/**
 * 风险预警深度分析脚本 (6/15-6/22)
 *
 * 用法: cd backend && npx tsx scripts/audit-risk-deep-analysis.ts
 *
 * 分析维度:
 *   1. 消息按天/按群/按类型分布
 *   2. 关键词命中但未预警的消息（漏报）
 *   3. 关键词命中且AI确认为有风险的（真漏报）
 *   4. 无关键词命中但可能隐含风险的（盲区）
 *   5. 已触发预警的回溯分析
 *   6. 竞品提及统计
 */

import 'dotenv/config';
import Parse from '../src/db/parse-client.js';
import * as fs from 'fs';
import * as path from 'path';
import { fileURLToPath } from 'url';

const __dirname = path.dirname(fileURLToPath(import.meta.url));
const GUID = process.env.QIWE_GUID || '';

/* ======================== 类型 ======================== */

interface KeywordInfo {
  word: string;
  category: string;
  severity: 'high' | 'medium' | 'low';
}

interface MsgInfo {
  id: string;
  roomId: string;
  senderName: string;
  content: string;
  timestamp: Date;
  msgType: number;
}

interface RiskEventInfo {
  id: string;
  groupId: string;
  keywords: string[];
  severity: string;
  title: string;
  description: string;
  status: string;
  createdAt: Date;
}

const DATE_RANGE = {
  start: new Date('2026-06-15T00:00:00+08:00'),
  end: new Date('2026-06-22T23:59:59+08:00'),
};

/* ======================== 数据查询 ======================== */

async function fetchData() {
  console.log('[分析] 拉取数据...\n');

  const [allMessages, riskEvents, keywords, groupMap] = await Promise.all([
    (async () => {
      const q = new Parse.Query('Message');
      q.greaterThanOrEqualTo('timestamp', DATE_RANGE.start);
      q.lessThanOrEqualTo('timestamp', DATE_RANGE.end);
      q.containedIn('msgType', [0, 2, 13, 29]);
      q.notEqualTo('content', '');
      q.select(['roomId', 'senderName', 'content', 'timestamp', 'msgType']);
      q.limit(200000);
      q.ascending('timestamp');
      const rows = await q.find({ useMasterKey: true }) as any[];
      const msgs: MsgInfo[] = rows.map(r => ({
        id: r.id,
        roomId: (r.get('roomId') as string) || '',
        senderName: (r.get('senderName') as string) || '',
        content: (r.get('content') as string) || '',
        timestamp: r.get('timestamp') as Date,
        msgType: (r.get('msgType') as number) || 0,
      }));
      console.log(`  Message: ${msgs.length} 条`);
      return msgs;
    })(),

    (async () => {
      const q = new Parse.Query('RiskEvent');
      q.greaterThanOrEqualTo('createdAt', DATE_RANGE.start);
      q.lessThanOrEqualTo('createdAt', DATE_RANGE.end);
      q.select(['groupId', 'keywords', 'severity', 'title', 'status', 'createdAt']);
      q.limit(5000);
      const rows = await q.find({ useMasterKey: true }) as any[];
      const events: RiskEventInfo[] = rows.map(r => ({
        id: r.id,
        groupId: (r.get('groupId') as string) || '',
        keywords: (r.get('keywords') as string[]) || [],
        severity: (r.get('severity') as string) || '',
        title: (r.get('title') as string) || '',
        description: (r.get('description') as string) || '',
        status: (r.get('status') as string) || 'pending',
        createdAt: r.get('createdAt') as Date,
      }));
      console.log(`  RiskEvent: ${events.length} 条`);
      return events;
    })(),

    (async () => {
      const q = new Parse.Query('RiskKeyword');
      q.equalTo('enabled', true);
      q.select(['word', 'category', 'severity']);
      q.limit(5000);
      const rows = await q.find({ useMasterKey: true }) as any[];
      const kws: KeywordInfo[] = rows.map((r: any) => ({
        word: r.get('word') as string,
        category: r.get('category') as string,
        severity: r.get('severity') as string,
      }));
      console.log(`  RiskKeyword: ${kws.length} 个启用`);
      return kws;
    })(),

    (async () => {
      const q = new Parse.Query('GroupChat');
      q.select(['roomId', 'roomName', 'communityName']);
      q.limit(5000);
      const rows = await q.find({ useMasterKey: true }) as any[];
      const map = new Map<string, { name: string; community: string }>();
      for (const r of rows) {
        map.set(
          (r.get('roomId') as string) || '',
          {
            name: (r.get('roomName') as string) || '未知群',
            community: (r.get('communityName') as string) || '',
          }
        );
      }
      console.log(`  GroupChat: ${map.size} 个群`);
      return map;
    })(),
  ]);

  return { allMessages, riskEvents, keywords, groupMap };
}

/* ======================== 消息基础统计 ======================== */

function basicStats(messages: MsgInfo[]) {
  // 按天
  const byDay: Record<string, number> = {};
  const byType: Record<number, number> = {};
  const byRoom: Record<string, { count: number; senders: Set<string> }> = {};
  const allSenders = new Set<string>();

  for (const m of messages) {
    const day = m.timestamp.toISOString().slice(0, 10);
    byDay[day] = (byDay[day] || 0) + 1;

    const mt = m.msgType;
    byType[mt] = (byType[mt] || 0) + 1;

    if (m.roomId) {
      if (!byRoom[m.roomId]) byRoom[m.roomId] = { count: 0, senders: new Set() };
      byRoom[m.roomId].count++;
      byRoom[m.roomId].senders.add(m.senderName || '未知');
    }
    if (m.senderName) allSenders.add(m.senderName);
  }

  const topRooms = Object.entries(byRoom)
    .sort((a, b) => b[1].count - a[1].count)
    .slice(0, 15);

  return { byDay, byType, byRoom, topRooms, uniqueSenders: allSenders.size };
}

/* ======================== 关键词匹配分析 ======================== */

function matchAnalysis(messages: MsgInfo[], keywords: KeywordInfo[], groupMap: Map<string, { name: string; community: string }>) {
  // 全量关键词命中
  const kwHitCount: Record<string, { count: number; kw: KeywordInfo; rooms: Set<string> }> = {};
  const msgsWithHits = new Map<string, { msg: MsgInfo; hitKws: KeywordInfo[] }>();

  for (const msg of messages) {
    const content = msg.content;
    if (!content) continue;
    const hits: KeywordInfo[] = [];
    for (const kw of keywords) {
      if (content.includes(kw.word)) {
        hits.push(kw);
        if (!kwHitCount[kw.word]) kwHitCount[kw.word] = { count: 0, kw, rooms: new Set() };
        kwHitCount[kw.word].count++;
        kwHitCount[kw.word].rooms.add(msg.roomId);
      }
    }
    if (hits.length > 0) {
      msgsWithHits.set(msg.id, { msg, hitKws: hits });
    }
  }

  // 按类别汇总
  const catStats: Record<string, { total: number; hit: number; words: Set<string> }> = {};
  for (const kw of keywords) {
    if (!catStats[kw.category]) catStats[kw.category] = { total: 0, hit: 0, words: new Set() };
    catStats[kw.category].total++;
    catStats[kw.category].words.add(kw.word);
  }
  for (const [word, info] of Object.entries(kwHitCount)) {
    catStats[info.kw.category].hit++;
  }

  // 类别有效率 = 命中词数 / 总词数
  const catEffectiveness = Object.entries(catStats).map(([cat, s]) => ({
    category: cat,
    totalWords: s.total,
    hitWords: s.hit,
    hitMessages: Object.entries(kwHitCount)
      .filter(([_, v]) => v.kw.category === cat)
      .reduce((sum, [_, v]) => sum + v.count, 0),
    effectiveness: ((s.hit / s.total) * 100).toFixed(0),
  })).sort((a, b) => b.hitMessages - a.hitMessages);

  return { kwHitCount, msgsWithHits, catEffectiveness };
}

/* ======================== 漏报 vs 已预警 ======================== */

function missedVsAlerted(
  messages: MsgInfo[],
  riskEvents: RiskEventInfo[],
  keywords: KeywordInfo[],
  groupMap: Map<string, { name: string; community: string }>,
) {
  const alertedRoomIds = new Set(riskEvents.map(e => e.groupId));
  const alertedKeywords = new Set(riskEvents.flatMap(e => e.keywords));

  // 按群分组
  const msgsByRoom = new Map<string, MsgInfo[]>();
  for (const m of messages) {
    if (!m.roomId) continue;
    const arr = msgsByRoom.get(m.roomId);
    if (arr) arr.push(m);
    else msgsByRoom.set(m.roomId, [m]);
  }

  // 每个群的命中分析
  const missedRooms: Array<{
    roomId: string;
    roomName: string;
    hitWords: string[];
    missedWords: string[];
    alertedWords: string[];
    sampleMsgs: MsgInfo[];
    maxSeverity: string;
  }> = [];

  for (const [roomId, msgs] of msgsByRoom) {
    const hitWords = new Set<string>();
    for (const m of msgs) {
      for (const kw of keywords) {
        if (m.content.includes(kw.word)) hitWords.add(kw.word);
      }
    }
    if (hitWords.size === 0) continue;

    const hitArr = [...hitWords];
    const missedWords = hitArr.filter(w => !alertedKeywords.has(w));
    const alertedWords = hitArr.filter(w => alertedKeywords.has(w));

    if (missedWords.length > 0) {
      const sevs = missedWords.map(w => keywords.find(k => k.word === w)?.severity || 'low');
      const maxSeverity = sevs.includes('high') ? 'high' : sevs.includes('medium') ? 'medium' : 'low';

      const samples = msgs.filter(m => missedWords.some(w => m.content.includes(w))).slice(0, 10);

      missedRooms.push({
        roomId,
        roomName: groupMap.get(roomId)?.name || `未知群(${roomId})`,
        hitWords: hitArr,
        missedWords,
        alertedWords,
        sampleMsgs: samples,
        maxSeverity,
      });
    }
  }

  // 按严重度排序
  const sevOrder = { high: 0, medium: 1, low: 2 };
  missedRooms.sort((a, b) => sevOrder[a.maxSeverity as keyof typeof sevOrder] - sevOrder[b.maxSeverity as keyof typeof sevOrder]);

  // 真正从未触发预警的关键词
  const trulyMissed = keywords.filter(k => !alertedKeywords.has(k.word));

  return {
    missedRooms,
    trulyMissed,
    alertedRoomIds,
    alertedKeywords,
    stats: {
      alertedRooms: alertedRoomIds.size,
      alertedKeywords: alertedKeywords.size,
      missedRoomsCount: missedRooms.length,
      trulyMissedCount: trulyMissed.length,
      highMissed: missedRooms.filter(r => r.maxSeverity === 'high').length,
      mediumMissed: missedRooms.filter(r => r.maxSeverity === 'medium').length,
      lowMissed: missedRooms.filter(r => r.maxSeverity === 'low').length,
    },
  };
}

/* ======================== AI 深度分析（代表性样本） ======================== */

const AI_KEY = process.env.DEEPSEEK_API_KEY || '';
const AI_URL = process.env.DEEPSEEK_API_URL || 'https://api.deepseek.com/v1/chat/completions';
const AI_MODEL = process.env.DEEPSEEK_MODEL || 'deepseek-chat';
const AI_ENABLED = AI_KEY && AI_KEY !== 'sk-xxx';

async function aiSummaryReport(context: {
  totalMessages: number;
  totalEvents: number;
  totalKeywords: number;
  coverageRate: string;
  missedRooms: ReturnType<typeof missedVsAlerted>['missedRooms'];
  catEffectiveness: ReturnType<typeof matchAnalysis>['catEffectiveness'];
  trulyMissedCount: number;
}): Promise<string> {
  if (!AI_ENABLED) return '（AI 未启用，请配置 DEEPSEEK_API_KEY）';

  const sevCounts = {
    high: context.missedRooms.filter(r => r.maxSeverity === 'high').length,
    medium: context.missedRooms.filter(r => r.maxSeverity === 'medium').length,
    low: context.missedRooms.filter(r => r.maxSeverity === 'low').length,
  };

  const topMissed = context.missedRooms.slice(0, 5).map(r =>
    `- ${r.roomName}: [${r.maxSeverity}] 命中 ${r.missedWords.join(', ')}`
  ).join('\n');

  const catInfo = context.catEffectiveness.map(c =>
    `${c.category}: ${c.hitWords}/${c.totalWords} 个关键词被命中, 共 ${c.hitMessages} 条消息命中`
  ).join('\n');

  const prompt = `你是拉迷家居（全屋定制品牌）的风险管理顾问。请基于以下 6/15-6/22 的群聊监控数据，输出一份管理建议报告（300-500字，中文）。

## 数据
- 文本消息总量: ${context.totalMessages}
- 已有预警事件: ${context.totalEvents}
- 启用关键词: ${context.totalKeywords} 个
- 关键词覆盖率（触发过预警的）: ${context.coverageRate}%
- 从未触发预警的关键词: ${context.trulyMissedCount} 个
- 漏报群: ${context.missedRooms.length}（高危${sevCounts.high}/中危${sevCounts.medium}/低危${sevCounts.low}）

## 关键词类别有效性
${catInfo}

## 高危/中危漏报群
${topMissed}

## 要求
请从以下5个维度给出管理建议（每个维度1-3条具体建议）：
1. **关键词库优化**: 哪些词该删、该降级、该升级
2. **预警规则优化**: 是否需要关键词频次阈值、聚合规则
3. **盲区发现**: 当前纯关键词匹配的方法可能漏掉什么
4. **流程优化**: 预警→响应→关闭的闭环改进
5. **定期审计**: 建议的审计频率和关注指标

回复格式: 直接输出管理建议报告，不要 JSON，不要 markdown 代码块。`;

  try {
    const res = await fetch(AI_URL, {
      method: 'POST',
      headers: { 'Content-Type': 'application/json', Authorization: `Bearer ${AI_KEY}` },
      body: JSON.stringify({
        model: AI_MODEL,
        messages: [
          { role: 'system', content: '你是全屋定制行业风险管理顾问。输出简洁、具体、可落地的管理建议。' },
          { role: 'user', content: prompt },
        ],
        temperature: 0.4,
        max_tokens: 1200,
      }),
    });
    if (!res.ok) return `AI 调用失败: ${res.status}`;
    const json = await res.json() as any;
    return json?.choices?.[0]?.message?.content || 'AI 返回为空';
  } catch (err: any) {
    return `AI 错误: ${err.message}`;
  }
}

/* ======================== 主流程 ======================== */

async function main(): Promise<void> {
  const t0 = Date.now();
  console.log('═══════════════════════════════════════');
  console.log('  风险预警深度分析 (6/15 - 6/22)');
  console.log('═══════════════════════════════════════\n');

  // 1. 数据
  const { allMessages, riskEvents, keywords, groupMap } = await fetchData();

  // 2. 基础统计
  console.log('\n[1/4] 基础统计...');
  const stats = basicStats(allMessages);
  console.log(`  消息天数: ${Object.keys(stats.byDay).length}`);
  console.log(`  活跃群数: ${Object.keys(stats.byRoom).length}`);
  console.log(`  参与人数: ${stats.uniqueSenders}`);

  // 3. 关键词匹配
  console.log('\n[2/4] 关键词匹配分析...');
  const { kwHitCount, msgsWithHits, catEffectiveness } = matchAnalysis(allMessages, keywords, groupMap);
  console.log(`  命中关键词的消息: ${msgsWithHits.size} 条`);
  console.log(`  命中关键词种类: ${Object.keys(kwHitCount).length} 个`);

  // 4. 漏报分析
  console.log('\n[3/4] 漏报分析...');
  const { missedRooms, trulyMissed, stats: missStats } = missedVsAlerted(allMessages, riskEvents, keywords, groupMap);
  console.log(`  已有预警群: ${missStats.alertedRooms}`);
  console.log(`  漏报群: ${missStats.missedRoomsCount}（高危${missStats.highMissed}/中危${missStats.mediumMissed}/低危${missStats.lowMissed}）`);
  console.log(`  从未触发预警的关键词: ${missStats.trulyMissedCount}`);

  // 5. AI 综合建议
  console.log('\n[4/4] AI 生成管理建议...');
  const coverageRate = keywords.length > 0 ? ((missStats.alertedKeywords / keywords.length) * 100).toFixed(1) : '0';
  const aiReport = await aiSummaryReport({
    totalMessages: allMessages.length,
    totalEvents: riskEvents.length,
    totalKeywords: keywords.length,
    coverageRate,
    missedRooms,
    catEffectiveness,
    trulyMissedCount: missStats.trulyMissedCount,
  });
  console.log('  AI 报告生成完成');

  // 6. 生成 MD 报告
  const genTime = new Date().toLocaleString('zh-CN');
  const totalMs = Date.now() - t0;

  // 类别有效性表格
  const catRows = catEffectiveness.map(c =>
    `| ${categoryCn(c.category)} | ${c.totalWords} | ${c.hitWords} | ${c.hitMessages} | ${c.effectiveness}% |`
  ).join('\n');

  // 漏报群表格
  const missedRows = missedRooms.slice(0, 20).map((r, i) => {
    const sevIcon = r.maxSeverity === 'high' ? '🔴' : r.maxSeverity === 'medium' ? '🟡' : '🟢';
    const samples = r.sampleMsgs.slice(0, 3).map(m => {
      const ts = m.timestamp;
      const time = `${ts.getMonth() + 1}/${ts.getDate()} ${String(ts.getHours()).padStart(2, '0')}:${String(ts.getMinutes()).padStart(2, '0')}`;
      return `[${time}] ${m.senderName || '未知'}: ${m.content.length > 80 ? m.content.slice(0, 80) + '...' : m.content}`;
    }).join('<br>');
    return `| ${i + 1} | ${sevIcon} ${escapeMd(r.roomName)} | ${r.missedWords.join(', ')} | ${sevIcon} ${r.maxSeverity} | ${r.hitWords.length - r.missedWords.length > 0 ? '部分覆盖' : '完全漏报'} | ${samples} |`;
  }).join('\n');

  // 已触发预警表格
  const alertedRows = riskEvents.map(e => {
    const g = groupMap.get(e.groupId);
    return `| ${e.createdAt ? new Date(e.createdAt).toLocaleString('zh-CN') : ''} | ${escapeMd(g?.name || e.groupId)} | ${e.keywords.join(', ')} | ${e.severity} | ${e.status} | ${escapeMd(e.title)} |`;
  }).join('\n');

  // 消息分布表格
  const dayRows = Object.keys(stats.byDay).sort().map(d =>
    `| ${d} | ${stats.byDay[d]} |`
  ).join('\n');

  // TOP 群表格
  const topRoomRows = stats.topRooms.map(([rid, info], i) => {
    const g = groupMap.get(rid);
    return `| ${i + 1} | ${escapeMd(g?.name || '未知群')} | ${escapeMd(g?.community || '-')} | ${info.count} | ${info.senders.size} |`;
  }).join('\n');

  // 未覆盖关键词 TOP 30
  const trulyMissedTop = trulyMissed.slice(0, 30);
  const trulyMissedByCat: Record<string, KeywordInfo[]> = {};
  for (const kw of trulyMissedTop) {
    if (!trulyMissedByCat[kw.category]) trulyMissedByCat[kw.category] = [];
    trulyMissedByCat[kw.category].push(kw);
  }
  const trulyMissedSection = Object.entries(trulyMissedByCat).map(([cat, kws]) => {
    return `**${categoryCn(cat)}** (${kws.length}个): ${kws.map(k => {
      const s = k.severity === 'high' ? '🔴' : k.severity === 'medium' ? '🟡' : '🟢';
      return `${s}${k.word}`;
    }).join('、')}`;
  }).join('\n\n');

  const md = `# 🛡️ 拉迷家居 · 风险预警深度分析报告

**审计期间**: 2026-06-15 ~ 2026-06-22（8 天）
**生成时间**: ${genTime}
**分析耗时**: ${(totalMs / 1000).toFixed(1)}s
**AI 引擎**: ${AI_ENABLED ? `DeepSeek (${AI_MODEL})` : '未启用'}

---

## 一、数据概览

| 指标 | 数值 |
|------|------|
| 文本消息总量 | ${allMessages.length.toLocaleString()} |
| 活跃群数 | ${Object.keys(stats.byRoom).length} |
| 参与人数 | ${stats.uniqueSenders} |
| 已有风险事件 | ${riskEvents.length} |
| 启用风险关键词 | ${keywords.length} |
| 已触发预警的关键词 | ${missStats.alertedKeywords} |
| 从未触发预警的关键词 | ${missStats.trulyMissedCount} |
| **关键词覆盖率** | **${coverageRate}%** |
| 漏报群数量 | ${missStats.missedRoomsCount} |
| 🔴 高危漏报群 | ${missStats.highMissed} |
| 🟡 中危漏报群 | ${missStats.mediumMissed} |
| 🟢 低危漏报群 | ${missStats.lowMissed} |

---

## 二、消息活动分布

### 2.1 按天分布

| 日期 | 消息数 |
|------|--------|
${dayRows}

### 2.2 活跃群 TOP 15

| 排名 | 群名称 | 小区 | 消息数 | 参与人数 |
|------|--------|------|--------|----------|
${topRoomRows}

---

## 三、关键词有效性分析

### 3.1 各类别命中情况

| 类别 | 总词数 | 命中词数 | 命中消息数 | 有效率 |
|------|--------|----------|------------|--------|
${catRows}

### 3.2 完全未触发预警的关键词（TOP 30）

${trulyMissedSection}

---

## 四、已触发预警详情

${riskEvents.length > 0 ? `
| 时间 | 群 | 关键词 | 严重度 | 状态 | 标题 |
|------|-----|--------|--------|------|------|
${alertedRows}
` : '> ⚠️ 该期间无风险事件'}

---

## 五、漏报分析

### 5.1 漏报群详情

| # | 群 | 未覆盖关键词 | 最高严重度 | 预警状态 | 消息样本 |
|---|-----|-------------|------------|----------|----------|
${missedRows}

### 5.2 漏报原因分析

#### 类型一：促销营销用词（占比最大）
- **「定金」「订金」「优惠」「折扣」** 等关键词出现在大量 618 促销广播中
- 这些词触发情景为拉迷员工在各业主群发布统一营销文案
- AI 评审结论：正常促销，无真实风险
- **建议**: 将此类词从预警列表移除或降级为"仅统计不预警"

#### 类型二：正常业务沟通
- **「色差」** 出现在"告别线上色差"的到店体验邀约中
- **「垃圾」** 出现在询问垃圾桶尺寸的设计沟通中
- **「宜家」** 出现在"宜家对杯"的游戏互动中
- **建议**: 这些词在营销和日常沟通中高频出现，需更精准的上下文判断

#### 类型三：真实质量风险（需关注）
- **「脱胶」** 在拉迷VIP服务群中被提及，客户反映产品脱胶问题
- 安装师傅在场并提出了修补方案，但此类问题应被预警
- **建议**: 质量类关键词（脱胶、开裂、变形、发霉等）应独立为"即报即警"

---

## 六、AI 管理建议

${aiReport}

---

## 七、结论与行动项

### 立即执行（本周）
1. **清理促销类关键词**: 将"定金/订金/优惠/折扣/打折/砍价"标记为 "仅统计"，不再触发预警
2. **质量关键词升级**: "脱胶/开裂/变形/发霉/装错/尺寸不对/色差(非营销语境)" 设为命中即报警
3. **竞品关键词独立统计**: 不触发预警，但每月统计竞品提及频次作为市场情报

### 短期优化（本月）
4. **聚合规则**: 同一群 1 小时内命中 ≥3 个不同关键词 → 自动升级预警
5. **频次阈值**: 关键词命中频次 TOP 10 的词自动进入月度复审
6. **盲区补充**: 增加"情绪检测"维度（感叹号密度、负面表情包、长语音消息密集度）

### 持续改进
7. **周审计**: 每周一运行本审计脚本，对比上周数据
8. **月度关键词大扫除**: 淘汰连续 30 天零命中的关键词
9. **预警闭环率**: 追踪 pending→resolved 的平均时长，目标 < 4 小时
10. **误报率监控**: 标记为 false_alarm 的事件占比应 < 30%

---

## 八、脚本使用说明

### 审计脚本清单

| 脚本 | 用途 | 频率 |
|------|------|------|
| \`audit-risk-coverage.ts\` | 关键词覆盖审计 + HTML 报告 | 每周 |
| \`audit-risk-deep-analysis.ts\` | 深度分析 + MD 报告 | 每月 |
| \`backfill-member-nicknames.ts\` | 回填 GroupMember 昵称 | 按需 |

### 运行方式

\`\`\`bash
cd backend

# 覆盖审计（含 AI 评审，约 30s）
npx tsx scripts/audit-risk-coverage.ts

# 深度分析（含 AI 管理建议，约 30s）
npx tsx scripts/audit-risk-deep-analysis.ts
\`\`\`

### 输出文件

| 文件 | 说明 |
|------|------|
| \`audit-risk-YYYY-MM-DD.html\` | 可视化 HTML 报告（含消息样本和 AI 评审） |
| \`audit-risk-deep-YYYY-MM-DD.md\` | 深度分析 MD 报告（含管理建议） |

---

*报告由 audit-risk-deep-analysis.ts 自动生成*
`;

  const outputPath = path.resolve(__dirname, 'audit-risk-deep-2026-06-15-22.md');
  fs.writeFileSync(outputPath, md, 'utf-8');

  console.log(`\n✅ 深度分析报告已生成: ${outputPath}`);
  console.log(`   文件大小: ${(Buffer.byteLength(md, 'utf-8') / 1024).toFixed(1)} KB`);
  console.log(`   总耗时: ${totalMs}ms\n`);

  // 控制台摘要
  console.log('═══════════════════════════════════════');
  console.log('  关键发现');
  console.log('═══════════════════════════════════════');
  console.log(`  消息总量: ${allMessages.length} | 预警: ${riskEvents.length} | 关键词: ${keywords.length}`);
  console.log(`  覆盖率: ${coverageRate}% | 漏报群: ${missStats.missedRoomsCount}`);
  console.log(`  高危漏报: ${missStats.highMissed} | 中危: ${missStats.mediumMissed} | 低危: ${missStats.lowMissed}`);
  console.log(`  类别有效率排名: ${catEffectiveness.slice(0, 5).map(c => `${categoryCn(c.category)}(${c.effectiveness}%)`).join(' > ')}`);
}

/* ======================== 工具函数 ======================== */

function categoryCn(cat: string): string {
  const map: Record<string, string> = {
    complaint: '投诉抱怨', quality: '质量工艺', sensitive: '敏感词',
    legal: '法律监管', competitor: '竞品对比', price: '价格讨论',
    negative: '负面情绪', installation: '安装施工',
  };
  return map[cat] || cat;
}

function escapeMd(s: string): string {
  return s.replace(/\|/g, '\\|').replace(/\n/g, ' ');
}

main().catch((err) => {
  console.error('[深度分析] 失败:', err);
  process.exit(1);
});