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feat: v0.14.0 — AI 处理器架构重构、仪表盘可视化增强与 CI/CD 流水线
AI 处理器架构重构（Electron）： - 新增 6 个独立 AI Handler（anchorPoint/optimizeCard/predict/rescue/socratic/visionExtract） - 新增 ipc/ 模块，IPC 通信解耦 - ai/index.ts 统一调度重构 仪表盘可视化增强： - 新增 KnowledgePreviewCard 知识预览卡片 - 新增 LearningPulse 学习脉搏动效 - 新增 ParticleBackground 粒子背景 - 新增 dashboard/styles/ 样式目录 - DashboardPage / EfficiencyChart / TrendChart 优化 3D 与动效系统： - 新增 lib/3d/ 3D 渲染工具 - 新增 springConfig.ts 弹簧动画配置 - 新增 performance.css 性能优化样式 - 新增 scheduler.ts 任务调度器 笔记与灵感模块： - 新增 classroomNoteStore.ts 课堂笔记存储 - 新增 overlay/ 浮层组件目录 - CaptureSidebar / NoteEditPage / InspirationPage 优化 费曼与闪卡模块： - SocraticDialogue / StepIndicator / FeynmanPage 交互增强 - FlipCard / ConfidenceSelector / StudySessionPage 优化 - useFeynmanStore / useStudySessionStore 状态管理改进 AI 系统与基础设施： - RemoteAIPlugin / errorMessages / sessionAnalyzer / useAIFallback 增强 - crypto 模块重构（backupCrypto/encryption/utils） - AI 网关 config.py / providers / vision chain 更新 CI/CD 与部署： - 新增 .github/workflows/（deploy-server/pr-check/release） - 新增 server/.env.example 环境变量模板 - 新增 server/.gitignore 全局优化： - AppLayout / Sidebar / CustomTitlebar / PageTransition 布局增强 - index.css / tokens.css / tailwind.config 样式体系升级 - vite.config / tsconfig / package.json 构建配置更新 - README 更新至 v0.14.0
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‎.github/workflows/deploy-server.yml‎

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name: Deploy AI Gateway
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on:
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push:
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branches: [main]
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paths: ['server/**']
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jobs:
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deploy:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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- name: Build and push Docker image
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run: |
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cd server
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docker build -t ai-gateway:${{ github.sha }} .
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- name: Deploy to server
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uses: appleboy/ssh-action@v1
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with:
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host: ${{ secrets.SERVER_HOST }}
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username: ${{ secrets.SERVER_USER }}
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key: ${{ secrets.SSH_PRIVATE_KEY }}
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script: |
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cd /opt/keban
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docker-compose pull
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docker-compose up -d --force-recreate
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sleep 10
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curl -f http://localhost:8000/health || (docker-compose rollback && exit 1)

‎.github/workflows/pr-check.yml‎

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name: PR Quality Check
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on:
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pull_request:
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branches: [main]
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jobs:
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quality:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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- uses: actions/setup-node@v4
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with:
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node-version: 20
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cache: 'npm'
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cache-dependency-path: client/package-lock.json
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- run: cd client && npm ci
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- run: cd client && npm run lint
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- run: cd client && npx tsc --noEmit
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- run: cd client && npm run test -- --run
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- run: cd client && npm run build

‎.github/workflows/release.yml‎

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name: Release Electron App
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on:
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push:
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branches: [main]
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paths: ['client/**']
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jobs:
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lint-test:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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- uses: actions/setup-node@v4
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with:
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node-version: 20
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cache: 'npm'
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cache-dependency-path: client/package-lock.json
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- run: cd client && npm ci
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- run: cd client && npm run lint
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- run: cd client && npm run test -- --run
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build:
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needs: lint-test
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strategy:
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matrix:
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os: [windows-latest, macos-latest]
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runs-on: ${{ matrix.os }}
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steps:
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- uses: actions/checkout@v4
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- uses: actions/setup-node@v4
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with:
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node-version: 20
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cache: 'npm'
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cache-dependency-path: client/package-lock.json
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- run: cd client && npm ci
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- run: cd client && npm run electron:build
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- uses: actions/upload-artifact@v4
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with:
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name: release-${{ matrix.os }}
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path: client/release/*.{exe,dmg,AppImage}
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release:
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needs: build
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runs-on: ubuntu-latest
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if: startsWith(github.ref, 'refs/tags/v')
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steps:
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- uses: actions/download-artifact@v4
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with:
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pattern: release-*
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- uses: softprops/action-gh-release@v2
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with:
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files: release-*/*

‎README.md‎

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<p align="center"><strong>你的 AI 智能学习伙伴 — 让每一分钟学习都高效有价值</strong></p>
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<p align="center">
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<img src="https://img.shields.io/badge/status-beta-green.svg" alt="Status" />
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<img src="https://img.shields.io/badge/version-v0.13.1-blue.svg" alt="Version" />
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<img src="https://img.shields.io/badge/version-v0.14.0-blue.svg" alt="Version" />
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<img src="https://img.shields.io/badge/license-Apache--2.0-blue.svg" alt="License" />
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</p>
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</p>

‎client/electron/ai/handlers/anchorPointHandler.ts‎

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/**
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* AI 记忆锚点生成功能 Handler
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*
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* 处理 ai_anchor_point IPC 请求，调用 AI 网关从笔记内容生成记忆锚点。
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*/
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import { safeHandle } from '../../ipcUtils.js';
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import { logger } from '../../logger.js';
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import { postJson, gatewayUrl, type AIFeatureDef } from '../utils.js';
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// ================================================================
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// IPC Handler
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// ================================================================
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/**
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* ai_anchor_point — POST /api/v1/ai/anchor-point
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*/
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function register(): void {
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safeHandle(
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'ai_anchor_point',
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async (
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_event,
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args: {
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content: string;
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title?: string;
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authToken?: string;
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userApiKey?: string;
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},
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) => {
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const startMs = Date.now();
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logger.info(`[AI] [anchor-point] IPC received: content_length=${args.content.length}, title=${args.title ?? '(empty)'}, hasAuth=${!!args.authToken}`);
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logger.debug(`[AI] [anchor-point] Content preview: ${args.content.slice(0, 80)}...`);
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const reqBody = {
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content: args.content,
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title: args.title ?? '',
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};
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logger.info(`[AI] [anchor-point] Target: ${gatewayUrl()}/api/v1/ai/anchor-point`);
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interface AnchorPointResp {
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concept: string;
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association: string;
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memory_technique: string;
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importance: number;
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}
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interface AnchorPointGenResp {
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anchor_points: AnchorPointResp[];
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status: string;
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model: string;
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tokens_used: number;
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latency_ms: number;
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}
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try {
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const { data: resp, requestId } = await postJson<typeof reqBody, AnchorPointGenResp>(
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'/api/v1/ai/anchor-point',
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reqBody,
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args.authToken,
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args.userApiKey,
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60000,
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);
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const elapsed = Date.now() - startMs;
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logger.info(`[AI] [anchor-point] ✔ Success: anchor_points=${resp.anchor_points.length}, status=${resp.status}, model=${resp.model}, tokens=${resp.tokens_used}, total=${elapsed}ms, reqId=${requestId ?? 'N/A'}`);
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return {
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anchorPoints: resp.anchor_points.map((ap) => ({
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concept: ap.concept,
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association: ap.association,
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memoryTechnique: ap.memory_technique,
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importance: ap.importance,
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})),
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status: resp.status,
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model: resp.model,
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tokensUsed: resp.tokens_used,
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latencyMs: resp.latency_ms,
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requestId,
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};
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} catch (err) {
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const elapsed = Date.now() - startMs;
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const error = err instanceof Error ? err : new Error(String(err));
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logger.error(`[AI] [anchor-point] ✖ Failed after ${elapsed}ms: ${error.message}`);
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if (error.cause) logger.error(`[AI] [anchor-point] Error cause: ${error.cause}`);
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throw error;
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}
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},
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);
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}
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// ================================================================
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// 功能定义导出
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// ================================================================
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export const feature: AIFeatureDef = {
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id: 'ai_anchor_point',
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name: 'AI 记忆锚点',
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version: '1.0.0',
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register,
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};

‎client/electron/ai/handlers/optimizeCardHandler.ts‎

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/**
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* AI 闪卡优化功能 Handler
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*
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* 处理 ai_optimize_card IPC 请求，调用 AI 网关优化已有闪卡的正反面内容。
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*/
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import { safeHandle } from '../../ipcUtils.js';
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import { logger } from '../../logger.js';
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import { postJson, gatewayUrl, type AIFeatureDef } from '../utils.js';
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// ================================================================
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// IPC Handler
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// ================================================================
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/**
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* ai_optimize_card — POST /api/v1/ai/optimize-card
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*/
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function register(): void {
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safeHandle(
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'ai_optimize_card',
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async (
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_event,
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args: {
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front: string;
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back: string;
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authToken?: string;
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userApiKey?: string;
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},
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) => {
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const startMs = Date.now();
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logger.info(`[AI] [optimize-card] IPC received: front_length=${args.front.length}, back_length=${args.back.length}, hasAuth=${!!args.authToken}`);
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logger.debug(`[AI] [optimize-card] Front preview: ${args.front.slice(0, 60)}, Back preview: ${args.back.slice(0, 60)}`);
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const reqBody = {
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front: args.front,
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back: args.back,
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};
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logger.info(`[AI] [optimize-card] Target: ${gatewayUrl()}/api/v1/ai/optimize-card`);
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interface OptimizeCardResp {
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suggested_front: string;
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suggested_back: string;
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improvements: string[];
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model: string;
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tokens_used: number;
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latency_ms: number;
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}
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try {
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const { data: resp, requestId } = await postJson<typeof reqBody, OptimizeCardResp>(
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'/api/v1/ai/optimize-card',
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reqBody,
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args.authToken,
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args.userApiKey,
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60000,
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);
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const elapsed = Date.now() - startMs;
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logger.info(`[AI] [optimize-card] ✔ Success: improvements=${resp.improvements.length}, model=${resp.model}, tokens=${resp.tokens_used}, total=${elapsed}ms, reqId=${requestId ?? 'N/A'}`);
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return {
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suggestedFront: resp.suggested_front,
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suggestedBack: resp.suggested_back,
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improvements: resp.improvements,
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model: resp.model,
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tokensUsed: resp.tokens_used,
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latencyMs: resp.latency_ms,
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requestId,
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};
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} catch (err) {
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const elapsed = Date.now() - startMs;
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const error = err instanceof Error ? err : new Error(String(err));
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logger.error(`[AI] [optimize-card] ✖ Failed after ${elapsed}ms: ${error.message}`);
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if (error.cause) logger.error(`[AI] [optimize-card] Error cause: ${error.cause}`);
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throw error;
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}
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},
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);
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}
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// ================================================================
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// 功能定义导出
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// ================================================================
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export const feature: AIFeatureDef = {
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id: 'ai_optimize_card',
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name: 'AI 闪卡优化',
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version: '1.0.0',
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register,
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};

‎client/electron/ai/handlers/predictHandler.ts‎

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/**
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* AI 学习预测功能 Handler
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*
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* 处理 ai_predict IPC 请求，调用 AI 网关基于笔记内容生成预测性问题。
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*/
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import { safeHandle } from '../../ipcUtils.js';
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import { logger } from '../../logger.js';
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import { postJson, gatewayUrl, type AIFeatureDef } from '../utils.js';
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// ================================================================
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// IPC Handler
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// ================================================================
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/**
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* ai_predict — POST /api/v1/ai/predict
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*/
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function register(): void {
19+
safeHandle(
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'ai_predict',
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async (
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_event,
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args: {
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content: string;
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authToken?: string;
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userApiKey?: string;
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},
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) => {
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const startMs = Date.now();
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logger.info(`[AI] [predict] IPC received: content_length=${args.content.length}, hasAuth=${!!args.authToken}`);
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logger.debug(`[AI] [predict] Content preview: ${args.content.slice(0, 80)}...`);
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const reqBody = { content: args.content };
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logger.info(`[AI] [predict] Target: ${gatewayUrl()}/api/v1/ai/predict`);
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interface PredictionResp {
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question: string;
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type: string;
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reason: string;
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curiosity_score: number;
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}
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interface PredictGenResp {
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predictions: PredictionResp[];
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status: string;
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model: string;
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tokens_used: number;
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latency_ms: number;
49+
}
50+
51+
try {
52+
const { data: resp, requestId } = await postJson<typeof reqBody, PredictGenResp>(
53+
'/api/v1/ai/predict',
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reqBody,
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args.authToken,
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args.userApiKey,
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60000,
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);
59+
60+
const elapsed = Date.now() - startMs;
61+
logger.info(`[AI] [predict] ✔ Success: predictions=${resp.predictions.length}, status=${resp.status}, model=${resp.model}, tokens=${resp.tokens_used}, total=${elapsed}ms, reqId=${requestId ?? 'N/A'}`);
62+
return {
63+
predictions: resp.predictions.map((p) => ({
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question: p.question,
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type: p.type,
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reason: p.reason,
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curiosityScore: p.curiosity_score,
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})),
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status: resp.status,
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model: resp.model,
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tokensUsed: resp.tokens_used,
72+
latencyMs: resp.latency_ms,
73+
requestId,
74+
};
75+
} catch (err) {
76+
const elapsed = Date.now() - startMs;
77+
const error = err instanceof Error ? err : new Error(String(err));
78+
logger.error(`[AI] [predict] ✖ Failed after ${elapsed}ms: ${error.message}`);
79+
if (error.cause) logger.error(`[AI] [predict] Error cause: ${error.cause}`);
80+
throw error;
81+
}
82+
},
83+
);
84+
}
85+
86+
// ================================================================
87+
// 功能定义导出
88+
// ================================================================
89+
90+
export const feature: AIFeatureDef = {
91+
id: 'ai_predict',
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name: 'AI 学习预测',
93+
version: '1.0.0',
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register,
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};

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