feat: v0.8.1 记忆深化 · 观测闭环 · 体验收口 — 窗口/输出上限全局单一配置 · 2478 用例全量回归 + E2E 冒烟
硬性契约：删除代码中一切写死的上下文窗口与最大输出上限（含六家模型元信息
钳制与全部兜底值）——唯一合法来源是设置面板「上下文长度」（llm.contextWindow）
与「最大输出上限」（llm.maxTokens），跨 Provider/模型原样透传。
P0 正确性收口：
- 迁移 11/12（SCHEMA_VERSION 5）：记忆表 embedding 列 + 分 Provider 窗口键清理
- 记忆生命周期接线：会话终态清理 working memory / episodic 90 天 TTL / access_count 回写
- 回放缓冲模块化 + 会话终态清理（杜绝 4MB/会话内存滞留）
- i18n 收口：主进程 main-locale（zh/en，ui.locale 热切换）+ 渲染层 17 处出层
P1 能力演进：
- 本地向量混合检索：0.6×向量余弦 + 0.4×TF-IDF，Ollama embeddings 首次投产，
存量记忆惰性回填，嵌入不可用自动回退 TF-IDF
- MEMORY.md 维护闭环：固化去重消除截断盲区；两阶段维护（AI 建议 → 用户确认 →
原子改写 + 语义记忆双轨同步 + 审计）；>50KB 告警
- 可观测闭环：cacheTokens 引擎→前端透传（Token 面板命中率/成本行）+ 输入框
上下文占用指示条
- MCP Prompts/Resources 对话可用：/mcp:{server}:{prompt} 与 @mcp:{server}:{uri}
P2 体验补全：
- 工具自定义策略（正则白/黑名单 + 频率 + 强制确认，热生效）
- 连续 ≥3 同类工具确认聚合为单弹框
- 会话消息游标分页（首屏 200 条向上翻页）
- 开机自启；Playwright + Electron E2E 冒烟（本地 mock LLM 零外联）
Review 回归修复：MCP 大小写失配 / 分页状态复位 / 清空=未配置语义（Number(null)=0
隐患）/ MEMORY.md 告警位置 / working_memories FK（迁移 13）/ 全局配置层废键清理；
附带根治权限加固启动时序、代理回环放行、safeStorage 降级、悬空 symlink 逃逸。
验证：typecheck/lint 0 问题；test:electron 2478/2478（0 跳过）；E2E 2/2；
docs/v0.8.1-迭代实施清单.md 全项留档。
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/**
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* MemoryMaintainer 测试（v0.8.1 P1-2 MEMORY.md 维护闭环）
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*
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* 锁定契约：
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* 1. parseMemoryEntries / buildMemoryEntriesDigest —— 分区条目摘要（纯条目行，
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* 消除 Consolidator 旧全文截断的去重盲区）
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* 2. apply 的精确匹配防线 —— LLM 建议的 entry 必须原样存在，防幻觉改写无关内容
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* 3. delete/update 动作重写 MEMORY.md + 同步 semantic_memories 双轨一致
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*/
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import { describe, it, expect, vi } from 'vitest';
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vi.mock('electron-log', () => ({
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default: { info: vi.fn(), warn: vi.fn(), error: vi.fn(), debug: vi.fn() },
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}));
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import { MemoryMaintainer, parseMemoryEntries, buildMemoryEntriesDigest } from '../maintainer';
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import type { MemoryMaintenanceAction } from '../maintainer';
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const SAMPLE = `# MEMORY.md — AI 持久记忆
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> 最后更新: 2026-09-07
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## 用户偏好
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- [沟通风格] 用户喜欢简洁的回答
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- [工具偏好] 项目使用 pnpm
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## 项目上下文
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- [Metona] 技术栈: Electron + React
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## 待办事项
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- [done] 旧待办已完成
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`;
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describe('parseMemoryEntries / buildMemoryEntriesDigest（v0.8.1 P1-2）', () => {
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it('解析分区与条目（跳过元数据头）', () => {
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const sections = parseMemoryEntries(SAMPLE);
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expect(sections).toHaveLength(3);
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expect(sections[0].section).toBe('用户偏好');
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expect(sections[0].entries).toEqual([
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'[沟通风格] 用户喜欢简洁的回答',
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'[工具偏好] 项目使用 pnpm',
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]);
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});
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it('digest 为纯条目行形态且条目全文可见（无 3000 字符截断盲区）', () => {
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const digest = buildMemoryEntriesDigest(parseMemoryEntries(SAMPLE));
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expect(digest).toContain('## 用户偏好');
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expect(digest).toContain('- [沟通风格] 用户喜欢简洁的回答');
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// 旧全文形态的头部元数据不进入 digest
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expect(digest).not.toContain('最后更新');
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// 超过旧 3000 字符预算的记忆尾部条目同样完整进入 digest
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const manyEntries = Array.from({ length: 200 }, (_, i) => `- 条目 ${i} ${'x'.repeat(20)}`);
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const bigMemory = `## 项目上下文\n${manyEntries.join('\n')}`;
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const bigDigest = buildMemoryEntriesDigest(parseMemoryEntries(bigMemory));
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expect(bigDigest).toContain('条目 199');
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});
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});
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describe('MemoryMaintainer.apply — 精确匹配与双轨同步', () => {
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function makeMaintainer(memory: string): {
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maintainer: MemoryMaintainer;
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getMemory: () => string;
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db: { prepare(sql: string): { run(...args: unknown[]): { changes: number } } };
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} {
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let current = memory;
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const semanticRows: Array<{ content: string }> = [{ content: '[沟通风格] 用户喜欢简洁的回答' }];
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const db = {
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prepare: (sql: string) => ({
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run: (...args: unknown[]) => {
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if (sql.startsWith('DELETE')) {
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const before = semanticRows.length;
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const target = semanticRows.find((r) => r.content === args[0]);
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if (target) semanticRows.splice(semanticRows.indexOf(target), 1);
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return { changes: before - semanticRows.length };
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}
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if (sql.startsWith('UPDATE')) {
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const row = semanticRows.find((r) => r.content === args[2]);
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if (row) {
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row.content = args[0] as string;
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return { changes: 1 };
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}
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return { changes: 0 };
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}
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return { changes: 0 };
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},
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}),
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};
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const maintainer = new MemoryMaintainer(
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() => {
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throw new Error('not used in apply');
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},
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{
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getFiles: () => ({ soul: '', memory: current }),
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rewriteMemory: (content: string) => {
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current = content;
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},
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} as never,
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() => db as never,
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);
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return { maintainer, getMemory: () => current, db };
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}
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it('delete 精确命中 → 行被移除；未命中条目被跳过（防幻觉改写）', () => {
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const { maintainer, getMemory } = makeMaintainer(SAMPLE);
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const actions: MemoryMaintenanceAction[] = [
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{ action: 'delete', section: '待办事项', entry: '[done] 旧待办已完成' },
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// 幻觉条目：文件中不存在 → 必须跳过
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{ action: 'delete', section: '用户偏好', entry: '不存在的条目' },
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];
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const result = maintainer.apply(actions);
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expect(result.applied).toBe(1);
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expect(result.skipped).toBe(1);
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const after = getMemory();
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expect(after).not.toContain('[done] 旧待办已完成');
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expect(after).toContain('用户喜欢简洁的回答');
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expect(after).toContain('## 待办事项'); // 分区头保留（空分区仍保留结构）
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});
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it('update（合并）→ 替换条目并同步 semantic_memories', () => {
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const { maintainer, getMemory, db } = makeMaintainer(SAMPLE);
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const actions: MemoryMaintenanceAction[] = [
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{
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action: 'update',
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section: '用户偏好',
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entry: '[沟通风格] 用户喜欢简洁的回答',
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newEntry: '[沟通风格] 用户喜欢简洁的回答，不需要过度解释',
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},
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];
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const result = maintainer.apply(actions);
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expect(result.applied).toBe(1);
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expect(getMemory()).toContain('不需要过度解释');
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const row = db
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.prepare('SELECT * FROM semantic_memories WHERE content = ?')
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.run('[沟通风格] 用户喜欢简洁的回答，不需要过度解释');
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expect(row).toBeDefined();
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});
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it('动作数上限 30（防 LLM 过度建议）', () => {
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const { maintainer } = makeMaintainer(SAMPLE);
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const actions: MemoryMaintenanceAction[] = Array.from({ length: 40 }, () => ({
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action: 'delete' as const,
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section: '待办事项',
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entry: '不存在的条目',
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}));
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const result = maintainer.apply(actions);
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expect(result.skipped).toBe(40);
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expect(result.applied).toBe(0);
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});
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});
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describe('MemoryMaintainer.analyze — sectionEntryCounts（v0.8.1 review O2）', () => {
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function makeAnalyzer(
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memory: string,
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llmReply: string,
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): {
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maintainer: MemoryMaintainer;
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} {
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const adapter = {
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send: vi.fn().mockResolvedValue({ content: llmReply }),
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} as never;
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return {
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maintainer: new MemoryMaintainer(
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() => adapter,
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{
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getFiles: () => ({ soul: '', memory }),
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rewriteMemory: () => {},
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} as never,
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(() => ({})) as never,
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),
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};
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}
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it('proposal 携带各分区条目数（空分区提示的数据源）', async () => {
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const { maintainer } = makeAnalyzer(
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SAMPLE,
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'[{"action":"delete","section":"待办事项","entry":"[done] 旧待办已完成","reason":"已完成"}]',
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);
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const proposal = await maintainer.analyze();
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expect(proposal.sectionEntryCounts['待办事项']).toBe(1);
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expect(proposal.sectionEntryCounts['用户偏好']).toBe(2);
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});
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});
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