fix: Fix vector_setting not found error (#26380)

web/app/components/header/account-setting/data-source-page-new/install-from-marketplace.tsx

@@ -52,7 +52,7 @@ const InstallFromMarketplace = ({
       <div className='flex items-center justify-between'>
         <div className='system-md-semibold flex cursor-pointer items-center gap-1 text-text-primary' onClick={() => setCollapse(!collapse)}>
           <RiArrowDownSLine className={cn('h-4 w-4', collapse && '-rotate-90')} />
-          {t('common.modelProvider.installProvider')}
+          {t('common.modelProvider.installDataSourceProvider')}
         </div>
         <div className='mb-2 flex items-center pt-2'>
           <span className='system-sm-regular pr-1 text-text-tertiary'>{t('common.modelProvider.discoverMore')}</span>

web/app/components/workflow/nodes/knowledge-base/components/option-card.tsx

@@ -86,7 +86,10 @@ const OptionCard = memo(({
         readonly && 'cursor-not-allowed',
         wrapperClassName && (typeof wrapperClassName === 'function' ? wrapperClassName(isActive) : wrapperClassName),
       )}
-      onClick={() => !readonly && enableSelect && id && onClick?.(id)}
+      onClick={(e) => {
+        e.stopPropagation()
+        !readonly && enableSelect && id && onClick?.(id)
+      }}
     >
       <div className={cn(
         'relative flex rounded-t-xl p-2',

web/app/components/workflow/nodes/knowledge-base/default.ts

@@ -2,6 +2,7 @@ import type { NodeDefault } from '../../types'
 import type { KnowledgeBaseNodeType } from './types'
 import { genNodeMetaData } from '@/app/components/workflow/utils'
 import { BlockEnum } from '@/app/components/workflow/types'
+import { IndexingType } from '@/app/components/datasets/create/step-two'
 
 const metaData = genNodeMetaData({
   sort: 3.1,
@@ -27,8 +28,17 @@ const nodeDefault: NodeDefault<KnowledgeBaseNodeType> = {
       chunk_structure,
       indexing_technique,
       retrieval_model,
+      embedding_model,
+      embedding_model_provider,
+      index_chunk_variable_selector,
     } = payload
 
+    const {
+      search_method,
+      reranking_enable,
+      reranking_model,
+    } = retrieval_model || {}
+
     if (!chunk_structure) {
       return {
         isValid: false,
@@ -36,6 +46,13 @@ const nodeDefault: NodeDefault<KnowledgeBaseNodeType> = {
       }
     }
 
+    if (index_chunk_variable_selector.length === 0) {
+      return {
+        isValid: false,
+        errorMessage: t('workflow.nodes.knowledgeBase.chunksVariableIsRequired'),
+      }
+    }
+
     if (!indexing_technique) {
       return {
         isValid: false,
@@ -43,13 +60,27 @@ const nodeDefault: NodeDefault<KnowledgeBaseNodeType> = {
       }
     }
 
-    if (!retrieval_model || !retrieval_model.search_method) {
+    if (indexing_technique === IndexingType.QUALIFIED && (!embedding_model || !embedding_model_provider)) {
+      return {
+        isValid: false,
+        errorMessage: t('workflow.nodes.knowledgeBase.embeddingModelIsRequired'),
+      }
+    }
+
+    if (!retrieval_model || !search_method) {
       return {
         isValid: false,
         errorMessage: t('workflow.nodes.knowledgeBase.retrievalSettingIsRequired'),
       }
     }
 
+    if (reranking_enable && (!reranking_model || !reranking_model.reranking_provider_name || !reranking_model.reranking_model_name)) {
+      return {
+        isValid: false,
+        errorMessage: t('workflow.nodes.knowledgeBase.rerankingModelIsRequired'),
+      }
+    }
+
     return {
       isValid: true,
       errorMessage: '',

web/app/components/workflow/nodes/knowledge-base/hooks/use-config.ts

@@ -9,13 +9,17 @@ import {
   ChunkStructureEnum,
   IndexMethodEnum,
   RetrievalSearchMethodEnum,
+  WeightedScoreEnum,
 } from '../types'
 import type {
-  HybridSearchModeEnum,
   KnowledgeBaseNodeType,
   RerankingModel,
 } from '../types'
+import {
+  HybridSearchModeEnum,
+} from '../types'
 import { isHighQualitySearchMethod } from '../utils'
+import { DEFAULT_WEIGHTED_SCORE, RerankingModeEnum } from '@/models/datasets'
 
 export const useConfig = (id: string) => {
   const store = useStoreApi()
@@ -35,6 +39,25 @@ export const useConfig = (id: string) => {
     })
   }, [id, handleNodeDataUpdateWithSyncDraft])
 
+  const getDefaultWeights = useCallback(({
+    embeddingModel,
+    embeddingModelProvider,
+  }: {
+    embeddingModel: string
+    embeddingModelProvider: string
+  }) => {
+    return {
+      vector_setting: {
+        vector_weight: DEFAULT_WEIGHTED_SCORE.other.semantic,
+        embedding_provider_name: embeddingModelProvider || '',
+        embedding_model_name: embeddingModel,
+      },
+      keyword_setting: {
+        keyword_weight: DEFAULT_WEIGHTED_SCORE.other.keyword,
+      },
+    }
+  }, [])
+
   const handleChunkStructureChange = useCallback((chunkStructure: ChunkStructureEnum) => {
     const nodeData = getNodeData()
     const {
@@ -80,39 +103,72 @@ export const useConfig = (id: string) => {
     embeddingModelProvider: string
   }) => {
     const nodeData = getNodeData()
-    handleNodeDataUpdate({
+    const defaultWeights = getDefaultWeights({
+      embeddingModel,
+      embeddingModelProvider,
+    })
+    const changeData = {
       embedding_model: embeddingModel,
       embedding_model_provider: embeddingModelProvider,
       retrieval_model: {
         ...nodeData?.data.retrieval_model,
+      },
+    }
+    if (changeData.retrieval_model.weights) {
+      changeData.retrieval_model = {
+        ...changeData.retrieval_model,
+        weights: {
+          ...changeData.retrieval_model.weights,
           vector_setting: {
-          ...nodeData?.data.retrieval_model.vector_setting,
+            ...changeData.retrieval_model.weights.vector_setting,
             embedding_provider_name: embeddingModelProvider,
             embedding_model_name: embeddingModel,
           },
         },
-    })
+      }
-  }, [getNodeData, handleNodeDataUpdate])
+    }
+    else {
+      changeData.retrieval_model = {
+        ...changeData.retrieval_model,
+        weights: defaultWeights,
+      }
+    }
+    handleNodeDataUpdate(changeData)
+  }, [getNodeData, getDefaultWeights, handleNodeDataUpdate])
 
   const handleRetrievalSearchMethodChange = useCallback((searchMethod: RetrievalSearchMethodEnum) => {
     const nodeData = getNodeData()
-    handleNodeDataUpdate({
+    const changeData = {
       retrieval_model: {
         ...nodeData?.data.retrieval_model,
         search_method: searchMethod,
+        reranking_mode: nodeData?.data.retrieval_model.reranking_mode || RerankingModeEnum.RerankingModel,
       },
-    })
+    }
+    if (searchMethod === RetrievalSearchMethodEnum.hybrid) {
+      changeData.retrieval_model = {
+        ...changeData.retrieval_model,
+        reranking_enable: changeData.retrieval_model.reranking_mode === RerankingModeEnum.RerankingModel,
+      }
+    }
+    handleNodeDataUpdate(changeData)
   }, [getNodeData, handleNodeDataUpdate])
 
   const handleHybridSearchModeChange = useCallback((hybridSearchMode: HybridSearchModeEnum) => {
     const nodeData = getNodeData()
+    const defaultWeights = getDefaultWeights({
+      embeddingModel: nodeData?.data.embedding_model || '',
+      embeddingModelProvider: nodeData?.data.embedding_model_provider || '',
+    })
     handleNodeDataUpdate({
       retrieval_model: {
         ...nodeData?.data.retrieval_model,
         reranking_mode: hybridSearchMode,
+        reranking_enable: hybridSearchMode === HybridSearchModeEnum.RerankingModel,
+        weights: nodeData?.data.retrieval_model.weights || defaultWeights,
       },
     })
-  }, [getNodeData, handleNodeDataUpdate])
+  }, [getNodeData, getDefaultWeights, handleNodeDataUpdate])
 
   const handleRerankingModelEnabledChange = useCallback((rerankingModelEnabled: boolean) => {
     const nodeData = getNodeData()
@@ -130,11 +186,10 @@ export const useConfig = (id: string) => {
       retrieval_model: {
         ...nodeData?.data.retrieval_model,
         weights: {
-          weight_type: 'weighted_score',
+          weight_type: WeightedScoreEnum.Customized,
           vector_setting: {
+            ...nodeData?.data.retrieval_model.weights?.vector_setting,
             vector_weight: weightedScore.value[0],
-            embedding_provider_name: '',
-            embedding_model_name: '',
           },
           keyword_setting: {
             keyword_weight: weightedScore.value[1],

web/i18n/en-US/common.ts

@@ -493,6 +493,7 @@ const translation = {
     toBeConfigured: 'To be configured',
     configureTip: 'Set up api-key or add model to use',
     installProvider: 'Install model providers',
+    installDataSourceProvider: 'Install data source providers',
     discoverMore: 'Discover more in ',
     emptyProviderTitle: 'Model provider not set up',
     emptyProviderTip: 'Please install a model provider first.',

web/i18n/en-US/workflow.ts

@@ -955,7 +955,10 @@ const translation = {
       aboutRetrieval: 'about retrieval method.',
       chunkIsRequired: 'Chunk structure is required',
       indexMethodIsRequired: 'Index method is required',
+      chunksVariableIsRequired: 'Chunks variable is required',
+      embeddingModelIsRequired: 'Embedding model is required',
       retrievalSettingIsRequired: 'Retrieval setting is required',
+      rerankingModelIsRequired: 'Reranking model is required',
     },
   },
   tracing: {

web/i18n/ja-JP/common.ts

@@ -484,6 +484,7 @@ const translation = {
     emptyProviderTitle: 'モデルプロバイダーが設定されていません',
     discoverMore: 'もっと発見する',
     installProvider: 'モデルプロバイダーをインストールする',
+    installDataSourceProvider: 'データソースプロバイダーをインストールする',
     configureTip: 'API キーを設定するか、使用するモデルを追加してください',
     toBeConfigured: '設定中',
     emptyProviderTip: '最初にモデルプロバイダーをインストールしてください。',

web/i18n/zh-Hans/common.ts

@@ -487,6 +487,7 @@ const translation = {
     toBeConfigured: '待配置',
     configureTip: '请配置 API 密钥，添加模型。',
     installProvider: '安装模型供应商',
+    installDataSourceProvider: '安装数据源供应商',
     discoverMore: '发现更多就在',
     emptyProviderTitle: '尚未安装模型供应商',
     emptyProviderTip: '请安装模型供应商。',

web/i18n/zh-Hans/workflow.ts

@@ -955,7 +955,10 @@ const translation = {
       aboutRetrieval: '关于知识检索。',
       chunkIsRequired: '分段结构是必需的',
       indexMethodIsRequired: '索引方法是必需的',
+      chunksVariableIsRequired: 'Chunks 变量是必需的',
+      embeddingModelIsRequired: 'Embedding 模型是必需的',
       retrievalSettingIsRequired: '检索设置是必需的',
+      rerankingModelIsRequired: 'Reranking 模型是必需的',
     },
   },
   tracing: {