Fix: Handle embedding dimension retrieval failure when creating knowledge base (#7324)

* fix(知识库): 处理获取嵌入维度为0时的错误情况

* fix(aiCore): 修复获取嵌入维度时错误处理不当的问题

修改各AI客户端获取嵌入维度的方法，在出错时抛出异常而不是返回0
同时在调用处移除对返回值为0的特殊处理，直接捕获异常

* refactor(aiCore): 移除获取嵌入维度的冗余try-catch块

简化代码结构，移除不必要的错误处理，因为错误会由上层调用者处理

src/renderer/src/aiCore/clients/anthropic/AnthropicAPIClient.ts

@@ -125,7 +125,7 @@ export class AnthropicAPIClient extends BaseApiClient<
 
   // @ts-ignore sdk未提供
   override async getEmbeddingDimensions(): Promise<number> {
-    return 0
+    throw new Error("Anthropic SDK doesn't support getEmbeddingDimensions method.")
   }
 
   override getTemperature(assistant: Assistant, model: Model): number | undefined {

src/renderer/src/aiCore/clients/gemini/GeminiAPIClient.ts

@@ -147,15 +147,12 @@ export class GeminiAPIClient extends BaseApiClient<
 
   override async getEmbeddingDimensions(model: Model): Promise<number> {
     const sdk = await this.getSdkInstance()
-    try {
+
-      const data = await sdk.models.embedContent({
+    const data = await sdk.models.embedContent({
-        model: model.id,
+      model: model.id,
-        contents: [{ role: 'user', parts: [{ text: 'hi' }] }]
+      contents: [{ role: 'user', parts: [{ text: 'hi' }] }]
-      })
+    })
-      return data.embeddings?.[0]?.values?.length || 0
+    return data.embeddings?.[0]?.values?.length || 0
-    } catch (e) {
-      return 0
-    }
   }
 
   override async listModels(): Promise<GeminiModel[]> {

src/renderer/src/aiCore/clients/openai/OpenAIBaseClient.ts

@@ -85,16 +85,13 @@ export abstract class OpenAIBaseClient<
 
   override async getEmbeddingDimensions(model: Model): Promise<number> {
     const sdk = await this.getSdkInstance()
-    try {
+
-      const data = await sdk.embeddings.create({
+    const data = await sdk.embeddings.create({
-        model: model.id,
+      model: model.id,
-        input: model?.provider === 'baidu-cloud' ? ['hi'] : 'hi',
+      input: model?.provider === 'baidu-cloud' ? ['hi'] : 'hi',
-        encoding_format: 'float'
+      encoding_format: 'float'
-      })
+    })
-      return data.data[0].embedding.length
+    return data.data[0].embedding.length
-    } catch (e) {
-      return 0
-    }
   }
 
   override async listModels(): Promise<OpenAI.Models.Model[]> {

src/renderer/src/aiCore/index.ts

@@ -114,7 +114,7 @@ export default class AiProvider {
       return dimensions
     } catch (error) {
       console.error('Error getting embedding dimensions:', error)
-      return 0
+      throw error
     }
   }
 

src/renderer/src/pages/knowledge/components/AddKnowledgePopup.tsx

@@ -116,7 +116,6 @@ const PopupContainer: React.FC<Props> = ({ title, resolve }) => {
             const aiProvider = new AiProvider(provider)
             values.dimensions = await aiProvider.getEmbeddingDimensions(selectedEmbeddingModel)
           } catch (error) {
-            console.error('Error getting embedding dimensions:', error)
             window.message.error(t('message.error.get_embedding_dimensions') + '\n' + getErrorMessage(error))
             setLoading(false)
             return

src/renderer/src/services/ApiService.ts

@@ -570,10 +570,7 @@ export async function checkApi(provider: Provider, model: Model): Promise<void>
   assistant.model = model
   try {
     if (isEmbeddingModel(model)) {
-      const result = await ai.getEmbeddingDimensions(model)
+      await ai.getEmbeddingDimensions(model)
-      if (result === 0) {
-        throw new Error(i18n.t('message.error.enter.model'))
-      }
     } else {
       const params: CompletionsParams = {
         callType: 'check',