修复实时更新偶发失效的问题；删除AI对话有关组件与依赖

electron/main.ts

@@ -21,7 +21,7 @@ import { videoService } from './services/videoService'
 import { snsService, isVideoUrl } from './services/snsService'
 import { contactExportService } from './services/contactExportService'
 import { windowsHelloService } from './services/windowsHelloService'
-import { llamaService } from './services/llamaService'
+
 import { registerNotificationHandlers, showNotification } from './windows/notificationWindow'
 import { httpService } from './services/httpService'
 
@@ -825,63 +825,6 @@ function registerIpcHandlers() {
     return await chatService.getContact(username)
   })
 
-  // Llama AI
-  ipcMain.handle('llama:init', async () => {
-    return await llamaService.init()
-  })
-
-  ipcMain.handle('llama:loadModel', async (_, modelPath: string) => {
-    return llamaService.loadModel(modelPath)
-  })
-
-  ipcMain.handle('llama:createSession', async (_, systemPrompt?: string) => {
-    return llamaService.createSession(systemPrompt)
-  })
-
-  ipcMain.handle('llama:chat', async (event, message: string, options?: { thinking?: boolean }) => {
-    // We use a callback to stream back to the renderer
-    const webContents = event.sender
-    try {
-      if (!webContents) return { success: false, error: 'No sender' }
-
-      const response = await llamaService.chat(message, options, (token) => {
-        if (!webContents.isDestroyed()) {
-          webContents.send('llama:token', token)
-        }
-      })
-      return { success: true, response }
-    } catch (e) {
-      return { success: false, error: String(e) }
-    }
-  })
-
-  ipcMain.handle('llama:downloadModel', async (event, url: string, savePath: string) => {
-    const webContents = event.sender
-    try {
-      await llamaService.downloadModel(url, savePath, (payload) => {
-        if (!webContents.isDestroyed()) {
-          webContents.send('llama:downloadProgress', payload)
-        }
-      })
-      return { success: true }
-    } catch (e) {
-      return { success: false, error: String(e) }
-    }
-  })
-
-  ipcMain.handle('llama:getModelsPath', async () => {
-    return llamaService.getModelsPath()
-  })
-
-  ipcMain.handle('llama:checkFileExists', async (_, filePath: string) => {
-    const { existsSync } = await import('fs')
-    return existsSync(filePath)
-  })
-
-  ipcMain.handle('llama:getModelStatus', async (_, modelPath: string) => {
-    return llamaService.getModelStatus(modelPath)
-  })
-
 
   ipcMain.handle('chat:getContactAvatar', async (_, username: string) => {
     return await chatService.getContactAvatar(username)

electron/preload.ts

@@ -288,27 +288,6 @@ contextBridge.exposeInMainWorld('electronAPI', {
     selectExportDir: () => ipcRenderer.invoke('sns:selectExportDir')
   },
 
-  // Llama AI
-  llama: {
-    loadModel: (modelPath: string) => ipcRenderer.invoke('llama:loadModel', modelPath),
-    createSession: (systemPrompt?: string) => ipcRenderer.invoke('llama:createSession', systemPrompt),
-    chat: (message: string, options?: any) => ipcRenderer.invoke('llama:chat', message, options),
-    downloadModel: (url: string, savePath: string) => ipcRenderer.invoke('llama:downloadModel', url, savePath),
-    getModelsPath: () => ipcRenderer.invoke('llama:getModelsPath'),
-    checkFileExists: (filePath: string) => ipcRenderer.invoke('llama:checkFileExists', filePath),
-    getModelStatus: (modelPath: string) => ipcRenderer.invoke('llama:getModelStatus', modelPath),
-    onToken: (callback: (token: string) => void) => {
-      const listener = (_: any, token: string) => callback(token)
-      ipcRenderer.on('llama:token', listener)
-      return () => ipcRenderer.removeListener('llama:token', listener)
-    },
-    onDownloadProgress: (callback: (payload: { downloaded: number; total: number; speed: number }) => void) => {
-      const listener = (_: any, payload: { downloaded: number; total: number; speed: number }) => callback(payload)
-      ipcRenderer.on('llama:downloadProgress', listener)
-      return () => ipcRenderer.removeListener('llama:downloadProgress', listener)
-    }
-  },
-
   // HTTP API 服务
   http: {
     start: (port?: number) => ipcRenderer.invoke('http:start', port),

electron/services/llamaService.ts

@@ -1,371 +0,0 @@
-import fs from "fs";
-import { app, BrowserWindow } from "electron";
-import path from "path";
-import { ConfigService } from './config';
-
-// Define interfaces locally to avoid static import of types that might not be available or cause issues
-type LlamaModel = any;
-type LlamaContext = any;
-type LlamaChatSession = any;
-
-export class LlamaService {
-    private _model: LlamaModel | null = null;
-    private _context: LlamaContext | null = null;
-    private _sequence: any = null;
-    private _session: LlamaChatSession | null = null;
-    private _llama: any = null;
-    private _nodeLlamaCpp: any = null;
-    private configService = new ConfigService();
-    private _initialized = false;
-
-    constructor() {
-        // 延迟初始化，只在需要时初始化
-    }
-
-    public async init() {
-        if (this._initialized) return;
-        
-        try {
-            // Dynamic import to handle ESM module in CJS context
-            this._nodeLlamaCpp = await import("node-llama-cpp");
-            this._llama = await this._nodeLlamaCpp.getLlama();
-            this._initialized = true;
-            console.log("[LlamaService] Llama initialized");
-        } catch (error) {
-            console.error("[LlamaService] Failed to initialize Llama:", error);
-        }
-    }
-
-    public async loadModel(modelPath: string) {
-        if (!this._llama) await this.init();
-
-        try {
-            console.log("[LlamaService] Loading model from:", modelPath);
-            if (!this._llama) {
-                throw new Error("Llama not initialized");
-            }
-            this._model = await this._llama.loadModel({
-                modelPath: modelPath,
-                gpuLayers: 'max', // Offload all layers to GPU if possible
-                useMlock: false   // Disable mlock to avoid "VirtualLock" errors (common on Windows)
-            });
-
-            if (!this._model) throw new Error("Failed to load model");
-
-            this._context = await this._model.createContext({
-                contextSize: 8192, // Balanced context size for better performance
-                batchSize: 2048    // Increase batch size for better prompt processing speed
-            });
-
-            if (!this._context) throw new Error("Failed to create context");
-
-            this._sequence = this._context.getSequence();
-
-            const { LlamaChatSession } = this._nodeLlamaCpp;
-            this._session = new LlamaChatSession({
-                contextSequence: this._sequence
-            });
-
-            console.log("[LlamaService] Model loaded successfully");
-            return true;
-        } catch (error) {
-            console.error("[LlamaService] Failed to load model:", error);
-            throw error;
-        }
-    }
-
-    public async createSession(systemPrompt?: string) {
-        if (!this._context) throw new Error("Model not loaded");
-        if (!this._nodeLlamaCpp) await this.init();
-
-        const { LlamaChatSession } = this._nodeLlamaCpp;
-
-        if (!this._sequence) {
-            this._sequence = this._context.getSequence();
-        }
-
-        this._session = new LlamaChatSession({
-            contextSequence: this._sequence,
-            systemPrompt: systemPrompt
-        });
-
-        return true;
-    }
-
-    public async chat(message: string, options: { thinking?: boolean } = {}, onToken: (token: string) => void) {
-        if (!this._session) throw new Error("Session not initialized");
-
-        const thinking = options.thinking ?? false;
-
-        // Sampling parameters based on mode
-        const samplingParams = thinking ? {
-            temperature: 0.6,
-            topP: 0.95,
-            topK: 20,
-            repeatPenalty: 1.5 // PresencePenalty=1.5
-        } : {
-            temperature: 0.7,
-            topP: 0.8,
-            topK: 20,
-            repeatPenalty: 1.5
-        };
-
-        try {
-            const response = await this._session.prompt(message, {
-                ...samplingParams,
-                onTextChunk: (chunk: string) => {
-                    onToken(chunk);
-                }
-            });
-            return response;
-        } catch (error) {
-            console.error("[LlamaService] Chat error:", error);
-            throw error;
-        }
-    }
-
-    public async getModelStatus(modelPath: string) {
-        try {
-            const exists = fs.existsSync(modelPath);
-            if (!exists) {
-                return { exists: false, path: modelPath };
-            }
-            const stats = fs.statSync(modelPath);
-            return {
-                exists: true,
-                path: modelPath,
-                size: stats.size
-            };
-        } catch (error) {
-            return { exists: false, error: String(error) };
-        }
-    }
-
-    private resolveModelDir(): string {
-        const configured = this.configService.get('whisperModelDir') as string | undefined;
-        if (configured) return configured;
-        return path.join(app.getPath('documents'), 'WeFlow', 'models');
-    }
-
-    public async downloadModel(url: string, savePath: string, onProgress: (payload: { downloaded: number; total: number; speed: number }) => void): Promise<void> {
-        // Ensure directory exists
-        const dir = path.dirname(savePath);
-        if (!fs.existsSync(dir)) {
-            fs.mkdirSync(dir, { recursive: true });
-        }
-
-        console.info(`[LlamaService] Multi-threaded download check for: ${savePath}`);
-
-        if (fs.existsSync(savePath)) {
-            fs.unlinkSync(savePath);
-        }
-
-        // 1. Get total size and check range support
-        let probeResult;
-        try {
-            probeResult = await this.probeUrl(url);
-        } catch (err) {
-            console.warn("[LlamaService] Probe failed, falling back to single-thread.", err);
-            return this.downloadSingleThread(url, savePath, onProgress);
-        }
-
-        const { totalSize, acceptRanges, finalUrl } = probeResult;
-        console.log(`[LlamaService] Total size: ${totalSize}, Accept-Ranges: ${acceptRanges}`);
-
-        if (totalSize <= 0 || !acceptRanges) {
-            console.warn("[LlamaService] Ranges not supported or size unknown, falling back to single-thread.");
-            return this.downloadSingleThread(finalUrl, savePath, onProgress);
-        }
-
-        const threadCount = 4;
-        const chunkSize = Math.ceil(totalSize / threadCount);
-        const fd = fs.openSync(savePath, 'w');
-
-        let downloadedLength = 0;
-        let lastDownloadedLength = 0;
-        let lastTime = Date.now();
-        let speed = 0;
-
-        const speedInterval = setInterval(() => {
-            const now = Date.now();
-            const duration = (now - lastTime) / 1000;
-            if (duration > 0) {
-                speed = (downloadedLength - lastDownloadedLength) / duration;
-                lastDownloadedLength = downloadedLength;
-                lastTime = now;
-                onProgress({ downloaded: downloadedLength, total: totalSize, speed });
-            }
-        }, 1000);
-
-        try {
-            const promises = [];
-            for (let i = 0; i < threadCount; i++) {
-                const start = i * chunkSize;
-                const end = i === threadCount - 1 ? totalSize - 1 : (i + 1) * chunkSize - 1;
-
-                promises.push(this.downloadChunk(finalUrl, fd, start, end, (bytes) => {
-                    downloadedLength += bytes;
-                }));
-            }
-
-            await Promise.all(promises);
-            console.log("[LlamaService] Multi-threaded download complete");
-
-            // Final progress update
-            onProgress({ downloaded: totalSize, total: totalSize, speed: 0 });
-        } catch (err) {
-            console.error("[LlamaService] Multi-threaded download failed:", err);
-            throw err;
-        } finally {
-            clearInterval(speedInterval);
-            fs.closeSync(fd);
-        }
-    }
-
-    private async probeUrl(url: string): Promise<{ totalSize: number, acceptRanges: boolean, finalUrl: string }> {
-        const protocol = url.startsWith('https') ? require('https') : require('http');
-        const options = {
-            method: 'GET',
-            headers: {
-                'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36',
-                'Referer': 'https://www.modelscope.cn/',
-                'Range': 'bytes=0-0'
-            }
-        };
-
-        return new Promise((resolve, reject) => {
-            const req = protocol.get(url, options, (res: any) => {
-                if ([301, 302, 307, 308].includes(res.statusCode)) {
-                    const location = res.headers.location;
-                    const nextUrl = new URL(location, url).href;
-                    this.probeUrl(nextUrl).then(resolve).catch(reject);
-                    return;
-                }
-
-                if (res.statusCode !== 206 && res.statusCode !== 200) {
-                    reject(new Error(`Probe failed: HTTP ${res.statusCode}`));
-                    return;
-                }
-
-                const contentRange = res.headers['content-range'];
-                let totalSize = 0;
-                if (contentRange) {
-                    const parts = contentRange.split('/');
-                    totalSize = parseInt(parts[parts.length - 1], 10);
-                } else {
-                    totalSize = parseInt(res.headers['content-length'] || '0', 10);
-                }
-
-                const acceptRanges = res.headers['accept-ranges'] === 'bytes' || !!contentRange;
-                resolve({ totalSize, acceptRanges, finalUrl: url });
-                res.destroy();
-            });
-            req.on('error', reject);
-        });
-    }
-
-    private async downloadChunk(url: string, fd: number, start: number, end: number, onData: (bytes: number) => void): Promise<void> {
-        const protocol = url.startsWith('https') ? require('https') : require('http');
-        const options = {
-            headers: {
-                'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36',
-                'Referer': 'https://www.modelscope.cn/',
-                'Range': `bytes=${start}-${end}`
-            }
-        };
-
-        return new Promise((resolve, reject) => {
-            const req = protocol.get(url, options, (res: any) => {
-                if (res.statusCode !== 206) {
-                    reject(new Error(`Chunk download failed: HTTP ${res.statusCode}`));
-                    return;
-                }
-
-                let currentOffset = start;
-                res.on('data', (chunk: Buffer) => {
-                    try {
-                        fs.writeSync(fd, chunk, 0, chunk.length, currentOffset);
-                        currentOffset += chunk.length;
-                        onData(chunk.length);
-                    } catch (err) {
-                        reject(err);
-                        res.destroy();
-                    }
-                });
-
-                res.on('end', () => resolve());
-                res.on('error', reject);
-            });
-            req.on('error', reject);
-        });
-    }
-
-    private async downloadSingleThread(url: string, savePath: string, onProgress: (payload: { downloaded: number; total: number; speed: number }) => void): Promise<void> {
-        return new Promise((resolve, reject) => {
-            const protocol = url.startsWith('https') ? require('https') : require('http');
-            const options = {
-                headers: {
-                    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36',
-                    'Referer': 'https://www.modelscope.cn/'
-                }
-            };
-
-            const request = protocol.get(url, options, (response: any) => {
-                if ([301, 302, 307, 308].includes(response.statusCode)) {
-                    const location = response.headers.location;
-                    const nextUrl = new URL(location, url).href;
-                    this.downloadSingleThread(nextUrl, savePath, onProgress).then(resolve).catch(reject);
-                    return;
-                }
-
-                if (response.statusCode !== 200) {
-                    reject(new Error(`Fallback download failed: HTTP ${response.statusCode}`));
-                    return;
-                }
-
-                const totalLength = parseInt(response.headers['content-length'] || '0', 10);
-                let downloadedLength = 0;
-                let lastDownloadedLength = 0;
-                let lastTime = Date.now();
-                let speed = 0;
-
-                const fileStream = fs.createWriteStream(savePath);
-                response.pipe(fileStream);
-
-                const speedInterval = setInterval(() => {
-                    const now = Date.now();
-                    const duration = (now - lastTime) / 1000;
-                    if (duration > 0) {
-                        speed = (downloadedLength - lastDownloadedLength) / duration;
-                        lastDownloadedLength = downloadedLength;
-                        lastTime = now;
-                        onProgress({ downloaded: downloadedLength, total: totalLength, speed });
-                    }
-                }, 1000);
-
-                response.on('data', (chunk: any) => {
-                    downloadedLength += chunk.length;
-                });
-
-                fileStream.on('finish', () => {
-                    clearInterval(speedInterval);
-                    fileStream.close();
-                    resolve();
-                });
-
-                fileStream.on('error', (err: any) => {
-                    clearInterval(speedInterval);
-                    fs.unlink(savePath, () => { });
-                    reject(err);
-                });
-            });
-            request.on('error', reject);
-        });
-    }
-
-    public getModelsPath() {
-        return this.resolveModelDir();
-    }
-}
-
-export const llamaService = new LlamaService();

electron/services/wcdbCore.ts

@@ -66,8 +66,12 @@ export class WcdbCore {
   private wcdbVerifyUser: any = null
   private wcdbStartMonitorPipe: any = null
   private wcdbStopMonitorPipe: any = null
+  private wcdbGetMonitorPipeName: any = null
 
   private monitorPipeClient: any = null
+  private monitorCallback: ((type: string, json: string) => void) | null = null
+  private monitorReconnectTimer: any = null
+  private monitorPipePath: string = ''
 
 
   private avatarUrlCache: Map<string, { url?: string; updatedAt: number }> = new Map()
@@ -92,23 +96,46 @@ export class WcdbCore {
   // 使用命名管道 IPC
   startMonitor(callback: (type: string, json: string) => void): boolean {
     if (!this.wcdbStartMonitorPipe) {
-      this.writeLog('startMonitor: wcdbStartMonitorPipe not available')
       return false
     }
 
+    this.monitorCallback = callback
+
     try {
       const result = this.wcdbStartMonitorPipe()
       if (result !== 0) {
-        this.writeLog(`startMonitor: wcdbStartMonitorPipe failed with ${result}`)
         return false
       }
 
+      // 从 DLL 获取动态管道名（含 PID）
+      let pipePath = '\\\\.\\pipe\\weflow_monitor'
+      if (this.wcdbGetMonitorPipeName) {
+        try {
+          const namePtr = [null as any]
+          if (this.wcdbGetMonitorPipeName(namePtr) === 0 && namePtr[0]) {
+            pipePath = this.koffi.decode(namePtr[0], 'char', -1)
+            this.wcdbFreeString(namePtr[0])
+          }
+        } catch {}
+      }
+
+      this.connectMonitorPipe(pipePath)
+      return true
+    } catch (e) {
+      console.error('[wcdbCore] startMonitor exception:', e)
+      return false
+    }
+  }
+
+  // 连接命名管道，支持断开后自动重连
+  private connectMonitorPipe(pipePath: string) {
+    this.monitorPipePath = pipePath
     const net = require('net')
-      const PIPE_PATH = '\\\\.\\pipe\\weflow_monitor'
 
     setTimeout(() => {
-        this.monitorPipeClient = net.createConnection(PIPE_PATH, () => {
+      if (!this.monitorCallback) return
-          this.writeLog('Monitor pipe connected')
+
+      this.monitorPipeClient = net.createConnection(this.monitorPipePath, () => {
       })
 
       let buffer = ''
@@ -120,35 +147,43 @@ export class WcdbCore {
           if (line.trim()) {
             try {
               const parsed = JSON.parse(line)
-                callback(parsed.action || 'update', line)
+              this.monitorCallback?.(parsed.action || 'update', line)
             } catch {
-                callback('update', line)
+              this.monitorCallback?.('update', line)
             }
           }
         }
       })
 
-        this.monitorPipeClient.on('error', (err: Error) => {
+      this.monitorPipeClient.on('error', () => {
-          this.writeLog(`Monitor pipe error: ${err.message}`)
       })
 
       this.monitorPipeClient.on('close', () => {
-          this.writeLog('Monitor pipe closed')
         this.monitorPipeClient = null
+        this.scheduleReconnect()
       })
     }, 100)
-
-      this.writeLog('Monitor started via named pipe IPC')
-      return true
-    } catch (e) {
-      console.error('打开数据库异常:', e)
-      return false
   }
+
+  // 定时重连
+  private scheduleReconnect() {
+    if (this.monitorReconnectTimer || !this.monitorCallback) return
+    this.monitorReconnectTimer = setTimeout(() => {
+      this.monitorReconnectTimer = null
+      if (this.monitorCallback && !this.monitorPipeClient) {
+        this.connectMonitorPipe(this.monitorPipePath)
+      }
+    }, 3000)
   }
 
 
 
   stopMonitor(): void {
+    this.monitorCallback = null
+    if (this.monitorReconnectTimer) {
+      clearTimeout(this.monitorReconnectTimer)
+      this.monitorReconnectTimer = null
+    }
     if (this.monitorPipeClient) {
       this.monitorPipeClient.destroy()
       this.monitorPipeClient = null
@@ -569,11 +604,13 @@ export class WcdbCore {
       try {
         this.wcdbStartMonitorPipe = this.lib.func('int32 wcdb_start_monitor_pipe()')
         this.wcdbStopMonitorPipe = this.lib.func('void wcdb_stop_monitor_pipe()')
+        this.wcdbGetMonitorPipeName = this.lib.func('int32 wcdb_get_monitor_pipe_name(_Out_ void** outName)')
         this.writeLog('Monitor pipe functions loaded')
       } catch (e) {
         console.warn('Failed to load monitor pipe functions:', e)
         this.wcdbStartMonitorPipe = null
         this.wcdbStopMonitorPipe = null
+        this.wcdbGetMonitorPipeName = null
       }
 
       // void VerifyUser(int64_t hwnd_ptr, const char* message, char* out_result, int max_len)

electron/services/wcdbService.ts

@@ -136,7 +136,6 @@ export class WcdbService {
    */
   setMonitor(callback: (type: string, json: string) => void): void {
     this.monitorListener = callback;
-    // Notify worker to enable monitor
     this.callWorker('setMonitor').catch(() => { });
   }
 

package.json

@@ -32,7 +32,6 @@
     "jszip": "^3.10.1",
     "koffi": "^2.9.0",
     "lucide-react": "^0.562.0",
-    "node-llama-cpp": "^3.15.1",
     "react": "^19.2.3",
     "react-dom": "^19.2.3",
     "react-markdown": "^10.1.0",

src/App.tsx

@@ -22,7 +22,6 @@ import SnsPage from './pages/SnsPage'
 import ContactsPage from './pages/ContactsPage'
 import ChatHistoryPage from './pages/ChatHistoryPage'
 import NotificationWindow from './pages/NotificationWindow'
-import AIChatPage from './pages/AIChatPage'
 
 import { useAppStore } from './stores/appStore'
 import { themes, useThemeStore, type ThemeId, type ThemeMode } from './stores/themeStore'
@@ -457,7 +456,7 @@ function App() {
               <Route path="/" element={<HomePage />} />
               <Route path="/home" element={<HomePage />} />
               <Route path="/chat" element={<ChatPage />} />
-              <Route path="/ai-chat" element={<AIChatPage />} />
+
               <Route path="/analytics" element={<AnalyticsWelcomePage />} />
               <Route path="/analytics/view" element={<AnalyticsPage />} />
               <Route path="/group-analytics" element={<GroupAnalyticsPage />} />

src/components/GlobalSessionMonitor.tsx

@@ -14,7 +14,6 @@ export function GlobalSessionMonitor() {
     } = useChatStore()
 
     const sessionsRef = useRef(sessions)
-
     // 保持 ref 同步
     useEffect(() => {
         sessionsRef.current = sessions
@@ -47,9 +46,10 @@ export function GlobalSessionMonitor() {
             return () => {
                 removeListener()
             }
+        } else {
         }
         return () => { }
-    }, []) // 空依赖数组 - 主要是静态的
+    }, [])
 
     const refreshSessions = async () => {
         try {

src/pages/AIChatPage.scss

@@ -1,552 +0,0 @@
-// AI 对话页面 - 简约大气风格
-.ai-chat-page {
-    display: flex;
-    height: 100%;
-    width: 100%;
-    background: var(--bg-gradient);
-    color: var(--text-primary);
-    overflow: hidden;
-
-    .chat-container {
-        flex: 1;
-        display: flex;
-        flex-direction: column;
-        max-width: 1200px;
-        margin: 0 auto;
-        width: 100%;
-    }
-
-    // ========== 顶部 Header - 已移除 ==========
-    // 模型选择器现已集成到输入框
-
-
-
-    // ========== 聊天区域 ==========
-    .chat-main {
-        flex: 1;
-        display: flex;
-        flex-direction: column;
-        background: var(--bg-secondary);
-        position: relative;
-        overflow: hidden;
-
-        // 空状态
-        .empty-state {
-            flex: 1;
-            display: flex;
-            flex-direction: column;
-            align-items: center;
-            justify-content: center;
-            padding: 40px;
-
-            .icon {
-                width: 80px;
-                height: 80px;
-                border-radius: 50%;
-                background: var(--primary-light);
-                display: flex;
-                align-items: center;
-                justify-content: center;
-                margin-bottom: 24px;
-
-                svg {
-                    width: 40px;
-                    height: 40px;
-                    color: var(--primary);
-                }
-            }
-
-            h2 {
-                font-size: 20px;
-                font-weight: 600;
-                color: var(--text-primary);
-                margin: 0 0 8px;
-            }
-
-            p {
-                font-size: 14px;
-                color: var(--text-tertiary);
-                margin: 0;
-            }
-        }
-
-        // 消息列表
-        .messages-list {
-            flex: 1;
-            overflow-y: auto;
-            padding: 24px 32px;
-            display: flex;
-            flex-direction: column;
-            gap: 20px;
-
-            &::-webkit-scrollbar {
-                width: 6px;
-            }
-
-            &::-webkit-scrollbar-track {
-                background: transparent;
-            }
-
-            &::-webkit-scrollbar-thumb {
-                background: var(--border-color);
-                border-radius: 3px;
-            }
-
-            .message-row {
-                display: flex;
-                gap: 12px;
-                max-width: 80%;
-                animation: messageIn 0.3s ease-out;
-
-                // 用户消息
-                &.user {
-                    align-self: flex-end;
-                    flex-direction: row-reverse;
-
-                    .avatar {
-                        background: var(--primary-light);
-                        color: var(--primary);
-                    }
-
-                    .bubble {
-                        background: var(--primary-gradient);
-                        color: white;
-                        border-radius: 18px 18px 4px 18px;
-                        box-shadow: 0 2px 10px color-mix(in srgb, var(--primary) 20%, transparent);
-
-                        .content {
-                            color: white;
-                        }
-                    }
-                }
-
-                // AI 消息
-                &.ai {
-                    align-self: flex-start;
-
-                    .avatar {
-                        background: var(--bg-tertiary);
-                        color: var(--text-secondary);
-                    }
-
-                    .bubble {
-                        background: var(--card-bg);
-                        border: 1px solid var(--border-color);
-                        border-radius: 18px 18px 18px 4px;
-                        backdrop-filter: blur(10px);
-                        -webkit-backdrop-filter: blur(10px);
-                    }
-                }
-
-                .avatar {
-                    flex-shrink: 0;
-                    width: 32px;
-                    height: 32px;
-                    border-radius: 50%;
-                    display: flex;
-                    align-items: center;
-                    justify-content: center;
-                }
-
-                .bubble {
-                    padding: 12px 16px;
-                    flex: 1;
-                    min-width: 0;
-
-                    .content,
-                    .markdown-content {
-                        font-size: 14px;
-                        line-height: 1.6;
-                        color: var(--text-primary);
-                        word-wrap: break-word;
-                        overflow-wrap: break-word;
-                    }
-
-                    // Markdown 样式
-                    .markdown-content {
-                        p {
-                            margin: 0 0 0.8em;
-
-                            &:last-child {
-                                margin-bottom: 0;
-                            }
-                        }
-
-                        h1,
-                        h2,
-                        h3,
-                        h4,
-                        h5,
-                        h6 {
-                            margin: 1em 0 0.5em;
-                            font-weight: 600;
-                            line-height: 1.3;
-                            color: var(--text-primary);
-
-                            &:first-child {
-                                margin-top: 0;
-                            }
-                        }
-
-                        h1 {
-                            font-size: 1.5em;
-                        }
-
-                        h2 {
-                            font-size: 1.3em;
-                        }
-
-                        h3 {
-                            font-size: 1.1em;
-                        }
-
-                        ul,
-                        ol {
-                            margin: 0.5em 0;
-                            padding-left: 1.5em;
-                        }
-
-                        li {
-                            margin: 0.3em 0;
-                        }
-
-                        code {
-                            background: var(--bg-tertiary);
-                            padding: 2px 6px;
-                            border-radius: 4px;
-                            font-family: 'Consolas', 'Monaco', monospace;
-                            font-size: 0.9em;
-                        }
-
-                        pre {
-                            background: var(--bg-tertiary);
-                            padding: 12px;
-                            border-radius: 8px;
-                            overflow-x: auto;
-                            margin: 0.8em 0;
-
-                            code {
-                                background: none;
-                                padding: 0;
-                            }
-                        }
-
-                        blockquote {
-                            border-left: 3px solid var(--primary);
-                            padding-left: 12px;
-                            margin: 0.8em 0;
-                            color: var(--text-secondary);
-                        }
-
-                        a {
-                            color: var(--primary);
-                            text-decoration: none;
-
-                            &:hover {
-                                text-decoration: underline;
-                            }
-                        }
-
-                        strong {
-                            font-weight: 600;
-                            color: var(--text-primary);
-                        }
-
-                        hr {
-                            border: none;
-                            border-top: 1px solid var(--border-color);
-                            margin: 1em 0;
-                        }
-
-                        table {
-                            border-collapse: collapse;
-                            width: 100%;
-                            margin: 0.8em 0;
-
-                            th,
-                            td {
-                                border: 1px solid var(--border-color);
-                                padding: 8px 12px;
-                                text-align: left;
-                            }
-
-                            th {
-                                background: var(--bg-tertiary);
-                                font-weight: 600;
-                            }
-                        }
-                    }
-                }
-            }
-
-            .list-spacer {
-                height: 100px;
-                flex-shrink: 0;
-            }
-        }
-
-        // 输入区域
-        .input-area {
-            position: absolute;
-            bottom: 24px;
-            left: 50%;
-            transform: translateX(-50%);
-            width: calc(100% - 64px);
-            max-width: 800px;
-            z-index: 10;
-
-            .input-wrapper {
-                display: flex;
-                align-items: flex-end;
-                gap: 10px;
-                background: var(--card-bg);
-                backdrop-filter: blur(20px);
-                -webkit-backdrop-filter: blur(20px);
-                border: 1px solid var(--border-color);
-                border-radius: 20px;
-                padding: 10px 14px;
-                box-shadow: 0 8px 32px rgba(0, 0, 0, 0.08);
-                transition: all 0.2s ease;
-
-                &:focus-within {
-                    border-color: var(--primary);
-                    box-shadow: 0 8px 32px rgba(0, 0, 0, 0.1),
-                        0 0 0 3px color-mix(in srgb, var(--primary) 15%, transparent);
-                }
-
-                textarea {
-                    flex: 1;
-                    min-height: 24px;
-                    max-height: 120px;
-                    padding: 8px 0;
-                    background: transparent;
-                    border: none;
-                    resize: none;
-                    color: var(--text-primary);
-                    font-size: 14px;
-                    font-family: inherit;
-                    line-height: 1.5;
-
-                    &:focus {
-                        outline: none;
-                    }
-
-                    &::placeholder {
-                        color: var(--text-tertiary);
-                    }
-
-                    &:disabled {
-                        cursor: not-allowed;
-                    }
-                }
-
-                .input-actions {
-                    display: flex;
-                    align-items: center;
-                    gap: 8px;
-                    flex-shrink: 0;
-
-                    // 模型选择器
-                    .model-selector {
-                        position: relative;
-
-                        .model-btn {
-                            display: flex;
-                            align-items: center;
-                            justify-content: center;
-                            gap: 6px;
-                            width: auto;
-                            height: 36px;
-                            padding: 6px 12px;
-                            background: transparent;
-                            border: 1px solid var(--border-color);
-                            border-radius: 10px;
-                            cursor: pointer;
-                            color: var(--text-secondary);
-                            font-size: 12px;
-                            font-weight: 500;
-                            white-space: nowrap;
-                            transition: all 0.2s ease;
-                            flex-shrink: 0;
-
-                            svg {
-                                flex-shrink: 0;
-
-                                &.spin {
-                                    animation: spin 1s linear infinite;
-                                }
-                            }
-
-                            &:hover:not(:disabled) {
-                                background: var(--bg-hover);
-                                border-color: var(--text-tertiary);
-                                color: var(--text-primary);
-                            }
-
-                            &.loaded {
-                                background: color-mix(in srgb, var(--primary) 15%, transparent);
-                                border-color: var(--primary);
-                                color: var(--primary);
-                            }
-
-                            &.loading {
-                                opacity: 0.7;
-                            }
-
-                            &.disabled {
-                                opacity: 0.5;
-                                cursor: not-allowed;
-                            }
-                        }
-
-                        .model-dropdown {
-                            position: absolute;
-                            bottom: 100%;
-                            right: 0;
-                            margin-bottom: 8px;
-                            background: var(--card-bg);
-                            backdrop-filter: blur(20px);
-                            -webkit-backdrop-filter: blur(20px);
-                            border: 1px solid var(--border-color);
-                            border-radius: 12px;
-                            box-shadow: 0 8px 24px rgba(0, 0, 0, 0.12);
-                            z-index: 100;
-                            overflow: hidden;
-                            animation: dropdownIn 0.2s ease-out;
-                            min-width: 140px;
-
-                            .model-option {
-                                display: flex;
-                                align-items: center;
-                                justify-content: space-between;
-                                padding: 10px 14px;
-                                cursor: pointer;
-                                font-size: 13px;
-                                color: var(--text-primary);
-                                transition: background 0.15s ease;
-                                white-space: nowrap;
-
-                                &:hover:not(.disabled) {
-                                    background: var(--bg-hover);
-                                }
-
-                                &.active {
-                                    background: color-mix(in srgb, var(--primary) 20%, transparent);
-                                    color: var(--primary);
-                                    font-weight: 600;
-
-                                    .check {
-                                        color: var(--primary);
-                                    }
-                                }
-
-                                .check {
-                                    margin-left: 8px;
-                                    color: var(--text-tertiary);
-                                    font-weight: 600;
-                                }
-                            }
-                        }
-                    }
-
-                    .mode-toggle {
-                        width: 36px;
-                        height: 36px;
-                        display: flex;
-                        align-items: center;
-                        justify-content: center;
-                        background: transparent;
-                        border: 1px solid var(--border-color);
-                        border-radius: 10px;
-                        cursor: pointer;
-                        color: var(--text-tertiary);
-                        transition: all 0.2s ease;
-                        flex-shrink: 0;
-
-                        &:hover:not(:disabled) {
-                            background: var(--bg-hover);
-                            color: var(--text-primary);
-                        }
-
-                        &.active {
-                            background: color-mix(in srgb, var(--primary) 15%, transparent);
-                            border-color: var(--primary);
-                            color: var(--primary);
-                        }
-
-                        &:disabled {
-                            opacity: 0.4;
-                            cursor: not-allowed;
-                        }
-                    }
-
-                    .send-btn {
-                        width: 36px;
-                        height: 36px;
-                        display: flex;
-                        align-items: center;
-                        justify-content: center;
-                        background: var(--primary-gradient);
-                        border: none;
-                        border-radius: 10px;
-                        cursor: pointer;
-                        color: white;
-                        transition: all 0.2s ease;
-                        flex-shrink: 0;
-                        box-shadow: 0 2px 8px color-mix(in srgb, var(--primary) 25%, transparent);
-
-                        &:hover:not(:disabled) {
-                            transform: scale(1.05);
-                            box-shadow: 0 4px 12px color-mix(in srgb, var(--primary) 35%, transparent);
-                        }
-
-                        &:active:not(:disabled) {
-                            transform: scale(0.98);
-                        }
-
-                        &:disabled {
-                            background: var(--bg-tertiary);
-                            color: var(--text-tertiary);
-                            box-shadow: none;
-                            cursor: not-allowed;
-                        }
-                    }
-                }
-            }
-        }
-    }
-}
-
-@keyframes messageIn {
-    from {
-        opacity: 0;
-        transform: translateY(8px);
-    }
-
-    to {
-        opacity: 1;
-        transform: translateY(0);
-    }
-}
-
-@keyframes dropdownIn {
-    from {
-        opacity: 0;
-        transform: translateY(-8px);
-    }
-
-    to {
-        opacity: 1;
-        transform: translateY(0);
-    }
-}
-
-@keyframes spin {
-    from {
-        transform: rotate(0deg);
-    }
-
-    to {
-        transform: rotate(360deg);
-    }
-}

src/pages/AIChatPage.tsx

@@ -1,391 +0,0 @@
-import { useState, useEffect, useRef, useCallback } from 'react'
-import { Send, Bot, User, Cpu, ChevronDown, Loader2 } from 'lucide-react'
-import { Virtuoso, VirtuosoHandle } from 'react-virtuoso'
-import { engineService, PRESET_MODELS, ModelInfo } from '../services/EngineService'
-import { MessageBubble } from '../components/MessageBubble'
-import './AIChatPage.scss'
-
-interface ChatMessage {
-    id: string;
-    role: 'user' | 'ai';
-    content: string;
-    timestamp: number;
-}
-
-// 消息数量限制，避免内存过载
-const MAX_MESSAGES = 200
-
-export default function AIChatPage() {
-    const [input, setInput] = useState('')
-    const [messages, setMessages] = useState<ChatMessage[]>([])
-    const [isTyping, setIsTyping] = useState(false)
-    const [models, setModels] = useState<ModelInfo[]>([...PRESET_MODELS])
-    const [selectedModel, setSelectedModel] = useState<string | null>(null)
-    const [modelLoaded, setModelLoaded] = useState(false)
-    const [loadingModel, setLoadingModel] = useState(false)
-    const [isThinkingMode, setIsThinkingMode] = useState(true)
-    const [showModelDropdown, setShowModelDropdown] = useState(false)
-
-    const textareaRef = useRef<HTMLTextAreaElement>(null)
-    const virtuosoRef = useRef<VirtuosoHandle>(null)
-    const dropdownRef = useRef<HTMLDivElement>(null)
-
-    // 流式渲染优化：使用 ref 缓存内容，使用 RAF 批量更新
-    const streamingContentRef = useRef('')
-    const streamingMessageIdRef = useRef<string | null>(null)
-    const rafIdRef = useRef<number | null>(null)
-
-    useEffect(() => {
-        checkModelsStatus()
-
-        // 初始化Llama服务（延迟初始化，用户进入此页面时启动）
-        const initLlama = async () => {
-            try {
-                await window.electronAPI.llama?.init()
-                console.log('[AIChatPage] Llama service initialized')
-            } catch (e) {
-                console.error('[AIChatPage] Failed to initialize Llama:', e)
-            }
-        }
-        initLlama()
-
-        // 清理函数：组件卸载时释放所有资源
-        return () => {
-            // 取消未完成的 RAF
-            if (rafIdRef.current !== null) {
-                cancelAnimationFrame(rafIdRef.current)
-                rafIdRef.current = null
-            }
-
-            // 清理 engine service 的回调引用
-            engineService.clearCallbacks()
-        }
-    }, [])
-
-    // 监听页面卸载事件，确保资源释放
-    useEffect(() => {
-        const handleBeforeUnload = () => {
-            // 清理回调和监听器
-            engineService.dispose()
-        }
-
-        window.addEventListener('beforeunload', handleBeforeUnload)
-        return () => window.removeEventListener('beforeunload', handleBeforeUnload)
-    }, [])
-
-    // 点击外部关闭下拉框
-    useEffect(() => {
-        const handleClickOutside = (event: MouseEvent) => {
-            if (dropdownRef.current && !dropdownRef.current.contains(event.target as Node)) {
-                setShowModelDropdown(false)
-            }
-        }
-
-        document.addEventListener('mousedown', handleClickOutside)
-        return () => document.removeEventListener('mousedown', handleClickOutside)
-    }, [])
-
-    const scrollToBottom = useCallback(() => {
-        // 使用 virtuoso 的 scrollToIndex 方法滚动到底部
-        if (virtuosoRef.current && messages.length > 0) {
-            virtuosoRef.current.scrollToIndex({
-                index: messages.length - 1,
-                behavior: 'smooth'
-            })
-        }
-    }, [messages.length])
-
-    const checkModelsStatus = async () => {
-        const updatedModels = await Promise.all(models.map(async (m) => {
-            const exists = await engineService.checkModelExists(m.path)
-            return { ...m, downloaded: exists }
-        }))
-        setModels(updatedModels)
-
-        // Auto-select first available model
-        if (!selectedModel) {
-            const available = updatedModels.find(m => m.downloaded)
-            if (available) {
-                setSelectedModel(available.path)
-            }
-        }
-    }
-
-    // 自动加载模型
-    const handleLoadModel = async (modelPath?: string) => {
-        const pathToLoad = modelPath || selectedModel
-        if (!pathToLoad) return false
-
-        setLoadingModel(true)
-        try {
-            await engineService.loadModel(pathToLoad)
-            // Initialize session with system prompt
-            await engineService.createSession("You are a helpful AI assistant.")
-            setModelLoaded(true)
-            return true
-        } catch (e) {
-            console.error("Load failed", e)
-            alert("模型加载失败: " + String(e))
-            return false
-        } finally {
-            setLoadingModel(false)
-        }
-    }
-
-    // 选择模型（如果有多个）
-    const handleSelectModel = (modelPath: string) => {
-        setSelectedModel(modelPath)
-        setShowModelDropdown(false)
-    }
-
-    // 获取可用的已下载模型
-    const availableModels = models.filter(m => m.downloaded)
-    const selectedModelInfo = models.find(m => m.path === selectedModel)
-
-    // 优化的流式更新函数：使用 RAF 批量更新
-    const updateStreamingMessage = useCallback(() => {
-        if (!streamingMessageIdRef.current) return
-
-        setMessages(prev => prev.map(msg =>
-            msg.id === streamingMessageIdRef.current
-                ? { ...msg, content: streamingContentRef.current }
-                : msg
-        ))
-
-        rafIdRef.current = null
-    }, [])
-
-    // Token 回调：使用 RAF 批量更新 UI
-    const handleToken = useCallback((token: string) => {
-        streamingContentRef.current += token
-
-        // 使用 requestAnimationFrame 批量更新，避免频繁渲染
-        if (rafIdRef.current === null) {
-            rafIdRef.current = requestAnimationFrame(updateStreamingMessage)
-        }
-    }, [updateStreamingMessage])
-
-    const handleSend = async () => {
-        if (!input.trim() || isTyping) return
-
-        // 如果模型未加载，先自动加载
-        if (!modelLoaded) {
-            if (!selectedModel) {
-                alert("请先下载模型（设置页面）")
-                return
-            }
-            const loaded = await handleLoadModel()
-            if (!loaded) return
-        }
-
-        const userMsg: ChatMessage = {
-            id: Date.now().toString(),
-            role: 'user',
-            content: input,
-            timestamp: Date.now()
-        }
-
-        setMessages(prev => {
-            const newMessages = [...prev, userMsg]
-            // 限制消息数量，避免内存过载
-            return newMessages.length > MAX_MESSAGES
-                ? newMessages.slice(-MAX_MESSAGES)
-                : newMessages
-        })
-        setInput('')
-        setIsTyping(true)
-
-        // Reset textarea height
-        if (textareaRef.current) {
-            textareaRef.current.style.height = 'auto'
-        }
-
-        const aiMsgId = (Date.now() + 1).toString()
-        streamingContentRef.current = ''
-        streamingMessageIdRef.current = aiMsgId
-
-        // Optimistic update for AI message start
-        setMessages(prev => {
-            const newMessages = [...prev, {
-                id: aiMsgId,
-                role: 'ai' as const,
-                content: '',
-                timestamp: Date.now()
-            }]
-            return newMessages.length > MAX_MESSAGES
-                ? newMessages.slice(-MAX_MESSAGES)
-                : newMessages
-        })
-
-        // Append thinking command based on mode
-        const msgWithSuffix = input + (isThinkingMode ? " /think" : " /no_think")
-
-        try {
-            await engineService.chat(msgWithSuffix, handleToken, { thinking: isThinkingMode })
-        } catch (e) {
-            console.error("Chat failed", e)
-            setMessages(prev => [...prev, {
-                id: Date.now().toString(),
-                role: 'ai',
-                content: "❌ Error: Failed to get response from AI.",
-                timestamp: Date.now()
-            }])
-        } finally {
-            setIsTyping(false)
-            streamingMessageIdRef.current = null
-
-            // 确保最终状态同步
-            if (rafIdRef.current !== null) {
-                cancelAnimationFrame(rafIdRef.current)
-                updateStreamingMessage()
-            }
-        }
-    }
-
-    // 渲染模型选择按钮（集成在输入框作为下拉项）
-    const renderModelSelector = () => {
-        // 没有可用模型
-        if (availableModels.length === 0) {
-            return (
-                <button
-                    className="model-btn disabled"
-                    title="请先在设置页面下载模型"
-                >
-                    <Bot size={16} />
-                    <span>无模型</span>
-                </button>
-            )
-        }
-
-        // 只有一个模型，直接显示
-        if (availableModels.length === 1) {
-            return (
-                <button
-                    className={`model-btn ${modelLoaded ? 'loaded' : ''} ${loadingModel ? 'loading' : ''}`}
-                    title={modelLoaded ? "模型已就绪" : "发送消息时自动加载"}
-                >
-                    {loadingModel ? (
-                        <Loader2 size={16} className="spin" />
-                    ) : (
-                        <Bot size={16} />
-                    )}
-                    <span>{loadingModel ? '加载中' : selectedModelInfo?.name || '模型'}</span>
-                </button>
-            )
-        }
-
-        // 多个模型，显示下拉选择
-        return (
-            <div className="model-selector" ref={dropdownRef}>
-                <button
-                    className={`model-btn ${modelLoaded ? 'loaded' : ''} ${loadingModel ? 'loading' : ''}`}
-                    onClick={() => !loadingModel && setShowModelDropdown(!showModelDropdown)}
-                    title="点击选择模型"
-                >
-                    {loadingModel ? (
-                        <Loader2 size={16} className="spin" />
-                    ) : (
-                        <Bot size={16} />
-                    )}
-                    <span>{loadingModel ? '加载中' : selectedModelInfo?.name || '选择模型'}</span>
-                    <ChevronDown size={13} className={showModelDropdown ? 'rotate' : ''} />
-                </button>
-
-                {showModelDropdown && (
-                    <div className="model-dropdown">
-                        {availableModels.map(model => (
-                            <div
-                                key={model.path}
-                                className={`model-option ${selectedModel === model.path ? 'active' : ''}`}
-                                onClick={() => handleSelectModel(model.path)}
-                            >
-                                <span>{model.name}</span>
-                                {selectedModel === model.path && (
-                                    <span className="check">✓</span>
-                                )}
-                            </div>
-                        ))}
-                    </div>
-                )}
-            </div>
-        )
-    }
-
-    return (
-        <div className="ai-chat-page">
-            <div className="chat-main">
-                {messages.length === 0 ? (
-                    <div className="empty-state">
-                        <div className="icon">
-                            <Bot size={40} />
-                        </div>
-                        <h2>AI 为你服务</h2>
-                        <p>
-                            {availableModels.length === 0
-                                ? "请先在设置页面下载模型"
-                                : "输入消息开始对话，模型将自动加载"
-                            }
-                        </p>
-                    </div>
-                ) : (
-                    <Virtuoso
-                        ref={virtuosoRef}
-                        data={messages}
-                        className="messages-list"
-                        initialTopMostItemIndex={messages.length - 1}
-                        followOutput="smooth"
-                        itemContent={(index, message) => (
-                            <MessageBubble key={message.id} message={message} />
-                        )}
-                        components={{
-                            Footer: () => <div className="list-spacer" />
-                        }}
-                    />
-                )}
-
-                <div className="input-area">
-                    <div className="input-wrapper">
-                        <textarea
-                            ref={textareaRef}
-                            value={input}
-                            onChange={e => {
-                                setInput(e.target.value)
-                                e.target.style.height = 'auto'
-                                e.target.style.height = `${Math.min(e.target.scrollHeight, 120)}px`
-                            }}
-                            onKeyDown={e => {
-                                if (e.key === 'Enter' && !e.shiftKey) {
-                                    e.preventDefault()
-                                    handleSend()
-                                    // Reset height after send
-                                    if (textareaRef.current) textareaRef.current.style.height = 'auto'
-                                }
-                            }}
-                            placeholder={availableModels.length === 0 ? "请先下载模型..." : "输入消息..."}
-                            disabled={availableModels.length === 0 || loadingModel}
-                            rows={1}
-                        />
-                        <div className="input-actions">
-                            {renderModelSelector()}
-                            <button
-                                className={`mode-toggle ${isThinkingMode ? 'active' : ''}`}
-                                onClick={() => setIsThinkingMode(!isThinkingMode)}
-                                title={isThinkingMode ? "深度思考模式已开启" : "深度思考模式已关闭"}
-                                disabled={availableModels.length === 0}
-                            >
-                                <Cpu size={18} />
-                            </button>
-                            <button
-                                className="send-btn"
-                                onClick={handleSend}
-                                disabled={!input.trim() || availableModels.length === 0 || isTyping || loadingModel}
-                            >
-                                <Send size={18} />
-                            </button>
-                        </div>
-                    </div>
-                </div>
-            </div>
-        </div>
-    )
-}

src/pages/SettingsPage.tsx

@@ -90,10 +90,6 @@ function SettingsPage() {
   const [whisperDownloadProgress, setWhisperDownloadProgress] = useState(0)
   const [whisperProgressData, setWhisperProgressData] = useState<{ downloaded: number; total: number; speed: number }>({ downloaded: 0, total: 0, speed: 0 })
   const [whisperModelStatus, setWhisperModelStatus] = useState<{ exists: boolean; modelPath?: string; tokensPath?: string } | null>(null)
-  const [llamaModelStatus, setLlamaModelStatus] = useState<{ exists: boolean; path?: string; size?: number } | null>(null)
-  const [isLlamaDownloading, setIsLlamaDownloading] = useState(false)
-  const [llamaDownloadProgress, setLlamaDownloadProgress] = useState(0)
-  const [llamaProgressData, setLlamaProgressData] = useState<{ downloaded: number; total: number; speed: number }>({ downloaded: 0, total: 0, speed: 0 })
 
   const formatBytes = (bytes: number) => {
     if (bytes === 0) return '0 B';
@@ -336,8 +332,7 @@ function SettingsPage() {
 
       if (savedWhisperModelDir) setWhisperModelDir(savedWhisperModelDir)
 
-      // Load Llama status after config
+
-      void checkLlamaModelStatus()
     } catch (e: any) {
       console.error('加载配置失败:', e)
     }
@@ -653,7 +648,6 @@ function SettingsPage() {
         setWhisperModelDir(dir)
         await configService.setWhisperModelDir(dir)
         showMessage('已选择 Whisper 模型目录', true)
-        await checkLlamaModelStatus()
       }
     } catch (e: any) {
       showMessage('选择目录失败', false)
@@ -689,68 +683,6 @@ function SettingsPage() {
   const handleResetWhisperModelDir = async () => {
     setWhisperModelDir('')
     await configService.setWhisperModelDir('')
-    await checkLlamaModelStatus()
-  }
-
-  const checkLlamaModelStatus = async () => {
-    try {
-      // @ts-ignore
-      const modelsPath = await window.electronAPI.llama?.getModelsPath()
-      if (!modelsPath) return
-      const modelName = "Qwen3-4B-Q4_K_M.gguf" // Hardcoded preset for now
-      const fullPath = `${modelsPath}\\${modelName}`
-      // @ts-ignore
-      const status = await window.electronAPI.llama?.getModelStatus(fullPath)
-      if (status) {
-        setLlamaModelStatus({
-          exists: status.exists,
-          path: status.path,
-          size: status.size
-        })
-      }
-    } catch (e) {
-      console.error("Check llama model status failed", e)
-    }
-  }
-
-  useEffect(() => {
-    const handleLlamaProgress = (payload: { downloaded: number; total: number; speed: number }) => {
-      setLlamaProgressData(payload)
-      if (payload.total > 0) {
-        setLlamaDownloadProgress((payload.downloaded / payload.total) * 100)
-      }
-    }
-    // @ts-ignore
-    const removeListener = window.electronAPI.llama?.onDownloadProgress(handleLlamaProgress)
-    return () => {
-      if (typeof removeListener === 'function') removeListener()
-    }
-  }, [])
-
-  const handleDownloadLlamaModel = async () => {
-    if (isLlamaDownloading) return
-    setIsLlamaDownloading(true)
-    setLlamaDownloadProgress(0)
-    try {
-      const modelUrl = "https://www.modelscope.cn/models/Qwen/Qwen3-4B-GGUF/resolve/master/Qwen3-4B-Q4_K_M.gguf"
-      // @ts-ignore
-      const modelsPath = await window.electronAPI.llama?.getModelsPath()
-      const modelName = "Qwen3-4B-Q4_K_M.gguf"
-      const fullPath = `${modelsPath}\\${modelName}`
-
-      // @ts-ignore
-      const result = await window.electronAPI.llama?.downloadModel(modelUrl, fullPath)
-      if (result?.success) {
-        showMessage('Qwen3 模型下载完成', true)
-        await checkLlamaModelStatus()
-      } else {
-        showMessage(`模型下载失败: ${result?.error || '未知错误'}`, false)
-      }
-    } catch (e: any) {
-      showMessage(`模型下载失败: ${e}`, false)
-    } finally {
-      setIsLlamaDownloading(false)
-    }
   }
 
   const handleAutoGetDbKey = async () => {
@@ -1452,7 +1384,7 @@ function SettingsPage() {
     <div className="tab-content">
       <div className="form-group">
         <label>模型管理</label>
-        <span className="form-hint">管理语音识别和 AI 对话模型</span>
+        <span className="form-hint">管理语音识别模型</span>
       </div>
 
       <div className="form-group">
@@ -1522,50 +1454,6 @@ function SettingsPage() {
         </div>
       </div>
 
-      <div className="form-group">
-        <label>AI 对话模型 (Llama)</label>
-        <span className="form-hint">用于 AI 助手对话功能</span>
-        <div className="setting-control vertical has-border">
-          <div className="model-status-card">
-            <div className="model-info">
-              <div className="model-name">Qwen3 4B (Preset) (~2.6GB)</div>
-              <div className="model-path">
-                {llamaModelStatus?.exists ? (
-                  <span className="status-indicator success"><Check size={14} /> 已安装</span>
-                ) : (
-                  <span className="status-indicator warning">未安装</span>
-                )}
-                {llamaModelStatus?.path && <div className="path-text" title={llamaModelStatus.path}>{llamaModelStatus.path}</div>}
-              </div>
-            </div>
-            <div className="model-actions">
-              {!llamaModelStatus?.exists && !isLlamaDownloading && (
-                <button
-                  className="btn-download"
-                  onClick={handleDownloadLlamaModel}
-                >
-                  <Download size={16} /> 下载模型
-                </button>
-              )}
-              {isLlamaDownloading && (
-                <div className="download-status">
-                  <div className="status-header">
-                    <span className="percent">{Math.floor(llamaDownloadProgress)}%</span>
-                    <span className="metrics">
-                      {formatBytes(llamaProgressData.downloaded)} / {formatBytes(llamaProgressData.total)}
-                      <span className="speed">({formatBytes(llamaProgressData.speed)}/s)</span>
-                    </span>
-                  </div>
-                  <div className="progress-bar-mini">
-                    <div className="fill" style={{ width: `${llamaDownloadProgress}%` }}></div>
-                  </div>
-                </div>
-              )}
-            </div>
-          </div>
-        </div>
-      </div>
-
       <div className="form-group">
         <label>自动转文字</label>
         <span className="form-hint">收到语音消息时自动转换为文字</span>

src/services/EngineService.ts

@@ -1,108 +0,0 @@
-
-export interface ModelInfo {
-    name: string;
-    path: string;
-    downloadUrl?: string; // If it's a known preset
-    size?: number;
-    downloaded: boolean;
-}
-
-export const PRESET_MODELS: ModelInfo[] = [
-    {
-        name: "Qwen3 4B (Preset)",
-        path: "Qwen3-4B-Q4_K_M.gguf",
-        downloadUrl: "https://www.modelscope.cn/models/Qwen/Qwen3-4B-GGUF/resolve/master/Qwen3-4B-Q4_K_M.gguf",
-        downloaded: false
-    }
-];
-
-class EngineService {
-    private onTokenCallback: ((token: string) => void) | null = null;
-    private onProgressCallback: ((percent: number) => void) | null = null;
-    private _removeTokenListener: (() => void) | null = null;
-    private _removeProgressListener: (() => void) | null = null;
-
-    constructor() {
-        // Initialize listeners
-        this._removeTokenListener = window.electronAPI.llama.onToken((token: string) => {
-            if (this.onTokenCallback) {
-                this.onTokenCallback(token);
-            }
-        });
-
-        this._removeProgressListener = window.electronAPI.llama.onDownloadProgress((percent: number) => {
-            if (this.onProgressCallback) {
-                this.onProgressCallback(percent);
-            }
-        });
-    }
-
-    public async checkModelExists(filename: string): Promise<boolean> {
-        const modelsPath = await window.electronAPI.llama.getModelsPath();
-        const fullPath = `${modelsPath}\\${filename}`; // Windows path separator
-        // We might need to handle path separator properly or let main process handle it
-        // Updated preload to take full path or handling in main?
-        // Let's rely on main process exposing join or just checking relative to models dir if implemented
-        // Actually main process `checkFileExists` takes a path.
-        // Let's assume we construct path here or Main helps. 
-        // Better: getModelsPath returns the directory.
-        return await window.electronAPI.llama.checkFileExists(fullPath);
-    }
-
-    public async getModelsPath(): Promise<string> {
-        return await window.electronAPI.llama.getModelsPath();
-    }
-
-    public async loadModel(filename: string) {
-        const modelsPath = await this.getModelsPath();
-        const fullPath = `${modelsPath}\\${filename}`;
-        console.log("Loading model:", fullPath);
-        return await window.electronAPI.llama.loadModel(fullPath);
-    }
-
-    public async createSession(systemPrompt?: string) {
-        return await window.electronAPI.llama.createSession(systemPrompt);
-    }
-
-    public async chat(message: string, onToken: (token: string) => void, options?: { thinking?: boolean }) {
-        this.onTokenCallback = onToken;
-        return await window.electronAPI.llama.chat(message, options);
-    }
-
-    public async downloadModel(url: string, filename: string, onProgress: (percent: number) => void) {
-        const modelsPath = await this.getModelsPath();
-        const fullPath = `${modelsPath}\\${filename}`;
-        this.onProgressCallback = onProgress;
-        return await window.electronAPI.llama.downloadModel(url, fullPath);
-    }
-
-    /**
-     * 清除当前的回调函数引用
-     * 用于避免内存泄漏
-     */
-    public clearCallbacks() {
-        this.onTokenCallback = null;
-        this.onProgressCallback = null;
-    }
-
-    /**
-     * 释放所有资源
-     * 包括事件监听器和回调引用
-     */
-    public dispose() {
-        // 清除回调
-        this.clearCallbacks();
-
-        // 移除事件监听器
-        if (this._removeTokenListener) {
-            this._removeTokenListener();
-            this._removeTokenListener = null;
-        }
-        if (this._removeProgressListener) {
-            this._removeProgressListener();
-            this._removeProgressListener = null;
-        }
-    }
-}
-
-export const engineService = new EngineService();

src/types/electron.d.ts

@@ -505,17 +505,6 @@ export interface ElectronAPI {
     selectExportDir: () => Promise<{ canceled: boolean; filePath?: string }>
     getSnsUsernames: () => Promise<{ success: boolean; usernames?: string[]; error?: string }>
   }
-  llama: {
-    loadModel: (modelPath: string) => Promise<boolean>
-    createSession: (systemPrompt?: string) => Promise<boolean>
-    chat: (message: string) => Promise<{ success: boolean; response?: any; error?: string }>
-    downloadModel: (url: string, savePath: string) => Promise<void>
-    getModelsPath: () => Promise<string>
-    checkFileExists: (filePath: string) => Promise<boolean>
-    getModelStatus: (modelPath: string) => Promise<{ exists: boolean; path?: string; size?: number; error?: string }>
-    onToken: (callback: (token: string) => void) => () => void
-    onDownloadProgress: (callback: (payload: { downloaded: number; total: number; speed: number }) => void) => () => void
-  }
   http: {
     start: (port?: number) => Promise<{ success: boolean; port?: number; error?: string }>
     stop: () => Promise<{ success: boolean }>