fix: knowledge base bugs

electron.vite.config.ts

@@ -35,7 +35,8 @@ export default defineConfig({
     build: {
       rollupOptions: {
         external: ['@lancedb/lancedb']
-      }
+      },
+      minify: true
     }
   },
   preload: {
@@ -51,6 +52,9 @@ export default defineConfig({
     },
     optimizeDeps: {
       exclude: []
+    },
+    build: {
+      minify: true
     }
   }
 })

src/main/services/KnowledgeService.ts

@@ -2,7 +2,7 @@ import * as fs from 'node:fs'
 import path from 'node:path'
 
 import { LocalPathLoader, RAGApplication, RAGApplicationBuilder, TextLoader } from '@llm-tools/embedjs'
-import { AddLoaderReturn, ExtractChunkData } from '@llm-tools/embedjs-interfaces'
+import type { AddLoaderReturn, ExtractChunkData } from '@llm-tools/embedjs-interfaces'
 import { LanceDb } from '@llm-tools/embedjs-lancedb'
 import { MarkdownLoader } from '@llm-tools/embedjs-loader-markdown'
 import { DocxLoader, ExcelLoader, PptLoader } from '@llm-tools/embedjs-loader-msoffice'

src/main/services/WindowService.ts

@@ -3,7 +3,7 @@ import { isLinux, isWin } from '@main/constant'
 import { app, BrowserWindow, Menu, MenuItem, shell } from 'electron'
 import Logger from 'electron-log'
 import windowStateKeeper from 'electron-window-state'
-import { join } from 'path'
+import path, { join } from 'path'
 
 import icon from '../../../build/icon.png?asset'
 import { titleBarOverlayDark, titleBarOverlayLight } from '../config'
@@ -137,8 +137,9 @@ export class WindowService {
       const { url } = details
 
       if (url.includes('http://file/')) {
-        const fileUrl = url.replace('http://file/', '')
-        const filePath = decodeURIComponent(fileUrl)
+        const fileName = url.replace('http://file/', '')
+        const storageDir = path.join(app.getPath('userData'), 'Data', 'Files')
+        const filePath = storageDir + '/' + fileName
         shell.openPath(filePath).catch((err) => Logger.error('Failed to open file:', err))
       } else {
         shell.openExternal(details.url)

src/renderer/src/config/prompts.ts

@@ -56,6 +56,7 @@ export const REFERENCE_PROMPT = `请根据参考资料回答问题，并使用
 
 1. **脚注标记**：在正文中使用 [^数字] 的形式标记脚注，例如 [^1]。
 2. **脚注内容**：在文档末尾使用 [^数字]: 脚注内容 的形式定义脚注的具体内容
+3. **脚注内容**：应该尽量简洁
 
 ## 我的问题是：
 

src/renderer/src/config/providers.ts

@@ -358,7 +358,7 @@ export const PROVIDER_CONFIG = {
       url: 'https://aihubmix.com?aff=SJyh'
     },
     websites: {
-      official: 'https://aihubmix.com/',
+      official: 'https://aihubmix.com?aff=SJyh',
       apiKey: 'https://aihubmix.com?aff=SJyh',
       docs: 'https://doc.aihubmix.com/',
       models: 'https://aihubmix.com/models'

src/renderer/src/i18n/locales/en-us.json

@@ -229,6 +229,7 @@
       "error.enter.api.host": "Please enter your API host first",
       "error.enter.api.key": "Please enter your API key first",
       "error.enter.model": "Please select a model first",
+      "error.enter.name": "Please enter the name of the knowledge base",
       "error.invalid.proxy.url": "Invalid proxy URL",
       "error.invalid.webdav": "Invalid WebDAV settings",
       "message.code_style": "Code style",
@@ -249,7 +250,7 @@
       "upgrade.success.title": "Upgrade successfully",
       "regenerate.confirm": "Regenerating will replace current message",
       "copy.success": "Copied!",
-      "get_embedding_dimensions": "Failed to get embedding dimensions"
+      "error.get_embedding_dimensions": "Failed to get embedding dimensions"
     },
     "minapp": {
       "title": "MinApp"
@@ -562,7 +563,8 @@
       "add_directory": "Add Directory",
       "directory_placeholder": "Enter Directory Path",
       "model_info": "Model Info",
-      "not_support": "Knowledge base database engine updated, the knowledge base will no longer be supported, please create a new knowledge base"
+      "not_support": "Knowledge base database engine updated, the knowledge base will no longer be supported, please create a new knowledge base",
+      "source": "Source"
     },
     "models": {
       "pinned": "Pinned",

src/renderer/src/i18n/locales/ru-ru.json

@@ -229,6 +229,7 @@
       "error.enter.api.host": "Пожалуйста, введите ваш API хост",
       "error.enter.api.key": "Пожалуйста, введите ваш API ключ",
       "error.enter.model": "Пожалуйста, выберите модель",
+      "error.enter.name": "Пожалуйста, введите название базы знаний",
       "error.invalid.proxy.url": "Неверный URL прокси",
       "error.invalid.webdav": "Неверные настройки WebDAV",
       "message.code_style": "Стиль кода",
@@ -249,7 +250,7 @@
       "upgrade.success.title": "Обновление успешно",
       "regenerate.confirm": "Перегенерация заменит текущее сообщение",
       "copy.success": "Скопировано!",
-      "get_embedding_dimensions": "Не удалось получить размерность встраивания"
+      "error.get_embedding_dimensions": "Не удалось получить размерность встраивания"
     },
     "minapp": {
       "title": "Встроенные приложения"
@@ -562,7 +563,8 @@
       "add_directory": "Добавить директорию",
       "directory_placeholder": "Введите путь к директории",
       "model_info": "Модель информации",
-      "not_support": "База знаний базы данных движок обновлен, база знаний больше не поддерживается, пожалуйста, создайте новую базу знаний"
+      "not_support": "База знаний базы данных движок обновлен, база знаний больше не поддерживается, пожалуйста, создайте новую базу знаний",
+      "source": "Источник"
     },
     "models": {
       "pinned": "Закреплено",

src/renderer/src/i18n/locales/zh-cn.json

@@ -230,6 +230,7 @@
       "error.enter.api.host": "请输入您的 API 地址",
       "error.enter.api.key": "请输入您的 API 密钥",
       "error.enter.model": "请选择一个模型",
+      "error.enter.name": "请输入知识库名称",
       "error.invalid.proxy.url": "无效的代理地址",
       "error.invalid.webdav": "无效的 WebDAV 设置",
       "message.code_style": "代码风格",
@@ -250,7 +251,7 @@
       "upgrade.success.title": "升级成功",
       "regenerate.confirm": "重新生成会覆盖当前消息",
       "copy.success": "复制成功",
-      "get_embedding_dimensions": "获取嵌入维度失败"
+      "error.get_embedding_dimensions": "获取嵌入维度失败"
     },
     "minapp": {
       "title": "小程序"
@@ -551,7 +552,8 @@
       "add_directory": "添加目录",
       "directory_placeholder": "请输入目录路径",
       "model_info": "模型信息",
-      "not_support": "知识库数据库引擎已更新，该知识库将不再支持，请重新创建知识库"
+      "not_support": "知识库数据库引擎已更新，该知识库将不再支持，请重新创建知识库",
+      "source": "来源"
     },
     "models": {
       "pinned": "已固定",

src/renderer/src/i18n/locales/zh-tw.json

@@ -229,6 +229,7 @@
       "error.enter.api.host": "請先輸入您的 API 主機地址",
       "error.enter.api.key": "請先輸入您的 API 密鑰",
       "error.enter.model": "請先選擇一個模型",
+      "error.enter.name": "請先輸入知識庫名稱",
       "error.invalid.proxy.url": "無效的代理 URL",
       "error.invalid.webdav": "無效的 WebDAV 設定",
       "message.code_style": "程式碼風格",
@@ -249,7 +250,7 @@
       "upgrade.success.title": "升級成功",
       "regenerate.confirm": "重新生成會覆蓋當前訊息",
       "copy.success": "複製成功",
-      "get_embedding_dimensions": "獲取嵌入維度失敗"
+      "error.get_embedding_dimensions": "獲取嵌入維度失敗"
     },
     "minapp": {
       "title": "小程序"
@@ -550,7 +551,8 @@
       "add_directory": "添加目錄",
       "directory_placeholder": "請輸入目錄路徑",
       "model_info": "模型信息",
-      "not_support": "知識庫數據庫引擎已更新，該知識庫將不再支持，請重新創建知識庫"
+      "not_support": "知識庫數據庫引擎已更新，該知識庫將不再支持，請重新創建知識庫",
+      "source": "來源"
     },
     "models": {
       "pinned": "已固定",

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

@@ -1,7 +1,7 @@
 import type { ExtractChunkData } from '@llm-tools/embedjs-interfaces'
 import { TopView } from '@renderer/components/TopView'
-import { getKnowledgeBaseParams } from '@renderer/services/KnowledgeService'
-import { KnowledgeBase } from '@renderer/types'
+import { getFileFromUrl, getKnowledgeBaseParams } from '@renderer/services/KnowledgeService'
+import { FileType, KnowledgeBase } from '@renderer/types'
 import { Input, List, Modal, Spin, Typography } from 'antd'
 import { useState } from 'react'
 import { useTranslation } from 'react-i18next'
@@ -21,7 +21,7 @@ interface Props extends ShowParams {
 const PopupContainer: React.FC<Props> = ({ base, resolve }) => {
   const [open, setOpen] = useState(true)
   const [loading, setLoading] = useState(false)
-  const [results, setResults] = useState<ExtractChunkData[]>([])
+  const [results, setResults] = useState<Array<ExtractChunkData & { file: FileType | null }>>([])
   const [searchKeyword, setSearchKeyword] = useState('')
   const { t } = useTranslation()
 
@@ -39,7 +39,13 @@ const PopupContainer: React.FC<Props> = ({ base, resolve }) => {
         search: value,
         base: getKnowledgeBaseParams(base)
       })
-      setResults(searchResults)
+      const results = await Promise.all(
+        searchResults.map(async (item) => {
+          const file = await getFileFromUrl(item.metadata.source)
+          return { ...item, file }
+        })
+      )
+      setResults(results)
     } catch (error) {
       console.error('Search failed:', error)
     } finally {
@@ -102,7 +108,16 @@ const PopupContainer: React.FC<Props> = ({ base, resolve }) => {
                     <ScoreTag>Score: {(item.score * 100).toFixed(1)}%</ScoreTag>
                     <Paragraph>{highlightText(item.pageContent)}</Paragraph>
                     <MetadataContainer>
-                      <Text type="secondary">Source: {item.metadata.source}</Text>
+                      <Text type="secondary">
+                        {t('knowledge_base.source')}:{' '}
+                        {item.file ? (
+                          <a href={`http://file/${item.file.name}`} target="_blank" rel="noreferrer">
+                            {item.file.origin_name}
+                          </a>
+                        ) : (
+                          item.metadata.source
+                        )}
+                      </Text>
                     </MetadataContainer>
                   </ResultItem>
                 </List.Item>

src/renderer/src/providers/BaseProvider.ts

@@ -1,10 +1,9 @@
 import { REFERENCE_PROMPT } from '@renderer/config/prompts'
 import { getOllamaKeepAliveTime } from '@renderer/hooks/useOllama'
-import { getKnowledgeBaseParams } from '@renderer/services/KnowledgeService'
+import { getKnowledgeReferences } from '@renderer/services/KnowledgeService'
 import store from '@renderer/store'
 import { Assistant, Message, Model, Provider, Suggestion } from '@renderer/types'
 import { delay } from '@renderer/utils'
-import { take } from 'lodash'
 import OpenAI from 'openai'
 
 import { CompletionsParams } from '.'
@@ -95,25 +94,8 @@ export default abstract class BaseProvider {
       return message.content
     }
 
-    const searchResults = await window.api.knowledgeBase.search({
-      search: message.content,
-      base: getKnowledgeBaseParams(base)
-    })
+    const references = await getKnowledgeReferences(base, message)
 
-    const references = take(searchResults, 6).map((item, index) => {
-      const sourceUrl = item.metadata.source
-      const baseItem = base.items.find((i) => i.uniqueId === item.metadata.uniqueLoaderId)
-
-      return {
-        id: index,
-        content: item.pageContent,
-        sourceUrl: sourceUrl.startsWith('http') ? sourceUrl : encodeURIComponent(sourceUrl),
-        type: baseItem?.type
-      }
-    })
-
-    const referencesContent = `\`\`\`json\n${JSON.stringify(references, null, 2)}\n\`\`\``
-
-    return REFERENCE_PROMPT.replace('{question}', message.content).replace('{references}', referencesContent)
+    return REFERENCE_PROMPT.replace('{question}', message.content).replace('{references}', references)
   }
 }

src/renderer/src/services/FileManager.ts

@@ -51,7 +51,7 @@ class FileManager {
 
     if (file) {
       const filesPath = store.getState().runtime.filesPath
-      file.path = filesPath + file.id
+      file.path = filesPath + '/' + file.id + file.ext
     }
 
     return file
@@ -91,7 +91,7 @@ class FileManager {
 
   static getFileUrl(file: FileType) {
     const filesPath = store.getState().runtime.filesPath
-    return 'file://' + filesPath + '/' + file.id + file.ext
+    return 'file://' + filesPath + '/' + file.name
   }
 }
 

src/renderer/src/services/KnowledgeService.ts

@@ -1,8 +1,10 @@
+import type { ExtractChunkData } from '@llm-tools/embedjs-interfaces'
 import AiProvider from '@renderer/providers/AiProvider'
-import { KnowledgeBase, KnowledgeBaseParams } from '@renderer/types'
-import { isEmpty } from 'lodash'
+import { FileType, KnowledgeBase, KnowledgeBaseParams, Message } from '@renderer/types'
+import { isEmpty, take } from 'lodash'
 
 import { getProviderByModel } from './AssistantService'
+import FileManager from './FileManager'
 
 export const getKnowledgeBaseParams = (base: KnowledgeBase): KnowledgeBaseParams => {
   const provider = getProviderByModel(base.model)
@@ -14,7 +16,7 @@ export const getKnowledgeBaseParams = (base: KnowledgeBase): KnowledgeBaseParams
 
   let host = aiProvider.getBaseURL()
 
-  if (host.includes('generativelanguage.googleapis.com')) {
+  if (provider.type === 'gemini') {
     host = host + '/v1beta/openai/'
   }
 
@@ -26,3 +28,69 @@ export const getKnowledgeBaseParams = (base: KnowledgeBase): KnowledgeBaseParams
     baseURL: host
   }
 }
+
+export const getFileFromUrl = async (url: string): Promise<FileType | null> => {
+  let fileName = ''
+
+  if (url && url.includes('CherryStudio')) {
+    if (url.includes('/Data/Files')) {
+      fileName = url.split('/Data/Files/')[1]
+    }
+
+    if (url.includes('\\Data\\Files')) {
+      fileName = url.split('\\Data\\Files\\')[1]
+    }
+  }
+
+  if (fileName) {
+    const fileId = fileName.split('.')[0]
+    const file = await FileManager.getFile(fileId)
+    if (file) {
+      return file
+    }
+  }
+
+  return null
+}
+
+export const getKnowledgeSourceUrl = async (item: ExtractChunkData & { file: FileType | null }) => {
+  if (item.metadata.source.startsWith('http')) {
+    return item.metadata.source
+  }
+
+  if (item.file) {
+    return `[${item.file.origin_name}](http://file/${item.file.name})`
+  }
+
+  return item.metadata.source
+}
+
+export const getKnowledgeReferences = async (base: KnowledgeBase, message: Message) => {
+  const searchResults = await window.api.knowledgeBase.search({
+    search: message.content,
+    base: getKnowledgeBaseParams(base)
+  })
+
+  const _searchResults = await Promise.all(
+    searchResults.map(async (item) => {
+      const file = await getFileFromUrl(item.metadata.source)
+      return { ...item, file }
+    })
+  )
+
+  const references = await Promise.all(
+    take(_searchResults, 6).map(async (item, index) => {
+      const baseItem = base.items.find((i) => i.uniqueId === item.metadata.uniqueLoaderId)
+      return {
+        id: index,
+        content: item.pageContent,
+        sourceUrl: await getKnowledgeSourceUrl(item),
+        type: baseItem?.type
+      }
+    })
+  )
+
+  const referencesContent = `\`\`\`json\n${JSON.stringify(references, null, 2)}\n\`\`\``
+
+  return referencesContent
+}