId="collections"
+          redirectToPlayground
         />
       )}
     </>

packages/gen-ai/frontend/src/app/AIAssets/components/vectorstores/__tests__/computeEmbeddingModelStatus.spec.ts

@@ -1,9 +1,6 @@
 /* eslint-disable camelcase */
 import type { AIModel, LlamaModel } from '~/app/types';
-import {
-  computeEmbeddingModelStatus,
-  EmbeddingModelStatus,
-} from '~/app/AIAssets/components/vectorstores/VectorStoreTableRow';
+import { computeEmbeddingModelStatus, EmbeddingModelStatus } from '~/app/utilities/utils';
 
 const makeAIModel = (model_id: string, overrides: Partial<AIModel> = {}): AIModel => ({
   model_name: 'test',

packages/gen-ai/frontend/src/app/Chatbot/components/chatbotConfiguration/ChatbotConfigurationModal.tsx

@@ -22,7 +22,11 @@ import {
   MaaSModel,
   VectorStore,
 } from '~/app/types';
-import { convertMaaSModelToAIModel, splitLlamaModelId } from '~/app/utilities/utils';
+import {
+  computeEmbeddingModelStatus,
+  convertMaaSModelToAIModel,
+  splitLlamaModelId,
+} from '~/app/utilities/utils';
 import { useGenAiAPI } from '~/app/hooks/useGenAiAPI';
 import useGuardrailsEnabled from '~/app/Chatbot/hooks/useGuardrailsEnabled';
 import useAiAssetVectorStoresEnabled from '~/app/hooks/useAiAssetVectorStoresEnabled';
@@ -137,14 +141,12 @@ const ChatbotConfigurationModal: React.FC<ChatbotConfigurationModalProps> = ({
 
   const availableCollections = React.useMemo(
     () =>
-      allCollections.filter((c) => {
-        const { id: normalizedEmbedId } = splitLlamaModelId(c.embedding_model);
-        return allModels.some((m) => {
-          const { id: normalizedModelId } = splitLlamaModelId(m.model_id);
-          return m.model_id === c.embedding_model || normalizedModelId === normalizedEmbedId;
-        });
-      }),
-    [allCollections, allModels],
+      allCollections.filter(
+        (c) =>
+          computeEmbeddingModelStatus(c.embedding_model, allModels, existingModels) !==
+          'not_available',
+      ),
+    [allCollections, allModels, existingModels],
   );
 
   const preSelectedCollections = React.useMemo(() => {

packages/gen-ai/frontend/src/app/utilities/utils.ts

@@ -1,7 +1,14 @@
 /* eslint-disable camelcase */
 import { K8sResourceCommon } from 'mod-arch-shared';
 import { fireMiscTrackingEvent } from '@odh-dashboard/internal/concepts/analyticsTracking/segmentIOUtils';
-import { AIModel, TokenInfo, MCPServerFromAPI, MCPServerConfig, MaaSModel } from '~/app/types';
+import {
+  AIModel,
+  LlamaModel,
+  TokenInfo,
+  MCPServerFromAPI,
+  MCPServerConfig,
+  MaaSModel,
+} from '~/app/types';
 
 /**
  * Generates a UUID v4 string
@@ -243,3 +250,39 @@ export const copyToClipboardWithTracking = async (
     // Do nothing
   }
 };
+
+export type EmbeddingModelStatus = 'not_available' | 'available' | 'registered';
+
+/**
+ * Determines whether a vector store's embedding model is available for use.
+ * - 'registered': the model is already registered and running in the LlamaStack Distribution (LSD).
+ * - 'available': the model exists in AI Assets or MaaS but is not yet installed in the LSD.
+ * - 'not_available': the model is unknown — the vector store cannot be used.
+ *
+ * @param assetModels - AI Assets + MaaS models (candidates that can be installed into the LSD)
+ * @param playgroundModels - models currently registered in the LSD (referred to as lsdModels elsewhere)
+ */
+export const computeEmbeddingModelStatus = (
+  embeddingModel: string,
+  assetModels: AIModel[],
+  playgroundModels: LlamaModel[],
+): EmbeddingModelStatus => {
+  const { id: normalizedId } = splitLlamaModelId(embeddingModel);
+
+  const isRegistered = playgroundModels.some(
+    (m) => m.modelId === embeddingModel || m.modelId === normalizedId,
+  );
+  if (isRegistered) {
+    return 'registered';
+  }
+
+  const isAvailable = assetModels.some((m) => {
+    const { id: normalizedModelId } = splitLlamaModelId(m.model_id);
+    return m.model_id === embeddingModel || normalizedModelId === normalizedId;
+  });
+  if (isAvailable) {
+    return 'available';
+  }
+
+  return 'not_available';
+};