feat: enhance index type handling and add error notification for missing embedding model (#16836)

web/app/components/datasets/create/step-two/index.tsx

@@ -169,12 +169,11 @@ const StepTwo = ({
   const [rules, setRules] = useState<PreProcessingRule[]>([])
   const [defaultConfig, setDefaultConfig] = useState<Rules>()
   const hasSetIndexType = !!indexingType
-  const [indexType, setIndexType] = useState<IndexingType>(
-    (indexingType
-      || isAPIKeySet)
-      ? IndexingType.QUALIFIED
-      : IndexingType.ECONOMICAL,
-  )
+  const [indexType, setIndexType] = useState<IndexingType>(() => {
+    if (hasSetIndexType)
+      return indexingType
+    return isAPIKeySet ? IndexingType.QUALIFIED : IndexingType.ECONOMICAL
+  })
 
   const [previewFile, setPreviewFile] = useState<DocumentItem>(
     (datasetId && documentDetail)
@@ -421,6 +420,13 @@ const StepTwo = ({
     }
     else { // create
       const indexMethod = getIndexing_technique()
+      if (indexMethod === IndexingType.QUALIFIED && (!embeddingModel.model || !embeddingModel.provider)) {
+        Toast.notify({
+          type: 'error',
+          message: t('appDebug.datasetConfig.embeddingModelRequired'),
+        })
+        return
+      }
       if (
         !isReRankModelSelected({
           rerankModelList,
@@ -568,7 +574,6 @@ const StepTwo = ({
     // get indexing type by props
     if (indexingType)
       setIndexType(indexingType as IndexingType)
-
     else
       setIndexType(isAPIKeySet ? IndexingType.QUALIFIED : IndexingType.ECONOMICAL)
   }, [isAPIKeySet, indexingType, datasetId])
@@ -848,9 +853,8 @@ const StepTwo = ({
               description={t('datasetCreation.stepTwo.qualifiedTip')}
               icon={<Image src={indexMethodIcon.high_quality} alt='' />}
               isActive={!hasSetIndexType && indexType === IndexingType.QUALIFIED}
-              disabled={!isAPIKeySet || hasSetIndexType}
+              disabled={hasSetIndexType}
               onSwitched={() => {
-                if (isAPIKeySet)
                 setIndexType(IndexingType.QUALIFIED)
               }}
             />
@@ -894,10 +898,9 @@ const StepTwo = ({
                     description={t('datasetCreation.stepTwo.economicalTip')}
                     icon={<Image src={indexMethodIcon.economical} alt='' />}
                     isActive={!hasSetIndexType && indexType === IndexingType.ECONOMICAL}
-                    disabled={!isAPIKeySet || hasSetIndexType || docForm !== ChunkingMode.text}
+                    disabled={hasSetIndexType || docForm !== ChunkingMode.text}
                     ref={economyDomRef}
                     onSwitched={() => {
-                      if (isAPIKeySet && docForm === ChunkingMode.text)
                       setIndexType(IndexingType.ECONOMICAL)
                     }}
                   />

web/i18n/en-US/app-debug.ts

@@ -483,6 +483,7 @@ const translation = {
       title: 'Multi-path retrieval',
       description: 'Based on user intent, queries across all Knowledge, retrieves relevant text from multi-sources, and selects the best results matching the user query after reranking.',
     },
+    embeddingModelRequired: 'A configured Embedding Model is required',
     rerankModelRequired: 'A configured Rerank Model is required',
     params: 'Params',
     top_k: 'Top K',

web/i18n/zh-Hans/app-debug.ts

@@ -475,6 +475,7 @@ const translation = {
       title: '多路召回',
       description: '根据用户意图同时匹配所有知识库，从多路知识库查询相关文本片段，经过重排序步骤，从多路查询结果中选择匹配用户问题的最佳结果。',
     },
+    embeddingModelRequired: '未配置 Embedding 模型',
     rerankModelRequired: '未配置 Rerank 模型',
     params: '参数设置',
     top_k: 'Top K',