add csv loader

src/main/services/KnowledgeService.ts

@@ -120,6 +120,7 @@ class KnowledgeService {
 
     if (item.type === 'file') {
       const file = item.content as FileType
+      console.log(file)
 
       if (file.ext === '.pdf') {
         return await ragApplication.addLoader(
@@ -165,6 +166,27 @@ class KnowledgeService {
         )
       }
 
+      if (file.ext === '.csv') {
+        try {
+          const module = await import('@llm-tools/embedjs-loader-csv/src/index.js')
+          // 使用module中的功能
+          console.log(module.CsvLoader) // 假设模块导出了一个默认值
+          return await ragApplication.addLoader(
+            new module.CsvLoader({
+              filePathOrUrl: file.path,
+              chunkSize: base.chunkSize,
+              chunkOverlap: base.chunkOverlap,
+              csvParseOptions: {
+                columns: true
+              }
+            }) as any,
+            forceReload
+          )
+        } catch (error) {
+          console.error('加载模块时出错:', error)
+        }
+      }
+
       if (['.md'].includes(file.ext)) {
         return await ragApplication.addLoader(
           new MarkdownLoader({

src/renderer/src/pages/knowledge/KnowledgeContent.tsx

@@ -33,7 +33,7 @@ interface KnowledgeContentProps {
   selectedBase: KnowledgeBase
 }
 
-const fileTypes = ['.pdf', '.docx', '.pptx', '.xlsx', '.txt', '.md', '.html']
+const fileTypes = ['.pdf', '.docx', '.pptx', '.xlsx', '.txt', '.md', '.html', '.csv']
 
 const KnowledgeContent: FC<KnowledgeContentProps> = ({ selectedBase }) => {
   const { t } = useTranslation()