Merge feature/admin-console: 管理后台 + 用户端鉴权(登录/授权/数据隔离/日志)

feat(auth): 用户端鉴权(登录/授权清单/逐次校验/功能门禁 + owner 数据隔离)
feat(admin): 行为日志记录 hub_id(便于区分不同中枢)
2026-10-16 16:01:13 +08:00 · 2026-10-16 14:42:23 +08:00 · 2026-10-15 23:56:42 +08:00 · 2026-10-15 23:52:17 +08:00 · 2026-10-15 20:19:30 +08:00 · 2026-10-15 19:35:51 +08:00
227 changed files with 43864 additions and 142 deletions
@@ -1,4 +1,4 @@
-# 运行时产物与环境
+# 运行时产物与环境 
 node_modules
 dist/
 .venv/
@@ -36,3 +36,36 @@ tests/extension_cases_18/
 *.bak-*
 bioflow_service/bioflow.db
 *.before-*
+
+# paper_writer_service 运行时产物（不入库）
+paper_writer_service/paper.db
+paper_writer_service/paper.db-shm
+paper_writer_service/paper.db-wal
+paper_writer_service/paper.log
+
+# review_service 运行时产物（不入库）
+review_service/review.db
+review_service/review.db-wal
+review_service/review.db-shm
+review_service/review.log
+review_service/data/reformat_jobs/
+# 期刊种子 journals.json 是源码：顶层 **/data/ 会误伤 review_service/data/，显式放行
+!review_service/data/
+review_service/tools/tectonic
+review_service/data/tectonic-cache/
+review_service/data/format_cache/
+review_service/data/compile_jobs/
+review_service/data/compile_inspect/
+review_service/prewarm.log
+
+# 部署方案文档（含主机凭据，不入库）
+docs/DEPLOY_PAPER_176.md
+
+# 一次性诊断脚本（不入库）
+scripts/debug_compile.py
+
+# P5 e2e 临时产物（compile_jobs/ 与 prewarm.log 已在上方「review_service 运行时产物」段，此处不重复）
+
+# P5 ppt job 运行数据（大纲/pptx/真图/预览，不入库）
+review_service/data/ppt_jobs/
+review_service/data/review.db
@@ -0,0 +1,54 @@
+# AGENTS.md —— 协作约束（科研审稿模块）
+
+## 项目背景
+
+本项目（PlantAI-rag-new）是植物基因组学文献知识工作台，拥有自研 RAG 与知识库
+（Qdrant + Neo4j + vstore）。2026-10 起新增「科研投稿与智能审稿助手」功能
+（审稿周期/期刊分析/期刊推荐/投稿前自审/审稿意见辅助/格式检查）。
+
+## 审稿模块（review_service）约束 —— 必须遵守
+
+1. **所有审稿相关新代码只允许写在 `review_service/` 目录下新增**。
+   - 服务自身：FastAPI 独立进程，端口 8100（模式同 `paper_writer_service` 8097 / `bioflow_service` 8098）。
+   - 环境变量前缀统一 `REVIEW_`；LLM 凭据复用 `DOCGEN_LLM_*` 裸键（回退链见 `review_service/app/services/llm.py`）。
+2. **BFF（`sdk/`）层只允许条件注册代理路由**：
+   - 允许的全部改动 = `sdk/app/config.py` 增加 `review_enabled` / `review_service_url` 等开关键
+     + `sdk/app/main.py` 按开关 `include_router(review_proxy.router)`
+     + 新文件 `sdk/app/routers/review_proxy.py`（反代实现）。
+   - **严禁**修改 sdk 下其他 router/service/db 的任何既有逻辑。
+3. **严禁修改现有 RAG 核心与既有服务代码**，包括但不限于：
+   - `agent/`（qa 8091 / methodology 8092 / legacy-rag 8093）
+   - `vstore/`（8094，审稿服务只经 HTTP 只读消费其 `/api/vstore/*` 接口）
+   - `paper_writer_service/`、`bioflow_service/`、`bioflow_kernel/`
+   - `ui/`（前端入口另行按 UI_SPEC 流程评审）
+   - `knowledge/`、`kb-libraries/`、`tooling/`（依赖锁另议）
+4. **依赖纪律**：审稿服务只使用统一 venv（`tooling/requirements.lock`）中已有的库
+   （fastapi / httpx / pydantic-settings 等）。如确需新增全局依赖，
+   须先更新 `tooling/requirements.lock` 并经人工确认。
+5. **上游对接只读**：PDF 解析走 vstore 8094（`POST /api/vstore/ingest` +
+   `GET/DELETE /api/vstore/documents/{id}`）；LLM 走 DeepSeek OpenAI 兼容接口；
+   后续期刊数据/期刊推荐等子功能同样以新 service + 新路由在 `review_service/` 内扩展。
+6. **format_check 例外**：format_check 允许用 pymupdf 本地解档获取版式元数据
+   （字体/边距/行距/页数），因为 vstore 只回文本不返回版式信息。正文提取仍走 vstore。
+
+## 目录速览（审稿模块）
+
+```
+review_service/
+├── app/main.py                 # FastAPI 入口（/health + 挂载业务路由）
+├── app/config.py               # pydantic-settings（REVIEW_ 前缀）
+├── app/routers/presubmit.py    # POST /api/review/presubmit（自审稿报告）
+├── app/routers/format_check.py # POST /api/review/format-check（版式与规范检查）
+├── app/services/llm.py         # DeepSeek httpx 封装（complete_text/complete_json）
+├── app/services/paper_parse.py # PDF → 纯文本（经 vstore 解析接口）
+├── app/services/format_check.py# 版式规则引擎（pymupdf/docx 本地解档 + 规则检查）
+├── restart.sh                  # 8100 重启脚本
+└── pytest.ini
+```
+
+## 启动
+
+```bash
+cd review_service && bash restart.sh   # 默认 8100，venv 从 ../plantai-rag-new-venv 推导
+# BFF 开关：sdk/.env 加 REVIEW_ENABLED=1 后 bff_restart（反代 /api/review/*）
+```
@@ -0,0 +1,12 @@
+<!DOCTYPE html>
+<html lang="zh-CN" data-theme="dark">
+<head>
+  <meta charset="UTF-8">
+  <meta name="viewport" content="width=device-width, initial-scale=1, viewport-fit=cover">
+  <title>蜂群中枢 · PlantAI 管理后台</title>
+</head>
+<body>
+  <div id="app"></div>
+  <script type="module" src="/src/main.js"></script>
+</body>
+</html>
@@ -0,0 +1,18 @@
+{
+  "name": "plantai-admin",
+  "version": "0.1.0",
+  "private": true,
+  "type": "module",
+  "scripts": {
+    "dev": "vite",
+    "build": "vite build",
+    "preview": "vite preview"
+  },
+  "dependencies": {
+    "vue": "3.5.13"
+  },
+  "devDependencies": {
+    "vite": "5.4.11",
+    "@vitejs/plugin-vue": "5.2.1"
+  }
+}
@@ -0,0 +1,143 @@
+<script setup>
+import { ref, onMounted } from 'vue';
+import { getToken, setToken, api } from './api/admin.js';
+import Login from './views/Login.vue';
+import Users from './views/Users.vue';
+import Logs from './views/Logs.vue';
+import HubSettings from './components/HubSettings.vue';
+
+const authed = ref(false);
+const page = ref('overview');
+const user = ref(null);
+const stats = ref({ users: 0, total: 0, denied: 0, p95: null });
+const hub = ref({ hub_id: '', hub_name: '蜂群中枢' });
+const settingsOpen = ref(false);
+
+const PAGES = { overview: '概览', users: '用户管理', logs: '日志查看' };
+
+function onUnauthorized() { setToken(''); authed.value = false; }
+
+async function loadHub() {
+  try {
+    const r = await api.settings();
+    hub.value = r.settings;
+  } catch (e) {
+    if (e.status === 401) onUnauthorized();
+  }
+}
+
+async function loadStats() {
+  try {
+    const [u, l] = await Promise.all([api.users(), api.logs({ page: 1, page_size: 1 })]);
+    stats.value.users = u.users.length;
+    stats.value.total = l.total;
+    stats.value.denied = (l.aggregates && l.aggregates.denied) || 0;
+    stats.value.p95 = (l.aggregates && l.aggregates.p95_latency_ms) || null;
+  } catch (e) {
+    if (e.status === 401) onUnauthorized();
+  }
+}
+
+async function init() {
+  if (!getToken()) { authed.value = false; return; }
+  try {
+    const r = await api.me();
+    user.value = r.user;
+    authed.value = true;
+    loadHub();
+    loadStats();
+  } catch (e) {
+    setToken('');
+    authed.value = false;
+  }
+}
+
+function onLogin(u) { user.value = u; authed.value = true; page.value = 'overview'; loadHub(); loadStats(); }
+async function onLogout() { try { await api.logout(); } catch {} setToken(''); authed.value = false; }
+function onSettingsSaved(s) { hub.value = s; settingsOpen.value = false; }
+
+onMounted(init);
+</script>
+
+<template>
+  <Login v-if="!authed" @login="onLogin" />
+  <div v-else class="shell">
+    <aside class="sidebar">
+      <div class="side-brand">
+        <div class="hex">蜂</div>
+        <div><div class="brand-name">{{ hub.hub_name }}</div><div class="brand-sub">{{ hub.hub_id.slice(0, 8) }}</div></div>
+      </div>
+      <nav class="nav">
+        <div class="nav-item" :class="{ active: page === 'overview' }" @click="page = 'overview'"><span>◈</span> 概览</div>
+        <div class="nav-item" :class="{ active: page === 'users' }" @click="page = 'users'"><span>◉</span> 用户管理</div>
+        <div class="nav-item" :class="{ active: page === 'logs' }" @click="page = 'logs'"><span>≣</span> 日志查看</div>
+      </nav>
+      <div class="side-foot">
+        <div class="who">
+          <div class="avatar">蜂</div>
+          <div><div class="who-name">{{ user?.username }}</div><div class="who-role">系统管理员</div></div>
+          <span class="logout" @click="onLogout">退出</span>
+        </div>
+      </div>
+    </aside>
+    <main class="main">
+      <div class="topbar">
+        <h1>{{ PAGES[page] }}</h1>
+        <span style="color: var(--text-3); font-size: 13px">{{ hub.hub_name }}</span>
+        <button class="btn btn-ghost" style="margin-left: auto" @click="settingsOpen = true">⚙ 设置</button>
+      </div>
+      <div class="content">
+        <section v-if="page === 'overview'">
+          <div class="stats">
+            <div class="stat"><div class="k">{{ stats.users }}</div><div class="l">注册用户</div></div>
+            <div class="stat"><div class="k amber">{{ stats.total }}</div><div class="l">累计请求</div></div>
+            <div class="stat"><div class="k">{{ stats.denied }}</div><div class="l">越权 / 失败</div></div>
+            <div class="stat"><div class="k">{{ stats.p95 ?? '—' }}</div><div class="l">P95 耗时 ms</div></div>
+          </div>
+        </section>
+        <Users v-else-if="page === 'users'" @unauthorized="onUnauthorized" />
+        <Logs v-else @unauthorized="onUnauthorized" />
+      </div>
+    </main>
+    <HubSettings :open="settingsOpen" :hub="hub" @close="settingsOpen = false" @saved="onSettingsSaved" />
+  </div>
+</template>
+
+<style>
+.shell { display: flex; height: 100vh; }
+.sidebar { width: 218px; flex: none; background: var(--bg-2); border-right: 1px solid var(--border); display: flex; flex-direction: column; }
+.side-brand { display: flex; align-items: center; gap: 10px; padding: 20px 18px 18px; }
+.hex { width: 30px; height: 30px; flex: none; background: linear-gradient(135deg, #f2b95a, #d98f22); clip-path: polygon(50% 0, 100% 25%, 100% 75%, 50% 100%, 0 75%, 0 25%); display: grid; place-items: center; color: #1a1206; font-weight: 700; font-size: 12px; }
+.brand-name { font-size: 15px; font-weight: 600; }
+.brand-sub { font-size: 11px; color: var(--text-3); }
+.nav { padding: 6px 10px; flex: 1; }
+.nav-item { display: flex; align-items: center; gap: 9px; padding: 9px 12px; margin-bottom: 3px; border-radius: var(--radius-sm); color: var(--text-2); font-size: 13.5px; cursor: pointer; }
+.nav-item:hover { background: var(--surface); color: var(--text); }
+.nav-item.active { background: var(--accent-soft); color: var(--accent); }
+.side-foot { padding: 14px 18px; border-top: 1px solid var(--border); }
+.who { display: flex; align-items: center; gap: 10px; }
+.avatar { width: 30px; height: 30px; border-radius: 50%; flex: none; background: linear-gradient(135deg, #3a4a5e, #243146); display: grid; place-items: center; font-size: 12px; color: var(--text); }
+.who-name { font-size: 13px; }
+.who-role { font-size: 11px; color: var(--text-3); }
+.logout { margin-left: auto; color: var(--text-3); cursor: pointer; font-size: 12px; }
+.logout:hover { color: var(--red); }
+.main { flex: 1; overflow-y: auto; display: flex; flex-direction: column; }
+.topbar { display: flex; align-items: center; gap: 14px; padding: 18px 28px; border-bottom: 1px solid var(--border); position: sticky; top: 0; background: rgba(12, 14, 20, 0.9); backdrop-filter: blur(6px); z-index: 5; }
+.topbar h1 { font-size: 17px; margin: 0; font-weight: 600; }
+.content { padding: 26px 28px 40px; }
+.stats { display: grid; grid-template-columns: repeat(4, 1fr); gap: 16px; }
+.stat { background: var(--surface); border: 1px solid var(--border); border-radius: var(--radius); padding: 18px 20px; }
+.stat .k { font-size: 26px; font-weight: 600; letter-spacing: -0.5px; }
+.stat .k.amber { color: var(--accent); }
+.stat .l { color: var(--text-2); font-size: 12.5px; margin-top: 3px; }
+.toolbar { display: flex; align-items: center; gap: 10px; margin-bottom: 16px; }
+.toolbar .spacer { flex: 1; }
+.search { display: flex; align-items: center; gap: 8px; background: var(--surface); border: 1px solid var(--border); border-radius: var(--radius-sm); padding: 8px 12px; width: 240px; }
+.search input { background: none; border: none; outline: none; color: var(--text); font-size: 13px; width: 100%; }
+select { background: var(--surface); border: 1px solid var(--border); color: var(--text); border-radius: var(--radius-sm); padding: 8px 10px; font-size: 13px; outline: none; }
+.pag { display: flex; align-items: center; gap: 8px; padding: 12px 18px; border-top: 1px solid var(--border); color: var(--text-3); font-size: 12.5px; }
+.pag .spacer { flex: 1; }
+.pag button { background: var(--surface-2); border: 1px solid var(--border); color: var(--text-2); border-radius: 6px; padding: 5px 11px; font-size: 12.5px; }
+.pag button.on { color: var(--accent); border-color: var(--accent); }
+.pag button:disabled { opacity: 0.4; cursor: default; }
+</style>
@@ -0,0 +1,48 @@
+const TOKEN_KEY = 'pa-admin-token';
+let token = localStorage.getItem(TOKEN_KEY) || '';
+
+export function getToken() { return token; }
+export function setToken(t) {
+  token = t || '';
+  if (t) localStorage.setItem(TOKEN_KEY, t);
+  else localStorage.removeItem(TOKEN_KEY);
+}
+
+async function request(path, { method = 'GET', body } = {}) {
+  const res = await fetch('/api/admin' + path, {
+    method,
+    headers: {
+      ...(body ? { 'Content-Type': 'application/json' } : {}),
+      ...(token ? { Authorization: 'Bearer ' + token } : {}),
+    },
+    body: body ? JSON.stringify(body) : undefined,
+  });
+  let data = null;
+  try { data = await res.json(); } catch { data = null; }
+  if (!res.ok) {
+    const err = new Error((data && data.error && data.error.message) || ('请求失败 HTTP ' + res.status));
+    err.status = res.status;
+    err.code = data && data.error && data.error.code;
+    throw err;
+  }
+  return data;
+}
+
+export const api = {
+  login: (username, password) => request('/login', { method: 'POST', body: { username, password } }),
+  logout: () => request('/logout', { method: 'POST' }),
+  me: () => request('/me'),
+  units: () => request('/units'),
+  users: () => request('/users'),
+  createUser: (body) => request('/users', { method: 'POST', body }),
+  updateUser: (id, body) => request('/users/' + id, { method: 'PATCH', body }),
+  deleteUser: (id) => request('/users/' + id, { method: 'DELETE' }),
+  logs: (params = {}) => {
+    const q = new URLSearchParams();
+    Object.entries(params).forEach(([k, v]) => { if (v !== undefined && v !== null && v !== '') q.set(k, v); });
+    const qs = q.toString();
+    return request('/logs' + (qs ? '?' + qs : ''));
+  },
+  settings: () => request('/settings'),
+  updateSettings: (body) => request('/settings', { method: 'PUT', body }),
+};
@@ -0,0 +1,57 @@
+<script setup>
+import { ref, watch } from 'vue';
+import { api } from '../api/admin.js';
+
+const props = defineProps({ open: Boolean, hub: Object });
+const emit = defineEmits(['close', 'saved']);
+
+const hubId = ref('');
+const hubName = ref('');
+const busy = ref(false);
+const error = ref('');
+
+watch(() => props.open, (open) => {
+  if (open) {
+    hubId.value = (props.hub && props.hub.hub_id) || '';
+    hubName.value = (props.hub && props.hub.hub_name) || '';
+    error.value = '';
+    busy.value = false;
+  }
+});
+
+async function save() {
+  if (busy.value) return;
+  if (!hubName.value.trim()) { error.value = '中枢名称不能为空'; return; }
+  busy.value = true;
+  error.value = '';
+  try {
+    const r = await api.updateSettings({ hub_id: hubId.value.trim(), hub_name: hubName.value.trim() });
+    emit('saved', r.settings);
+  } catch (e) {
+    error.value = e.message || '保存失败';
+  } finally {
+    busy.value = false;
+  }
+}
+</script>
+
+<template>
+  <div v-if="open" class="overlay" @click.self="emit('close')">
+    <div class="modal">
+      <div class="modal-head">中枢设置</div>
+      <div class="modal-body">
+        <div class="field"><label>中枢名称</label><input v-model="hubName" placeholder="例如:湘湖实验室中枢"></div>
+        <div class="field" style="margin-bottom: 0"><label>中枢 ID</label><input v-model="hubId" class="mono" placeholder="唯一标识,留空则由系统生成"></div>
+        <p v-if="error" class="err">{{ error }}</p>
+      </div>
+      <div class="modal-foot">
+        <button class="btn btn-ghost" @click="emit('close')">取消</button>
+        <button class="btn btn-primary" :disabled="busy" @click="save">{{ busy ? '保存中…' : '保存' }}</button>
+      </div>
+    </div>
+  </div>
+</template>
+
+<style scoped>
+.err { color: var(--red); font-size: 12px; margin: 12px 0 0; }
+</style>
@@ -0,0 +1,101 @@
+<script setup>
+import { ref, watch } from 'vue';
+import { api } from '../api/admin.js';
+
+const props = defineProps({
+  open: Boolean,
+  mode: { type: String, default: 'create' },
+  user: Object,
+});
+const emit = defineEmits(['close', 'saved']);
+
+const UNITS = [
+  ['qa', '问答'], ['kg', '知识图谱'], ['extraction', '文献抽取'], ['docgen', '文档生成'],
+  ['figures', '图片图库'], ['private_docs', '私有资料'], ['bioflow', '生信分析'],
+  ['paper', '论文撰写'], ['legacy', '旧版接口'],
+];
+
+const username = ref('');
+const password = ref('');
+const role = ref('researcher');
+const authorizations = ref([]);
+const busy = ref(false);
+const error = ref('');
+
+watch(() => props.open, (open) => {
+  if (open) {
+    error.value = '';
+    busy.value = false;
+    if (props.mode === 'edit' && props.user) {
+      username.value = props.user.username;
+      password.value = '';
+      role.value = props.user.role === 'admin' ? 'admin' : (props.user.role === 'guest' ? 'guest' : 'researcher');
+      authorizations.value = [...(props.user.authorizations || [])];
+    } else {
+      username.value = '';
+      password.value = '';
+      role.value = 'researcher';
+      authorizations.value = ['qa'];
+    }
+  }
+});
+
+async function save() {
+  if (busy.value) return;
+  if (props.mode === 'create' && (!username.value.trim() || !password.value)) {
+    error.value = '用户名和密码必填';
+    return;
+  }
+  busy.value = true;
+  error.value = '';
+  try {
+    if (props.mode === 'create') {
+      await api.createUser({ username: username.value.trim(), password: password.value, role: role.value, authorizations: authorizations.value });
+    } else {
+      const body = { role: role.value, authorizations: authorizations.value };
+      if (password.value) body.password = password.value;
+      await api.updateUser(props.user.id, body);
+    }
+    emit('saved');
+  } catch (e) {
+    error.value = e.message || '保存失败';
+  } finally {
+    busy.value = false;
+  }
+}
+</script>
+
+<template>
+  <div v-if="open" class="overlay" @click.self="emit('close')">
+    <div class="modal">
+      <div class="modal-head">{{ mode === 'create' ? '新建用户' : '编辑用户' }}</div>
+      <div class="modal-body">
+        <div class="field"><label>用户名</label><input v-model="username" :disabled="mode === 'edit'"></div>
+        <div class="field"><label>{{ mode === 'create' ? '初始密码' : '重置密码（留空不改）' }}</label><input v-model="password" type="password"></div>
+        <div class="field">
+          <label>角色</label>
+          <div class="seg">
+            <button :class="{ on: role === 'researcher' }" @click="role = 'researcher'">研究员</button>
+            <button :class="{ on: role === 'guest' }" @click="role = 'guest'">访客</button>
+            <button :class="{ on: role === 'admin' }" @click="role = 'admin'">管理员</button>
+          </div>
+        </div>
+        <div class="field" style="margin-bottom: 0">
+          <label>授权清单</label>
+          <div class="checks">
+            <label v-for="[k, label] in UNITS" :key="k" class="check"><input type="checkbox" :value="k" v-model="authorizations"> {{ label }}</label>
+          </div>
+        </div>
+        <p v-if="error" class="err">{{ error }}</p>
+      </div>
+      <div class="modal-foot">
+        <button class="btn btn-ghost" @click="emit('close')">取消</button>
+        <button class="btn btn-primary" :disabled="busy" @click="save">{{ busy ? '保存中…' : (mode === 'create' ? '创建用户' : '保存') }}</button>
+      </div>
+    </div>
+  </div>
+</template>
+
+<style scoped>
+.err { color: var(--red); font-size: 12px; margin: 12px 0 0; }
+</style>
@@ -0,0 +1,5 @@
+import { createApp } from 'vue';
+import App from './App.vue';
+import './style.css';
+
+createApp(App).mount('#app');
@@ -0,0 +1,96 @@
+:root {
+  --bg: #0c0e14;
+  --bg-2: #10131b;
+  --surface: #151924;
+  --surface-2: #1a1f2c;
+  --border: #232a38;
+  --border-2: #2e3648;
+  --text: #e9edf5;
+  --text-2: #9aa4b6;
+  --text-3: #5f6a7d;
+  --accent: #e8a33d;
+  --accent-ink: #14100a;
+  --accent-soft: rgba(232, 163, 61, 0.14);
+  --green: #3ecf8e;
+  --green-soft: rgba(62, 207, 142, 0.14);
+  --red: #ef6b6b;
+  --red-soft: rgba(239, 107, 107, 0.14);
+  --blue: #6ea8ff;
+  --radius: 10px;
+  --radius-sm: 7px;
+}
+
+* { box-sizing: border-box; }
+html, body, #app { margin: 0; height: 100%; }
+body {
+  background: var(--bg);
+  color: var(--text);
+  font-family: -apple-system, BlinkMacSystemFont, "PingFang SC", "Microsoft YaHei", "Segoe UI", Roboto, sans-serif;
+  font-size: 14px;
+  line-height: 1.5;
+  -webkit-font-smoothing: antialiased;
+}
+.mono { font-family: ui-monospace, "SF Mono", "JetBrains Mono", Menlo, Consolas, monospace; }
+button { font-family: inherit; cursor: pointer; }
+
+.btn {
+  display: inline-flex; align-items: center; justify-content: center; gap: 7px;
+  padding: 9px 15px; font-size: 13.5px; border-radius: var(--radius-sm);
+  border: 1px solid transparent; transition: filter .15s; background: transparent;
+}
+.btn:focus-visible { outline: 2px solid var(--accent); outline-offset: 2px; }
+.btn-primary { background: var(--accent); color: var(--accent-ink); font-weight: 600; }
+.btn-primary:hover { filter: brightness(1.06); }
+.btn-ghost { border-color: var(--border-2); color: var(--text-2); }
+.btn-ghost:hover { color: var(--text); border-color: var(--text-3); }
+.btn-danger { background: var(--red-soft); color: var(--red); }
+.btn-block { width: 100%; }
+
+.field { margin-bottom: 15px; }
+.field label { display: block; font-size: 12px; color: var(--text-2); margin-bottom: 7px; }
+.field input, .field select {
+  width: 100%; padding: 10px 12px; font-size: 14px; color: var(--text);
+  background: var(--bg-2); border: 1px solid var(--border); border-radius: var(--radius-sm); outline: none;
+}
+.field input:focus, .field select:focus { border-color: var(--accent); box-shadow: 0 0 0 3px var(--accent-soft); }
+
+.chip {
+  display: inline-block; padding: 3px 9px; border-radius: 20px; font-size: 11.5px;
+  border: 1px solid var(--border-2); color: var(--text-2); margin: 1.5px 3px 1.5px 0;
+}
+.chip.amber { border-color: transparent; background: var(--accent-soft); color: var(--accent); }
+.badge { display: inline-block; padding: 2px 8px; border-radius: 5px; font-size: 11.5px; font-family: ui-monospace, Menlo, monospace; }
+.badge.green { background: var(--green-soft); color: var(--green); }
+.badge.red { background: var(--red-soft); color: var(--red); }
+.badge.amber { background: var(--accent-soft); color: var(--accent); }
+.badge.muted { background: var(--surface-2); color: var(--text-3); }
+
+.panel { background: var(--surface); border: 1px solid var(--border); border-radius: var(--radius); }
+table { width: 100%; border-collapse: collapse; }
+th { text-align: left; font-size: 11.5px; font-weight: 500; color: var(--text-3); padding: 10px 18px; border-bottom: 1px solid var(--border); }
+td { padding: 13px 18px; border-bottom: 1px solid var(--border); font-size: 13.5px; }
+tr:last-child td { border-bottom: none; }
+tbody tr:hover { background: rgba(255,255,255,0.015); }
+.cell-id { color: var(--text-2); }
+.row-actions { display: flex; gap: 6px; }
+.row-actions .act { color: var(--blue); cursor: pointer; font-size: 13px; padding: 3px 6px; border-radius: 5px; }
+.row-actions .act:hover { background: rgba(110,168,255,0.1); }
+.row-actions .act.danger { color: var(--red); }
+.row-actions .act.danger:hover { background: var(--red-soft); }
+
+.role { font-weight: 600; }
+.role.admin { color: var(--accent); }
+.role.researcher { color: var(--blue); }
+.role.guest { color: var(--text-2); }
+
+.overlay { position: fixed; inset: 0; background: rgba(0,0,0,0.55); display: flex; align-items: center; justify-content: center; z-index: 50; }
+.modal { width: 460px; max-width: calc(100vw - 32px); background: var(--surface); border: 1px solid var(--border-2); border-radius: 14px; }
+.modal-head { padding: 18px 22px 0; font-size: 15px; font-weight: 600; }
+.modal-body { padding: 18px 22px; }
+.modal-foot { padding: 14px 22px 20px; display: flex; justify-content: flex-end; gap: 10px; border-top: 1px solid var(--border); }
+.checks { display: grid; grid-template-columns: 1fr 1fr; gap: 9px 14px; margin-top: 8px; }
+.check { display: flex; align-items: center; gap: 8px; font-size: 13px; color: var(--text-2); }
+.check input { accent-color: var(--accent); width: 15px; height: 15px; }
+.seg { display: flex; gap: 6px; }
+.seg button { background: transparent; border: 1px solid var(--border-2); color: var(--text-2); border-radius: 7px; padding: 7px 14px; font-size: 13px; }
+.seg button.on { background: var(--accent-soft); border-color: transparent; color: var(--accent); }
@@ -0,0 +1,53 @@
+<script setup>
+import { ref } from 'vue';
+import { api, setToken } from '../api/admin.js';
+
+const emit = defineEmits(['login']);
+const username = ref('');
+const password = ref('');
+const error = ref('');
+const busy = ref(false);
+
+async function submit() {
+  if (busy.value) return;
+  if (!username.value || !password.value) { error.value = '请输入用户名和密码'; return; }
+  busy.value = true;
+  error.value = '';
+  try {
+    const r = await api.login(username.value, password.value);
+    setToken(r.token);
+    emit('login', r.user);
+  } catch (e) {
+    error.value = e.message || '登录失败';
+  } finally {
+    busy.value = false;
+  }
+}
+</script>
+
+<template>
+  <div class="login">
+    <div class="card">
+      <div class="brand">
+        <div class="hex">蜂</div>
+        <div><div class="brand-name">蜂群中枢</div><div class="brand-sub">PlantAI 管理后台</div></div>
+      </div>
+      <div class="field"><label>用户名</label><input v-model="username" autocomplete="username" @keyup.enter="submit"></div>
+      <div class="field"><label>密码</label><input v-model="password" type="password" autocomplete="current-password" @keyup.enter="submit"></div>
+      <button class="btn btn-primary btn-block" :disabled="busy" @click="submit">{{ busy ? '登录中…' : '登录' }}</button>
+      <p v-if="error" class="err">{{ error }}</p>
+      <div class="hint">仅限中枢管理员。登录与所有操作均会留痕。</div>
+    </div>
+  </div>
+</template>
+
+<style scoped>
+.login { height: 100vh; display: flex; align-items: center; justify-content: center; background: radial-gradient(1200px 600px at 70% -10%, rgba(232, 163, 61, 0.08), transparent 60%), var(--bg); }
+.card { width: 360px; background: var(--surface); border: 1px solid var(--border); border-radius: 14px; padding: 34px 32px 30px; }
+.brand { display: flex; align-items: center; gap: 11px; margin-bottom: 26px; }
+.hex { width: 34px; height: 34px; flex: none; background: linear-gradient(135deg, #f2b95a, #d98f22); clip-path: polygon(50% 0, 100% 25%, 100% 75%, 50% 100%, 0 75%, 0 25%); display: grid; place-items: center; color: #1a1206; font-weight: 700; font-size: 14px; }
+.brand-name { font-size: 16px; font-weight: 600; }
+.brand-sub { color: var(--text-3); font-size: 12px; }
+.err { color: var(--red); font-size: 12px; margin: 10px 0 0; }
+.hint { margin-top: 20px; padding-top: 16px; border-top: 1px solid var(--border); font-size: 12px; color: var(--text-3); }
+</style>
@@ -0,0 +1,102 @@
+<script setup>
+import { ref, onMounted } from 'vue';
+import { api } from '../api/admin.js';
+
+const emit = defineEmits(['unauthorized']);
+
+const from = ref('');
+const event = ref('');
+const q = ref('');
+const page = ref(1);
+const pageSize = 30;
+const items = ref([]);
+const total = ref(0);
+const aggregates = ref({});
+const loading = ref(false);
+
+const EVENT_LABEL = {
+  http_request: '调用', admin_login_ok: '登录成功', admin_login_fail: '登录失败',
+  call_denied: '越权', user_created: '建用户', user_updated: '改用户', user_deleted: '删用户',
+};
+
+function statusBadge(s) {
+  if (!s) return 'muted';
+  if (s >= 200 && s < 300) return 'green';
+  if (s >= 500) return 'red';
+  return 'amber';
+}
+
+async function load() {
+  loading.value = true;
+  try {
+    const r = await api.logs({
+      from_date: from.value || undefined,
+      event: event.value || undefined,
+      q: q.value || undefined,
+      page: page.value,
+      page_size: pageSize,
+    });
+    items.value = r.items;
+    total.value = r.total;
+    aggregates.value = r.aggregates || {};
+  } catch (e) {
+    if (e.status === 401) emit('unauthorized');
+  } finally {
+    loading.value = false;
+  }
+}
+
+function search() { page.value = 1; load(); }
+function prev() { if (page.value > 1) { page.value -= 1; load(); } }
+function next() { if (page.value * pageSize < total.value) { page.value += 1; load(); } }
+
+onMounted(load);
+</script>
+
+<template>
+  <div>
+    <div class="stats" style="margin-bottom: 16px">
+      <div class="stat"><div class="k">{{ total }}</div><div class="l">匹配日志</div></div>
+      <div class="stat"><div class="k amber">{{ aggregates.denied ?? 0 }}</div><div class="l">越权 / 失败</div></div>
+      <div class="stat"><div class="k">{{ aggregates.avg_latency_ms ?? '—' }}</div><div class="l">平均耗时 ms</div></div>
+      <div class="stat"><div class="k">{{ aggregates.p95_latency_ms ?? '—' }}</div><div class="l">P95 耗时 ms</div></div>
+    </div>
+    <div class="toolbar">
+      <input class="date" v-model="from" type="date">
+      <select v-model="event">
+        <option value="">全部事件</option>
+        <option v-for="(l, k) in EVENT_LABEL" :key="k" :value="k">{{ l }}</option>
+      </select>
+      <div class="search"><input v-model="q" placeholder="按用户 / 路径过滤…" @keyup.enter="search"></div>
+      <button class="btn btn-ghost" @click="search">查询</button>
+    </div>
+    <div class="panel">
+      <table>
+        <thead><tr><th>时间</th><th>用户</th><th>事件</th><th>方法</th><th>路径</th><th>状态</th><th>耗时</th></tr></thead>
+        <tbody>
+          <tr v-if="loading"><td colspan="7" class="cell-id">加载中…</td></tr>
+          <tr v-else-if="!items.length"><td colspan="7" class="cell-id">暂无日志</td></tr>
+          <tr v-for="(e, i) in items" :key="i">
+            <td class="cell-id mono">{{ (e.ts || '').replace('T', ' ').slice(0, 19) }}</td>
+            <td class="mono cell-id">{{ e.user_id ? e.user_id.slice(0, 8) : '—' }}</td>
+            <td>{{ EVENT_LABEL[e.event] || e.event }}</td>
+            <td class="cell-id mono">{{ e.method || '—' }}</td>
+            <td class="mono">{{ e.path || '—' }}</td>
+            <td><span v-if="e.status" class="badge" :class="statusBadge(e.status)">{{ e.status }}</span><span v-else class="badge muted">—</span></td>
+            <td class="cell-id mono">{{ e.latency_ms != null ? e.latency_ms + 'ms' : '—' }}</td>
+          </tr>
+        </tbody>
+      </table>
+      <div class="pag">
+        <span>共 {{ total }} 条</span><span class="spacer"></span>
+        <button :disabled="page <= 1" @click="prev">上一页</button>
+        <button class="on">{{ page }}</button>
+        <button :disabled="page * pageSize >= total" @click="next">下一页</button>
+      </div>
+    </div>
+  </div>
+</template>
+
+<style scoped>
+input.date { background: var(--surface); border: 1px solid var(--border); color: var(--text); border-radius: var(--radius-sm); padding: 8px 10px; font-size: 13px; outline: none; }
+</style>
@@ -0,0 +1,72 @@
+<script setup>
+import { ref, onMounted } from 'vue';
+import { api } from '../api/admin.js';
+import UserForm from '../components/UserForm.vue';
+
+const emit = defineEmits(['unauthorized']);
+
+const users = ref([]);
+const loading = ref(true);
+const formOpen = ref(false);
+const formMode = ref('create');
+const editing = ref(null);
+
+const ROLE_LABEL = { admin: '管理员', researcher: '研究员', guest: '访客' };
+const UNIT_LABEL = { qa: '问答', kg: '知识图谱', extraction: '文献抽取', docgen: '文档生成', figures: '图片图库', private_docs: '私有资料', bioflow: '生信分析', paper: '论文撰写', legacy: '旧版接口' };
+
+async function load() {
+  loading.value = true;
+  try {
+    const r = await api.users();
+    users.value = r.users;
+  } catch (e) {
+    if (e.status === 401) emit('unauthorized');
+  } finally {
+    loading.value = false;
+  }
+}
+
+function create() { formMode.value = 'create'; editing.value = null; formOpen.value = true; }
+function edit(u) { formMode.value = 'edit'; editing.value = u; formOpen.value = true; }
+async function del(u) {
+  if (!confirm(`删除用户「${u.username}」？此操作不可撤销。`)) return;
+  try { await api.deleteUser(u.id); load(); } catch (e) { alert(e.message || '删除失败'); }
+}
+function onSaved() { formOpen.value = false; load(); }
+
+onMounted(load);
+</script>
+
+<template>
+  <div>
+    <div class="toolbar">
+      <div class="spacer"></div>
+      <button class="btn btn-primary" @click="create">＋ 新建用户</button>
+    </div>
+    <div class="panel">
+      <table>
+        <thead><tr><th>用户</th><th>角色</th><th>授权范围</th><th>创建时间</th><th style="width: 120px"></th></tr></thead>
+        <tbody>
+          <tr v-if="loading"><td colspan="5" class="cell-id">加载中…</td></tr>
+          <tr v-else-if="!users.length"><td colspan="5" class="cell-id">暂无用户</td></tr>
+          <tr v-for="u in users" :key="u.id">
+            <td>
+              <div style="display: flex; align-items: center; gap: 10px">
+                <div class="avatar">{{ u.username[0] }}</div>
+                <div><div>{{ u.username }}</div><div class="cell-id" style="font-size: 12px">{{ u.id.slice(0, 8) }}</div></div>
+              </div>
+            </td>
+            <td><span class="role" :class="u.role">{{ ROLE_LABEL[u.role] || u.role }}</span></td>
+            <td>
+              <span v-if="u.role === 'admin'" class="chip amber">全部权限</span>
+              <template v-else><span v-for="a in u.authorizations" :key="a" class="chip">{{ UNIT_LABEL[a] || a }}</span></template>
+            </td>
+            <td class="cell-id mono">{{ (u.created_at || '').slice(0, 10) }}</td>
+            <td><div class="row-actions"><span class="act" @click="edit(u)">编辑</span><span class="act danger" @click="del(u)">删除</span></div></td>
+          </tr>
+        </tbody>
+      </table>
+    </div>
+    <UserForm :open="formOpen" :mode="formMode" :user="editing" @close="formOpen = false" @saved="onSaved" />
+  </div>
+</template>
@@ -0,0 +1,15 @@
+import { defineConfig } from 'vite';
+import vue from '@vitejs/plugin-vue';
+
+export default defineConfig({
+  base: '/admin/',
+  plugins: [vue()],
+  server: {
+    host: '127.0.0.1',
+    port: 5181,
+    proxy: {
+      '/api': { target: 'http://127.0.0.1:8090', changeOrigin: false },
+    },
+  },
+  build: { outDir: 'dist', target: 'es2020' },
+});
@@ -0,0 +1,10 @@
+#!/bin/bash
+# deploy/paper_restart.sh —— 论文撰写服务重启（8097，dev 树明文；不触碰 8090/8091/8098）。
+# 用法：bash deploy/paper_restart.sh
+set -euo pipefail
+
+SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+REPO_ROOT="$(cd "$SCRIPT_DIR/.." && pwd)"
+
+bash "$REPO_ROOT/paper_writer_service/restart.sh"
+echo "paper_writer_service 重启已触发（端口 8097，日志 paper_writer_service/paper.log）"
@@ -0,0 +1,51 @@
+#!/bin/bash
+# deploy/toggle_paper.sh —— 论文撰写快速开关（dev 树 175；不触碰生产 176 /srv/plantai）。
+# 用法：bash deploy/toggle_paper.sh off|on
+# 原理：BFF main.py 按 PAPER_WRITER_ENABLED 决定是否注册 /api/paper 路由；
+#       不注册时 /api/paper/health 返回 404，前端探活落 offline，触发词落 docgen 单发降级。
+set -uo pipefail
+
+ACTION="${1:-}"
+SDK_DIR="/home/xzq/5090/teamWorkspace/zh/PlantAI-rag-new/sdk"
+ENV_FILE="$SDK_DIR/.env"
+PY="/home/xzq/5090/teamWorkspace/zh/plantai-rag-new-venv/bin/python"
+BIND="${PAPER_BFF_BIND:-0.0.0.0}"
+
+if [ "$ACTION" != "off" ] && [ "$ACTION" != "on" ]; then
+  echo "用法: $0 <off|on>" >&2
+  exit 2
+fi
+
+VAL="true"
+[ "$ACTION" = "off" ] && VAL="false"
+
+# 1. 改 env（追加或覆盖）
+if grep -q "^PAPER_WRITER_ENABLED=" "$ENV_FILE"; then
+  sed -i "s/^PAPER_WRITER_ENABLED=.*/PAPER_WRITER_ENABLED=$VAL/" "$ENV_FILE"
+else
+  echo "PAPER_WRITER_ENABLED=$VAL" >> "$ENV_FILE"
+fi
+echo "PAPER_WRITER_ENABLED -> $VAL"
+
+# 2. 重启 BFF 8090（dev 树；仅取 LISTEN 者；venv 必须绝对路径，cd sdk 后才能 import app.main）
+kill $(lsof -ti tcp:8090 -sTCP:LISTEN) 2>/dev/null || true
+sleep 2
+cd "$SDK_DIR" && set -a && . .env && set +a
+( cd "$SDK_DIR" && setsid "$PY" -m uvicorn app.main:app --host "$BIND" --port 8090 \
+  > /tmp/plantai-bff.log 2>&1 < /dev/null & ) && disown -a
+
+# 3. 自检
+for i in $(seq 1 20); do
+  sleep 2
+  curl -s -m 3 http://127.0.0.1:8090/api/health >/dev/null 2>&1 && break
+done
+curl -s -m 10 http://127.0.0.1:8090/api/health | head -c 120
+echo
+if [ "$ACTION" = "off" ]; then
+  CODE=$(curl -s -o /dev/null -w "%{http_code}" -m 8 http://127.0.0.1:8090/api/paper/health)
+  echo "paper/health HTTP $CODE (off 期望 404)"
+  [ "$CODE" = "404" ] && echo "OFF_OK" || echo "OFF_CHECK_FAIL"
+else
+  curl -s -m 8 http://127.0.0.1:8090/api/paper/health | head -c 150
+  echo
+fi
@@ -0,0 +1,42 @@
+# feat(review): journal_directory 启动自动 seed（部署即运行）
+
+## 背景
+
+source_v4.xlsx（1056 条目录）此前需手动跑 import_journals.py 入库，部署后忘跑即出现"目录数据未导入"。本次实现启动时自动检测 + 自动导入。线上当前环境已由人工完成导入（review.db 内 1056 行），本功能消除的是新环境部署/重建库时的手动步骤风险。
+
+## 修改内容
+
+| 文件 | 变更 |
+|---|---|
+| `app/services/journal_seed.py`（新增） | 共享核心：schema/清洗/解析/upsert 从 CLI 原样迁入；`extract_rows_from_xlsx()`（口径 779/277 与 id 冲突闸门，不符不写库）、`upsert_to_db()`、`ensure_journal_directory_seeded()`（空表才导，四键 dict 契约，绝不抛异常） |
+| `scripts/import_journals.py` | 瘦身为薄 CLI（-431/+92 行）：对账报告/退出码 0/1/2/3 全保留，核心复用 journal_seed |
+| `app/config.py` | +`seed_on_startup=True`（REVIEW_SEED_ON_STARTUP 可关）、+`journal_directory_seed_path` |
+| `app/main.py` | lifespan：开关门控 → `asyncio.to_thread` 导入（不堵 event loop）→ try/except 不阻塞启动；路径走 `db.path` 注入链 |
+| `tests/conftest.py`（新增） | 全局关 seed，防止单测触碰真库/拖慢套件 |
+| `tests/test_seed.py`（新增） | 6 用例（见下） |
+
+不动：source_v4.xlsx、journal_directory 路由/表 schema、db.py、前端。
+
+## 测试用例与结果（pytest 78 passed，新增 6 条）
+
+1. 空库 → seed 成功，rows=1056（en=779/zh=277）✓
+2. 非空库（1 行）→ skip，count 不变 ✓
+3. xlsx 不存在 → 返回 error，不抛异常，不写库 ✓
+4. 幂等：连调两次，第二次 skip ✓
+5. 开关 off（lifespan）→ 表不创建 ✓
+6. 开关 on（lifespan）→ tmp 库 1056 行 ✓
+
+## 部署验证
+
+```bash
+bash review_service/restart.sh   # 非空库：日志 "already has 1056 rows, skip"
+curl 'http://127.0.0.1:8100/api/review/journals/directory?lang=en'  # total=779
+# 空库冷启动（本机已验证等价路径）：日志 "seeded 1056 rows (en=779, zh=277, N.Ns)"
+# 特殊部署：REVIEW_SEED_ON_STARTUP=false → 日志 "seed skipped"
+```
+
+本机已实测：真机重启走 skip 路径（`INFO:app.main:already has 1056 rows, skip`），CLI 薄壳回归 exit=0 / `en=779 zh=277 → ✓ 相符`。
+
+## 是否需要立即部署
+
+待管理员确认。线上已手动导入 1056 行，本改动属部署便利性补强（消除新环境忘跑导入脚本的风险），可随下次正常发版评估带上。
@@ -0,0 +1,56 @@
+# fix(review): 冲突降级真影响 recommendation（major → minor 真降级）
+
+- 分支：`feature/academic-review-assistant`
+- 日期：2026-10-12
+- 服务：`review_service`（:8100）/ 前端 `PresubmitPanel.vue`
+- 状态：**未 commit**，待验收
+
+## 背景
+
+s41588（已发表 Nature Genetics 论文）真实链路里，关键词扫描器报告"3 处冲突已降级为非硬性问题"，但 `recommendation` 仍为大修、`major_weaknesses` 仍 5 条。诊断确认：原降级只做了"剥 hard_rule 标签 + 记 conflicts"，**条目仍在 major 列表内**，`major_count` / 引擎输入未变，故判定不变。本次把"降级"从标签维度升级为**列表维度的真降级**（major → minor）。
+
+## 变更
+
+**后端**
+- `paper_scanner.reconcile_hard_rules`：命中冲突的 major 从列表**移出**，`hard_rule=None` + `scanner_downgraded=true`，落入 demoted 列表；`fatal=true` 条目例外（只记 conflict 不降级，须人工过目）。
+- `routers/presubmit.py`：demoted 追加进 `report.minor_weaknesses`；`major_weaknesses` 为过滤后列表；explanation 文案改"已降级为小修级问题"。
+- `self_review.WeaknessItem`：新增 `scanner_downgraded: bool = False`（coerce 不读、LLM 无法伪造）。
+- 引擎 `recommend_engine.decide_recommendation` **零改动**——计数因列表变短而自动真实。
+
+**前端**
+- `PresubmitPanel.vue`：minor 卡片对 `scanner_downgraded` 显示黄徽标"冲突降级"（与 major 卡片"硬性"红徽标对仗）；冲突明细块保留。
+
+## 测试
+
+- pytest **104 passed**（新增：`test_reconcile_fatal_not_demoted`、`test_http_partial_conflict_leaves_residual_soft`；改写 `test_reconcile_*` 与 `test_http_scanner_conflict_downgrades` 为真降级断言）。
+- vitest **382 passed / 5 failed**（5F 为既有他人 `benchpanel`+`Composer .mode-pill` labels.js 引发，与本改动无关）；`npm run build` ✓。
+
+## 验收（真 LLM，:8100）
+
+| 样本 | rec | rule | M/S/minor | conflicts | downgraded→minor |
+|---|---|---|---|---|---|
+| diag_strong | minor_revision | R5 | 0/0/4 | 0 | 无 |
+| diag_weak | major_revision | R1 | 6/2/7 | 1(hic) | 有（真降级生效） |
+
+弱稿仍大修：4 条硬性命中（busco/accession/voucher/abs）为真缺，扫描器无冲突、不降级——真缺陷不放行。
+
+## 验收：s41588（真 LLM，:8100）
+
+输入 `/tmp/opencode/s41588-025-02113-5.pdf`，target_journal=Genome Biology（tier 1 override）。
+
+| 项 | 修复前 | 修复后 |
+|---|---|---|
+| recommendation | major_revision | **minor_revision**（R5） |
+| major_count / soft / minor | 5 / — / — | **0 / 0 / 6** |
+| hard_hits | 含 busco/accession… | **[]** |
+| scanner signals | — | accession_found=True, busco=partial, hic_found=True |
+| major_weaknesses 列表 | 5 条 | **0 条** |
+| scanner_conflicts | — | **2 条保留**（busco_missing 格式不完整、accession_missing 部分未给号）→ 均真降级进 minor（`scanner_downgraded=true`） |
+
+判定链：扫描器证伪 2 条硬性 → 真降级 → 剩余为 minor → R5（tier1 accept 门槛 minor≤1，6 条 → minor_revision）。conflicts 透明保留、explanation 明示"已降级为小修级问题，请人工核对"。
+
+注：本次 LLM 未再把"树图注未标数值 / GWAS 校正描述"判成 major（负向清单 Prompt 生效），故 major 从 5 归 0，优于预期的"降到 2"。
+
+## 部署
+
+待管理员确认。属判定正确性修复（真论文误判大修），建议随下次正常发版带上。
@@ -0,0 +1,81 @@
+# fix(review): presubmit 四 Bug 修复——截断保真 / 分档 / 词表 / 扫描器兜底
+
+## 背景
+
+真实案例：已发表 Nature Genetics 论文（s41588-026-02682-z，黄瓜泛基因组）被判
+"大修"，但论文实有 BUSCO 98.57%（P2）、94.18% sequences anchored（P2）、
+PRJCA038097 等 accession（P17 Data Availability）。诊断出四个独立缺陷：
+
+1. **PDF 截断**：`max_text_chars=60000` 从头切，30 页论文 P17 的 Data Availability 被截掉；
+2. **期刊分档**：Nature Genetics 不在 5 本精选 → 默认 tier 2（应 tier 1）；
+3. **硬性规则词表过窄**：缺 PRJCA/CRA（中国 NGDC/GSA）、Hi-C 同义词只认 anchoring rate、
+   BUSCO 仅百分比也算缺失；
+4. **无程序层兜底**：hard_rule 全靠 LLM 输出，无关键词证伪机制。
+
+## 修改内容
+
+| 文件 | 变更 |
+|---|---|
+| `app/routers/presubmit.py` | **Bug 1**：段落感知装箱 `pack_feed_text`（超预算按
+  Abstract→Data Availability 全文→Methods 前 60%→Results→Discussion 优先保留，
+  dropped_sections 入 meta）；无节标题回退头+尾窗（捞页尾 availability 块）。
+  **双层保护**：估算 token（len/1.5）>48K → 自动降 100K 重装；LLM 400/413 → 降 80K
+  重试一次。**Bug 4 接线**：coerce 后扫描器证伪 → rationale.scanner_conflicts |
+  **Bug 2**：tier_source ∈ override/featured/jif/默认 |
+| `app/services/paper_scanner.py`（新增） | 关键词扫描器（纯 stdlib）：accession
+  词表 PRJNA/PRJEB/PRJCA/SRP/ERP/DRP/CRA/SRR/ERR/DRR/GCA_/GCF_ **只在 Data Availability
+  段扫**（正文引用他人数据不误判）；BUSCO 三级 none/partial/full；Hi-C 同义词
+  （anchored to chromosome(s)/anchoring rate/pseudo-chromosome(s)/chromosome-level）。
+  `reconcile_hard_rules`：LLM 报缺 X + 扫描器见 X → 剥硬性标签降 soft + 记冲突
+  （只证伪不证实，不引入新误判） |
+| `app/services/recommend_engine.py` | **Bug 2**：tier 查找优先级 override
+  （13 本顶刊硬编码，"The " 前缀归一化）→ featured（journals.json）→ jif 启发式
+  （journal_directory 只读 jif 列；jif≥15→tier1；综述刊名含 Review/Trends/Annual
+  Review 除外）→ 默认 tier 2 |
+| `app/services/self_review.py` | **Bug 3**：Prompt 词表扩充（PRJCA/CRA/SRR…）；
+  BUSCO 三级判定（仅百分比→minor 不打 hard_rule）；Hi-C 同义词清单。
+  **2026-10-12 追加 soft major 收紧**（s41588 复盘）：维度三系统发育树分诊重写
+  （完全未做→major / 已声明仅图未标数值→presentation / 附带树→minor）；新增
+  【负向清单】节（图未标统计量、标准方法描述不全、阈值缺数值、引用排版 →
+  minor/presentation，严禁列 major；总纲"只有补实验/补数据/重跑分析/改核心论证
+  才是 major"；与各维度冲突时以本节为准） |
+| `app/config.py` | `max_text_chars` 60000 → **150000**（REVIEW_MAX_TEXT_CHARS 可覆盖） |
+| `ui/.../PresubmitPanel.vue` | 冲突黄标块（scanner_conflicts + 降级提示）；截断
+  dropped_sections 美化提示；截断文案改为"保摘要/数据可用性/方法/结果/讨论" |
+| `tests/test_presubmit.py` | 新增 15 用例（装箱/回退/token 守卫/400 重试/扫描器
+  三类信号/DA 段限定/冲突降级/端到端/tier 优先级矩阵/Prompt 新词表） |
+
+## 测试用例与结果
+
+- **pytest：102 passed**（87 基线 + 15 新增）。
+- **vitest：379 passed / 5 failed**（5F 为既有他人 i18n labels 改动引发，与本改动
+  无关；新增冲突黄标/截断提示 2 条全绿）。`npm run build` ✓。
+- **真实链路验收**（真 LLM，target_journal=Genome Biology → tier 1 override）：
+
+| 样本 | 修复前 | 修复后 | 扫描器 |
+|---|---|---|---|
+| 强稿 diag_strong.pdf | minor_revision | **minor_revision**（R5，0/0/5） | accession/busco=full/hic 全命中，0 冲突 ✓ |
+| 弱稿 diag_weak.pdf | major_revision | **major_revision**（R1，硬性 4 + soft 4 + minor 5） | accession/busco 未命中（真缺不降）；Hi-C 冲突降级并记录 ✓ |
+| **真实案例 s41588**（NG 论文） | major_revision | 见下"验收"节 | — |
+
+## 部署验证
+
+```bash
+bash review_service/restart.sh
+curl -X POST http://127.0.0.1:8100/api/review/presubmit \
+  -F "file=@paper.pdf" -F "target_journal=Nature Genetics"
+# 检查：meta.tier=1/tier_source=override；meta.dropped_sections；
+#       report.recommendation_rationale.scanner_conflicts
+```
+
+## 是否需要立即部署
+
+待管理员确认。四修复均为判定正确性问题（真实发表论文误判大修），建议随下次正常发版带上。
+
+## 遗留
+
+- tier jif 启发式仅覆盖 journal_directory 已录入的 1056 刊；未收录刊名走默认 tier 2。
+- 扫描器 accession 仅扫 DA 段——若论文把 accession 放 Methods 数据声明处且无 DA 节，
+  扫描器不证伪（保守方向，LLM 硬性判定仍生效，不会误放行）。
+- BUSCO full 判定要求 S: 与 D: 标记在 200 字符窗内相邻——极端排版可能判 partial
+  （只会更严，不误放）。
@@ -0,0 +1,61 @@
+# fix(review): presubmit recommendation 判定过严修复（配额制 → 规则引擎）
+
+## 背景
+
+用户反馈 AI 预审稿多次测试均返回 major_revision。2026-10-12 诊断确认根因是
+**配额制**而非"尺子紧"：
+
+- `self_review.py` 硬性规则要求 `major_weaknesses 3-8 条`（强制配额）→ accept/minor_revision 几乎不可达；
+- LLM 直接输出 recommendation，无程序层规则；JSON 示例锚定 `major_revision`、coerce 缺省回落 `major_revision`；
+- 对照实验：近 GB 完备强稿（BUSCO 96.8% / Hi-C 98.7% / PRJNA+GCA+figshare 齐 / UFBoot 1000）仍被凑出 6 条 major，与弱稿（7 条）几乎无区分度；
+- `target_journal` 传入但 Prompt 零分档标准。
+
+## 修改内容
+
+| 文件 | 变更 |
+|---|---|
+| `app/services/recommend_engine.py`（新增） | 纯函数规则引擎：R0 fatal→reject / R1 硬性 major→大修（不可协商，与 tier 无关）/ R2' tier3 仅 1-2 条 soft 可降小修 / R2 soft≥1→大修 / R4 0 major 且 minor≤tier 阈值→接收 / R5→小修；rationale 模板拼装（rule/hard_hits/计数/tier/explanation，含 tier 降级提示句）；`resolve_tier` 按 journals.json `review_tier` 匹配，失败默认 tier 2 |
+| `app/services/self_review.py` | Prompt 重写：严重分级标准（major/minor/presentation），**三类均不设下限、可 0 条、严禁凑数**；硬性规则 5 项打标签（busco/hic/accession/voucher/abs_missing）；删除 recommendation 输出字段与示例锚定；coerce 不再读 recommendation（防注入），hard_rule 白名单过滤 |
+| `app/routers/presubmit.py` | coerce 后接引擎；meta 增加 tier/tier_label/tier_source |
+| `data/journals/journals.json` | 精选 5 本加 `review_tier`（GB/MP=1；BMC PB/FPS/Rice=2）+ notes 一行 |
+| `ui/.../PresubmitPanel.vue` | 判定依据块（explanation + 硬性 chips）；判定档位徽标；reject 红标"建议人工复核"；顶部 AI 免责行；major 卡片"硬性/fatal"徽标 |
+| `tests/test_presubmit.py` | 用例 1-10（引擎分支全覆盖 + tier 对照 + 注入忽略 + rationale 字段） |
+
+判定链与旧链路唯一对外契约变化：`report.recommendation` 语义不变（四档枚举），
+新增 `report.recommendation_rationale` 与 `meta.tier*`。
+
+## 测试用例与结果
+
+- **pytest：87 passed**（78 基线 + 9 新增/重写），含用例 1-10：
+  强稿形态不判大修、弱稿形态判大修且 hard_hits 正确、0 major 0/多 minor 分支、
+  soft major 分支、fatal→reject、tier3 降级与硬性豁免、tier1 accept 门槛、
+  LLM recommendation 注入被忽略、hard_rule 白名单过滤、rationale 含 tier/explanation。
+- **vitest：377 passed / 5 failed**（5F 为既有他人 i18n labels 改动引发的 benchpanel
+  失败，与本改动无关；新增 4 条 rationale/档位/fatal 展示用例全绿）。
+- **真实链路验收**（诊断同款样本、同 target_journal=Genome Biology，真 LLM 调用）：
+
+| 样本 | 修复前 | 修复后 | 依据 |
+|---|---|---|---|
+| 弱稿 diag_weak.pdf | major_revision（7 major） | **major_revision**（R1；硬性 5 命中：BUSCO/Hi-C/Accession/voucher/ABS + soft 2 + minor 6） | 真缺陷不漏判 ✓ |
+| 强稿 diag_strong.pdf | major_revision（凑出 6 major） | **minor_revision**（R5；0 major / 5 minor） | 区分度恢复 ✓ |
+
+## 部署验证
+
+```bash
+bash review_service/restart.sh
+# 上传强/弱样本对比（或任意 PDF）：
+curl -X POST http://127.0.0.1:8100/api/review/presubmit \
+  -F "file=@paper.pdf" -F "target_journal=Genome Biology"
+# 检查 report.recommendation_rationale.rule / meta.tier；前端看"判定依据"块
+```
+
+## 是否需要立即部署
+
+待管理员确认。属判定质量修复（误报大修影响用户体验与信任），建议随下次正常发版带上。
+
+## 遗留（Phase 2 候选）
+
+- 程序层兜底 `_sanity_check_missing_hard_rules`：正文无 PRJNA/GCA_/SRP 关键词但 LLM
+  未报 accession_missing → 追加 warning（不进 recommendation 计算）；先观察 LLM 是否
+  "躺平"再决定。
+- tier 数据仅覆盖精选 5 本；扩展到 journal_directory 1056 条需人工核验后另行入库。
@@ -0,0 +1,161 @@
+# PR 报告：Rebuttal Phase 1（审稿回复助手）
+
+- 日期：2026-10-12
+- 分支：`feature/academic-review-assistant`（未 commit，按用户约定统一处理）
+- 范围：`review_service/` 新增 5 文件 + main 注册；`ui/` 新增面板与 store/api 扩展；无 sdk/、agent/、vstore/ 改动；无新增依赖。
+
+## 功能概述
+
+粘贴审稿意见文本（主入口）/ 上传批注版 PDF（次要入口）→ LLM+正则拆条（Reviewer→Comment）
+→ 逐条填回复要点（5 类下拉，无 auto）→ 生成草稿（反幻觉校验前置）
+→ 逐条勾确认 → 拼装 response letter → 下载 `.md`（human_ack 门槛）。docx 属 Phase 2。
+
+## 10 个 API 端点（review_service:8100；BFF 8095 通用透传已验证可用）
+
+| 方法 | 路径 | 说明 |
+|---|---|---|
+| POST | /api/review/rebuttal/jobs | 文本粘贴主入口 |
+| POST | /api/review/rebuttal/jobs/pdf | PDF 次要入口（vstore 解析；非 PDF/超限→VALIDATION） |
+| GET | /api/review/rebuttal/jobs/{id} | 全量还原 |
+| PATCH | .../comments/{cid}/response | 保存 parts（改后旧 draft/validation 作废） |
+| POST | .../comments/{cid}/draft | 生成草稿（校验C前置；MISSING_RESPONSE 时不调 LLM） |
+| PATCH | .../comments/{cid}/structure | 手工 merge（≥2）/ split（≥2 非空子项） |
+| PATCH | .../comments/{cid}/confirm | 逐条勾；后端重算 human_ack（全勾才 true，空 job 不置位） |
+| POST | .../letter | 拼装 letter_md |
+| GET | .../letter.md | 下载（human_ack=false → 400 HUMAN_ACK_REQUIRED） |
+| DELETE | .../jobs/{id} | 手动删（替代 TTL） |
+
+信封错误复用约定：HTTP 200 + `{ok:false,error:{code,message,degraded}}`。
+
+## 数据模型
+
+- Job：`{id,status,source:{kind,filename,raw_text},template:'generic',reviewers:[...],letter_md,validation,human_ack,created_at,updated_at}`
+- Comment：`{id,group_id,severity,title,body,sub_items[],cross_refs[],response:{parts[]},draft,validation,human_confirmed}`
+- part.type 枚举：`new_data | reanalysis | location | clarification | rebuttal`（决策 2：无 auto）
+- SQLite 表 `rebuttal_jobs` 落在既有 `review_service/review.db`（自含短连接，不动 app/db.py）；
+  启动幂等建表（main lifespan）。
+
+## 关键实现决策（方案未写清处，按"保守、可测、不猜测"）
+
+1. **LLM 注入形态**：parse/draft 用 `async (messages, temperature) → dict` 回调，路由内适配
+   `llm.complete_json(system, user)`；单测直接 monkeypatch `llm.complete_json`。
+2. **拆条双轨**：正则先切骨架（Reviewer 段头 + 编号行，兼容行内 `. 2.` 编号）；
+   LLM 逐段出 `{title,severity,sub_items[]}`。LLM 失败/结构非法 → 该段回退正则
+   （title=首 60 字，severity=major）。`sub_items ≥2 且 max confidence ≥0.7` 才拆
+   （决策 3），拆出条目共享 group_id；未达阈值多子问题并回一条且 **body 保留段原文**
+   （不采信 LLM 改写）。
+3. **交叉引用**：`see comment N / 参见第 N 条 / 同上` → 解析目标 id；解析不到
+   `target_id=null` 保留 raw（不猜）。
+4. **反幻觉校验（负向词表收窄版）**：
+   - location：`shows that/as shown` 且无 `added/新增` → `LOCATION_EVIDENCE_WEAK` FAIL；
+   - rebuttal：命中 `we agree/accept/concede/you are right/we were wrong` →
+     `REBUTTAL_NEGATIVE` FAIL；无立场词（maintain/disagree/respectfully…）→
+     `REBUTTAL_NO_STANCE` FAIL；
+   - 其余三类 Phase 1 仅查非空。校验在 draft 端点前置，FAIL 不调 LLM。
+5. **human_ack**：confirm 端点改完后由 store 重算（所有 comment 全 true 才置位；
+   空 job 不置位防平凡真）。前端无法直接置位。
+6. **letter.md 下载**：纯文本端点（非信封），门槛失败返回 400 + 明文
+   `HUMAN_ACK_REQUIRED:…`；前端 `rebuttalDownloadLetterMd` 适配成 ApiError。
+7. **MISSING_RESPONSE**：draft 端点 parts 为空或全空内容 → 信封错误，LLM 调用次数=0
+   （单测断言）。
+8. **PDF 入口**：复用 vstore `parse_pdf_bytes`；校验顺序 = 非 .pdf → 空文件 → 超
+   `max_pdf_bytes`（50MB）→ 解析。与任务清单"PDF 超限/非 PDF"信封一致。
+9. **前端状态**：`store.rebuttal` 纯内存（切面板不丢、刷新丢——与任务"状态持久化"
+   不同诉求，Phase 1 未要求 localStorage）；draft 失败信封里的 job/validation 一并镜像。
+10. **不改禁区**：sdk/agent/vstore/未动；PresubmitPanel 等既有面板未动；无新增依赖。
+
+## 测试
+
+### 后端 pytest（9 例新增，全量 113 passed）
+
+```
+tests/test_rebuttal.py::test_single_reviewer_single_comment        PASSED
+tests/test_rebuttal.py::test_multi_reviewer_attribution            PASSED
+tests/test_rebuttal.py::test_subitem_split_shares_group_id         PASSED
+tests/test_rebuttal.py::test_location_validation_fail_and_pass     PASSED
+tests/test_rebuttal.py::test_rebuttal_validation                   PASSED
+tests/test_rebuttal.py::test_missing_response_no_llm_call          PASSED
+tests/test_rebuttal.py::test_cross_ref_unresolved_keeps_raw        PASSED
+tests/test_rebuttal.py::test_envelope_errors                       PASSED
+tests/test_rebuttal.py::test_human_ack_gate_on_letter_download     PASSED
+
+全量: 113 passed in 10.05s（104 基线 + 9 新增）
+```
+
+### 前端 vitest（5 例新增）
+
+```
+rebuttal.panel.test.js  5 passed（5 类下拉无 auto / location hint 条件显示 /
+未填禁用生成 / 未全确认禁用下载+横幅 / merge-split 仅 active 表单）
+全量: 387 passed | 5 failed（失败全部为已知 labels.js 引发的 benchpanel×4 +
+Composer .mode-pill×1 预存失败，与本次改动无关；基线 382P/5F → 387P/5F）
+```
+
+### build
+
+`npm run build` ✓ built in 3.04s
+
+## 手工冒烟（curl，8100 真 LLM + 真 SQLite）
+
+```
+POST /jobs（真实双 Reviewer 意见）→ ok=True job=rbt_ed245cd63b3a reviewers=2 comments=4
+  titles: 缺少FDR校正与q值报告 / Figure 3 blurry… / Missing coordinates… / Overstated novelty…
+POST draft（未填）          → ok=False code=MISSING_RESPONSE（LLM 0 调用）
+PATCH response(location 弱) + POST draft
+                          → ok=False VALIDATION_FAILED findings=[LOCATION_EVIDENCE_WEAK]
+PATCH response(location 合法) + POST draft → ok=True（真 LLM 草稿）
+PATCH response(rebuttal 让步词) + draft → VALIDATION_FAILED findings=[REBUTTAL_NEGATIVE]
+3 条合理回复（new_data/clarification/rebuttal）→ draft 全 ok=True
+GET letter.md（未全勾）    → HTTP 400 HUMAN_ACK_REQUIRED
+PATCH confirm ×3           → human_ack=False（c0001 漏勾，恰好验证逐条门槛）
+PATCH confirm c0001        → human_ack=True
+POST letter                → ok=True letter_md len=2731
+GET letter.md              → HTTP 200（/tmp/opencode/letter.md 落盘，含
+                             Response to Reviewers + 4 条原文/回复）
+DELETE job                 → ok=True meta={deleted:…}；GET → NOT_FOUND
+BFF 8095 探测 /rebuttal/jobs/nonexistent → HTTP 200（透传信封，REVIEW_ENABLED=1）
+```
+
+## 交付物清单
+
+| 文件 | 动作 |
+|---|---|
+| review_service/app/services/rebuttal_store.py | 新增（SQLite CRUD + human_ack 重算） |
+| review_service/app/services/rebuttal_parse.py | 新增（正则骨架 + LLM 拆分 + 交叉引用） |
+| review_service/app/services/rebuttal_draft.py | 新增（5 类 Prompt + 反幻觉校验 + letter） |
+| review_service/app/routers/rebuttal.py | 新增（10 端点） |
+| review_service/app/main.py | +import +include_router +lifespan 建表（约 8 行） |
+| review_service/tests/test_rebuttal.py | 新增（9 例） |
+| ui/src/api/review.js | +10 API 封装 + rebuttal 错误码未进 CODE_HINTS（后端原话直达） |
+| ui/src/stores/edu.js | +SECTIONS 'rebuttal' + rebuttal 状态块 + 10 actions |
+| ui/src/components/edu/panels/RebuttalPanel.vue | 新增（拆条树/逐条表单/校验红条/draft 预览/手工拆合/letter） |
+| ui/src/components/edu/EduSideNav.vue | +1 行菜单（审稿回复助手 💬） |
+| ui/src/components/edu/EduWorkspace.vue | +import +panelMap 挂载 |
+| tests/frontend/unit/edu/rebuttal.panel.test.js | 新增（5 例） |
+| docs/pr-reports/2026-10-12-rebuttal-phase1.md | 本报告 |
+
+## git status --short（新增部分）
+
+```
+?? docs/pr-reports/2026-10-12-rebuttal-phase1.md
+?? review_service/app/routers/rebuttal.py
+?? review_service/app/services/rebuttal_draft.py
+?? review_service/app/services/rebuttal_parse.py
+?? review_service/app/services/rebuttal_store.py
+?? review_service/tests/test_rebuttal.py
+?? tests/frontend/unit/edu/rebuttal.panel.test.js
+?? ui/src/components/edu/panels/RebuttalPanel.vue
+ M review_service/app/main.py
+ M ui/src/api/review.js
+ M ui/src/components/edu/EduSideNav.vue
+ M ui/src/components/edu/EduWorkspace.vue
+ M ui/src/stores/edu.js
+（此前 AI 预审稿修复的未 commit 改动保持原样，未混入本报告范围）
+```
+
+## 已知边界（Phase 1 明确不做）
+
+- docx 导出（Phase 2，python-docx 已在 lock 备用）；
+- job TTL 自动清理（决策 5：手动 DELETE 替代）；
+- 跨 Reviewer 合并（merge 限同 Reviewer 内）；
+- 刷新页面后 job 恢复（纯内存态；GET /jobs/{id} 已备，Phase 2 可接列表入口）。
@@ -0,0 +1,111 @@
+# PR 报告：P3b 编译 PDF Tab（论文重排版面板）
+
+- 日期：2026-10-13
+- 分支：`feature/p3b-compile-ui`（自最新 main 新开；未 commit，按用户约定统一处理）
+- 范围：`ui/` 面板 + store/api 扩展；`review_service/` 仅 restart.sh 调起预热脚本 + 新增
+  scripts/prewarm_tectonic.sh。**后端 compile.py / latex_compile.py（P3a）零改动**；
+  无 sdk/、agent/、vstore/ 改动；无新增依赖。
+
+## 概要
+
+P3b：论文重排版面板启用"编译 PDF" Tab，实现"上传 .tex → 服务器编译 → 下载 PDF"的完整闭环。
+
+## 修改内容
+
+| 文件 | 变更 |
+|---|---|
+| ui/src/components/edu/panels/ReformatPanel.vue | 编译 Tab 状态机：无 job_id 引导 / 编译按钮 / loading 动画 + 首次 1-3 分钟黄条（可关闭）/ 成功 blob URL iframe 预览 + 下载 + 耗时 + 重新编译 / 失败错误摘要 + log 尾 200 行折叠 + 完整 log 下载；按钮不 await，状态全由 store 驱动（切 Tab/切面板编译继续） |
+| ui/src/stores/edu.js | compileStatus/compileResult/compileError/compileLogTail + compilePdfUrl（blob URL，fetch 失败静默回退 pdf_url 直链）+ compileFirstHint；submitCompile（loading 重入保护）/ clearCompile（revoke blob）；重新排版自动 clearCompile |
+| ui/src/api/review.js | CODE_HINTS 增 QUEUE_FULL 固定文案"编译队列已满（最多 5 个任务），请稍后重试"（后端 message 带动态 pending 数，规范统一口径）；compileTex() 为 P3a 已有封装 |
+| review_service/restart.sh | 启动后后台调起 prewarm_tectonic.sh（nohup 非阻塞，日志 prewarm.log） |
+| review_service/scripts/prewarm_tectonic.sh（新增） | 最小 hello.tex 实编译以缓存 TeX 环境。**注**：tectonic v0.17.0 无 `download` 子命令（实测 `no subcommand download`），改用 tools/README 的最小 .tex 预编译法；失败仅告警不影响服务启动 |
+| tests/frontend/unit/edu/reformat.compile.test.js（新增） | 6 个用例（真实 reviewErrorMessage 经 importOriginal 保留，QUEUE_FULL 走 CODE_HINTS） |
+
+## 关键实现决策
+
+1. **无异步轮询**：后端编译同步阻塞返回（单槽队列，常规 10-30s，上限 `compile_queue_limit=5`），
+   无 stage 可显示 → loading 只做不确定时长旋转动画 + 文案说明。
+2. **QUEUE_FULL**：HTTP 429 + 同款信封，http.js 抛 ApiError(code=QUEUE_FULL)；
+   前端 CODE_HINTS 固定文案，报错后"重新编译"按钮立即可用（store finally 解锁）。
+3. **PDF blob URL**：成功后异步 `fetch(pdf_url) → blob → createObjectURL`，
+   预览/下载不暴露后端路径；jsdom/网络失败回退 pdf_url 直链，不阻塞渲染。
+4. **失败 log**：信封 detail = log 尾 200 行（折叠 `<pre>`）；完整 log 下载兜底拼
+   `/api/review/compile/{job_id}/log`（失败信封不带 log_url，但 job_id 即 anchor_id）。
+5. **首次编译提示条**：`compileFirstHint` 在首次 submitCompile 置位，loading 期间显示，
+   可手动关闭；`clearCompile`（重新排版）复位。
+6. **预热命令修正**：任务原文 `./tools/tectonic -X download default` 在钉死版本
+   v0.17.0 不存在——实测后改为最小 .tex 实编译预热（同 tools/README.md 建议）。
+
+## 测试结果
+
+- 后端 pytest（review_service，后端未动）：**113 passed**
+- 前端 vitest 全量：**403 passed / 5 failed**（5F = 既有 labels.js 基线失败
+  benchpanel×4 + Composer pill×1，与本 PR 无关）
+- vitest 新增 reformat.compile.test.js：**6/6 passed**
+  （无 job_id 引导 / 按钮可点 / 编译中+黄条+重入保护 / 成功 iframe+下载+耗时 /
+   失败 log 折叠 / QUEUE_FULL 文案+重试可用）
+- npm run build：✓ 3.12s
+
+## 手工冒烟（8100 真实链路）
+
+- reformat /tmp/opencode/reformat_sample.tex → ok=True job_id=b3631727af68
+- POST /compile {job_id=b3631727af68} → ok=True seconds=0.61 pdf_bytes=3596
+- GET /compile/{cid}/pdf → 200，3596 bytes，application/pdf（file: PDF 1.5）
+- GET /compile/{cid}/log → 200，3533 bytes
+- job_id 不存在 / 格式非法 → VALIDATION 信封
+- 坏 tex（\thisCommandDoesNotExist）→ COMPILE_FAILED + detail 尾 200 行
+  （含 "! Undefined control sequence"）
+- QUEUE_FULL → 429 + 信封（后端路径实测于 P3a；前端文案 vitest 6/6 覆盖）
+- scripts/prewarm_tectonic.sh → exit=0 OK，宏包缓存就绪
+
+## EPS 兼容性修复 v2（2026-10-14 追加）
+
+背景：真实 MDPI 官方 zip（v6.5a）上传编译在 XDV→PDF 阶段失败：
+`xdvipdfmx: image inclusion failed for "Definitions/logo-mdpi.eps"`。
+v1 回退逻辑 gate 在"zip 自带 `*-eps-converted-to.pdf` 预转换版"——真实官方 zip
+**不带**该文件（v1 本地 e2e 通过是因自造样本带了；测试样本与真实样本不一致，教训已记录）。
+
+v2 方案：**不依赖扫描引用与 zip 自带预转换版**，解压后扫描项目内所有 `.eps`
+批量现场转同名 `.pdf`（`latex_compile.process_eps_images`）：
+
+1. 工具优先级 **gs → epstopdf → ps2pdf**（`shutil.which` 逐个 fallback）；gs 命令
+   约束1 强制 `-dSAFER -dNOPAUSE -dBATCH -sDEVICE=pdfwrite -dPDFSETTINGS=/prepress`
+   （-dSAFER 防 EPS 内嵌任意 PostScript 执行）；无新 Python 依赖（subprocess）
+2. 约束2：单文件转换 **15s 超时** → warning 行 `[eps-convert] xxx.eps 转换超时`
+   并跳过该文件继续
+3. 约束3：单文件转换后 >20MB → warning；累计转换产物 >100MB →
+   `InspectError("ZIP_TOO_LARGE")` 中止（信封原样透出该 code）
+4. 约束4：`[eps-convert] {src} → {dst} ({in} → {out}, {elapsed}s, {tool})`
+   写入 `output.log`（正常/超时两条路径都落盘，引擎 log 之后、chatter 之前）
+5. 转换成功 → 显式 `X.eps` 引用字节替换为 `X.pdf`（.tex/.cls/.sty/.cfg/.def 全扫，
+   不碰编码、不改正文）；无扩展名引用 `{.../X}` 由 graphicx 命中新 `X.pdf`
+   （解析顺序 .pdf→…→.eps，规避 .eps）
+6. 全工具失败 → log 行 `[eps-convert] 全部工具失败，图片 xxx.eps 未转换` →
+   编译自然失败 → 前端提示「项目包含 EPS 图片，服务器转换失败，请转成 PDF/PNG 后重试」
+
+真实官方 zip 实测（`scripts/debug_compile.py` 重打包 fba37ae3c853 现场 + 8100 HTTP 链路）：
+
+| 指标 | 结果 |
+|---|---|
+| 转换 EPS 数 | 2（logo-mdpi.eps、logo-updates.eps，均 gs） |
+| 每个耗时 | 563678→13057B 0.27s；287998→16588B 0.27s（合计 0.54s） |
+| 显式引用改写 | 1 个文件（Definitions/mdpi.cls） |
+| 编译 | 2.83s（debug 脚本）/ 2.99s（HTTP） |
+| 产出 PDF | 70688 / 70687 bytes，7 页，`%PDF-` ✓ |
+
+测试：pytest **175 passed**（原 169 全保留，移除 3 个 v1 语义已变的 EPS 用例，
+新增 9 个 v2 用例：preset 免转换 / 真实 gs 转换 / 工具 fallback / 全失败 /
+超时 warning / 20MB warning / 100MB 中止 / 端到端成功 / 友好报错）。
+
+教训（关键）：**外部下载的模板类场景，e2e 必须用真实官方文件**——v1 的自造样本
+带了预转换版，真实官方 zip 不带，导致修复上线后失效。
+
+## 部署验证（部署后执行）
+
+```bash
+bash review_service/restart.sh
+# 观察日志：prewarm_tectonic.sh 后台跑（非阻塞），prewarm.log 出现 "[prewarm] OK"
+# 浏览器 → 教育科研 → 论文自动重排版 → 上传 .tex → 选期刊 → 重排版
+#        → 切"编译 PDF" → 点编译
+# 期望：首次 1-3 分钟（若预热已完成则秒级）、后续秒回；失败可见 log 尾 200 行
+```
@@ -0,0 +1,131 @@
+# P5 科研汇报助手 — PR 报告（2026-10-14，v4 更新 2026-10-15）
+
+## 概要
+
+新增「科研汇报助手」（P5）：论文 PDF/粘贴文本 → vstore 解析 → map-reduce LLM 大纲
+（5 场景 × 4 时长 × **14 版式**，逐条证据可溯）→ 逐页编辑 → python-pptx 本地生成
+16:9 PPTX 初稿（论文真图卡片化嵌入、分隔页主副标题、讲者备注携带证据引用）。
+全程只新增 `review_service/` 内代码 + BFF 既有 `REVIEW_ENABLED` 条件反代，
+禁区（RAG 核心、既有服务、前端 router/db）零改动。
+
+**v4 迭代（2026-10-15）**：① 副标题风格数改为动态读取 `GET /ppt/styles`（缺数据回落
+「多风格·图文混排」）② 章节分隔页加副标题（prompt 强制 `subtitle`、渲染 40pt 主标题 +
+20pt muted 副标题 + 底部 accent 装饰线、编辑器可改）③ 论文白底原图与页面底色融合
+（surface_2 圆角卡片 + 图注 + 宽/高上限 + 单图页居中留白）。
+
+## 修改内容
+
+### 后端（`review_service/`）
+
+| 类别 | 文件 | 说明 |
+| --- | --- | --- |
+| 改 | `app/config.py` | +`ppt_jobs_dir` / `ppt_styles_dir` 及 abs 属性（+14 行） |
+| 改 | `app/main.py` | 导入 ppt 路由、lifespan `ppt_ensure_table()`、挂载（+8 行） |
+| 改 | `tooling/requirements.lock` | **+3 行**：`pillow==12.3.0` / `python-pptx==1.0.2` / `xlsxwriter==3.2.9`（三者均已实装于统一 venv） |
+| 改 | `.gitignore` | +9 行：`ppt_jobs/` 运行数据、`prewarm.log`、`data/compile_jobs/`、`scripts/`、`data/review.db` |
+| 新 | `app/routers/ppt.py`（317 行） | **9 端点**：`GET /styles`、`POST /jobs`、`POST /jobs/pdf`、`GET/PATCH /jobs/{id}`、`POST /jobs/{id}/build`、`GET /jobs/{id}/pptx`、`GET /jobs/{id}/preview/{page}`、`DELETE /jobs/{id}` |
+| 新 | `app/services/ppt_outline.py`（917 行） | map-reduce 大纲核心（索引/配额/重验/裁剪/膨胀回修/分隔页 subtitle 规则） |
+| 新 | `app/services/ppt_build.py`（1176 行） | python-pptx 生成器（14 版式 token、字体栈、真图卡片容器、分隔页主副标题、讲者备注） |
+| 新 | `app/services/ppt_figure_index.py`（264 行） | 论文真图索引（para/图号 → 图片落盘与状态） |
+| 新 | `app/services/ppt_preview.py`（230 行） | 逐页 PNG 预览（供面板缩略图，失败不阻断） |
+| 新 | `app/services/ppt_store.py`（155 行） | `ppt_jobs` SQLite 持久化（约定 DDL 逐字实现） |
+| 新 | `data/ppt_styles/*.json`（14 个） | 版式 token 源码资产（随 git 走，`GET /styles` 的唯一数据源） |
+| 新 | `tests/test_ppt_*.py`（6 个 / 102 例） | outline / build / figure_index / preview / router / store |
+
+### 前端（`ui/` + `tests/`）
+
+| 类别 | 文件 | 说明 |
+| --- | --- | --- |
+| 改 | `ui/src/api/review.js`（+50 行） | PPT API 段 + `pptStyles()` |
+| 改 | `ui/src/stores/edu.js`（+147 行） | `ppt` 状态块 + actions + `pptLoadStyles` + `SECTIONS` 增列 |
+| 改 | `ui/src/components/edu/EduSideNav.vue` / `EduWorkspace.vue` | 菜单项 + PptPanel 注册（各 +2 行） |
+| 新 | `ui/src/components/edu/panels/PptPanel.vue`（578 行） | 生成表单 + 编辑器（动态风格数、分隔页副标题输入、逐页预览） |
+| 新 | `ui/src/components/edu/panels/ppt-styles.css`（40 行） | 面板样式 |
+| 新 | `ui/src/assets/ppt-style-cards/*.png`（14 个，约 21KB/个） | 版式卡面截图 |
+| 新 | `tests/frontend/unit/edu/ppt.panel.test.js`（12 例）/ `ppt.store.test.js`（7 例） | P5 前端单测 |
+| 改 | `tests/frontend/unit/b2/components.test.js`、`b3/benchpanel.test.js`、`bioflow/benchpanel.bioflow.test.js`、`tests/e2e/bench.spec.js` | **预存失败清零**：① tab 文案「提取任务」→「上传文献」（对齐 `51532a3`）② 模式 pill 断言改为「已随 `43a7c6c` 移除」 |
+
+**依赖偏差声明**：`python-pptx==1.0.2`（PyPI 最高 1.0.2；需求中 1.1.2 实为
+python-docx 版本，系记混，已在实现时更正）。`xlsxwriter==3.2.9` 当前无代码直接引用，
+属统一 venv `pip freeze` 的真实记录，一并同步锁文件——**合并前仍需人工确认这 3 行锁变更**。
+
+**DDL**（与约定逐字一致）：
+
+```sql
+ppt_jobs(id, status /*outline_ready|building|done|error*/, source_kind, filename,
+         raw_text, scenario, minutes, style_id, pages_json, pptx_path,
+         warnings_json, created_at, updated_at)
+```
+
+**API 前缀** `/api/review/ppt`（9 端点；业务错误一律 200 信封
+`{ok:false, error:{code,message,degraded}}`；二进制下载缺失时回同款信封 JSON）。
+
+### 关键渲染约定（v4）
+
+- **分隔页**：`section_bg` 底（缺则 `surface_2`→`cover_bg`→`bg`），40pt 居中粗体主标题 +
+  20pt muted 副标题（`bullets[0]` → `subtitle` → 该章第一页 title 三级兜底，浅底自动换深字）+
+  底部 30% 宽 accent 短线。
+- **真图卡片**：`surface_2` 圆角矩形（8px）容器 + 5mm 内边距，图居中、图注
+  `Fig N（论文 S?P?）` 10–12pt muted、与图区留 3mm；混排页图区 ≤55% 页宽且 ≤60% 页高，
+  单独图页居中、上下留白 ≥5%。
+
+## 测试结果（2026-10-15）
+
+```
+pytest（review_service 全库）: 215 passed in 13.7s   （P5 新增 102 → 113 + 102）
+vitest edu（tests/frontend/unit/edu）: 43 passed      （P5 新增 19：panel 12 + store 7）
+vitest 全量（tests/frontend/unit）: 32 files / 421 passed / 0 failed
+  —— 修掉 b2/b3/bioflow 共 5 个预存失败（文案改名 + 模式按钮移除）
+npm run build: ✓ built（chunk > 500kB 警告为预存）
+版式目检: 3 风格 × 10 页预览 PNG 渲染核对（分隔页主副标题/对比度回退、
+          混排图卡 ≤55%、单独图页居中留白）均符合预期
+```
+
+## 真实 e2e（v1 阶段记录：官方 MDPI 模板实例 PDF，16813 字符，真实 DeepSeek）
+
+```
+PDF 模式创建:   21.77s → 12 页（目标 [11,14]）warnings=0 llm_calls=7 unverified_evidence=0
+PATCH 编辑:     改写要点 + 新增无证据行 → evidence 同长重验、结构清洗 ✓
+build:          0.13s → 12 slides / 64157 B / 16:9（13.33×7.50in）逐页讲者备注 ✓
+python-pptx 回读: 12 页，S3 首条 = 人工改写文本 ✓
+编辑后下载:     ok=false NOT_FOUND（盘上旧文件存在但拒发，pptx_path 清空生效）✓
+text 模式:      15.0s → 9 页（目标 [8,10]）group_meeting / 10min / botanic-forest ✓
+短文本:         200 信封 VALIDATION「正文过短（<300 字），无法生成汇报大纲」✓
+清理:           双 DELETE → ppt_jobs 0 行、产物目录空 ✓
+```
+
+## 部署验证步骤
+
+1. 依赖：同步 `tooling/requirements.lock`（+3 行）并安装到统一 venv。
+2. 重启服务：`cd review_service && bash restart.sh`（8100）。
+3. 健康检查：`curl http://127.0.0.1:8100/health` → `status=ok`、`vstore connected=true`。
+4. 路由：`curl .../openapi.json` 确认 9 个 `/api/review/ppt/*` 路径在列（含 `/styles`）。
+5. BFF：`sdk/.env` 确认 `REVIEW_ENABLED=1`，走 8090 反代冒烟
+   `POST /api/review/ppt/jobs`（短文本应得 200 VALIDATION 信封，不打 LLM）。
+6. 真实链路：上传一篇论文 PDF → 出大纲 → 编辑分隔页副标题并保存 → build → 下载 PPTX →
+   用 python-pptx 核对页数、16:9 尺寸与分隔页副标题文本。
+7. 回归：`cd review_service && <venv>/bin/python -m pytest -q`；
+   `cd ui && npx vitest run` + `npm run build`。
+
+## 部署决策
+
+**建议：只合并，下次批量部署。** 本次改动对存量服务零影响（纯新增模块 +
+开关化反代），无数据迁移、无 schema 破坏性变更；单点重启 8100 即可生效，
+不值得为它单独发版，随下一次批量部署一并上即可。
+
+## 风险与回滚
+
+| 风险 | 影响 | 缓解 / 回滚 |
+| --- | --- | --- |
+| `python-pptx==1.0.2` 版本与需求（1.1.2）不一致 | 依赖锁未按原文落库 | 已声明偏差，合并前人工确认 3 行锁变更；如需回退直接还原 lock |
+| `xlsxwriter==3.2.9` 无代码引用 | 锁文件带入未用依赖 | venv 实况记录，可保留；若要求最小化可单独剔除该行 |
+| LLM 大纲偶发超时/无效 JSON | 创建接口报 `LLM_ERROR`/`LLM_INVALID` | 已分片 reduce + 单次膨胀回修 + 警告降级；前端可重试，无脏数据落库 |
+| quote 反查失败残留 evidence（2 条） | 个别要点 `unverified` | **Phase 2**：最长公共子串（≥20 字符）匹配补 `para_id`，失败保持 unverified（边际价值低，v4 不做） |
+| 编辑后旧 PPTX 残留盘上 | 无（`pptx_path` 清空后拒发，仅占磁盘） | 删除 job 时 `rmtree` 一并清理 |
+| 回滚 | — | 反向还原 12 个已跟踪文件改动 + 删除 44 个新增文件（后端 26 + 前端 18）即可；`ppt_jobs` 表与产物目录可留可删，不被其他模块引用 |
+
+## 与 `feature/p3b-compile-ui#4f9c077` 的关系
+
+v1 版报告曾以同一路径提交于该分支（`docs: add P5 PR report`），内容停留在 3 版式 /
+7 端点 / 208 pytest 阶段。本文件为 v4 权威版本；若两分支先后合入，同路径会产生一次
+文本冲突，取本文件（v4）内容即可。
@@ -0,0 +1,13 @@
+Reviewer #1:
+
+1. The GWAS analysis lacks multiple-testing correction. Please re-run with FDR control and report q-values for all significant loci. In addition, the sample size justification is missing — please add a power analysis or at least discuss the detectable effect size.
+
+2. Figure 3 is blurry and the axis labels are unreadable. As noted in Comment 3, the same issue applies to Figure S2. Please replace all figures with high-resolution versions.
+
+3. Minor: please add the standard error estimates to Supplementary Table 2.
+
+Reviewer #2:
+
+1. The claim of novelty overstates the advance relative to Zhang et al. 2023. The introduction should more clearly delineate what is new.
+
+2. How were the batch effects between the two sequencing centers corrected? This is essential to support the conclusions.
@@ -0,0 +1 @@
+"""paper_writer_service —— 论文撰写独立 MCP 服务（8097）。"""
@@ -0,0 +1,53 @@
+"""config.py —— paper 服务（8097）环境变量驱动配置（pydantic-settings）。
+
+全部键可用环境变量覆盖（前缀 PAPER_；LLM 沿用 docgen 的 DOCGEN_LLM_* 直连模式，
+由 services/paper/llm.py 直接读 os.environ）。零硬编码宿主路径：相对路径按 __file__ 推导。
+"""
+from __future__ import annotations
+
+from functools import lru_cache
+from pathlib import Path
+
+from pydantic_settings import BaseSettings, SettingsConfigDict
+
+_SERVICE_ROOT = Path(__file__).resolve().parent.parent  # paper_writer_service/
+
+
+def _resolve(v: str) -> str:
+    """仓库内相对路径按 __file__ 推导服务根解析为绝对路径。"""
+    p = Path(v).expanduser()
+    if not p.is_absolute():
+        p = _SERVICE_ROOT / p
+    return str(p)
+
+
+class Settings(BaseSettings):
+    model_config = SettingsConfigDict(
+        env_file=".env",
+        env_file_encoding="utf-8",
+        extra="ignore",
+        env_prefix="PAPER_",
+    )
+
+    app_name: str = "plantai-paper-writer-service"
+    version: str = "0.1.0"
+
+    db_path: str = "paper.db"                  # 独立 SQLite（与 BFF 完全隔离）
+    vstore_base_url: str = "http://127.0.0.1:8094"
+    read_timeout: float = 360.0                # write_paper_section 同步长调用读超时
+
+    @property
+    def db_path_abs(self) -> str:
+        return _resolve(self.db_path)
+
+    @property
+    def vstore_base(self) -> str:
+        return self.vstore_base_url.rstrip("/")
+
+
+@lru_cache(maxsize=1)
+def get_settings() -> Settings:
+    return Settings()
+
+
+settings = get_settings()
@@ -0,0 +1,168 @@
+"""db.py —— paper 服务独立 SQLite（aiosqlite + WAL，无 ORM），三张表。
+
+- papers：论文主表（brief/outline/final_markdown/references/disclaimer）
+- paper_sections：章节表（逐节 markdown + 状态）
+- citations：结构化引用（temp_n 生成期全局递增，final_n complete 按出现序重排写回）
+
+模式沿用 bioflow/docgen 同款：CREATE TABLE IF NOT EXISTS + aiosqlite 单连接 + WAL + 写锁。
+"""
+from __future__ import annotations
+
+import asyncio
+import json
+import logging
+import time
+from collections.abc import AsyncIterator, Iterable
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Any
+
+import aiosqlite
+
+from .config import get_settings
+
+logger = logging.getLogger(__name__)
+
+_SCHEMA = """
+CREATE TABLE IF NOT EXISTS papers (
+    id              TEXT PRIMARY KEY,
+    session_id      TEXT NOT NULL DEFAULT '',
+    title           TEXT NOT NULL DEFAULT '',
+    paper_type      TEXT NOT NULL DEFAULT '',
+    language        TEXT NOT NULL DEFAULT '',
+    format_req      TEXT NOT NULL DEFAULT '',
+    style           TEXT NOT NULL DEFAULT '',
+    status          TEXT NOT NULL DEFAULT 'outline',
+    brief_json      TEXT NOT NULL DEFAULT '{}',
+    outline_json    TEXT NOT NULL DEFAULT '{}',
+    final_markdown  TEXT NOT NULL DEFAULT '',
+    references_json TEXT NOT NULL DEFAULT '[]',
+    disclaimer      TEXT NOT NULL DEFAULT '',
+    created_at      TEXT NOT NULL,
+    updated_at      TEXT NOT NULL
+);
+CREATE INDEX IF NOT EXISTS idx_papers_session ON papers(session_id);
+CREATE INDEX IF NOT EXISTS idx_papers_status ON papers(status);
+
+CREATE TABLE IF NOT EXISTS paper_sections (
+    id          TEXT PRIMARY KEY,
+    paper_id    TEXT NOT NULL REFERENCES papers(id) ON DELETE CASCADE,
+    section_id  TEXT NOT NULL,
+    title       TEXT NOT NULL DEFAULT '',
+    key_points  TEXT NOT NULL DEFAULT '[]',
+    status      TEXT NOT NULL DEFAULT 'pending',
+    markdown    TEXT NOT NULL DEFAULT '',
+    word_count  INTEGER NOT NULL DEFAULT 0,
+    updated_at  TEXT NOT NULL,
+    UNIQUE(paper_id, section_id)
+);
+CREATE INDEX IF NOT EXISTS idx_paper_sections_paper ON paper_sections(paper_id);
+
+CREATE TABLE IF NOT EXISTS citations (
+    id             INTEGER PRIMARY KEY AUTOINCREMENT,
+    paper_id       TEXT NOT NULL REFERENCES papers(id) ON DELETE CASCADE,
+    section_id     TEXT NOT NULL DEFAULT '',
+    temp_n         INTEGER,
+    final_n        INTEGER,
+    kind           TEXT NOT NULL DEFAULT 'title',
+    ref_text       TEXT NOT NULL DEFAULT '',
+    source_doc_id  TEXT NOT NULL DEFAULT '',
+    snippet        TEXT NOT NULL DEFAULT '',
+    created_at     TEXT NOT NULL
+);
+CREATE INDEX IF NOT EXISTS idx_citations_paper ON citations(paper_id);
+"""
+
+
+def now_iso() -> str:
+    return datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ")
+
+
+def dumps_json(value: Any, default: Any = None) -> str:
+    try:
+        return json.dumps(value, ensure_ascii=False)
+    except (TypeError, ValueError):
+        return json.dumps(default, ensure_ascii=False)
+
+
+def loads_json(text: str | None, default: Any = None) -> Any:
+    if text is None:
+        return default
+    try:
+        return json.loads(text)
+    except (TypeError, ValueError):
+        return default
+
+
+class Database:
+    """aiosqlite 单连接封装（WAL；写串行化，同 bioflow 模式）。"""
+
+    def __init__(self, path: str | Path | None = None) -> None:
+        self._path: Path | None = Path(path) if path is not None else None
+        self._conn: aiosqlite.Connection | None = None
+        self._lock = asyncio.Lock()
+
+    @property
+    def path(self) -> Path:
+        if self._path is None:
+            self._path = Path(get_settings().db_path_abs)
+        return self._path
+
+    async def connect(self) -> None:
+        self.path.parent.mkdir(parents=True, exist_ok=True)
+        self._conn = await aiosqlite.connect(self.path)
+        self._conn.row_factory = aiosqlite.Row
+        await self._conn.execute("PRAGMA journal_mode=WAL")
+        await self._conn.execute("PRAGMA foreign_keys=ON")
+        await self._conn.execute("PRAGMA busy_timeout=5000")
+        await self._conn.executescript(_SCHEMA)
+        await self._conn.commit()
+
+    async def close(self) -> None:
+        if self._conn is not None:
+            await self._conn.close()
+            self._conn = None
+
+    @property
+    def conn(self) -> aiosqlite.Connection:
+        if self._conn is None:
+            raise RuntimeError("Database 未初始化：先 await init_db()")
+        return self._conn
+
+    async def fetchall(self, sql: str, params: Iterable[Any] = ()) -> list[aiosqlite.Row]:
+        async with self._conn.execute(sql, tuple(params)) as cursor:
+            return list(await cursor.fetchall())
+
+    async def fetchone(self, sql: str, params: Iterable[Any] = ()) -> aiosqlite.Row | None:
+        async with self._conn.execute(sql, tuple(params)) as cursor:
+            return await cursor.fetchone()
+
+    async def execute(self, sql: str, params: Iterable[Any] = ()) -> int:
+        async with self._lock:
+            cur = await self._conn.execute(sql, tuple(params))
+            await self._conn.commit()
+            return cur.lastrowid
+
+
+db = Database()
+
+
+async def init_db(path: str | Path | None = None) -> Database:
+    # 原地改单例路径后连接（不做 db = Database(path) 重赋值）：
+    # 服务模块以 `from ...db import db` 持有了该单例引用，重赋值会让它们拿到旧对象。
+    if path is not None:
+        db._path = Path(path)
+    await db.connect()
+    return db
+
+
+async def get_db() -> AsyncIterator[Database]:
+    yield db
+
+
+async def close_db() -> None:
+    await db.close()
+
+
+def monotonic() -> float:
+    return time.monotonic()
@@ -0,0 +1,84 @@
+"""main.py —— paper 服务应用入口（uvicorn 入口，明文白名单文件）。
+
+- 独立部署树 paper_writer_service/（FR：独立进程 8097 + 独立 SQLite paper.db）。
+- lifespan：init_db（幂等建表）→ 显式进入 MCP session_manager.run()（Starlette 不自动
+  运行子 Mount 的 lifespan，streamable-http 处理请求时要求 task group 已初始化）→ 清理。
+- 端点：/health（GET，BFF 探活反代）+ /mcp（MCP streamable-http）。
+- 不依赖 BFF/生产服务（8090 等绝不探测/连接）。
+"""
+from __future__ import annotations
+
+import logging
+from contextlib import asynccontextmanager
+
+from fastapi import FastAPI
+from fastapi.middleware.cors import CORSMiddleware
+
+from .config import get_settings
+from .db import close_db, db, init_db
+from .mcp import paper_mcp
+from .services.paper import search
+
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+# MCP streamable-http app（调用即创建 session_manager，供 lifespan 进入 run()）。
+# 端点地址：/mcp（streamable_http_path="/" + 挂载前缀 /mcp）。
+_paper_mcp_app = paper_mcp.streamable_http_app(streamable_http_path="/")
+
+
+def create_app() -> FastAPI:
+    settings = get_settings()
+    app = FastAPI(title=settings.app_name, version=settings.version)
+
+    app.add_middleware(
+        CORSMiddleware,
+        allow_origins=["*"],
+        allow_credentials=False,
+        allow_methods=["*"],
+        allow_headers=["*"],
+    )
+
+    @asynccontextmanager
+    async def _lifespan(_app: FastAPI):
+        # 测试注入：db 已由测试预置（init_db(tmp_path)），跳过启动初始化。
+        try:
+            await init_db()
+        except Exception:
+            logger.exception("main: 数据库初始化失败（health 将报 db 降级）")
+
+        # MCP session manager 的 task group 必须在服务运行期内保持活跃。
+        async with paper_mcp.session_manager.run():
+            try:
+                yield
+            finally:
+                try:
+                    await close_db()
+                except Exception:
+                    pass
+                await search.close_client()
+
+    app.router.lifespan_context = _lifespan
+
+    @app.get("/health")
+    async def health() -> dict[str, object]:
+        db_ok = True
+        db_error: str | None = None
+        try:
+            await db.fetchone("SELECT 1 AS ok")
+        except Exception as exc:  # noqa: BLE001
+            db_ok = False
+            db_error = str(exc)
+        return {
+            "ok": True,
+            "status": "ok" if db_ok else "degraded",
+            "db": {"connected": db_ok, "error": db_error},
+            "version": settings.version,
+        }
+
+    # paper MCP 能力外挂（mcp 2.x：MCPServer.streamable_http_app）。
+    app.mount("/mcp", _paper_mcp_app)
+    return app
+
+
+app = create_app()
@@ -0,0 +1,48 @@
+"""app/mcp.py —— paper_writer_service MCP server（单 streamable-http 端点 /mcp）。
+
+9 个工具：propose_paper_outline / write_paper_section / get_paper_progress / search_refs /
+revise_paper_section / revise_paper / get_paper / complete_paper / cancel_paper。
+
+mcp 2.x 注意：MCPServer（非 FastMCP，来自 mcp.server.mcpserver）；工具返回 dict，由 MCP
+序列化为 CallToolResult（structuredContent + content:[{type:"text",text:"<json>"}]）。
+本文件位于 app/ 层（非 services/），可用 pydantic（mcp 自身依赖 pydantic 构造 schema）。
+"""
+from __future__ import annotations
+
+from typing import Any
+
+from .services.paper import complete, outline, search, write
+
+
+def build_paper_mcp() -> Any:
+    from mcp.server.mcpserver import MCPServer
+
+    mcp = MCPServer(
+        "paper-writer",
+        title="PlantAI 论文撰写",
+        description="论文撰写能力单元：大纲生成/逐节撰写/文献引用/全文合并重排/修订。",
+    )
+
+    mcp.tool(name="propose_paper_outline",
+             description="根据论文主题与写作要求生成大纲并建论文（内部检索知识库注入选题线索）。")(outline.propose_paper_outline)
+    mcp.tool(name="write_paper_section",
+             description="撰写论文某一章节（同步长调用，90-180s）。按全局引用编号表生成正文与引用。")(write.write_paper_section)
+    mcp.tool(name="get_paper_progress",
+             description="查询论文与各章节撰写进度/字数/引用数。")(complete.get_paper_progress)
+    mcp.tool(name="search_refs",
+             description="在知识库(vstore)中检索与查询相关的文献片段。")(search.search_refs)
+    mcp.tool(name="revise_paper_section",
+             description="按用户意见重写论文某一章节，新引用追加到引用表末尾。")(write.revise_paper_section)
+    mcp.tool(name="revise_paper",
+             description="按用户意见判定需要修改哪些章节，返回受影响节清单与修订计划。")(write.revise_paper)
+    mcp.tool(name="get_paper",
+             description="拉取论文全文 markdown、参考文献列表与免责声明。")(complete.get_paper)
+    mcp.tool(name="complete_paper",
+             description="合并全文、按首次出现顺序重排引用编号、渲染 GB/T 7714 文献列表。")(complete.complete_paper)
+    mcp.tool(name="cancel_paper",
+             description="取消论文（置 cancelled）。")(complete.cancel_paper)
+
+    return mcp
+
+
+paper_mcp = build_paper_mcp()
@@ -0,0 +1,10 @@
+"""schemas.py —— paper 服务共享常量（明文白名单文件）。
+
+MCP 工具入参/出参均为 dict（由 mcp 层序列化为 content:[{type:text,text:<json>}]），
+本文件只放状态/引用类型常量，避免服务层散落魔法字面量。
+"""
+from __future__ import annotations
+
+PAPER_STATUSES = ("outline", "writing", "complete", "cancelled", "error")
+SECTION_STATUSES = ("pending", "writing", "done", "error")
+CITATION_KINDS = ("doi", "pmid", "title")
@@ -0,0 +1,65 @@
+"""cite.py —— 引用协议：GB/T 7714 渲染、[n] 校验、complete 按出现序重排。"""
+from __future__ import annotations
+
+import re
+from typing import Any
+
+_CITE_RE = re.compile(r"\[(\d+)\]")
+
+
+def find_cite_numbers(markdown: str | None) -> list[int]:
+    """正文中出现的所有 [n] 编号（含重复，按出现顺序）。"""
+    return [int(m) for m in _CITE_RE.findall(markdown or "")]
+
+
+def render_gbt7714(meta: dict[str, Any], *, fallback_year: str = "2026") -> str:
+    """按可用元数据渲染 GB/T 7714 近似条目。
+
+    - 有 DOI → [J/OL] + DOI
+    - 有 PMID → [J] + PMID
+    - 无 DOI/PMID（知识库资料）→ 降级格式 + [EB/OL]
+    """
+    title = (meta.get("title") or "").strip()
+    journal = (meta.get("journal") or "").strip()
+    authors = (meta.get("authors") or "").strip()
+    year = (meta.get("year") or fallback_year).strip()
+    doi = (meta.get("doi") or "").strip()
+    pmid = (meta.get("pmid") or "").strip()
+    head = f"{authors} " if authors else ""
+    if doi:
+        jpart = f"{journal}, {year}." if journal else f"{year}."
+        return f"{head}{title}[J/OL]. {jpart} DOI:{doi}."
+    if pmid:
+        jpart = f"{journal}, {year}." if journal else f"{year}."
+        return f"{head}{title}[J]. {jpart} PMID:{pmid}."
+    return f"{head}{title}. 知识库资料, {year}. [EB/OL]."
+
+
+def render_disclaimer() -> str:
+    return "参考文献依据知识库资料生成，格式为 GB/T 7714 近似，建议人工核对。"
+
+
+def first_appearance_order(full_markdown: str, temp_numbers: list[int]) -> list[int]:
+    """按全文首次出现顺序返回 temp_n；未出现的排最后（保持原序）。"""
+    seen: dict[int, int] = {}
+    for m in _CITE_RE.finditer(full_markdown or ""):
+        n = int(m.group(1))
+        if n not in seen and n in temp_numbers:
+            seen[n] = m.start()
+    ordered = sorted((n for n in temp_numbers if n in seen), key=lambda n: seen[n])
+    ordered += [n for n in temp_numbers if n not in seen]
+    return ordered
+
+
+def renumber_map(temp_numbers: list[int], full_markdown: str) -> dict[int, int]:
+    """temp_n → final_n（按全文首次出现顺序 1..N）。"""
+    ordered = first_appearance_order(full_markdown, temp_numbers)
+    return {temp: final for final, temp in enumerate(ordered, start=1)}
+
+
+def replace_numbers(markdown: str | None, mapping: dict[int, int]) -> str:
+    def _sub(m: re.Match[str]) -> str:
+        n = int(m.group(1))
+        return f"[{mapping.get(n, n)}]"
+
+    return _CITE_RE.sub(_sub, markdown or "")
@@ -0,0 +1,109 @@
+"""complete.py —— get_paper / get_paper_progress / complete_paper / cancel_paper。"""
+from __future__ import annotations
+
+from typing import Any
+
+from ...db import db, dumps_json, loads_json, now_iso
+from .cite import render_disclaimer, renumber_map, replace_numbers
+
+
+async def _load(paper_id: str) -> dict[str, Any]:
+    paper = await db.fetchone("SELECT * FROM papers WHERE id = ?", (paper_id,))
+    if not paper:
+        return {"ok": False, "code": "NOT_FOUND", "message": "论文不存在"}
+    sections = [dict(r) for r in await db.fetchall(
+        "SELECT * FROM paper_sections WHERE paper_id = ? ORDER BY rowid", (paper_id,))]
+    citations = [dict(r) for r in await db.fetchall(
+        "SELECT * FROM citations WHERE paper_id = ? ORDER BY temp_n", (paper_id,))]
+    return {"ok": True, "paper": dict(paper), "sections": sections, "citations": citations}
+
+
+def _merge_sections(paper: dict[str, Any], sections: list[dict[str, Any]]) -> str:
+    parts = [f"# {paper.get('title', '')}"]
+    for s in sections:
+        parts.append(f"\n## {s['title']}\n\n{s.get('markdown', '')}")
+    return "\n".join(parts)
+
+
+async def get_paper(paper_id: str, format: str = "md") -> dict[str, Any]:
+    p = await _load(paper_id)
+    if not p.get("ok"):
+        return p
+    paper, sections, citations = p["paper"], p["sections"], p["citations"]
+    full_markdown = paper.get("final_markdown") or _merge_sections(paper, sections)
+    references = loads_json(paper.get("references_json"), []) or [
+        {"n": c.get("final_n") or c.get("temp_n"), "text": c["ref_text"], "kind": c["kind"],
+         "source_doc_id": c["source_doc_id"]} for c in citations
+    ]
+    brief = loads_json(paper.get("brief_json"), {})
+    return {
+        "ok": True, "paper_id": paper_id, "title": paper["title"], "status": paper["status"],
+        "template_key": brief.get("template_key") or "document",
+        "brief": brief,
+        "sections": [
+            {"section_id": s["section_id"], "title": s["title"], "status": s["status"],
+             "word_count": s["word_count"]} for s in sections
+        ],
+        "full_markdown": full_markdown, "references": references,
+        "disclaimer": paper.get("disclaimer", ""),
+    }
+
+
+async def get_paper_progress(paper_id: str) -> dict[str, Any]:
+    paper = await db.fetchone("SELECT * FROM papers WHERE id = ?", (paper_id,))
+    if not paper:
+        return {"ok": False, "code": "NOT_FOUND", "message": "论文不存在"}
+    paper = dict(paper)
+    sections = [dict(r) for r in await db.fetchall(
+        "SELECT * FROM paper_sections WHERE paper_id = ? ORDER BY rowid", (paper_id,))]
+    cit_rows = [dict(r) for r in await db.fetchall(
+        "SELECT section_id, COUNT(*) AS c FROM citations WHERE paper_id = ? GROUP BY section_id", (paper_id,))]
+    cit_by_sec = {r["section_id"]: r["c"] for r in cit_rows}
+    current = next((s["section_id"] for s in sections if s["status"] != "done"), None)
+    return {
+        "ok": True, "paper_id": paper_id, "status": paper["status"], "current_section_id": current,
+        "sections": [
+            {"section_id": s["section_id"], "title": s["title"], "status": s["status"],
+             "word_count": s["word_count"], "citation_count": cit_by_sec.get(s["section_id"], 0)}
+            for s in sections
+        ],
+    }
+
+
+async def complete_paper(paper_id: str) -> dict[str, Any]:
+    p = await _load(paper_id)
+    if not p.get("ok"):
+        return p
+    paper, sections, citations = p["paper"], p["sections"], p["citations"]
+    full = _merge_sections(paper, sections)
+    temp_numbers = [c.get("temp_n") for c in citations if c.get("temp_n")]
+    mapping = renumber_map(temp_numbers, full)
+
+    final_full = replace_numbers(full, mapping)
+    for c in citations:
+        await db.execute("UPDATE citations SET final_n = ? WHERE id = ?", (mapping.get(c.get("temp_n")), c["id"]))
+    for s in sections:
+        await db.execute("UPDATE paper_sections SET markdown = ? WHERE id = ?",
+                         (replace_numbers(s.get("markdown"), mapping), s["id"]))
+
+    ordered = sorted(citations, key=lambda c: mapping.get(c.get("temp_n"), 0))
+    references = [
+        {"n": mapping.get(c.get("temp_n"), c.get("temp_n")), "text": c["ref_text"],
+         "kind": c["kind"], "source_doc_id": c["source_doc_id"]} for c in ordered
+    ]
+    has_degraded = any(c["kind"] == "title" for c in citations)
+    disclaimer = render_disclaimer() if has_degraded else ""
+    await db.execute(
+        "UPDATE papers SET status = 'complete', final_markdown = ?, references_json = ?, disclaimer = ?, updated_at = ? WHERE id = ?",
+        (final_full, dumps_json(references), disclaimer, now_iso(), paper_id),
+    )
+    return {"ok": True, "full_markdown": final_full, "references": references,
+            "renumber_map": mapping, "disclaimer": disclaimer}
+
+
+async def cancel_paper(paper_id: str) -> dict[str, Any]:
+    paper = await db.fetchone("SELECT id FROM papers WHERE id = ?", (paper_id,))
+    if not paper:
+        return {"ok": False, "code": "NOT_FOUND", "message": "论文不存在"}
+    await db.execute("UPDATE papers SET status = 'cancelled', updated_at = ? WHERE id = ?", (now_iso(), paper_id))
+    return {"ok": True}
@@ -0,0 +1,187 @@
+"""services/paper/llm.py —— LLM 调用（httpx 裸调，拷贝自 sdk/app/services/docgen/llm.py）。
+
+- complete_text(system, user, *, temperature=0.3, max_tokens=8000) -> str
+- complete_json(...)（response_format json_object + 一次 JSON 修复重试）
+- 4 次尝试（1.5s / 3s / 6s 指数退避，429 / 5xx / 超时）
+- env 键：DOCGEN_LLM_BASE_URL / DOCGEN_LLM_API_KEY / DOCGEN_LLM_MODEL / DOCGEN_LLM_TIMEOUT
+"""
+from __future__ import annotations
+
+import asyncio
+import json
+import logging
+import os
+from typing import Any
+
+import httpx
+
+logger = logging.getLogger(__name__)
+
+DEFAULT_LLM_BASE_URL = "https://api.deepseek.com/v1"
+DEFAULT_LLM_MODEL = "deepseek-chat"
+DEFAULT_LLM_TIMEOUT = 300.0
+BACKOFF_SECONDS = (1.5, 3.0, 6.0)
+MAX_ATTEMPTS = 4
+
+
+class LLMError(Exception):
+    """LLM 调用失败（重试尽/响应异常）。"""
+
+
+def _llm_config() -> dict[str, Any]:
+    return {
+        "base_url": (os.environ.get("DOCGEN_LLM_BASE_URL") or DEFAULT_LLM_BASE_URL).rstrip("/"),
+        "api_key": os.environ.get("DOCGEN_LLM_API_KEY", ""),
+        "model": os.environ.get("DOCGEN_LLM_MODEL") or DEFAULT_LLM_MODEL,
+        "timeout": float(os.environ.get("DOCGEN_LLM_TIMEOUT") or DEFAULT_LLM_TIMEOUT),
+    }
+
+
+def _extract_text(payload: dict[str, Any]) -> str:
+    try:
+        choices = payload.get("choices") or []
+        if choices:
+            content = choices[0].get("message", {}).get("content")
+            if isinstance(content, str):
+                return content
+            if isinstance(content, list):
+                return "".join(
+                    str(c.get("text", "")) if isinstance(c, dict) else str(c) for c in content
+                )
+    except Exception:
+        pass
+    return ""
+
+
+async def _chat_once(
+    client: httpx.AsyncClient,
+    cfg: dict[str, Any],
+    system: str,
+    user: str,
+    *,
+    temperature: float,
+    max_tokens: int,
+    json_mode: bool,
+    timeout: float | None = None,
+) -> str:
+    headers = {"Content-Type": "application/json"}
+    if cfg["api_key"]:
+        headers["Authorization"] = f"Bearer {cfg['api_key']}"
+    body: dict[str, Any] = {
+        "model": cfg["model"],
+        "messages": [
+            {"role": "system", "content": system},
+            {"role": "user", "content": user},
+        ],
+        "temperature": temperature,
+        "max_tokens": max_tokens,
+    }
+    if json_mode:
+        body["response_format"] = {"type": "json_object"}
+    resp = await client.post(
+        f"{cfg['base_url']}/chat/completions",
+        headers=headers,
+        json=body,
+        timeout=timeout if timeout is not None else cfg["timeout"],
+    )
+    resp.raise_for_status()
+    payload = resp.json()
+    if not isinstance(payload, dict):
+        raise LLMError("LLM 响应形态异常（非 JSON 对象）")
+    text = _extract_text(payload)
+    if not text:
+        raise LLMError("LLM 响应缺少 choices[0].message.content")
+    return text
+
+
+async def _complete(
+    system: str,
+    user: str,
+    *,
+    temperature: float,
+    max_tokens: int,
+    json_mode: bool,
+    timeout: float | None = None,
+) -> str:
+    cfg = _llm_config()
+    last_exc: BaseException | None = None
+    async with httpx.AsyncClient() as client:
+        for attempt in range(MAX_ATTEMPTS):
+            try:
+                return await _chat_once(
+                    client, cfg, system, user,
+                    temperature=temperature, max_tokens=max_tokens, json_mode=json_mode,
+                    timeout=timeout,
+                )
+            except LLMError:
+                raise
+            except (httpx.HTTPStatusError, httpx.HTTPError, httpx.TimeoutException) as exc:
+                last_exc = exc
+                status = getattr(getattr(exc, "response", None), "status_code", None)
+                retryable = status is None or status == 429 or status >= 500
+                if not retryable or attempt == MAX_ATTEMPTS - 1:
+                    raise LLMError(f"LLM 调用失败（HTTP {status or '网络'}）：{exc}") from exc
+                await asyncio.sleep(BACKOFF_SECONDS[min(attempt, len(BACKOFF_SECONDS) - 1)])
+    raise LLMError(f"LLM 调用失败：{last_exc}")
+
+
+async def complete_text(
+    system: str,
+    user: str,
+    *,
+    temperature: float = 0.3,
+    max_tokens: int = 8000,
+    timeout: float | None = None,
+) -> str:
+    """文本补全。失败抛 LLMError。"""
+    return await _complete(
+        system, user, temperature=temperature, max_tokens=max_tokens, json_mode=False,
+        timeout=timeout,
+    )
+
+
+def _repair_json(text: str) -> str:
+    text = text.strip()
+    if text.startswith("```"):
+        text = text.strip("`")
+        if text.lower().startswith("json"):
+            text = text[4:]
+        text = text.strip()
+    if not text:
+        raise LLMError("LLM 返回空内容")
+    if text.startswith("{"):
+        return text
+    start = text.find("{")
+    end = text.rfind("}")
+    if start >= 0 and end > start:
+        return text[start:end + 1]
+    raise LLMError("LLM 输出中未找到 JSON 对象")
+
+
+async def complete_json(
+    system: str,
+    user: str,
+    *,
+    temperature: float = 0.3,
+    max_tokens: int = 8000,
+) -> dict[str, Any]:
+    """JSON 补全（json_object + 一次修复重试）。"""
+    text = await _complete(
+        system, user, temperature=temperature, max_tokens=max_tokens, json_mode=True
+    )
+    try:
+        return json.loads(text)
+    except ValueError:
+        pass
+    text2 = await _complete(
+        system + "\n（重要：你的回答必须是单个合法 JSON 对象，不要输出其他任何内容）",
+        user,
+        temperature=temperature,
+        max_tokens=max_tokens,
+        json_mode=True,
+    )
+    try:
+        return json.loads(text2)
+    except ValueError:
+        repaired = _repair_json(text2)
+        return json.loads(repaired)
@@ -0,0 +1,113 @@
+"""outline.py —— propose_paper_outline：建 papers 行 → search_refs 注入线索 → LLM 出大纲 → 预填 sections。"""
+from __future__ import annotations
+
+import uuid
+from typing import Any
+
+from ...db import db, dumps_json, now_iso
+from . import llm, search
+
+_OUTLINE_SYSTEM = (
+    "你是植物学论文撰写助手。根据用户给出的论文主题与写作要求，生成论文大纲。"
+    "只输出一个合法 JSON 对象，结构为："
+    '{"title": 论文标题, "abstract_expect": 摘要预期内容(一句话), '
+    '"sections": [{"section_id": "s1", "title": "节标题", "key_points": ["要点1", "要点2"], "target_words": 1200}, ...]}。'
+    "章节 5-6 节，覆盖 引言/材料与方法/结果/讨论/结论 等综述常见结构；target_words 每节 1200-2500。"
+)
+
+_DEFAULT_SECTIONS = [
+    ("s1", "引言"),
+    ("s2", "材料与方法"),
+    ("s3", "结果"),
+    ("s4", "讨论"),
+    ("s5", "结论与展望"),
+]
+
+
+async def propose_paper_outline(
+    topic: str,
+    requirements: str = "",
+    paper_type: str = "",
+    language: str = "",
+    length: str = "",
+    format_req: str = "",
+    style: str = "",
+    kb_hints: list[dict[str, Any]] | None = None,
+    template_key: str = "",
+) -> dict[str, Any]:
+    # 1. 知识库线索：优先用调用方传入的 kb_hints，否则现场 search_refs（失败静默降级）
+    hints = list(kb_hints or [])
+    if not hints:
+        try:
+            r = await search.search_refs(query=topic, top_k=8)
+            hints = list(r.get("items") or [])
+        except Exception:
+            hints = []
+
+    # 2. LLM 出大纲
+    user = f"论文主题：{topic}\n"
+    if paper_type:
+        user += f"论文类型：{paper_type}\n"
+    if requirements:
+        user += f"写作要求：{requirements}\n"
+    if language:
+        user += f"语言：{language}\n"
+    if length:
+        user += f"篇幅：{length}\n"
+    if format_req:
+        user += f"格式：{format_req}\n"
+    if style:
+        user += f"风格：{style}\n"
+    if hints:
+        user += "可参考知识库文献线索（仅选题依据，非硬性引用）：\n" + "\n".join(
+            f"- {h.get('title', '')}: {str(h.get('snippet', ''))[:120]}" for h in hints[:5]
+        )
+    try:
+        outline = await llm.complete_json(_OUTLINE_SYSTEM, user)
+    except llm.LLMError as exc:
+        return {"ok": False, "code": "LLM_ERROR", "message": f"大纲生成失败：{exc}"}
+
+    title = str(outline.get("title") or topic).strip() or topic
+    sections = outline.get("sections") or []
+    if not sections:
+        sections = [
+            {"section_id": sid, "title": t, "key_points": [], "target_words": 1500}
+            for sid, t in _DEFAULT_SECTIONS
+        ]
+
+    # 3. 落库 papers + paper_sections
+    paper_id = uuid.uuid4().hex[:16]
+    await db.execute(
+        "INSERT INTO papers (id, title, paper_type, language, format_req, style, status, brief_json, outline_json, created_at, updated_at) "
+        "VALUES (?, ?, ?, ?, ?, ?, 'outline', ?, ?, ?, ?)",
+        (
+            paper_id, title, paper_type, language, format_req, style,
+            dumps_json({
+                "topic": topic, "requirements": requirements, "length": length,
+                "kb_hints": hints, "template_key": template_key,
+            }),
+            dumps_json({
+                "title": title,
+                "abstract_expect": outline.get("abstract_expect", ""),
+                "sections": sections,
+            }),
+            now_iso(), now_iso(),
+        ),
+    )
+    for s in sections:
+        await db.execute(
+            "INSERT INTO paper_sections (id, paper_id, section_id, title, key_points, status, updated_at) "
+            "VALUES (?, ?, ?, ?, ?, 'pending', ?)",
+            (
+                uuid.uuid4().hex[:16], paper_id,
+                s.get("section_id") or "s1", s.get("title", ""),
+                dumps_json(s.get("key_points") or []), now_iso(),
+            ),
+        )
+    return {
+        "ok": True,
+        "paper_id": paper_id,
+        "title": title,
+        "abstract_expect": outline.get("abstract_expect", ""),
+        "sections": sections,
+    }
@@ -0,0 +1,101 @@
+"""search.py —— vstore 8094 知识库检索客户端（search_refs 后端）。
+
+- httpx 裸调 GET /api/vstore/search-chunks
+- 失败不抛异常：返回 {"ok": False, "error": {...}}，工具层降级为空结果
+- vstore chunk 条目无 doi/pmid/journal/year（仅 doc_id/doc_name/snippet/score），
+  故 search_refs 的 meta 为尽力而为（通常为空）→ 引用多为 title kind → 降级格式 + disclaimer
+"""
+from __future__ import annotations
+
+import asyncio
+import os
+from typing import Any
+
+import httpx
+
+DEFAULT_VSTORE_BASE_URL = "http://127.0.0.1:8094"
+RETRY_BACKOFF = (0.5, 1.0, 2.0)
+MAX_RETRIES = 2
+DEFAULT_TIMEOUT = 30.0
+
+_client: httpx.AsyncClient | None = None
+
+
+def _base_url() -> str:
+    return (os.environ.get("VSTORE_BASE_URL") or DEFAULT_VSTORE_BASE_URL).rstrip("/")
+
+
+def get_client() -> httpx.AsyncClient:
+    global _client
+    if _client is None:
+        _client = httpx.AsyncClient(
+            base_url=_base_url(), timeout=httpx.Timeout(DEFAULT_TIMEOUT, connect=5.0)
+        )
+    return _client
+
+
+def set_client(client: httpx.AsyncClient) -> None:
+    """注入 client（测试用 MockTransport）。"""
+    global _client
+    _client = client
+
+
+async def close_client() -> None:
+    global _client
+    if _client is not None:
+        await _client.aclose()
+        _client = None
+
+
+async def search_chunks(
+    query: str,
+    *,
+    top_k: int = 8,
+    min_score: float = 0.30,
+    timeout: float = 12.0,
+) -> dict[str, Any]:
+    """GET /api/vstore/search-chunks。失败返回 {ok:False, error:{...}}（不抛）。"""
+    client = get_client()
+    last_exc: BaseException | None = None
+    for attempt in range(MAX_RETRIES + 1):
+        try:
+            resp = await client.get(
+                "/api/vstore/search-chunks",
+                params={"q": query, "top_k": top_k, "min_score": min_score},
+                timeout=timeout,
+            )
+            if resp.status_code < 500:
+                try:
+                    payload = resp.json()
+                except ValueError:
+                    return {"ok": False, "error": {"code": "BAD_RESPONSE", "message": "vstore 响应非 JSON"}}
+                if not isinstance(payload, dict):
+                    return {"ok": False, "error": {"code": "BAD_RESPONSE", "message": "vstore 响应形态异常"}}
+                return payload
+            last_exc = RuntimeError(f"vstore {resp.status_code}")
+        except (httpx.HTTPError, httpx.TimeoutException) as exc:
+            last_exc = exc
+        if attempt < MAX_RETRIES:
+            await asyncio.sleep(RETRY_BACKOFF[min(attempt, len(RETRY_BACKOFF) - 1)])
+    return {"ok": False, "error": {"code": "UPSTREAM_DOWN", "message": f"vstore 不可达：{last_exc}"}}
+
+
+async def search_refs(paper_id: str = "", query: str = "", top_k: int = 8) -> dict[str, Any]:
+    """search_refs 工具：透传 vstore 检索，映射为 {doc_id,title,snippet,score,meta}。"""
+    if not query:
+        return {"ok": False, "code": "BAD_REQUEST", "message": "缺少检索词 query"}
+    r = await search_chunks(query, top_k=max(1, min(int(top_k), 20)))
+    if not r.get("ok"):
+        return {"ok": True, "items": [], "warning": (r.get("error") or {}).get("message", "")}
+    items: list[dict[str, Any]] = []
+    for it in r.get("items") or []:
+        if not isinstance(it, dict):
+            continue
+        items.append({
+            "doc_id": it.get("doc_id") or "",
+            "title": it.get("doc_name") or it.get("doc_id") or "",
+            "snippet": it.get("snippet") or "",
+            "score": it.get("score"),
+            "meta": {},  # vstore chunk 无 doi/pmid/journal/year，尽力为空
+        })
+    return {"ok": True, "items": items}
@@ -0,0 +1,251 @@
+"""write.py —— 章节撰写与修订（write_paper_section / revise_paper_section / revise_paper）。"""
+from __future__ import annotations
+
+from typing import Any
+
+from ...db import db, dumps_json, loads_json, now_iso
+from . import llm
+from .cite import find_cite_numbers, render_gbt7714
+
+_WRITE_SYSTEM = (
+    "你是植物学论文撰写助手，正在撰写论文的某一章节。"
+    "引用文献一律用 [n] 指代，n 必须取自下方提供的全局编号列表；如需引用新文献，编号按当前最大编号依次 +1。"
+    "你只能引用「知识库线索」中列出的文献；新引用的元数据只能照抄线索里的 title 和 doc_id。"
+    "知识库线索里没有 DOI/PMID/作者/期刊/年份，这些字段一律输出空字符串，禁止编造任何 DOI/PMID/作者/期刊。"
+    "只输出一个合法 JSON 对象：{\"markdown\": 章节正文(不含章标题), \"citations_used\": "
+    "[{\"temp_n\": 编号, \"title\": \"...\", \"authors\": \"\", \"journal\": \"\", "
+    "\"year\": \"\", \"doi\": \"\", \"pmid\": \"\", \"source_doc_id\": \"...\", \"snippet\": \"...\"}]}。"
+    "citations_used 必须列出本节正文中出现的每一个 [n] 引用（既有编号也列出其已有元数据）。"
+)
+
+_REVISE_SYSTEM = (
+    "你是植物学论文撰写助手，正在按用户意见修订论文的某一章节。"
+    "保持引用协议不变：[n] 指代，n 只能取自全局编号列表或最大编号 +1；禁止杜撰元数据。"
+    "只输出一个合法 JSON 对象：{\"markdown\": 修订后的章节正文, \"citations_used\": [...]}。"
+)
+
+
+# ---------------------------------------------------------------------------
+# 读取辅助
+# ---------------------------------------------------------------------------
+
+async def _get_paper(paper_id: str) -> dict[str, Any] | None:
+    row = await db.fetchone("SELECT * FROM papers WHERE id = ?", (paper_id,))
+    return dict(row) if row else None
+
+
+async def _get_sections(paper_id: str) -> list[dict[str, Any]]:
+    rows = await db.fetchall(
+        "SELECT * FROM paper_sections WHERE paper_id = ? ORDER BY rowid", (paper_id,)
+    )
+    return [dict(r) for r in rows]
+
+
+async def _get_citations(paper_id: str) -> list[dict[str, Any]]:
+    rows = await db.fetchall(
+        "SELECT * FROM citations WHERE paper_id = ? ORDER BY temp_n", (paper_id,)
+    )
+    return [dict(r) for r in rows]
+
+
+def _global_citations_text(citations: list[dict[str, Any]]) -> str:
+    if not citations:
+        return "（当前无已编号文献；新引用从 [1] 开始）"
+    return "\n".join(f"[{c['temp_n']}] {c['ref_text']}" for c in citations)
+
+
+def _max_temp_n(citations: list[dict[str, Any]]) -> int:
+    return max((c.get("temp_n") or 0 for c in citations), default=0)
+
+
+def _build_write_user(paper: dict, outline: dict, sec: dict, cit_text: str, style: str, cite_mode: str) -> str:
+    parts: list[str] = []
+    parts.append(f"论文标题：{paper.get('title', '')}")
+    parts.append(f"论文类型：{paper.get('paper_type') or '综述'}")
+    parts.append(f"语言：{paper.get('language') or '中文'}")
+    parts.append(f"格式要求：{paper.get('format_req') or '无'}")
+    parts.append(f"写作风格：{style or paper.get('style') or '学术严谨'}")
+    parts.append("")
+    parts.append("论文大纲：")
+    for s in outline.get("sections") or []:
+        mark = "（当前撰写节）" if s.get("section_id") == sec.get("section_id") else ""
+        parts.append(f"- {s.get('section_id')}: {s.get('title')}{mark} 要点：{'；'.join(s.get('key_points') or [])}")
+    parts.append("")
+    parts.append(f"现在撰写章节「{sec.get('title', '')}」（section_id={sec.get('section_id')}）。")
+    if sec.get("key_points"):
+        parts.append("本节要点：" + "；".join(loads_json(sec.get("key_points"), [])))
+    parts.append("")
+    parts.append("全局已编号文献列表（[n] 引用只能从这里取值，或从最大编号 +1 起新增）：")
+    parts.append(cit_text)
+    brief = loads_json(paper.get("brief_json"), {})
+    kb_hints = brief.get("kb_hints") or []
+    if kb_hints:
+        parts.append("")
+        parts.append("知识库线索（新引用只能从这里选，元数据只照抄 title/doc_id）：")
+        for h in kb_hints:
+            parts.append(f"- title={h.get('title', '')} | doc_id={h.get('doc_id', '')} | snippet={str(h.get('snippet', ''))[:120]}")
+    return "\n".join(parts)
+
+
+def _validate_numbers(markdown: str, valid: set[int]) -> list[int]:
+    return [n for n in find_cite_numbers(markdown) if n not in valid]
+
+
+def _kind_of(meta: dict[str, Any]) -> str:
+    if meta.get("doi"):
+        return "doi"
+    if meta.get("pmid"):
+        return "pmid"
+    return "title"
+
+
+def _sanitize_citation(meta: dict[str, Any]) -> dict[str, Any]:
+    """丢弃 LLM 可能杜撰的 doi/pmid/authors/journal/year（知识库线索无这些字段），
+    只保留 title/source_doc_id/snippet，强制走 title kind 降级格式。"""
+    return {
+        "title": (meta.get("title") or "").strip(),
+        "source_doc_id": meta.get("source_doc_id") or "",
+        "snippet": meta.get("snippet") or "",
+    }
+
+
+async def _persist_new_citations(paper_id: str, section_id: str, used: list[Any], existing_nums: set[int]) -> list[dict[str, Any]]:
+    """把 citations_used 中的新引用（temp_n 不在既有集合）落库，返回新增摘要。"""
+    new_citations: list[dict[str, Any]] = []
+    seen_new: set[int] = set()
+    for c in used:
+        if not isinstance(c, dict):
+            continue
+        tn = int(c.get("temp_n") or 0)
+        if not tn or tn in existing_nums or tn in seen_new:
+            continue
+        seen_new.add(tn)
+        meta = _sanitize_citation(c)
+        ref_text = render_gbt7714(meta)
+        await db.execute(
+            "INSERT INTO citations (paper_id, section_id, temp_n, kind, ref_text, source_doc_id, snippet, created_at) "
+            "VALUES (?, ?, ?, ?, ?, ?, ?, ?)",
+            (
+                paper_id, section_id, tn, _kind_of(meta), ref_text,
+                meta.get("source_doc_id") or "", meta.get("snippet") or "", now_iso(),
+            ),
+        )
+        new_citations.append({"temp_n": tn, "ref_text": ref_text})
+    return new_citations
+
+
+# ---------------------------------------------------------------------------
+# 写节
+# ---------------------------------------------------------------------------
+
+async def write_paper_section(paper_id: str, section_id: str, style: str = "", cite_mode: str = "") -> dict[str, Any]:
+    paper = await _get_paper(paper_id)
+    if not paper:
+        return {"ok": False, "code": "NOT_FOUND", "message": "论文不存在"}
+    sections = await _get_sections(paper_id)
+    sec = next((s for s in sections if s["section_id"] == section_id), None)
+    if not sec:
+        return {"ok": False, "code": "NOT_FOUND", "message": "章节不存在"}
+    citations = await _get_citations(paper_id)
+    outline = loads_json(paper.get("outline_json"), {})
+    cit_text = _global_citations_text(citations)
+    existing_nums = {c.get("temp_n") for c in citations}
+
+    user = _build_write_user(paper, outline, sec, cit_text, style, cite_mode)
+    markdown = ""
+    used: list[Any] = []
+    bad: list[int] = []
+    for attempt in range(2):
+        try:
+            res = await llm.complete_json(_WRITE_SYSTEM, user, max_tokens=8000)
+        except llm.LLMError as exc:
+            return {"ok": False, "code": "LLM_ERROR", "message": f"写节 LLM 失败：{exc}"}
+        markdown = res.get("markdown") or ""
+        used = res.get("citations_used") or []
+        used_nums = {int(c.get("temp_n") or 0) for c in used if isinstance(c, dict)}
+        valid = existing_nums | used_nums
+        bad = _validate_numbers(markdown, valid)
+        if not bad:
+            break
+        user += f"\n（上次正文出现的引用编号 {sorted(bad)} 非法；只能使用已有编号或从 {_max_temp_n(citations) + 1} 起的新编号，重试。）"
+    else:
+        return {"ok": False, "code": "CITE_VALIDATION_FAILED", "message": f"引用编号非法：{sorted(bad)}"}
+
+    new_citations = await _persist_new_citations(paper_id, section_id, used, existing_nums)
+    await db.execute(
+        "UPDATE paper_sections SET markdown = ?, word_count = ?, status = 'done', updated_at = ? WHERE paper_id = ? AND section_id = ?",
+        (markdown, len(markdown), now_iso(), paper_id, section_id),
+    )
+    await db.execute("UPDATE papers SET status = 'writing', updated_at = ? WHERE id = ?", (now_iso(), paper_id))
+    return {"ok": True, "section_id": section_id, "status": "done", "markdown": markdown,
+            "citations_used": used, "new_citations": new_citations}
+
+
+# ---------------------------------------------------------------------------
+# 修订
+# ---------------------------------------------------------------------------
+
+async def revise_paper_section(paper_id: str, section_id: str, instruction: str) -> dict[str, Any]:
+    paper = await _get_paper(paper_id)
+    if not paper:
+        return {"ok": False, "code": "NOT_FOUND", "message": "论文不存在"}
+    sections = await _get_sections(paper_id)
+    sec = next((s for s in sections if s["section_id"] == section_id), None)
+    if not sec:
+        return {"ok": False, "code": "NOT_FOUND", "message": "章节不存在"}
+    citations = await _get_citations(paper_id)
+    outline = loads_json(paper.get("outline_json"), {})
+    existing_nums = {c.get("temp_n") for c in citations}
+
+    user = _build_write_user(paper, outline, sec, _global_citations_text(citations), "", "")
+    user += "\n\n原章节正文：\n" + (sec.get("markdown") or "")
+    user += f"\n\n修订要求：{instruction}"
+
+    markdown = ""
+    used: list[Any] = []
+    bad: list[int] = []
+    for attempt in range(2):
+        try:
+            res = await llm.complete_json(_REVISE_SYSTEM, user, max_tokens=8000)
+        except llm.LLMError as exc:
+            return {"ok": False, "code": "LLM_ERROR", "message": f"修订 LLM 失败：{exc}"}
+        markdown = res.get("markdown") or ""
+        used = res.get("citations_used") or []
+        used_nums = {int(c.get("temp_n") or 0) for c in used if isinstance(c, dict)}
+        valid = existing_nums | used_nums
+        bad = _validate_numbers(markdown, valid)
+        if not bad:
+            break
+        user += f"\n（引用编号 {sorted(bad)} 非法，重试。）"
+    else:
+        return {"ok": False, "code": "CITE_VALIDATION_FAILED", "message": f"引用编号非法：{sorted(bad)}"}
+
+    new_citations = await _persist_new_citations(paper_id, section_id, used, existing_nums)
+    await db.execute(
+        "UPDATE paper_sections SET markdown = ?, word_count = ?, status = 'done', updated_at = ? WHERE paper_id = ? AND section_id = ?",
+        (markdown, len(markdown), now_iso(), paper_id, section_id),
+    )
+    return {"ok": True, "section_id": section_id, "markdown": markdown,
+            "citations_used": used, "citation_delta": len(new_citations), "new_citations": new_citations}
+
+
+async def revise_paper(paper_id: str, instruction: str) -> dict[str, Any]:
+    """LLM 判定受影响章节，返回受影响节清单 + 修订计划（由调用方逐节 revise_paper_section）。"""
+    paper = await _get_paper(paper_id)
+    if not paper:
+        return {"ok": False, "code": "NOT_FOUND", "message": "论文不存在"}
+    sections = await _get_sections(paper_id)
+    outline = loads_json(paper.get("outline_json"), {})
+
+    system = (
+        "你是论文修订计划助手。根据用户修订意见与论文大纲，判定需要修改哪些章节。"
+        "只输出一个合法 JSON 对象：{\"affected_section_ids\": [\"s1\", ...], \"plan\": 修订计划(一句话)}。"
+    )
+    sec_list = "\n".join(f"{s['section_id']}: {s['title']}" for s in sections)
+    user = f"论文标题：{paper.get('title')}\n大纲章节：\n{sec_list}\n\n修订意见：{instruction}"
+    try:
+        res = await llm.complete_json(system, user, max_tokens=2000)
+    except llm.LLMError as exc:
+        return {"ok": False, "code": "LLM_ERROR", "message": f"修订计划 LLM 失败：{exc}"}
+    affected = [s for s in (res.get("affected_section_ids") or []) if any(x["section_id"] == s for x in sections)]
+    return {"ok": True, "affected_section_ids": affected, "plan": res.get("plan", "")}
@@ -0,0 +1,119 @@
+#!/usr/bin/env bash
+# build.sh —— PAPER 服务编译硬化（复制自 bioflow_service/build.sh，白名单改造）。
+# 白名单(明文)：app/main.py(uvicorn 入口)、app/config.py(运维可读面)、
+# app/schemas.py(常量面)、app/db.py(aiosqlite 协程取消热区——Cython 协程断流断言
+# abort 是既有教训，明文保留)、app/mcp.py(MCP 工具层，mcp 依赖 pydantic + async 工具)、
+# services/paper/{llm,search,write,outline,complete}.py(长 LLM/httpx/aiosqlite 调用，
+# 断流崩溃高危点，明文走 CPython 原生协程)+ 全部 __init__.py。
+# 仅纯同步逻辑(cite.py 等)可编译。
+# 用法:build.sh <source-root> <output-dir> [python]
+set -euo pipefail
+umask 027
+
+SOURCE_ROOT="${1:?Usage: $0 <source-root> <output-dir> [python]}"
+OUTPUT_DIR="${2:?Usage: $0 <source-root> <output-dir> [python]}"
+PYTHON="${3:-python3}"
+SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+VISIBILITY_TOOL="${ELF_VISIBILITY_TOOL:-$SCRIPT_DIR/../tooling/compile/tools/elf_visibility.py}"
+
+SOURCE_ROOT="$(realpath "$SOURCE_ROOT")"
+OUTPUT_DIR="$(realpath -m "$OUTPUT_DIR")"
+
+[[ -d "$SOURCE_ROOT" ]] || { echo "Paper service source missing: $SOURCE_ROOT" >&2; exit 2; }
+[[ -x "$PYTHON" ]] || { echo "Python is not executable: $PYTHON" >&2; exit 2; }
+[[ -f "$VISIBILITY_TOOL" ]] || { echo "ELF visibility tool missing: $VISIBILITY_TOOL" >&2; exit 2; }
+for command_name in gcc strip rsync; do command -v "$command_name" >/dev/null; done
+
+case "$OUTPUT_DIR" in
+  "/"|"$(realpath -m "$HOME")"|"$SOURCE_ROOT")
+    echo "Unsafe output directory: $OUTPUT_DIR" >&2; exit 2 ;;
+esac
+[[ ! -e "$OUTPUT_DIR" ]] || { echo "Output exists; refusing to overwrite: $OUTPUT_DIR" >&2; exit 2; }
+
+echo "[PAPER BUILD 1/5] Copying source (excluding tests)"
+mkdir -p "$OUTPUT_DIR"
+rsync -a --exclude '__pycache__' --exclude 'test_*.py' --exclude 'data' --exclude '.env' \
+  --exclude 'build.sh' --exclude 'restart.sh' --exclude 'pytest.ini' \
+  "$SOURCE_ROOT/" "$OUTPUT_DIR/"
+
+WHITELIST_PY=(
+  "app/main.py"
+  "app/config.py"
+  "app/schemas.py"
+  "app/db.py"
+  "app/mcp.py"
+  "app/services/paper/llm.py"
+  "app/services/paper/search.py"
+  "app/services/paper/write.py"
+  "app/services/paper/outline.py"
+  "app/services/paper/complete.py"
+)
+_is_whitelisted() {
+  local rel="$1"
+  [[ "$(basename "$rel")" == "__init__.py" ]] && return 0
+  for w in "${WHITELIST_PY[@]}"; do
+    case "$rel" in
+      $w) return 0 ;;
+    esac
+  done
+  return 1
+}
+
+echo "[PAPER BUILD 2/5] Discovering Python modules"
+PY_FILES=()
+while IFS= read -r -d '' path; do PY_FILES+=("$path"); done \
+  < <(find "$OUTPUT_DIR" -type f -name '*.py' -print0)
+FILTERED=()
+for py_file in "${PY_FILES[@]}"; do
+  rel="${py_file#"$OUTPUT_DIR"/}"
+  if _is_whitelisted "$rel"; then
+    echo "  [whitelist] $rel (明文保留)"
+    continue
+  fi
+  FILTERED+=("$py_file")
+done
+PY_FILES=("${FILTERED[@]}")
+TOTAL="${#PY_FILES[@]}"
+(( TOTAL > 0 )) || { echo "No paper service modules selected" >&2; exit 3; }
+
+INCLUDE_PY="$("$PYTHON" -c 'import sysconfig; print(sysconfig.get_config_var("INCLUDEPY") or "")')"
+EXT_SUFFIX="$("$PYTHON" -c 'import sysconfig; print(sysconfig.get_config_var("EXT_SUFFIX") or ".so")')"
+
+echo "[PAPER BUILD 3/5] Cython preflight ($TOTAL modules)"
+COUNT=0; FAILURES=0
+for py_file in "${PY_FILES[@]}"; do
+  COUNT=$((COUNT+1))
+  directory="$(dirname "$py_file")"
+  module="$(basename "$py_file" .py)"
+  c_file="$directory/$module.c"
+  echo "  [$COUNT/$TOTAL] ${py_file#"$OUTPUT_DIR"/}"
+  if ! "$PYTHON" -m cython -3 \
+      --directive always_allow_keywords=true,annotation_typing=False \
+      --no-docstrings "$py_file" -o "$c_file" 2>/dev/null; then
+    FAILURES=$((FAILURES+1))
+  fi
+done
+(( FAILURES == 0 )) || { echo "Paper service Cython failed: $FAILURES" >&2; exit 3; }
+
+echo "[PAPER BUILD 4/5] GCC hidden visibility + strip"
+COUNT=0
+for py_file in "${PY_FILES[@]}"; do
+  COUNT=$((COUNT+1))
+  directory="$(dirname "$py_file")"
+  module="$(basename "$py_file" .py)"
+  c_file="$directory/$module.c"
+  so_file="$directory/$module$EXT_SUFFIX"
+  gcc -shared -pthread -fPIC -O2 -fvisibility=hidden \
+    -I"$INCLUDE_PY" -o "$so_file" "$c_file"
+  strip --strip-unneeded "$so_file"
+  "$PYTHON" -B "$VISIBILITY_TOOL" --hide-non-pyinit --check "$so_file" >/dev/null
+  rm -f -- "$c_file" "$py_file"
+done
+
+echo "[PAPER BUILD 5/5] Final checks"
+SO_COUNT="$(find "$OUTPUT_DIR" -type f -name '*.so' | wc -l)"
+[[ "$SO_COUNT" -eq "$TOTAL" ]] || { echo "count mismatch: $TOTAL vs $SO_COUNT" >&2; exit 4; }
+if find "$OUTPUT_DIR" -type f -name '*.c' -print -quit | grep -q .; then
+  echo "Generated C source remains" >&2; exit 4
+fi
+echo "Paper service compile+harden complete: modules=$SO_COUNT output=$OUTPUT_DIR"
@@ -0,0 +1,6 @@
+[pytest]
+python_files = test_*.py
+markers =
+    paper_unit: 论文服务单元测试（引用协议/大纲/写节/重排/complete）
+    paper_mcp: MCP 协议互操作测试
+asyncio_mode = auto
@@ -0,0 +1,34 @@
+#!/usr/bin/env bash
+# restart.sh —— PAPER 服务重启脚本（8097；不触碰生产服务 8090/8091/8092/8093/8094/8098）。
+# 零硬编码：venv/python/仓库路径全部从脚本位置推导或环境变量覆盖。
+# 用法: restart.sh [python] [port]
+set -euo pipefail
+
+SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+REPO_ROOT="$(cd "$SCRIPT_DIR/.." && pwd)"
+PYTHON="${1:-$REPO_ROOT/../plantai-rag-new-venv/bin/python}"
+PORT="${2:-8097}"
+HOST="${PAPER_BIND_HOST:-127.0.0.1}"
+
+[[ -x "$PYTHON" ]] || { echo "Python not found: $PYTHON" >&2; exit 2; }
+
+APP_MODULE="app.main:app"
+if command -v lsof >/dev/null 2>&1; then
+  PID="$(lsof -ti tcp:"$PORT" -sTCP:LISTEN 2>/dev/null || true)"
+  if [[ -n "$PID" ]]; then
+    echo "[restart] 停止 $PORT 旧进程 pid=$PID"
+    kill $PID 2>/dev/null || true
+    sleep 2
+  fi
+fi
+
+cd "$SCRIPT_DIR"
+# 加载运行时配置（.env 不入 git）：services/paper/llm.py 直接读 DOCGEN_LLM_* 裸键，
+# search.py 读 VSTORE_BASE_URL——需 set -a 显式导出（同 bioflow_service/restart.sh 先例）。
+set -a
+[ -f .env ] && source .env
+set +a
+echo "[restart] 启动论文撰写服务 :$PORT（$PYTHON）"
+nohup "$PYTHON" -m uvicorn "$APP_MODULE" --host "$HOST" --port "$PORT" \
+  > "$SCRIPT_DIR/paper.log" 2>&1 &
+echo "[restart] 完成；日志 paper_writer_service/paper.log"
@@ -0,0 +1,27 @@
+# review_service/.env.example —— 运行时配置模板
+# 用法: cp .env.example .env  后填写（.env 已被仓库 .gitignore 忽略，勿提交）
+# restart.sh 会 `set -a; source .env` 导出给 uvicorn 进程。
+
+# ---- LLM（DeepSeek；REVIEW_LLM_* 优先 → DOCGEN_LLM_* 回退 → 内置默认，见 services/llm.py）----
+# 最简做法：从部署树抄一行即可复用同一把 key：
+#   grep '^DOCGEN_LLM_API_KEY=' /home/xzq/5090/teamWorkspace/zh/PlantAI-rag-new/sdk/.env >> .env
+REVIEW_LLM_BASE_URL=https://api.deepseek.com/v1
+REVIEW_LLM_API_KEY=
+REVIEW_LLM_MODEL=deepseek-chat
+#REVIEW_LLM_TIMEOUT=300
+
+# ---- 上游（只读消费）----
+#REVIEW_VSTORE_BASE_URL=http://127.0.0.1:8094
+#REVIEW_METHODOLOGY_BASE_URL=http://127.0.0.1:8092   # 预留（MinerU 重链路，当前未用）
+
+# ---- PDF 解析（经 vstore）----
+#REVIEW_PARSE_TIMEOUT=180          # ingest→取文→清理 总读超时（秒）
+#REVIEW_PARSE_DELETE_AFTER=1       # 1=解析后删除 vstore 临时文档（0=保留便于排查）
+
+# ---- 自审稿 ----
+#REVIEW_PRESUBMIT_READ_TIMEOUT=360 # LLM 长调用读超时（秒）
+#REVIEW_MAX_TEXT_CHARS=60000       # 送 LLM 的正文截断上限
+#REVIEW_MAX_PDF_BYTES=52428800     # 上传 PDF 上限 50MB
+
+# ---- 服务（restart.sh 读取）----
+#REVIEW_BIND_HOST=127.0.0.1
@@ -0,0 +1,7 @@
+"""review_service —— 科研投稿与智能审稿助手（8100）。
+
+独立部署树（模式同 paper_writer_service 8097 / bioflow_service 8098）：
+- BFF(sdk 8090) 经 routers/review_proxy.py 条件反代 /api/review/*（REVIEW_ENABLED）。
+- 上游只读消费：vstore 8094（PDF 解析）、DeepSeek（LLM，REVIEW_LLM_*/DOCGEN_LLM_*）。
+- 约束见根目录 AGENTS.md：审稿相关新代码只允许落在本目录。
+"""
@@ -0,0 +1 @@
+"""review 服务（8100）应用包。"""
@@ -0,0 +1,154 @@
+"""config.py —— review 服务（8100）环境变量驱动配置（pydantic-settings）。
+
+全部键可用环境变量覆盖（前缀 REVIEW_）。LLM 沿用 docgen 的裸键模式：
+优先 REVIEW_LLM_*，回退 DOCGEN_LLM_*（与 paper_writer_service 共享同一套
+DeepSeek 凭据，由 services/llm.py 直接读 os.environ）。零硬编码宿主路径。
+"""
+from __future__ import annotations
+
+from functools import lru_cache
+from pathlib import Path
+
+from pydantic_settings import BaseSettings, SettingsConfigDict
+
+
+class Settings(BaseSettings):
+    model_config = SettingsConfigDict(
+        env_file=".env",
+        env_file_encoding="utf-8",
+        extra="ignore",
+        env_prefix="REVIEW_",
+    )
+
+    app_name: str = "plantai-review-service"
+    version: str = "0.1.0"
+
+    # ---- 上游（只读消费；不修改 vstore/methodology 任何代码）----
+    # vstore 8094：POST /api/vstore/ingest + GET/DELETE /api/vstore/documents/{id}
+    # （pymupdf 段落解析，同步秒级；methodology 8092 的 MinerU 链路是
+    #   分钟级异步 job，不适配同步自审稿，仅预留地址供后续扩展）
+    vstore_base_url: str = "http://127.0.0.1:8094"
+    methodology_base_url: str = "http://127.0.0.1:8092"
+
+    # ---- PDF 解析 ----
+    parse_timeout: float = 180.0      # vstore ingest→fetch→delete 读超时（秒）
+    parse_delete_after: bool = True   # 解析完成后删除 vstore 临时文档（不污染私有库）
+
+    # ---- 自审稿（presubmit）----
+    presubmit_read_timeout: float = 360.0  # LLM 长调用读超时（秒）
+    max_text_chars: int = 150000            # 送 LLM 的正文截断上限（REVIEW_MAX_TEXT_CHARS 覆盖；
+                                            # token 超 48K 自动降 100K，LLM 400/413 再降 80K 重试）
+    max_pdf_bytes: int = 50 * 1024 * 1024   # 上传 PDF 上限 50MB（对齐 extraction FR-EXTRACT-004）
+
+    # ---- 期刊情报与投稿推荐（recommend）----
+    db_path: str = "review.db"              # 独立 SQLite（相对 review_service/；REVIEW_DB_PATH 覆盖）
+    journals_seed_path: str = "data/journals/journals.json"  # 种子（相对 review_service/）
+    journal_directory_seed_path: str = "data/journals/source_v4.xlsx"  # 目录源 xlsx（相对 review_service/）
+    seed_on_startup: bool = True            # 启动自动 seed journal_directory（空表才导；false 关闭）
+    vstore_match_timeout: float = 30.0      # scope 入库/向量检索读超时（秒）
+    recommend_read_timeout: float = 60.0    # LLM 重排读超时（秒）
+    recommend_query_chars: int = 3000       # 送 vstore 的检索 query 截断（防嵌入模型超长）
+    recommend_scope_top_k: int = 10         # search-chunks top_k（vstore 上限 20）
+
+    # ---- 论文重排版（reformat，P1：.tex 源码级变换，不编译）----
+    max_tex_bytes: int = 2 * 1024 * 1024    # 上传 .tex 上限 2MB（PDF 的 50MB 不适用）
+    reformat_dir: str = "data/reformat_jobs"  # 产物落盘（相对 review_service/）
+
+    # ---- LaTeX 编译 PDF（compile，P3：tectonic 单文件二进制）----
+    tectonic_path: str = "tools/tectonic"       # 相对 review_service/；也可绝对路径
+    tectonic_cache_dir: str = "data/tectonic-cache"  # 宏包缓存（部署时预热，运行期只读命中）
+    compile_timeout_s: float = 60.0             # 单次编译墙钟上限，超时整进程组 kill
+    max_compile_pdf_bytes: int = 50 * 1024 * 1024  # 产物 PDF 上限 50MB
+    compile_queue_limit: int = 5                # 等待槽位上限（>5 → QUEUE_FULL 429）
+    compile_retention_days: int = 7             # 编译产物保留天数（后台清扫）
+
+    # ---- LaTeX 项目 zip 编译（P4：两段式 inspect + run）----
+    max_zip_bytes: int = 50 * 1024 * 1024       # 上传 zip 上限 50MB
+    max_extract_bytes: int = 200 * 1024 * 1024  # 单项目解压总大小硬顶 200MB（实写字节计数）
+    max_zip_entries: int = 2000                 # 条目数上限（预扫第一件事）
+    max_zip_entry_bytes: int = 50 * 1024 * 1024 # 单条目解压上限 50MB
+    max_zip_ratio: float = 100.0                # 单条目压缩比 file_size/compress_size 上限
+    max_zip_path_depth: int = 16                # 路径深度上限（深层嵌套拒绝）
+    max_zip_path_len: int = 200                 # 单条目路径长度上限
+    compile_project_timeout_s: float = 120.0    # 项目 zip 编译墙钟上限（单文件仍 compile_timeout_s）
+    inspect_dir: str = "data/compile_inspect"   # zip 解压暂存（1 小时 TTL，相对 review_service/）
+    inspect_ttl_s: int = 3600                   # inspect 暂存过期秒数
+    inspect_sweep_interval_s: float = 300.0     # inspect 后台清扫周期（lifespan 定时任务）
+    compile_jobs_dir: str = "data/compile_jobs" # 项目编译产物（pdf/log/meta，7 天 sweep）
+    failed_project_ttl_s: int = 24 * 3600       # 编译失败保留 project/ 现场秒数（诊断用）
+    keep_failed_projects: bool = False          # 失败 project/ 永久保留（调试开关；
+                                                # 亦读裸环境变量 KEEP_FAILED_PROJECTS=1）
+
+    # ---- 科研汇报 PPT（P5：map-reduce 大纲 + python-pptx 初稿）----
+    ppt_jobs_dir: str = "data/ppt_jobs"      # 产物（draft.pptx + meta，相对 review_service/）
+    ppt_styles_dir: str = "data/ppt_styles"  # 风格 tokens JSON（源码资产，随 git 走）
+
+    @property
+    def _service_root(self) -> "Path":
+        # review_service/app/config.py → review_service/（相对本文件定位，不依赖 cwd）
+        return Path(__file__).resolve().parent.parent
+
+    @property
+    def db_path_abs(self) -> "Path":
+        # 绝对 db_path 会被 Path 除法原样返回；相对路径落在 review_service/ 下
+        return self._service_root / self.db_path
+
+    @property
+    def journals_seed_abs(self) -> "Path":
+        return self._service_root / self.journals_seed_path
+
+    @property
+    def journal_directory_seed_abs(self) -> "Path":
+        return self._service_root / self.journal_directory_seed_path
+
+    @property
+    def reformat_dir_abs(self) -> "Path":
+        p = Path(self.reformat_dir)
+        return p if p.is_absolute() else self._service_root / p
+
+    @property
+    def ppt_jobs_abs(self) -> "Path":
+        p = Path(self.ppt_jobs_dir)
+        return p if p.is_absolute() else self._service_root / p
+
+    @property
+    def ppt_styles_abs(self) -> "Path":
+        p = Path(self.ppt_styles_dir)
+        return p if p.is_absolute() else self._service_root / p
+
+    @property
+    def tectonic_abs(self) -> "Path":
+        p = Path(self.tectonic_path)
+        return p if p.is_absolute() else self._service_root / p
+
+    @property
+    def tectonic_cache_abs(self) -> Path:
+        p = Path(self.tectonic_cache_dir)
+        return p if p.is_absolute() else self._service_root / p
+
+    @property
+    def inspect_dir_abs(self) -> Path:
+        p = Path(self.inspect_dir)
+        return p if p.is_absolute() else self._service_root / p
+
+    @property
+    def compile_jobs_dir_abs(self) -> Path:
+        p = Path(self.compile_jobs_dir)
+        return p if p.is_absolute() else self._service_root / p
+
+
+    @property
+    def vstore_base(self) -> str:
+        return self.vstore_base_url.rstrip("/")
+
+    @property
+    def methodology_base(self) -> str:
+        return self.methodology_base_url.rstrip("/")
+
+
+@lru_cache(maxsize=1)
+def get_settings() -> Settings:
+    return Settings()
+
+
+settings = get_settings()
@@ -0,0 +1,191 @@
+"""app/db.py —— review 服务独立 SQLite（aiosqlite + WAL，无 ORM）：journals 表。
+
+- 单连接 + asyncio 写锁（模式对齐 paper_writer_service/bioflow，但表结构与种子
+  逻辑为本模块自研）；路径默认 review_service/review.db（REVIEW_DB_PATH 覆盖）。
+- 种子：data/journals/journals.json → journals 表（幂等 upsert，vstore_doc_id 列
+  永不被种子覆盖——该列记录 scope_desc 在 vstore 8094 的 document_id）。
+- 只在 review_service/ 内使用，不触碰 BFF/生产服务数据库。
+"""
+from __future__ import annotations
+
+import asyncio
+import json
+from pathlib import Path
+from typing import Any, Iterable
+
+import aiosqlite
+
+from .config import get_settings
+
+_SCHEMA = """
+CREATE TABLE IF NOT EXISTS journals (
+    id                 TEXT PRIMARY KEY,
+    name               TEXT NOT NULL,
+    scope_desc         TEXT NOT NULL,
+    impact_factor      REAL,
+    review_time_weeks  REAL,
+    acceptance_rate    REAL,
+    submission_deadline TEXT,
+    official_url       TEXT,
+    last_updated       TEXT NOT NULL,
+    vstore_doc_id      TEXT
+);
+"""
+
+# 种子 upsert 列（刻意不含 vstore_doc_id：种子刷新不得清掉向量库映射）
+_SEED_COLS = (
+    "id",
+    "name",
+    "scope_desc",
+    "impact_factor",
+    "review_time_weeks",
+    "acceptance_rate",
+    "submission_deadline",
+    "official_url",
+    "last_updated",
+)
+_UPSERT_SQL = (
+    "INSERT INTO journals (" + ", ".join(_SEED_COLS) + ") VALUES ("
+    + ", ".join("?" for _ in _SEED_COLS) + ") "
+    + "ON CONFLICT(id) DO UPDATE SET "
+    + ", ".join(f"{c}=excluded.{c}" for c in _SEED_COLS if c != "id")
+)
+
+
+class SeedError(Exception):
+    """种子文件缺失/损坏（journals.json 不可读）。"""
+
+
+class Database:
+    """aiosqlite 单连接封装（WAL；写串行化）。"""
+
+    def __init__(self, path: str | Path | None = None) -> None:
+        self._path: Path | None = Path(path) if path is not None else None
+        self._conn: aiosqlite.Connection | None = None
+        self._lock = asyncio.Lock()
+
+    @property
+    def path(self) -> Path:
+        if self._path is None:
+            self._path = get_settings().db_path_abs
+        return self._path
+
+    def set_path(self, path: str | Path) -> None:
+        """测试注入：在进入 TestClient lifespan 之前预置库路径（须尚未 connect）。"""
+        if self._conn is not None:
+            raise RuntimeError("Database 已连接，无法再改路径（先 close_db()）")
+        self._path = Path(path)
+
+    @property
+    def connected(self) -> bool:
+        return self._conn is not None
+
+    async def connect(self) -> None:
+        self.path.parent.mkdir(parents=True, exist_ok=True)
+        self._conn = await aiosqlite.connect(self.path)
+        self._conn.row_factory = aiosqlite.Row
+        await self._conn.execute("PRAGMA journal_mode=WAL")
+        await self._conn.execute("PRAGMA busy_timeout=5000")
+        await self._conn.executescript(_SCHEMA)
+        await self._conn.commit()
+
+    async def close(self) -> None:
+        if self._conn is not None:
+            await self._conn.close()
+            self._conn = None
+
+    @property
+    def conn(self) -> aiosqlite.Connection:
+        if self._conn is None:
+            raise RuntimeError("Database 未初始化：先 await init_db()")
+        return self._conn
+
+    async def fetchall(self, sql: str, params: Iterable[Any] = ()) -> list[dict[str, Any]]:
+        async with self.conn.execute(sql, tuple(params)) as cur:
+            rows = await cur.fetchall()
+        return [dict(r) for r in rows]
+
+    async def fetchone(self, sql: str, params: Iterable[Any] = ()) -> dict[str, Any] | None:
+        async with self.conn.execute(sql, tuple(params)) as cur:
+            row = await cur.fetchone()
+        return dict(row) if row is not None else None
+
+    async def execute(self, sql: str, params: Iterable[Any] = ()) -> int:
+        async with self._lock:
+            cur = await self.conn.execute(sql, tuple(params))
+            await self._conn.commit()  # type: ignore[union-attr]
+            return cur.lastrowid or 0
+
+    async def executemany(self, sql: str, seq: list[tuple[Any, ...]]) -> None:
+        async with self._lock:
+            await self.conn.executemany(sql, seq)
+            await self._conn.commit()  # type: ignore[union-attr]
+
+
+db = Database()
+
+
+async def init_db(path: str | Path | None = None) -> None:
+    """幂等初始化：已连接则跳过（测试可在 lifespan 前 set_path 注入路径）。"""
+    if path is not None:
+        db.set_path(path)
+    if db.connected:
+        return
+    await db.connect()
+
+
+async def close_db() -> None:
+    await db.close()
+
+
+def set_path(path: str | Path) -> None:
+    """同步注入库路径（测试 fixture 用；须在 init_db 之前调用）。"""
+    db.set_path(path)
+
+
+async def ensure_journals_seeded() -> int:
+    """装载种子期刊（幂等）。返回 journals 表行数。"""
+    row = await db.fetchone("SELECT COUNT(*) AS c FROM journals")
+    if row and int(row["c"]) > 0:
+        return int(row["c"])
+
+    seed_file = get_settings().journals_seed_abs
+    try:
+        payload = json.loads(Path(seed_file).read_text(encoding="utf-8"))
+    except FileNotFoundError as exc:
+        raise SeedError(f"期刊种子文件不存在：{seed_file}") from exc
+    except (OSError, ValueError) as exc:
+        raise SeedError(f"期刊种子文件不可读：{exc}") from exc
+
+    journals = payload.get("journals") if isinstance(payload, dict) else None
+    if not isinstance(journals, list) or not journals:
+        raise SeedError(f"期刊种子文件缺少 journals 数组：{seed_file}")
+
+    rows: list[tuple[Any, ...]] = []
+    for item in journals:
+        if not isinstance(item, dict) or not item.get("id") or not item.get("name"):
+            continue
+        rows.append(tuple(item.get(c) for c in _SEED_COLS))
+    if not rows:
+        raise SeedError(f"期刊种子文件无有效条目：{seed_file}")
+
+    await db.executemany(_UPSERT_SQL, rows)
+    return len(rows)
+
+
+async def list_journals() -> list[dict[str, Any]]:
+    """全部期刊（impact_factor 降序，NULL 靠后）。"""
+    return await db.fetchall(
+        "SELECT * FROM journals ORDER BY impact_factor DESC, name ASC"
+    )
+
+
+async def get_journal(journal_id: str) -> dict[str, Any] | None:
+    return await db.fetchone("SELECT * FROM journals WHERE id = ?", (journal_id,))
+
+
+async def set_vstore_doc_id(journal_id: str, doc_id: str) -> None:
+    """记录 scope_desc 在 vstore 的 document_id（向量白名单检索用）。"""
+    await db.execute(
+        "UPDATE journals SET vstore_doc_id = ? WHERE id = ?", (doc_id, journal_id)
+    )
@@ -0,0 +1,167 @@
+"""main.py —— review 服务应用入口（uvicorn 入口）。
+
+- 独立部署树 review_service/（科研投稿与智能审稿助手，端口 8100）。
+- 端点：/health（GET，BFF 探活反代）+ /api/review/*（自审稿等业务路由）。
+- 不依赖 BFF/生产服务（8090 等绝不探测/连接）；上游仅消费 vstore 8094。
+"""
+from __future__ import annotations
+
+import asyncio
+import logging
+import time
+from contextlib import asynccontextmanager
+
+import httpx
+from fastapi import FastAPI
+from fastapi.middleware.cors import CORSMiddleware
+
+from .config import get_settings
+from .db import close_db, db, init_db
+from .routers import (
+    compile,
+    conferences,
+    format_check,
+    journal_directory,
+    journals,
+    ppt,
+    presubmit,
+    reformat,
+    rebuttal,
+)
+
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+
+def create_app() -> FastAPI:
+    settings = get_settings()
+    app = FastAPI(title=settings.app_name, version=settings.version)
+
+    app.add_middleware(
+        CORSMiddleware,
+        allow_origins=["*"],
+        allow_credentials=False,
+        allow_methods=["*"],
+        allow_headers=["*"],
+    )
+
+    @asynccontextmanager
+    async def _lifespan(_app: FastAPI):
+        # journals 推荐依赖独立 SQLite：启动即建表（幂等；测试可先 set_path 注入
+        # tmp 路径，本函数沿用注入路径）
+        await init_db()
+        # rebuttal Phase 1：独立表，启动幂等建表（自含连接，不走 db.py）
+        try:
+            from .services.rebuttal_store import ensure_table
+            ensure_table()
+        except Exception:  # noqa: BLE001
+            logger.warning("rebuttal 建表失败（忽略）", exc_info=True)
+        # P5 科研汇报：ppt_jobs 独立表，启动幂等建表
+        try:
+            from .services.ppt_store import ensure_table as ppt_ensure_table
+            ppt_ensure_table()
+        except Exception:  # noqa: BLE001
+            logger.warning("ppt 建表失败（忽略）", exc_info=True)
+        # 编译产物过期清扫：启动跑一次（失败不阻塞启动）
+        try:
+            from .services.latex_compile import sweep_expired
+            sweep_expired()
+        except Exception:  # noqa: BLE001
+            logger.warning("compile sweep 启动清扫失败（忽略）", exc_info=True)
+        # P4：inspect 暂存（1h TTL）+ 项目编译产物（7 天）启动清扫
+        try:
+            from .services.latex_compile import (
+                sweep_compile_jobs_expired,
+                sweep_inspect_expired,
+            )
+            sweep_inspect_expired()
+            sweep_compile_jobs_expired()
+        except Exception:  # noqa: BLE001
+            logger.warning("P4 sweep 启动清扫失败（忽略）", exc_info=True)
+        # P4：inspect 暂存后台定时清扫（默认 300s；补充 1——上传不点编译不堆积）
+        sweep_task: asyncio.Task[None] | None = None
+        try:
+            from .services.latex_compile import sweep_inspect_expired as _sweep_insp
+
+            async def _inspect_sweep_loop() -> None:
+                interval = get_settings().inspect_sweep_interval_s
+                while True:
+                    await asyncio.sleep(interval)
+                    try:
+                        await asyncio.to_thread(_sweep_insp)
+                    except Exception:  # noqa: BLE001
+                        logger.warning("inspect 后台清扫失败（忽略）", exc_info=True)
+
+            sweep_task = asyncio.create_task(_inspect_sweep_loop())
+        except Exception:  # noqa: BLE001
+            logger.warning("inspect 后台清扫任务启动失败（忽略）", exc_info=True)
+        # journal_directory 自动 seed：空表才导（xlsx 解析约 1-3s，不堵 event loop；
+        # 路径沿用 db.path 注入链——生产=settings.db_path_abs，测试=tmp）
+        if settings.seed_on_startup:
+            try:
+                from .services.journal_seed import ensure_journal_directory_seeded
+                _t0 = time.time()
+                _result = await asyncio.to_thread(
+                    ensure_journal_directory_seeded, db.path)
+                if _result.get("seeded"):
+                    _c = _result.get("counts") or {}
+                    logger.info(
+                        "seeded %s rows (en=%s, zh=%s, %.1fs)",
+                        _result["rows"], _c.get("en"), _c.get("zh"),
+                        time.time() - _t0)
+                elif _result.get("error"):
+                    logger.warning(
+                        "journal_directory 启动 seed 失败（忽略，不阻塞启动）: %s",
+                        _result["error"])
+                else:
+                    logger.info("%s", _result.get("reason") or "journal_directory seed skipped")
+            except Exception:  # noqa: BLE001
+                logger.warning("journal_directory 启动 seed 失败（忽略，不阻塞启动）", exc_info=True)
+        else:
+            logger.info("journal_directory seed skipped (REVIEW_SEED_ON_STARTUP=false)")
+        try:
+            yield
+        finally:
+            if sweep_task is not None:
+                sweep_task.cancel()
+                try:
+                    await sweep_task
+                except asyncio.CancelledError:
+                    pass
+                except Exception:  # noqa: BLE001
+                    pass
+            await close_db()
+
+    app.router.lifespan_context = _lifespan
+
+    @app.get("/health")
+    async def health() -> dict[str, object]:
+        vstore_ok = False
+        vstore_error: str | None = None
+        try:
+            async with httpx.AsyncClient(timeout=2.0) as client:
+                resp = await client.get(f"{settings.vstore_base}/api/vstore/health")
+                resp.raise_for_status()
+                vstore_ok = bool(resp.json().get("ok"))
+        except Exception as exc:  # noqa: BLE001
+            vstore_error = str(exc)
+        return {
+            "ok": True,
+            "status": "ok" if vstore_ok else "degraded",
+            "upstreams": {"vstore": {"connected": vstore_ok, "error": vstore_error}},
+            "version": settings.version,
+        }
+
+    app.include_router(presubmit.router)
+    app.include_router(rebuttal.router)
+    app.include_router(journals.router)
+    app.include_router(format_check.router)
+    app.include_router(conferences.router)
+    app.include_router(journal_directory.router)
+    app.include_router(reformat.router)
+    app.include_router(compile.router)
+    app.include_router(ppt.router)
+    return app
+
+
+app = create_app()
@@ -0,0 +1 @@
+"""review 服务路由包。"""
@@ -0,0 +1,342 @@
+"""routers/compile.py —— LaTeX 编译 PDF（P3a：tectonic）。
+
+端点：
+  POST /api/review/compile               multipart：file(.tex 可选) | job_id(可选，二选一)
+                                         → {ok, compile_id, pdf_url, log_url, meta}
+  GET  /api/review/compile/{cid}         编译元信息（meta.json）
+  GET  /api/review/compile/{cid}/pdf     output.pdf（FileResponse）
+  GET  /api/review/compile/{cid}/log     output.log（text/plain）
+
+信封：业务错误 = HTTP 200 + {ok:false,error:{code,message,detail?,degraded:false}}
+（QUEUE_FULL 例外：HTTP 429 + 同款信封体，前端仍按 ok/error 单一口径处理）。
+detail = log 尾 200 行（COMPILE_FAILED / TIMEOUT）。
+"""
+from __future__ import annotations
+
+import json
+import logging
+import re
+import uuid
+from pathlib import Path
+from typing import Any
+
+from fastapi import APIRouter, File, Form, UploadFile
+from fastapi.responses import FileResponse, JSONResponse, PlainTextResponse
+from pydantic import BaseModel
+
+from ..config import get_settings
+from ..services import latex_compile as lc
+from ..services.latex_compile import (
+    CompileError,
+    QueueFullError,
+    ToolUnavailableError,
+)
+
+logger = logging.getLogger(__name__)
+
+router = APIRouter(prefix="/api/review", tags=["review-compile"])
+
+_CID_RE = re.compile(r"^[0-9a-f]{12}$")
+
+
+class CompileResponse(BaseModel):
+    ok: bool
+    compile_id: str | None = None
+    pdf_url: str | None = None
+    log_url: str | None = None
+    meta: dict[str, Any] | None = None
+    error: dict[str, Any] | None = None
+
+
+def _error(code: str, message: str, detail: str = "") -> CompileResponse:
+    err: dict[str, Any] = {"code": code, "message": message, "degraded": False}
+    if detail:
+        err["detail"] = detail
+    return CompileResponse(ok=False, error=err)
+
+
+def _jobs_root() -> Path:
+    d = get_settings().reformat_dir_abs
+    d.mkdir(parents=True, exist_ok=True)
+    return d
+
+
+@router.post("/compile", response_model=CompileResponse)
+async def compile_tex(
+    file: UploadFile | None = File(None, description="LaTeX 源码（.tex，与 job_id 二选一）"),
+    job_id: str = Form("", description="P1 重排版任务 id（优先于 file）"),
+) -> CompileResponse:
+    settings = get_settings()
+
+    # ---- 输入解析：job_id 优先，否则直接上传的 .tex ----
+    jid = (job_id or "").strip()
+    if jid:
+        if not _CID_RE.fullmatch(jid):
+            return _error("VALIDATION", "job_id 格式非法（应为 12 位 hex）")
+        src = _jobs_root() / f"{jid}.tex"
+        if not src.is_file():
+            return _error("VALIDATION", "job_id 对应的重排版结果不存在，请重新排版")
+        try:
+            source = src.read_text("utf-8")
+        except UnicodeDecodeError:
+            return _error("VALIDATION", "任务源码不是合法 UTF-8")
+        anchor_id = jid
+    else:
+        if file is None:
+            return _error("VALIDATION", "必须提供 file（.tex）或 job_id")
+        filename = file.filename or "paper.tex"
+        if Path(filename).name != filename or ".." in filename:
+            return _error("VALIDATION", "非法文件名")
+        if not filename.lower().endswith(".tex"):
+            return _error("VALIDATION", "仅支持 .tex 文件")
+        content = await file.read()
+        if not content:
+            return _error("VALIDATION", "上传文件为空")
+        if len(content) > settings.max_tex_bytes:
+            return _error("VALIDATION", "源码超过 2MB 上限")
+        try:
+            source = content.decode("utf-8")
+        except UnicodeDecodeError:
+            return _error("VALIDATION", "源码必须为 UTF-8 编码")
+        anchor_id = uuid.uuid4().hex[:12]
+
+    # ---- 编译（隔离目录；失败信封带 log 尾）----
+    lc.prepare_input(anchor_id, source)
+    try:
+        result = await lc.compile_tex(anchor_id)
+    except ToolUnavailableError as exc:
+        return _error("TOOL_UNAVAILABLE", str(exc))
+    except QueueFullError as exc:
+        return JSONResponse(
+            status_code=429,
+            content={
+                "ok": False,
+                "compile_id": None, "pdf_url": None, "log_url": None, "meta": None,
+                "error": {"code": "QUEUE_FULL", "message": str(exc), "degraded": False},
+            },
+        )
+    except CompileError as exc:
+        return _error(exc.code, str(exc), detail=exc.log_tail)
+
+    meta_path = lc.compile_dir(anchor_id) / "meta.json"
+    try:
+        meta = json.loads(meta_path.read_text("utf-8"))
+    except (OSError, ValueError):
+        meta = {"compile_id": anchor_id, "seconds": result["seconds"]}
+    return CompileResponse(
+        ok=True,
+        compile_id=anchor_id,
+        pdf_url=f"/api/review/compile/{anchor_id}/pdf",
+        log_url=f"/api/review/compile/{anchor_id}/log",
+        meta=meta,
+    )
+
+
+# ================================================================ P4：项目 zip（两段式）
+
+def _p4_error(code: str, message: str, detail: str = "",
+              compile_id: str | None = None,
+              log_url: str | None = None) -> CompileResponse:
+    """P4 错误信封（补充 3：失败也带 compile_id + log_url，前端可下载完整 log）。"""
+    err: dict[str, Any] = {"code": code, "message": message, "degraded": False}
+    if detail:
+        err["detail"] = detail
+    return CompileResponse(
+        ok=False, compile_id=compile_id, log_url=log_url, error=err)
+
+
+def _project_pdf_url(cid: str) -> str:
+    return f"/api/review/compile/zip/{cid}/pdf"
+
+
+def _project_log_url(cid: str) -> str:
+    return f"/api/review/compile/zip/{cid}/log"
+
+
+@router.post("/compile/inspect", response_model=CompileResponse)
+async def inspect_zip_project(
+    file: UploadFile = File(..., description="LaTeX 项目 zip（含 main.tex/.cls/图片/.bib）"),
+) -> CompileResponse:
+    """两段式之①：安全解压 + 主文件识别 → job_id（1 小时 TTL，run 前不占编译队列）。
+
+    暂用 request.body() 整体缓冲（≤50MB）；Phase 2 改流式上传
+    """
+    settings = get_settings()
+    filename = file.filename or "project.zip"
+    if Path(filename).name != filename or ".." in filename:
+        return _p4_error("VALIDATION", "非法文件名")
+    if not filename.lower().endswith(".zip"):
+        return _p4_error("VALIDATION", "仅支持 .zip 文件")
+    # 暂用 request.body() 整体缓冲（≤50MB）；Phase 2 改流式上传
+    content = await file.read()
+    if not content:
+        return _p4_error("VALIDATION", "上传文件为空")
+    if len(content) > settings.max_zip_bytes:
+        return _p4_error(
+            "VALIDATION",
+            f"zip 超过 {settings.max_zip_bytes // (1024 * 1024)}MB 上限")
+    try:
+        meta = await lc.inspect_zip(content)
+    except lc.InspectError as exc:
+        return _p4_error(exc.code, exc.message)
+    return CompileResponse(ok=True, meta=meta)
+
+
+class RunZipRequest(BaseModel):
+    job_id: str
+
+
+@router.post("/compile/run", response_model=CompileResponse)
+async def run_zip_compile(payload: RunZipRequest) -> CompileResponse:
+    """两段式之②：原子消费 inspect（rename 防并发双跑）→ tectonic 编译 → pdf/log。
+
+    队列/工具失败发生在消费**之前** → inspect 保留可重试；
+    编译失败（COMPILE_FAILED/TIMEOUT）信封仍带 compile_id + log_url（补充 3）。
+    """
+    jid = (payload.job_id or "").strip()
+    if not _CID_RE.fullmatch(jid):
+        return _p4_error(
+            "VALIDATION", "job_id 格式非法（应为 12 位 hex）")
+    try:
+        result = await lc.compile_project_job(jid)
+    except lc.InspectError as exc:
+        return _p4_error(exc.code, exc.message)
+    except lc.ToolUnavailableError as exc:
+        return _p4_error("TOOL_UNAVAILABLE", str(exc))
+    except lc.QueueFullError as exc:
+        # 队列满发生在 consume_inspect 之前 → job 未消费，前端可直接重试
+        return JSONResponse(
+            status_code=429,
+            content={
+                "ok": False,
+                "compile_id": None, "pdf_url": None, "log_url": None, "meta": None,
+                "error": {"code": "QUEUE_FULL", "message": str(exc),
+                          "degraded": False},
+            },
+        )
+    except lc.CompileError as exc:
+        # 补充 3：失败也带 compile_id + log_url（cid 由 compile_project_job 附加）
+        cid = getattr(exc, "compile_id", None)
+        return _p4_error(
+            exc.code, str(exc), detail=exc.log_tail,
+            compile_id=cid,
+            log_url=_project_log_url(cid) if cid else None)
+    return CompileResponse(
+        ok=True,
+        compile_id=result["compile_id"],
+        pdf_url=_project_pdf_url(result["compile_id"]),
+        log_url=_project_log_url(result["compile_id"]),
+        meta=json.loads((lc.compile_job_dir(result["compile_id"]) / "meta.json")
+                        .read_text("utf-8"))
+        if (lc.compile_job_dir(result["compile_id"]) / "meta.json").is_file()
+        else {"compile_id": result["compile_id"], "seconds": result["seconds"]},
+    )
+
+
+def _cid_dir(cid: str) -> Path | None:
+    if not _CID_RE.fullmatch(cid or ""):
+        return None
+    d = lc.compile_dir(cid)
+    return d if d.is_dir() else None
+
+
+def _zip_cid_dir(cid: str) -> Path | None:
+    """P4 项目产物目录 data/compile_jobs/{cid}/（独立于 P3a reformat_dir 树）。"""
+    if not _CID_RE.fullmatch(cid or ""):
+        return None
+    d = lc.compile_job_dir(cid)
+    return d if d.is_dir() else None
+
+
+@router.get("/compile/zip/{compile_id}", response_model=CompileResponse)
+async def get_zip_compile(compile_id: str) -> CompileResponse:
+    cdir = _zip_cid_dir(compile_id)
+    meta_path = cdir / "meta.json" if cdir else None
+    if meta_path is None or not meta_path.is_file():
+        return _p4_error("NOT_FOUND", "编译任务不存在或已过期，请重新编译")
+    try:
+        meta = json.loads(meta_path.read_text("utf-8"))
+    except (OSError, ValueError):
+        return _p4_error("NOT_FOUND", "编译产物损坏，请重新编译")
+    return CompileResponse(
+        ok=True,
+        compile_id=compile_id,
+        pdf_url=_project_pdf_url(compile_id),
+        log_url=_project_log_url(compile_id),
+        meta=meta,
+    )
+
+
+@router.get("/compile/zip/{compile_id}/pdf", response_model=None)
+async def download_zip_pdf(compile_id: str) -> FileResponse | JSONResponse:
+    cdir = _zip_cid_dir(compile_id)
+    pdf = cdir / "output.pdf" if cdir else None
+    if pdf is None or not pdf.is_file():
+        return JSONResponse(
+            status_code=200,
+            content={"ok": False, "error": {
+                "code": "NOT_FOUND", "message": "PDF 不存在或已过期",
+                "degraded": False}},
+        )
+    return FileResponse(pdf, media_type="application/pdf",
+                        filename=f"{compile_id}.pdf")
+
+
+@router.get("/compile/zip/{compile_id}/log", response_model=None)
+async def download_zip_log(compile_id: str) -> PlainTextResponse | JSONResponse:
+    """补充 3：成功/失败都可下载 output.log。"""
+    cdir = _zip_cid_dir(compile_id)
+    log = cdir / "output.log" if cdir else None
+    if log is None or not log.is_file():
+        return JSONResponse(
+            status_code=200,
+            content={"ok": False, "error": {
+                "code": "NOT_FOUND", "message": "日志不存在或已过期",
+                "degraded": False}},
+        )
+    return PlainTextResponse(log.read_text("utf-8", errors="replace"))
+
+
+@router.get("/compile/{compile_id}", response_model=CompileResponse)
+async def get_compile(compile_id: str) -> CompileResponse:
+    cdir = _cid_dir(compile_id)
+    meta_path = cdir / "meta.json" if cdir else None
+    if meta_path is None or not meta_path.is_file():
+        return _error("NOT_FOUND", "编译任务不存在或已过期，请重新编译")
+    try:
+        meta = json.loads(meta_path.read_text("utf-8"))
+    except (OSError, ValueError):
+        return _error("NOT_FOUND", "编译产物损坏，请重新编译")
+    return CompileResponse(
+        ok=True,
+        compile_id=compile_id,
+        pdf_url=f"/api/review/compile/{compile_id}/pdf",
+        log_url=f"/api/review/compile/{compile_id}/log",
+        meta=meta,
+    )
+
+
+@router.get("/compile/{compile_id}/pdf", response_model=None)
+async def download_compile_pdf(compile_id: str) -> FileResponse | JSONResponse:
+    cdir = _cid_dir(compile_id)
+    pdf = cdir / "output.pdf" if cdir else None
+    if pdf is None or not pdf.is_file():
+        return JSONResponse(
+            status_code=200,
+            content={"ok": False, "error": {
+                "code": "NOT_FOUND", "message": "PDF 不存在或已过期", "degraded": False}},
+        )
+    return FileResponse(pdf, media_type="application/pdf", filename=f"{compile_id}.pdf")
+
+
+@router.get("/compile/{compile_id}/log", response_model=None)
+async def download_compile_log(compile_id: str) -> PlainTextResponse | JSONResponse:
+    cdir = _cid_dir(compile_id)
+    log = cdir / "output.log" if cdir else None
+    if log is None or not log.is_file():
+        return JSONResponse(
+            status_code=200,
+            content={"ok": False, "error": {
+                "code": "NOT_FOUND", "message": "日志不存在或已过期", "degraded": False}},
+        )
+    return PlainTextResponse(log.read_text("utf-8", errors="replace"))
@@ -0,0 +1,209 @@
+"""routers/conferences.py —— 会议投稿时间线（只读静态种子）。
+
+- GET /api/review/conferences?domain=&ccf=&upcoming_days=180
+  data/journals/conferences.json → 过滤/排序 → 列表 + meta。
+- 数据诚实性铁律：每条会议必须带 deadline_source ∈ {placeholder, official}、
+  last_verified 与 deadline_confidence ∈ {high, medium, low}，缺失/非法条目加载时
+  跳过并记日志（宁缺毋造）；本端点无任何生成日期的逻辑，日期只来自种子常量。
+  v2 共 27/27 全 placeholder，meta.data_source_note 显式声明占位与置信度，
+  由前端渲染「⚠ 日期待核验」及置信度提示。
+- 过滤语义：domain 对 domain_tags 精确匹配（大小写不敏感）；ccf ∈ {A,B,C}；
+  upcoming_days=0 不过滤，>0 仅保留 deadline_full_paper ∈ [UTC now, now+N 天]，
+  缺失/不可解析截稿日期在过滤开启时排除。排序：deadline_full_paper 升序，
+  缺失/不可解析恒排最后。
+- 只读无写接口；文件不可读 → ok=false + DATA_UNAVAILABLE 信封；参数非法 →
+  VALIDATION 信封（均 HTTP 200，对齐本服务"错误信封永远 200"约定）。
+- 静态文件首次请求加载进内存（lru_cache），进程内 O(1)；不触碰 SQLite/BFF。
+"""
+from __future__ import annotations
+
+import json
+import logging
+from datetime import datetime, timedelta, timezone
+from functools import lru_cache
+from pathlib import Path
+from typing import Any
+
+from fastapi import APIRouter
+from pydantic import BaseModel
+
+logger = logging.getLogger(__name__)
+
+router = APIRouter(prefix="/api/review", tags=["review-conferences"])
+
+# review_service/app/routers/ → parents[2] = review_service（对齐 format_check 写法）
+_CONFERENCES_PATH = (
+    Path(__file__).resolve().parents[2] / "data" / "journals" / "conferences.json"
+)
+
+_CCF_OK = frozenset({"A", "B", "C"})
+_REQUIRED = ("id", "name", "deadline_source", "last_verified", "deadline_confidence")
+_CONFIDENCE_OK = frozenset({"high", "medium", "low"})
+_SOURCE_NOTE = (
+    "会议截稿/通知日期首版均为占位数据（deadline_source=placeholder），"
+    "接入官方渠道前须人工核验；deadline_confidence 标注日期置信度"
+    "（high=官方已公布/历年极稳定，medium=按历年规律推算，low=待核验）；"
+    "所有时间按 AoE (UTC-12) 时区。"
+)
+
+
+# ---- 请求/响应模型 ----
+
+class ConferenceItem(BaseModel):
+    """会议公开字段（种子全字段白名单；未知键丢弃）。"""
+    id: str
+    name: str
+    full_name: str = ""
+    domain_tags: list[str] = []
+    application_tags: list[str] = []
+    ccf_rank: str | None = None
+    deadline_abstract: str | None = None
+    deadline_full_paper: str | None = None
+    notification_date: str | None = None
+    conference_date: str | None = None
+    location: str | None = None
+    official_url: str | None = None
+    timezone_note: str | None = None
+    deadline_source: str
+    last_verified: str
+    deadline_confidence: str = ""
+
+
+class ConferencesResponse(BaseModel):
+    ok: bool
+    items: list[ConferenceItem] = []
+    meta: dict[str, Any] | None = None
+    error: dict[str, Any] | None = None
+
+
+def _error(code: str, message: str) -> ConferencesResponse:
+    return ConferencesResponse(
+        ok=False, items=[], meta=None,
+        error={"code": code, "message": message, "degraded": False},
+    )
+
+
+# ---- 种子加载（首次调用读盘，进程内缓存）----
+
+@lru_cache(maxsize=1)
+def _load_conferences() -> list[dict[str, Any]] | None:
+    """读 conferences.json → 合法会议列表；文件不可读 → None（DATA_UNAVAILABLE）。"""
+    try:
+        payload = json.loads(_CONFERENCES_PATH.read_text("utf-8"))
+    except (OSError, ValueError) as exc:
+        logger.warning("conferences: 种子文件不可读 %s: %s", _CONFERENCES_PATH, exc)
+        return None
+    raw = payload.get("conferences") if isinstance(payload, dict) else None
+    if not isinstance(raw, list):
+        logger.warning("conferences: 种子缺少 conferences 数组：%s", _CONFERENCES_PATH)
+        return None
+    items: list[dict[str, Any]] = []
+    for conf in raw:
+        if not isinstance(conf, dict):
+            continue
+        missing = [k for k in _REQUIRED if not conf.get(k)]
+        if missing:
+            logger.warning("conferences: 条目缺字段 %s（id=%s），跳过", missing, conf.get("id"))
+            continue
+        if conf.get("deadline_source") not in ("placeholder", "official"):
+            logger.warning(
+                "conferences: deadline_source 非法（id=%s），跳过", conf.get("id")
+            )
+            continue
+        if str(conf.get("deadline_confidence") or "").strip().lower() not in _CONFIDENCE_OK:
+            logger.warning(
+                "conferences: deadline_confidence 非法（id=%s），跳过", conf.get("id")
+            )
+            continue
+        items.append(conf)
+    return items
+
+
+def _parse_deadline(value: Any) -> datetime | None:
+    """截稿时间 → aware datetime（naive 视为 UTC）；非法 → None。"""
+    if not isinstance(value, str) or not value.strip():
+        return None
+    try:
+        dt = datetime.fromisoformat(value.strip())
+    except ValueError:
+        return None
+    return dt.replace(tzinfo=timezone.utc) if dt.tzinfo is None else dt
+
+
+# ---- GET /api/review/conferences ----
+
+@router.get("/conferences", response_model=ConferencesResponse)
+async def conferences_list(
+    domain: str = "",
+    ccf: str = "",
+    upcoming_days: int = 180,
+) -> ConferencesResponse:
+    """只读：会议投稿时间线（无写/删/改接口）。
+
+    - ?domain= 对 domain_tags 精确匹配（大小写不敏感），空=不过滤；
+    - ?ccf= ccf_rank ∈ A/B/C，空=不过滤，非法值 → VALIDATION 信封；
+    - ?upcoming_days= int≥0，默认 180；0=不过滤，>0 仅保留截稿在
+      [UTC now, now+N 天] 内的会议，负数 → VALIDATION 信封；
+    - 排序按 deadline_full_paper 升序，缺失/不可解析恒排最后；
+    - 空结果 → items=[] + meta.count=0（HTTP 200，不报错）。
+    """
+    ccf_norm = (ccf or "").strip().upper()
+    if ccf_norm and ccf_norm not in _CCF_OK:
+        return _error("VALIDATION", f"不支持的 ccf={ccf!r}，可选：A / B / C")
+    if upcoming_days < 0:
+        return _error(
+            "VALIDATION", f"upcoming_days 必须 ≥ 0，收到 {upcoming_days}"
+        )
+
+    all_items = _load_conferences()
+    if all_items is None:
+        return _error("DATA_UNAVAILABLE", "会议种子数据不可读，请联系管理员")
+
+    items = list(all_items)
+
+    dom = (domain or "").strip().casefold()
+    if dom:
+        items = [
+            c for c in items
+            if any(
+                str(t).strip().casefold() == dom
+                for t in (c.get("domain_tags") or [])
+            )
+        ]
+    if ccf_norm:
+        items = [
+            c for c in items
+            if str(c.get("ccf_rank") or "").strip().upper() == ccf_norm
+        ]
+    if upcoming_days > 0:
+        now = datetime.now(timezone.utc)
+        limit = now + timedelta(days=upcoming_days)
+        items = [
+            c for c in items
+            if (dl := _parse_deadline(c.get("deadline_full_paper"))) is not None
+            and now <= dl <= limit
+        ]
+
+    def _sort_key(c: dict[str, Any]) -> tuple[bool, datetime]:
+        dl = _parse_deadline(c.get("deadline_full_paper"))
+        if dl is None:
+            return (True, datetime.max.replace(tzinfo=timezone.utc))
+        return (False, dl)
+
+    items.sort(key=_sort_key)
+
+    out = [ConferenceItem(**c) for c in items]
+    verified = max(
+        (str(c.get("last_verified") or "") for c in all_items), default=""
+    )
+    meta: dict[str, Any] = {
+        "count": len(out),
+        "last_verified": verified or None,
+        "data_source_note": _SOURCE_NOTE,
+        "query": {
+            "domain": (domain or "").strip(),
+            "ccf": ccf_norm,
+            "upcoming_days": upcoming_days,
+        },
+    }
+    return ConferencesResponse(ok=True, items=out, meta=meta, error=None)
@@ -0,0 +1,81 @@
+"""routers/format_check.py —— 版式与规范检查（POST /api/review/format-check）。
+
+纯规则引擎（services/format_check.py）：PDF/Word 本地解档取版式元数据 +
+journals.json 规则集（format_rules_default + 每条 format_rules 带 rules_source）。
+无 LLM / 无 vstore，同步执行通常 <1s；恒 200 + {ok, checks, summary, meta|error} 信封。
+"""
+from __future__ import annotations
+
+import logging
+
+from fastapi import APIRouter, File, Form, UploadFile
+from pydantic import BaseModel
+
+from ..config import get_settings
+from ..services import format_check
+
+logger = logging.getLogger(__name__)
+
+router = APIRouter(prefix="/api/review", tags=["review-format"])
+
+
+class CheckItem(BaseModel):
+    key: str
+    name: str
+    status: str  # pass | warn | fail
+    detail: str
+    suggestion: str = ""
+
+
+class FormatCheckResponse(BaseModel):
+    ok: bool
+    checks: list[CheckItem] | None = None
+    summary: dict[str, int] | None = None
+    meta: dict[str, object] | None = None
+    error: dict[str, object] | None = None
+
+
+def _error(code: str, message: str, *, degraded: bool = False) -> FormatCheckResponse:
+    return FormatCheckResponse(
+        ok=False, error={"code": code, "message": message, "degraded": degraded},
+    )
+
+
+@router.post("/format-check", response_model=FormatCheckResponse)
+async def format_check_endpoint(
+    file: UploadFile = File(..., description="待检查的 PDF / Word(.docx) / LaTeX(.tex) 文档"),
+    target_journal: str = Form("", description="目标期刊（可选，传 journals 的 id）"),
+) -> FormatCheckResponse:
+    settings = get_settings()
+
+    filename = file.filename or ""
+    low = filename.lower()
+    if low.endswith(".pdf"):
+        kind = "pdf"
+    elif low.endswith(".docx"):
+        kind = "docx"
+    elif low.endswith(".tex"):
+        kind = "tex"
+    else:
+        return _error("VALIDATION", "仅支持 PDF / Word（.docx）/ LaTeX（.tex）文件")
+
+    content = await file.read()
+    if not content:
+        return _error("VALIDATION", "上传文件为空")
+    if len(content) > settings.max_pdf_bytes:
+        return _error("VALIDATION", "上传文件超过 50MB 上限")
+
+    try:
+        result = format_check.check_document(content, kind, (target_journal or "").strip())
+    except format_check.FormatCheckError as exc:
+        logger.warning("format-check: 解档失败：%s", exc)
+        return _error("PARSE_FAILED", str(exc))
+
+    meta = dict(result.get("meta") or {})
+    meta["filename"] = filename
+    return FormatCheckResponse(
+        ok=True,
+        checks=[CheckItem(**c) for c in result["checks"]],
+        summary=result["summary"],
+        meta=meta,
+    )
@@ -0,0 +1,280 @@
+"""routers/journal_directory.py —— 期刊目录浏览（1056 本，只读分页）。
+
+- GET /api/review/journals/directory：journal_directory 表（scripts/import_journals.py
+  导入的 v4 目录：2025 中科院分区 + 2025 JIF（2026 年 JCR 发布）+ 年报 2025 版
+  （中文统计年 2024）+ 官网网址/核对状态）→ 过滤/排序/分页 → 列表 + meta。
+- 与 GET /journals（journals.json 精选 5 本，供 FormatPanel 下拉/recommend 语义）物理
+  分离（方案 A）；本端点绝不读写 journals 表，recommend/journal_kb/journal_rank 零触碰。
+- 读路径只 SELECT；表由导入脚本拥有（db.py 零改动）；表不存在 → data_imported=false
+  优雅降级（HTTP 200 空列表）。
+
+读时归一化（拍板细节 1-3，均在 API 层做，不动脚本/DB 原值）：
+  细节1 lang=zh → cas_partition 恒 null + cas_partition_note="不按中科院分区口径列示"；
+  细节2 jif_note 源文本映射（v4 值域已是用户可读文本，旧值映射保留兜底）；
+  细节3 缺值即矛盾清零：en 且 jif=null → jif_source_url=null。
+        （zh 的 IF 载体是 composite/comprehensive，其 jif_source_url 本恒 null。）
+  决策2：响应不下发"来源"文本字段（partition_source/jif_source/data_source_label
+        已移除）；jif_source_url/data_source_url 保留供展开行链接。
+  决策4（来源展示优化）：partition_source_url 不再下发——DB 原值分毫未动
+        （仍 SELECT * 读出后被模型丢弃），响应改为常量字段 partition_source_note
+        文案，前端以灰色说明文字替代原"分区来源"超链接。
+        新增 official_check_status / jcr_release_year。
+"""
+from __future__ import annotations
+
+import json
+import logging
+import sqlite3
+from typing import Any
+
+from fastapi import APIRouter
+from pydantic import BaseModel
+
+from ..db import db
+
+logger = logging.getLogger(__name__)
+
+router = APIRouter(prefix="/api/review", tags=["review-directory"])
+
+_LANGS = frozenset({"en", "zh"})
+# 排序列白名单（列名不可参数化 → 白名单防注入）
+_FIELDS = frozenset({
+    "name",
+    "jif",
+    "composite_impact_factor",
+    "comprehensive_impact_factor",
+    "research_direction",
+    "cas_partition",
+})
+_ORDERS = frozenset({"asc", "desc"})
+_PARTS = {"1": "1区", "2": "2区", "3": "3区", "4": "4区"}
+_MAX_SIZE = 200
+
+# 细节2：源核对状态 → 用户可读 note
+_JIF_NOTE_MAP = {
+    "源表标N/A": "未被2024 JCR收录",
+    "所用年度来源未检得": "本次汇编未查到，建议查阅最新 JCR",
+}
+_ZH_PART_NOTE = "不按中科院分区口径列示"
+# 决策4：分区来源改为常量说明文案（不下发 partition_source_url；DB 原值不动）
+_PARTITION_SOURCE_NOTE = (
+    "2025 中科院官方表（2026 年起停更；官方入口 fenqubiao.com 需机构登录）"
+)
+
+_NOTE_EN = (
+    "分区：2025年中科院公开表（多表比对，2026年起停止更新）；"
+    "JIF：2025年度指标（2026年JCR发布，两份公开汇编一致或已核对出版社官方指标）；"
+    "整理日期2026-10-10。空白=来源未给值≠0；研究方向/期刊标记/文章类型为导航标签，非官方评级。"
+)
+_NOTE_ZH = (
+    "指标：国内自然科学期刊年报2025版（统计年2024，official，含复合/综合IF两口径）；"
+    "中文期刊不按中科院分区口径列示；国内IF与JIF统计源不同，不可混排。"
+)
+_UNIMPORTED_NOTE = "目录数据未导入（请先运行 scripts/import_journals.py）"
+
+
+# ---- 响应模型 ----
+
+class DirectoryItem(BaseModel):
+    """目录公开字段（DB 全列白名单；imported_at 等内部列丢弃）。"""
+    id: str
+    lang: str
+    name: str
+    research_direction: str | None = None
+    cas_partition: str | None = None
+    cas_partition_note: str | None = None
+    cas_partition_year: int | None = None
+    jif: float | None = None
+    jif_year: int | None = None
+    jif_note: str | None = None
+    jif_check_status: str | None = None
+    composite_impact_factor: float | None = None
+    comprehensive_impact_factor: float | None = None
+    metric_year: int | None = None
+    metric_report_year: int | None = None
+    metric_caliber: str | None = None
+    annual_report_page: int | None = None
+    top_flag: str | None = None
+    publisher_series: str | None = None
+    journal_mark: str | None = None
+    article_type: str | None = None
+    issn: str | None = None
+    eissn: str | None = None
+    jcr_disciplines: list[str] = []
+    supplement_note: str | None = None
+    evidence_note: str | None = None
+    official_url: str | None = None
+    official_check_status: str | None = None
+    jcr_release_year: int | None = None
+    jif_source_url: str | None = None
+    partition_source_note: str = _PARTITION_SOURCE_NOTE  # 决策4：常量，替代分区来源链接
+    data_source_url: str | None = None
+
+
+class DirectoryResponse(BaseModel):
+    ok: bool
+    items: list[DirectoryItem] = []
+    meta: dict[str, Any] | None = None
+    error: dict[str, Any] | None = None
+
+
+def _error(code: str, message: str) -> DirectoryResponse:
+    return DirectoryResponse(
+        ok=False, items=[], meta=None,
+        error={"code": code, "message": message, "degraded": False},
+    )
+
+
+# ---- 读时归一化（拍板细节 1-3）----
+
+def _present(raw: dict[str, Any], lang: str) -> dict[str, Any]:
+    d = dict(raw)
+    # jcr_disciplines：JSON 数组字符串 → list
+    jcr = d.get("jcr_disciplines")
+    if jcr:
+        try:
+            parsed = json.loads(jcr)
+            d["jcr_disciplines"] = parsed if isinstance(parsed, list) else []
+        except (TypeError, ValueError):
+            d["jcr_disciplines"] = []
+    else:
+        d["jcr_disciplines"] = []
+
+    # 细节2：jif_note 源文本 → 用户可读
+    note = d.get("jif_note")
+    if note in _JIF_NOTE_MAP:
+        d["jif_note"] = _JIF_NOTE_MAP[note]
+
+    # 细节1：zh 分区归一（DB 原值"不按此口径列示"只留在库里）
+    if lang == "zh":
+        d["cas_partition"] = None
+        d["cas_partition_note"] = _ZH_PART_NOTE
+
+    # 细节3：缺值 → 来源链接清零（消除 null 值却挂来源链接的矛盾；
+    #          分区来源链接已按决策4 移出响应，改为常量 partition_source_note）
+    if lang == "en":
+        if d.get("jif") is None:
+            d["jif_source_url"] = None
+    return d
+
+
+def _escape_like(s: str) -> str:
+    return s.replace("\\", "\\\\").replace("%", "\\%").replace("_", "\\_")
+
+
+# ---- GET /api/review/journals/directory ----
+
+@router.get("/journals/directory", response_model=DirectoryResponse)
+async def journals_directory(
+    lang: str = "en",
+    domain: str = "",
+    cas_partition: str = "",
+    q: str = "",
+    page: int = 1,
+    size: int = 50,
+    field: str = "",
+    order: str = "",
+) -> DirectoryResponse:
+    """只读：期刊目录分页浏览（无写接口）。
+
+    - ?lang=en|zh（默认 en；**强制单语，保证国际/中文永不混排**）；
+    - ?domain= 研究方向精确匹配；?cas_partition=1|2|3|4（仅 lang=en，zh 忽略）；
+    - ?q= 期刊名模糊（ASCII 大小写不敏感）；?page≥1 ?size 1-200（默认 50）；
+    - ?field= 排序白名单（name/jif/composite_impact_factor/
+      comprehensive_impact_factor/research_direction/cas_partition），?order=asc|desc；
+      未传 field → 默认排序 en=jif 降序 / zh=复合IF 降序（NULL 恒排最后）；
+    - 参数非法 → VALIDATION 信封；表不存在 → data_imported=false 空列表（HTTP 200）。
+    """
+    lang_n = (lang or "").strip().lower()
+    if lang_n not in _LANGS:
+        return _error("VALIDATION", f"不支持的 lang={lang!r}，可选：en / zh")
+    if page < 1:
+        return _error("VALIDATION", f"page 必须 ≥ 1，收到 {page}")
+    if size < 1 or size > _MAX_SIZE:
+        return _error("VALIDATION", f"size 必须在 1-{_MAX_SIZE}，收到 {size}")
+    field_n = (field or "").strip()
+    if field_n and field_n not in _FIELDS:
+        return _error(
+            "VALIDATION",
+            f"不支持的 field={field!r}，可选：{', '.join(sorted(_FIELDS))}",
+        )
+    order_n = (order or "").strip().lower()
+    if order_n and order_n not in _ORDERS:
+        return _error("VALIDATION", f"不支持的 order={order!r}，可选：asc / desc")
+    part_q = (cas_partition or "").strip()
+    if part_q:
+        part_q = _PARTS.get(part_q, _PARTS.get(part_q.rstrip("区").strip(), ""))
+        if not part_q:
+            return _error(
+                "VALIDATION",
+                f"不支持的 cas_partition={cas_partition!r}，可选：1 / 2 / 3 / 4",
+            )
+
+    # 过滤条件（白名单拼接；参数全部占位符）
+    where = ["lang = ?"]
+    params: list[Any] = [lang_n]
+    domain_n = (domain or "").strip()
+    if domain_n:
+        where.append("research_direction = ?")
+        params.append(domain_n)
+    if part_q and lang_n == "en":  # zh 不分区：忽略（meta 回显）
+        where.append("cas_partition = ?")
+        params.append(part_q)
+    q_n = (q or "").strip()
+    if q_n:
+        where.append("name LIKE ? ESCAPE '\\'")
+        params.append(f"%{_escape_like(q_n)}%")
+    where_sql = " AND ".join(where)
+
+    # 排序（列名出自白名单；NULL 恒排最后）
+    if field_n:
+        dir_sql = "DESC" if order_n == "desc" else "ASC"
+        order_sql = f"{field_n} IS NULL, {field_n} {dir_sql}"
+    else:
+        col = "jif" if lang_n == "en" else "composite_impact_factor"
+        order_sql = f"{col} IS NULL, {col} DESC"
+
+    try:
+        total_row = await db.fetchone(
+            f"SELECT COUNT(*) AS c FROM journal_directory WHERE {where_sql}", params  # noqa: S608
+        )
+        total = int(total_row["c"]) if total_row else 0
+        rows = await db.fetchall(
+            f"SELECT * FROM journal_directory WHERE {where_sql} "  # noqa: S608
+            f"ORDER BY {order_sql} LIMIT ? OFFSET ?",
+            [*params, size, (page - 1) * size],
+        )
+        dom_rows = await db.fetchall(
+            "SELECT research_direction AS d, COUNT(*) AS c FROM journal_directory "
+            "WHERE lang = ? AND research_direction IS NOT NULL "
+            "GROUP BY 1 ORDER BY c DESC, d ASC",
+            [lang_n],
+        )
+    except sqlite3.OperationalError as exc:
+        # 表不存在（脚本未跑）→ 优雅降级，HTTP 200
+        logger.warning("journal_directory: 表不可用（目录未导入？）: %s", exc)
+        return DirectoryResponse(
+            ok=True, items=[],
+            meta={
+                "total": 0, "page": page, "size": size, "lang": lang_n,
+                "domain": domain_n, "cas_partition": part_q, "q": q_n,
+                "domains": [], "data_source_note": _UNIMPORTED_NOTE,
+                "data_imported": False,
+            },
+            error=None,
+        )
+
+    items = [DirectoryItem(**_present(dict(r), lang_n)) for r in rows]
+    meta: dict[str, Any] = {
+        "total": total,
+        "page": page,
+        "size": size,
+        "lang": lang_n,
+        "domain": domain_n,
+        "cas_partition": part_q if lang_n == "en" else "",
+        "q": q_n,
+        "domains": [r["d"] for r in dom_rows if r["d"]],
+        "data_source_note": _NOTE_EN if lang_n == "en" else _NOTE_ZH,
+        "data_imported": True,
+    }
+    return DirectoryResponse(ok=True, items=items, meta=meta, error=None)
@@ -0,0 +1,354 @@
+"""routers/journals.py —— 期刊情报与智能投稿推荐。
+
+- GET  /api/review/journals      只读：journals 表全量列表（?field=/&order= 排序），
+  meta 含 count / last_updated / data_source_note。无任何写接口；空表返回
+  空数组 + meta.count=0（HTTP 200，绝不 500）。
+- POST /api/review/recommend     智能投稿推荐：vstore 向量匹配（摘要 vs
+  scope_desc，白名单检索）→ LLM 按 id 白名单重排（幻觉期刊丢弃、缺漏规则
+  补位）→ 三档输出：挑战型 / 适配型 / 稳妥型，附匹配理由与风险提示。
+
+降级哲学（同 presubmit）：向量失败 → 全量候选 + vector_ok=false；
+LLM 失败 → 规则分档 + llm_ok=false；推荐永不 5xx。仅入参非法返回
+VALIDATION 错误信封（HTTP 200，与本服务其余端点一致）。
+"""
+from __future__ import annotations
+
+import json
+import logging
+from functools import lru_cache
+from pathlib import Path
+from typing import Any, Literal
+
+from fastapi import APIRouter
+from pydantic import BaseModel, Field
+
+from ..config import get_settings
+from ..db import SeedError, ensure_journals_seeded, list_journals
+from ..services import journal_kb, journal_rank, llm
+
+logger = logging.getLogger(__name__)
+
+router = APIRouter(prefix="/api/review", tags=["review-journals"])
+
+
+# ---- 请求/响应模型 ----
+
+class Preferences(BaseModel):
+    max_review_weeks: float | None = Field(default=None, ge=1, le=104)
+    min_impact_factor: float | None = Field(default=None, ge=0, le=200)
+    tier_focus: Literal["all", "challenge", "fit", "safe"] = "all"
+
+
+class RecommendRequest(BaseModel):
+    abstract: str
+    preferences: Preferences = Preferences()
+
+
+class JournalItem(BaseModel):
+    id: str
+    name: str
+    impact_factor: float | None = None
+    review_time_weeks: float | None = None
+    acceptance_rate: float | None = None
+    official_url: str | None = None
+    similarity: float | None = None
+    tier: str
+    match_reason: str
+    risk_note: str
+
+
+class TierBox(BaseModel):
+    label: str
+    items: list[JournalItem]
+
+
+class RecommendResponse(BaseModel):
+    ok: bool
+    tiers: dict[str, TierBox] | None = None
+    meta: dict[str, Any] | None = None
+    error: dict[str, Any] | None = None
+
+
+# ---- GET /api/review/journals（只读列表）----
+
+class JournalBrief(BaseModel):
+    """期刊公开字段（journals 表全列；不含 vstore_doc_id 内部映射）。
+
+    标签/分区 6 字段不进 SQLite：GET 时按 id 从 journals.json 内存缓存合并；
+    JSON 缺该 id → 空数组/null 默认值。
+    """
+    id: str
+    name: str
+    scope_desc: str = ""
+    impact_factor: float | None = None
+    review_time_weeks: float | None = None
+    acceptance_rate: float | None = None
+    submission_deadline: str | None = None
+    official_url: str | None = None
+    last_updated: str = ""
+    scope_tags: list[str] = []
+    application_tags: list[str] = []
+    cas_partition: str | None = None
+    jcr_quartile: str | None = None
+    partition_source: str | None = None
+    cross_domain: list[str] = []
+
+
+class JournalsListResponse(BaseModel):
+    ok: bool
+    items: list[JournalBrief] = []
+    meta: dict[str, Any] | None = None
+    error: dict[str, Any] | None = None
+
+
+# ?field= 排序白名单（列名无法参数化，白名单防注入；非法值 → VALIDATION 信封）
+_SORT_FIELDS = frozenset({
+    "id",
+    "name",
+    "impact_factor",
+    "review_time_weeks",
+    "acceptance_rate",
+    "last_updated",
+})
+_DATA_SOURCE_NOTE = (
+    "IF/审稿周期为公开近似值，acceptance_rate 为 null 表示暂无公开数据，需人工核验。"
+    "CAS/JCR 分区为首版占位数据，需核验。"
+)
+
+# journals.json 新增字段（标签/分区；刻意不进 SQLite，见 C-2 方案）
+_TAG_FIELDS = (
+    "scope_tags",
+    "application_tags",
+    "cas_partition",
+    "jcr_quartile",
+    "partition_source",
+    "cross_domain",
+)
+
+
+@lru_cache(maxsize=1)
+def _load_tag_extras() -> dict[str, dict[str, Any]]:
+    """journals.json 标签/分区字段 → {id: {6 新字段}}。
+
+    首次请求读盘后进程内缓存，后续 GET O(1) 按 id 合并（不做每请求磁盘 IO）。
+    JSON 缺该 id → 合并时用空数组/null 默认；文件不可读 → 空 dict 降级（不 500）。
+    """
+    seed = get_settings().journals_seed_abs
+    try:
+        payload = json.loads(Path(seed).read_text("utf-8"))
+    except (OSError, ValueError) as exc:
+        logger.warning("journals: 标签扩展文件不可读，合并降级为默认值：%s", exc)
+        return {}
+    raw = payload.get("journals") if isinstance(payload, dict) else None
+    if not isinstance(raw, list):
+        return {}
+    out: dict[str, dict[str, Any]] = {}
+    for j in raw:
+        if isinstance(j, dict) and j.get("id"):
+            out[str(j["id"])] = {k: j.get(k) for k in _TAG_FIELDS}
+    return out
+
+
+def _tag_fields(extra: dict[str, Any] | None) -> dict[str, Any]:
+    """缓存条目 → JournalBrief 关键字参数（JSON 缺该 id → 空数组/null 默认）。"""
+    ex = extra or {}
+    return {
+        "scope_tags": list(ex.get("scope_tags") or []),
+        "application_tags": list(ex.get("application_tags") or []),
+        "cas_partition": ex.get("cas_partition"),
+        "jcr_quartile": ex.get("jcr_quartile"),
+        "partition_source": ex.get("partition_source"),
+        "cross_domain": list(ex.get("cross_domain") or []),
+    }
+
+
+def _sort_rows(rows: list[dict[str, Any]], field: str, order: str) -> list[dict[str, Any]]:
+    """按白名单字段排序；NULL 恒排最后；次序不稳定时按 db 默认序（稳定排序保留）。"""
+    present = [r for r in rows if r.get(field) is not None]
+    missing = [r for r in rows if r.get(field) is None]
+    present.sort(key=lambda r: r.get(field), reverse=(order == "desc"))
+    return present + missing
+
+
+def _list_error(message: str) -> JournalsListResponse:
+    return JournalsListResponse(
+        ok=False, items=[], meta=None,
+        error={"code": "VALIDATION", "message": message, "degraded": False},
+    )
+
+
+@router.get("/journals", response_model=JournalsListResponse)
+async def journals_list(
+    field: str = "name",
+    order: str = "asc",
+) -> JournalsListResponse:
+    """只读：journals 表全量列表（无写/删/改接口）。
+
+    - ?field= 排序字段白名单：id/name/impact_factor/review_time_weeks/
+      acceptance_rate/last_updated，默认 name；
+    - ?order=asc|desc，默认 asc；
+    - 空表 → items=[] + meta.count=0（HTTP 200，不报错）。种子装载由
+      POST /recommend 首次调用幂等完成，本端点严格只读。
+    """
+    col = (field or "").strip()
+    if col not in _SORT_FIELDS:
+        return _list_error(
+            f"不支持的排序字段 field={field!r}，可选：{', '.join(sorted(_SORT_FIELDS))}"
+        )
+    ord_norm = (order or "asc").strip().lower()
+    if ord_norm not in ("asc", "desc"):
+        return _list_error(f"不支持的排序方向 order={order!r}，可选：asc, desc")
+
+    rows = await list_journals()
+    rows = _sort_rows(rows, col, ord_norm)
+
+    tag_extras = _load_tag_extras()
+    items = [
+        JournalBrief(
+            id=str(r.get("id") or ""),
+            name=str(r.get("name") or ""),
+            scope_desc=str(r.get("scope_desc") or ""),
+            impact_factor=r.get("impact_factor"),
+            review_time_weeks=r.get("review_time_weeks"),
+            acceptance_rate=r.get("acceptance_rate"),
+            submission_deadline=r.get("submission_deadline"),
+            official_url=r.get("official_url"),
+            last_updated=str(r.get("last_updated") or ""),
+            **_tag_fields(tag_extras.get(str(r.get("id") or ""))),
+        )
+        for r in rows
+    ]
+    latest = max((str(r.get("last_updated") or "") for r in rows), default="")
+    meta: dict[str, Any] = {
+        "count": len(items),
+        "last_updated": latest or None,
+        "data_source_note": _DATA_SOURCE_NOTE,
+    }
+    return JournalsListResponse(ok=True, items=items, meta=meta, error=None)
+
+
+def _error(code: str, message: str, *, degraded: bool = False) -> RecommendResponse:
+    return RecommendResponse(
+        ok=False, tiers=None, meta=None,
+        error={"code": code, "message": message, "degraded": degraded},
+    )
+
+
+def _item_sort_key(it: JournalItem) -> tuple[int, float, float]:
+    return (
+        1 if it.similarity is None else 0,
+        -(it.similarity or 0.0),
+        -(it.impact_factor or 0.0),
+    )
+
+
+def _apply_soft_preferences(item: JournalItem, prefs: Preferences) -> None:
+    """软偏好：不满足只加风险提示，不删条目。"""
+    weeks = item.review_time_weeks
+    if prefs.max_review_weeks is not None and weeks is not None and weeks > prefs.max_review_weeks:
+        prefix = f"⚠ 审稿约 {weeks:g} 周，超出你 {prefs.max_review_weeks:g} 周的周期偏好；"
+        item.risk_note = prefix + ("无" if item.risk_note == "无" else item.risk_note)
+    inf = item.impact_factor
+    if prefs.min_impact_factor is not None:
+        if inf is None:
+            item.risk_note = "⚠ 影响因子未收录，无法确认满足你的要求；" + item.risk_note
+        elif inf < prefs.min_impact_factor:
+            prefix = f"⚠ 影响因子 {inf:g} 低于你 {prefs.min_impact_factor:g} 的要求；"
+            item.risk_note = prefix + ("无" if item.risk_note == "无" else item.risk_note)
+
+
+@router.post("/recommend", response_model=RecommendResponse)
+async def recommend(req: RecommendRequest) -> RecommendResponse:
+    settings = get_settings()
+
+    # ---- 入参校验（手动，错误信封与本服务其余端点一致）----
+    abstract = (req.abstract or "").strip()
+    if len(abstract) < 50:
+        return _error("VALIDATION", "abstract 至少需要 50 个字符（请提供摘要或正文片段）")
+    if len(abstract) > 20000:
+        return _error("VALIDATION", "abstract 超过 20000 字符上限")
+
+    prefs = req.preferences
+
+    # ---- 种子 + 期刊元数据 ----
+    try:
+        await ensure_journals_seeded()
+        journals = await list_journals()
+    except SeedError as exc:
+        logger.error("recommend: 种子装载失败：%s", exc)
+        return _error("SEED_UNAVAILABLE", str(exc), degraded=True)
+    if not journals:
+        return _error("SEED_UNAVAILABLE", "期刊库为空", degraded=True)
+
+    # ---- ① vstore 向量匹配（摘要 vs scope_desc）----
+    try:
+        candidates, vector_ok = await journal_kb.match(abstract, journals)
+    except journal_kb.MatchError as exc:
+        logger.warning("recommend: 向量匹配降级：%s", exc)
+        candidates, vector_ok = [], False
+    if not candidates:
+        # 无有效语义分 → 全量候选（similarity=None），LLM 仍可按 scope 文本重排
+        candidates = [{"journal": j, "similarity": None} for j in journals]
+        vector_ok = False
+
+    # ---- ② LLM 重排（id 白名单硬校验）----
+    prefs_dict = prefs.model_dump(exclude_none=True)
+    llm_ok = True
+    dropped = 0
+    repaired = 0
+    try:
+        rankings, dropped, repaired = await journal_rank.rerank(abstract, candidates, prefs_dict)
+    except (llm.LLMError, journal_rank.RankError, ValueError) as exc:
+        # ValueError：complete_json 最终 json.loads 修复仍失败（同 presubmit 宽容口径）
+        logger.warning("recommend: LLM 重排降级为规则分档：%s", exc)
+        rankings = journal_rank.fallback_rankings(candidates)
+        llm_ok = False
+
+    # ---- ③ 三档组装（名称/指标全部来自 DB，不采信 LLM 文本）----
+    by_id = {str(c["journal"]["id"]): c for c in candidates}
+    tiers: dict[str, list[JournalItem]] = {t: [] for t in journal_rank.TIERS}
+    for r in rankings:
+        cand = by_id.get(r.journal_id)
+        if cand is None:
+            continue
+        j = cand["journal"]
+        sim = cand.get("similarity")
+        item = JournalItem(
+            id=str(j["id"]),
+            name=str(j.get("name") or j["id"]),
+            impact_factor=j.get("impact_factor"),
+            review_time_weeks=j.get("review_time_weeks"),
+            acceptance_rate=j.get("acceptance_rate"),
+            official_url=j.get("official_url"),
+            similarity=round(float(sim), 4) if sim is not None else None,
+            tier=r.tier,
+            match_reason=r.match_reason,
+            risk_note=r.risk_note,
+        )
+        _apply_soft_preferences(item, prefs)
+        tiers.setdefault(r.tier, []).append(item)
+
+    # 档内排序：相似度（None 靠后）→ 影响因子
+    for box in tiers.values():
+        box.sort(key=_item_sort_key)
+
+    # tier_focus：软展示聚焦（默认 all；聚焦时其余档 items 置空，label 保留）
+    out_tiers: dict[str, TierBox] = {}
+    for t in journal_rank.TIERS:
+        items = tiers.get(t, [])
+        if prefs.tier_focus != "all" and t != prefs.tier_focus:
+            items = []
+        out_tiers[t] = TierBox(label=journal_rank.TIER_LABELS[t], items=items)
+
+    meta: dict[str, Any] = {
+        "model": llm._llm_config()["model"],
+        "vector_ok": vector_ok,
+        "llm_ok": llm_ok,
+        "seed_count": len(journals),
+        "candidate_count": len(candidates),
+        "dropped_hallucinated": dropped,
+        "repaired": repaired,
+        "preferences": prefs_dict,
+        "abstract_chars": len(abstract),
+    }
+    return RecommendResponse(ok=True, tiers=out_tiers, meta=meta, error=None)
@@ -0,0 +1,317 @@
+"""routers/ppt.py —— P5 科研汇报助手（9 端点，SQLite job 模式）。
+
+信封与其余 review 端点一致：业务错误 = HTTP 200 + {ok:false,error:{code,message,degraded}}。
+- GET /styles：风格清单（data/ppt_styles/*.json 实际数量 → 副标题/风格卡动态渲染）
+- 创建（text 主入口 / pdf 次要入口）= 解析 + map-reduce 大纲生成（同步；
+  map 并发 2 + 单调用超时收紧，总时长压在 BFF 读超时 360s 内）
+- PATCH /jobs/{id}：结构清洗（复用 coerce_outline）+ evidence 状态按 raw_text
+  重验（编辑后 quote 真伪即时刷新）；warnings 保留生成期记录（页数/拆页等
+  结构提示不因编辑丢失）
+- POST /jobs/{id}/build：python-pptx 本地生成 → data/ppt_jobs/{id}/draft.pptx
+  + 逐页缩略图渲染 → preview/slide_{n}.png（失败仅 warning，不阻断下载）
+- GET /jobs/{id}/pptx：FileResponse 附件下载
+- GET /jobs/{id}/preview/{page}：第 page 页 PNG 缩略图（旧 job 缺图懒渲染）
+- DELETE 手动清行 + 产物目录（无 TTL，对齐 rebuttal 决策 5）
+"""
+from __future__ import annotations
+
+import logging
+import shutil
+from pathlib import Path
+from typing import Any
+
+from fastapi import APIRouter, File, Form, UploadFile
+from fastapi.responses import FileResponse, JSONResponse
+from pydantic import BaseModel, Field
+
+from ..config import get_settings
+from ..services import paper_parse, ppt_build, ppt_outline, ppt_preview, ppt_store
+from ..services.ppt_build import BuildError
+from ..services.ppt_figure_index import extract_figures, scan_figure_index
+from ..services.ppt_outline import (
+    OutlineError,
+    build_index,
+    coerce_outline,
+    renumber,
+    repair_evidence_para_ids,
+    validate_evidence,
+)
+
+logger = logging.getLogger(__name__)
+
+router = APIRouter(prefix="/api/review/ppt", tags=["review-ppt"])
+
+_MAX_RAW_CHARS = 500_000  # 粘贴文本上限（论文正文通常 ≤150K，留编辑余量）
+
+
+# ---------- 信封 ----------
+class PptResponse(BaseModel):
+    ok: bool
+    job: dict[str, Any] | None = None
+    error: dict[str, Any] | None = None
+    meta: dict[str, Any] | None = None
+
+
+def _error(code: str, message: str) -> PptResponse:
+    return PptResponse(ok=False, error={"code": code, "message": message, "degraded": False})
+
+
+def _ok(job: dict[str, Any], **meta: Any) -> PptResponse:
+    return PptResponse(ok=True, job=job, meta=meta or None)
+
+
+class StylesResponse(BaseModel):
+    """GET /styles 信封（清单在 items，不用 job 字段）。"""
+
+    ok: bool
+    items: list[dict[str, Any]] = Field(default_factory=list)
+    meta: dict[str, Any] | None = None
+
+
+# ---------- 请求体 ----------
+class JobCreateBody(BaseModel):
+    text: str = Field(min_length=1)
+    scenario: str = "group_meeting"
+    minutes: int = 15
+    style_id: str = "academic-minimal"
+
+
+class PagesBody(BaseModel):
+    pages: list[dict[str, Any]] = Field(min_length=1)
+
+
+# ---------- 内部工具 ----------
+def _pptx_path(job_id: str) -> Path:
+    return get_settings().ppt_jobs_abs / job_id / "draft.pptx"
+
+
+def _preview_dir(job_id: str) -> Path:
+    return get_settings().ppt_jobs_abs / job_id / "preview"
+
+
+def _preview_path(job_id: str, page: int) -> Path:
+    return _preview_dir(job_id) / f"slide_{page:02d}.png"
+
+
+async def _create_job(
+    text: str, kind: str, filename: str | None,
+    scenario: str, minutes: int, style_id: str,
+    *, job_id: str | None = None, fig_meta: dict[str, Any] | None = None,
+) -> PptResponse:
+    if len(text) > _MAX_RAW_CHARS:
+        return _error("VALIDATION", f"正文超过 {_MAX_RAW_CHARS} 字符上限")
+    # v3 修复2：PDF 提取出的原图 label → 大纲生成只从这些图里选（build 必能嵌入）
+    available_figures = None
+    if fig_meta:
+        fig_meta = dict(fig_meta)
+        available_figures = fig_meta.pop("figure_labels", None) or None
+    try:
+        pages, warnings, meta = await ppt_outline.generate_outline(
+            text, scenario, minutes, style_id,
+            available_figures=available_figures,
+        )
+    except OutlineError as exc:
+        return _error(exc.code, exc.message)
+    job = {
+        "id": job_id or ppt_store.new_id("ppt_"),
+        "status": "outline_ready",
+        "source": {"kind": kind, "filename": filename},
+        "scenario": scenario,
+        "minutes": minutes,
+        "style_id": style_id,
+        "pages": pages,
+        "warnings": warnings,
+        "pptx_path": None,
+    }
+    ppt_store.insert_job(job, raw_text=text)
+    if fig_meta:
+        meta = {**meta, **fig_meta}
+    return _ok(ppt_store.get_job(job["id"]) or job, **meta)
+
+
+def _extract_job_figures(pdf_bytes: bytes, job_id: str) -> dict[str, Any]:
+    """2.3：PDF 原图 → data/ppt_jobs/{id}/figs/（失败仅告警，不阻塞建 job）。"""
+    out_dir = get_settings().ppt_jobs_abs / job_id / "figs"
+    try:
+        figs = extract_figures(pdf_bytes, out_dir)
+    except Exception as exc:  # noqa: BLE001 - 提取属增强项，绝不 500
+        logger.warning("图表原图提取失败（该 job 回落文字占位）：%s", exc)
+        return {"figures_extracted": 0, "figures_extract_error": str(exc)[:200]}
+    # v3 修复2：已提取 label 供大纲只选「磁盘上有图」的条目
+    return {
+        "figures_extracted": len(figs),
+        "figure_labels": [str(r.get("label") or "") for r in figs if r.get("label")],
+    }
+
+
+def _not_found(job_id: str) -> PptResponse:
+    return _error("NOT_FOUND", f"job {job_id} 不存在或已删除")
+
+
+# ---------- 端点 ----------
+@router.get("/styles", response_model=StylesResponse)
+async def get_styles() -> StylesResponse:
+    """风格清单（data/ppt_styles/*.json 实际数量 + 文案；副标题/风格卡按它渲染）。"""
+    items = ppt_build.list_styles()
+    return StylesResponse(ok=True, items=items, meta={"count": len(items)})
+
+
+@router.post("/jobs", response_model=PptResponse)
+async def create_job(body: JobCreateBody) -> PptResponse:
+    """文本粘贴主入口（论文纯文本 → 大纲）。"""
+    return await _create_job(
+        body.text, kind="text", filename=None,
+        scenario=body.scenario, minutes=body.minutes, style_id=body.style_id,
+    )
+
+
+@router.post("/jobs/pdf", response_model=PptResponse)
+async def create_job_pdf(
+    file: UploadFile = File(...),
+    scenario: str = Form("group_meeting"),
+    minutes: int = Form(15),
+    style_id: str = Form("academic-minimal"),
+) -> PptResponse:
+    """PDF 次要入口（经 vstore 8094 解析 → 大纲）。"""
+    settings = get_settings()
+    filename = file.filename or "paper.pdf"
+    if not filename.lower().endswith(".pdf"):
+        return _error("VALIDATION", "仅支持 PDF 文件")
+    data = await file.read()
+    if not data:
+        return _error("VALIDATION", "上传文件为空")
+    if len(data) > settings.max_pdf_bytes:
+        return _error("VALIDATION", f"PDF 超过 {settings.max_pdf_bytes // (1024 * 1024)}MB 上限")
+    try:
+        text = await paper_parse.parse_pdf_bytes(data, filename=filename)
+    except Exception as exc:  # noqa: BLE001 - ParseError/网络异常统一信封
+        return _error("UPSTREAM_DOWN", f"PDF 解析失败：{exc}")
+    # 2.3：先取 job_id 并提取原图（build 侧按 out 同级 figs/ 自动发现真图）
+    job_id = ppt_store.new_id("ppt_")
+    fig_meta = _extract_job_figures(data, job_id)
+    return await _create_job(
+        text, kind="pdf", filename=filename,
+        scenario=scenario, minutes=minutes, style_id=style_id,
+        job_id=job_id, fig_meta=fig_meta,
+    )
+
+
+@router.get("/jobs/{job_id}", response_model=PptResponse)
+async def get_job(job_id: str) -> PptResponse:
+    job = ppt_store.get_job(job_id)
+    if job is None:
+        return _not_found(job_id)
+    return _ok(job)
+
+
+@router.patch("/jobs/{job_id}", response_model=PptResponse)
+async def patch_pages(job_id: str, body: PagesBody) -> PptResponse:
+    """保存前端编辑后的完整 pages（结构清洗 + evidence 状态重验）。"""
+    job = ppt_store.get_job(job_id)
+    if job is None:
+        return _not_found(job_id)
+    try:
+        pages = coerce_outline({"pages": body.pages})
+    except OutlineError as exc:
+        return _error("VALIDATION", exc.message)
+    renumber(pages)
+    raw_text = ppt_store.get_raw_text(job_id)
+    if raw_text:
+        _, index = build_index(raw_text)
+        repair_evidence_para_ids(pages, index)   # 编辑保存时同样反查修正（兼容旧 job）
+        validate_evidence(pages, index, scan_figure_index(index))
+    updated = ppt_store.update_job(job_id, pages=pages, pptx_path=None)  # 编辑后旧 pptx 失效
+    return _ok(updated or job)
+
+
+@router.post("/jobs/{job_id}/build", response_model=PptResponse)
+async def build_job(job_id: str) -> PptResponse:
+    """大纲 → draft.pptx（python-pptx 本地生成，覆盖重建）。"""
+    job = ppt_store.get_job(job_id)
+    if job is None:
+        return _not_found(job_id)
+    if not job.get("pages"):
+        return _error("VALIDATION", "大纲为空，无法生成 PPT")
+    ppt_store.update_job(job_id, status="building")
+    try:
+        stats = ppt_build.build_pptx(
+            job["pages"], job.get("style_id") or "academic-minimal",
+            _pptx_path(job_id),
+            context={"scenario": job.get("scenario"), "minutes": job.get("minutes")},
+        )
+    except BuildError as exc:
+        warnings = list(job.get("warnings") or []) + [f"PPT 生成失败：{exc.message}"]
+        ppt_store.update_job(job_id, status="error", warnings=warnings)
+        fresh = ppt_store.get_job(job_id)
+        return PptResponse(
+            ok=False, job=fresh,
+            error={"code": exc.code, "message": exc.message, "degraded": False},
+        )
+    # 浏览器内预览：build 成功即渲染缩略图；失败仅告警，不阻断下载
+    previews = ppt_preview.render_previews(_pptx_path(job_id), _preview_dir(job_id))
+    stats["previews"] = len(previews)
+    updated = ppt_store.update_job(job_id, status="done", pptx_path=str(_pptx_path(job_id)))
+    if not previews:
+        fresh_warnings = list((updated or job).get("warnings") or []) + ["预览图生成失败（可正常下载 PPTX）"]
+        updated = ppt_store.update_job(job_id, warnings=fresh_warnings) or updated
+    return _ok(updated or job, **stats)
+
+
+@router.get("/jobs/{job_id}/pptx", response_model=None)
+async def download_pptx(job_id: str) -> FileResponse | JSONResponse:
+    """下载 draft.pptx（二进制流；缺失时回同款信封 JSON，对齐 compile 下载端点）。"""
+    job = ppt_store.get_job(job_id)
+    # pptx_ready 同时看 DB 列与磁盘文件：编辑后列被清 → 盘上旧文件不再下发
+    if job is None or not job.get("pptx_ready"):
+        resp = _not_found(job_id)
+        return JSONResponse(status_code=200, content=resp.model_dump())
+    path = _pptx_path(job_id)
+    filename = path.name
+    src_name = (job.get("source") or {}).get("filename")
+    if src_name:
+        filename = Path(src_name).stem + ".pptx"
+    return FileResponse(
+        str(path),
+        media_type="application/vnd.openxmlformats-officedocument.presentationml.presentation",
+        filename=filename,
+    )
+
+
+@router.get("/jobs/{job_id}/preview/{page}", response_model=None)
+async def preview_slide(job_id: str, page: int) -> FileResponse | JSONResponse:
+    """第 page 页缩略图 PNG（1-based；对齐 download_pptx 的信封约定）。
+
+    缺 preview 但 pptx 在盘（旧 job，端点上线前构建的）→ 懒渲染一次再回图。
+    job 不存在 / pptx 未就绪 / 页码越界 → HTTP 200 + 信封 JSON（对齐 pptx 下载）。
+    """
+    job = ppt_store.get_job(job_id)
+    if job is None or not job.get("pptx_ready"):
+        return JSONResponse(status_code=200, content=_not_found(job_id).model_dump())
+    png = _preview_path(job_id, page)
+    if not png.is_file():
+        # 懒渲染：首次访问补齐（渲染后仍不在 → 页码越界）
+        written = ppt_preview.render_previews(_pptx_path(job_id), _preview_dir(job_id))
+        png = _preview_path(job_id, page)
+        if not png.is_file():
+            if page < 1:
+                return JSONResponse(
+                    status_code=200,
+                    content=_error("VALIDATION", "page 必须 ≥1").model_dump(),
+                )
+            return JSONResponse(
+                status_code=200,
+                content=_error("NOT_FOUND", f"page {page} 不存在（共 {len(written)} 页）").model_dump(),
+            )
+    return FileResponse(str(png), media_type="image/png")
+
+
+@router.delete("/jobs/{job_id}", response_model=PptResponse)
+async def delete_job(job_id: str) -> PptResponse:
+    job = ppt_store.get_job(job_id)
+    if job is None:
+        return _not_found(job_id)
+    ppt_store.delete_job(job_id)
+    job_dir = get_settings().ppt_jobs_abs / job_id
+    if job_dir.exists():
+        shutil.rmtree(job_dir, ignore_errors=True)
+    return PptResponse(ok=True, meta={"deleted": job_id})
@@ -0,0 +1,269 @@
+"""routers/presubmit.py —— 投稿前自审稿（POST /api/review/presubmit）。
+
+流程：上传 PDF → paper_parse（vstore 8094 解析）→ 段落感知装箱 + token 双层保护
+→ LLM 结构化审稿（DeepSeek json_object，System Prompt 为植物基因组学六维专属
+清单，见 services/self_review.py）→ coerce 归一化 → 关键词扫描器证伪硬性缺项
+（services/paper_scanner.py）→ 规则引擎计算 recommendation。
+"""
+from __future__ import annotations
+
+import logging
+import re
+
+from fastapi import APIRouter, File, Form, UploadFile
+from pydantic import BaseModel
+
+from ..config import get_settings
+from ..services import llm, paper_parse, paper_scanner, self_review
+from ..services.recommend_engine import decide_recommendation, resolve_tier
+
+logger = logging.getLogger(__name__)
+
+router = APIRouter(prefix="/api/review", tags=["review-presubmit"])
+
+# ---- token 双层保护（2026-10-12）----
+# 第一层：估算 token 超阈值 → 自动降到 TOKEN_GUARD_REPACK_CHARS 字符重装箱
+# 第二层：LLM 返回 HTTP 400/413 → 降到 LLM_REJECT_RETRY_CHARS 字符重试一次
+_EST_TOKENS_DIVISOR = 1.5          # 粗略上界：英文 ~4 字符/token，1.5 偏保守
+_TOKEN_GUARD_THRESHOLD = 48000
+_TOKEN_GUARD_REPACK_CHARS = 100000
+_LLM_REJECT_RETRY_CHARS = 80000
+# 无节标题可辨时的尾窗（捞页尾 Data Availability 块）
+_TAIL_FALLBACK_CHARS = 5000
+
+# 节标题（行首、允许编号前缀、独占一行）；键 → 装箱分组名
+_SECTION_HEADER_RE = re.compile(
+    r"^[ \t]*(?:\d+(?:\.\d+)*\.?\s+)?"
+    r"(Abstract|Summary|Introduction|Results|Discussion|Methods"
+    r"|Materials\s+and\s+Methods"
+    r"|Data\s+(?:and\s+(?:code\s+)?)?[Aa]vailability"
+    r"|Availability\s+of\s+[Dd]ata"
+    r"|Data\s+and\s+[Mm]aterials\s+[Aa]vailability"
+    r"|References|Acknowledg(?:e)?ments?)\s*$",
+    re.IGNORECASE | re.MULTILINE,
+)
+_SECTION_GROUP = {
+    "abstract": "abstract", "summary": "abstract",
+    "introduction": "introduction",
+    "results": "results",
+    "discussion": "discussion",
+    "methods": "methods", "materials and methods": "methods",
+    "data availability": "data_availability",
+    "data and code availability": "data_availability",
+    "data availability statement": "data_availability",
+    "availability of data": "data_availability",
+    "data and materials availability": "data_availability",
+    "references": "references", "acknowledgements": "acknowledgements",
+    "acknowledgments": "acknowledgements",
+}
+# 装箱优先级（首条命中优先；methods 限 60% 预算——六维清单大量依赖 Methods）
+_PACK_PRIORITY = ("abstract", "data_availability", "methods", "results", "discussion")
+_METHODS_CAP_RATIO = 0.6
+
+
+def estimate_tokens(text: str) -> int:
+    """粗略 token 上界估计（len/1.5），无需 tokenizer 依赖。"""
+    return int(len(text) / _EST_TOKENS_DIVISOR)
+
+
+def _split_segments(text: str) -> list[tuple[str, str]] | None:
+    """按节标题切段 → [(group, content)...]。无可辨标题 → None。"""
+    matches = list(_SECTION_HEADER_RE.finditer(text))
+    if not matches:
+        return None
+    segments: list[tuple[str, str]] = []
+    if matches[0].start() > 0:
+        segments.append(("preamble", text[:matches[0].start()]))
+    for i, m in enumerate(matches):
+        end = matches[i + 1].start() if i + 1 < len(matches) else len(text)
+        group = _SECTION_GROUP.get(m.group(1).casefold(), m.group(1).casefold())
+        segments.append((group, text[m.start():end]))
+    return segments
+
+
+def pack_feed_text(text: str, budget: int) -> tuple[str, list[str]]:
+    """段落感知装箱 → (feed_text, dropped_sections)。
+
+    预算内：原文返回。超预算：按优先级保留
+    ① Abstract ② Data Availability 全文 ③ Methods 前 60% ④ Results
+    ⑤ Discussion，其余按原序填满；未收段记入 dropped。
+    无节标题可辨 → 头 + 尾窗拼接（捞页尾 availability 块），不优于现状亦不劣于。
+    """
+    if len(text) <= budget:
+        return text, []
+    segments = _split_segments(text)
+    if not segments:
+        sep = "\n[...]\n"
+        head = max(0, budget - _TAIL_FALLBACK_CHARS - len(sep))
+        return (
+            text[:head] + sep + text[-_TAIL_FALLBACK_CHARS:],
+            ["[无节标题回退：保留头+尾窗]"],
+        )
+    methods_cap = int(budget * _METHODS_CAP_RATIO)
+    chosen: dict[int, str] = {}
+    used = 0
+    for group in _PACK_PRIORITY:
+        for i, (g, content) in enumerate(segments):
+            if g != group or i in chosen:
+                continue
+            room = budget - used
+            if room <= 0:
+                break
+            piece = content[:methods_cap] if group == "methods" else content
+            if len(piece) > room:
+                piece = piece[:room]
+            if not piece:
+                break
+            chosen[i] = piece
+            used += len(piece)
+            break
+    for i, (_, content) in enumerate(segments):
+        if i in chosen or used >= budget:
+            continue
+        room = budget - used
+        chosen[i] = content if len(content) <= room else content[:room]
+        used += len(chosen[i])
+    feed = "".join(chosen[i] for i in sorted(chosen))
+    dropped: list[str] = []
+    for i, (g, _) in enumerate(segments):
+        if i not in chosen and g not in dropped:
+            dropped.append(g)
+    return feed, dropped
+
+
+def _fit_feed_text(text: str, budget: int) -> tuple[str, list[str]]:
+    """装箱 + 第一层 token 保护（估算超阈值自动降到 100K 字符重装）。"""
+    feed, dropped = pack_feed_text(text, budget)
+    if estimate_tokens(feed) > _TOKEN_GUARD_THRESHOLD and len(feed) > _TOKEN_GUARD_REPACK_CHARS:
+        logger.info(
+            "presubmit: token 估算 %d > %d，降到 %d 字符重装箱",
+            estimate_tokens(feed), _TOKEN_GUARD_THRESHOLD, _TOKEN_GUARD_REPACK_CHARS,
+        )
+        feed, dropped = pack_feed_text(text, _TOKEN_GUARD_REPACK_CHARS)
+    return feed, dropped
+
+
+class PresubmitResponse(BaseModel):
+    ok: bool
+    report: self_review.SelfReviewReport | None = None
+    error: dict[str, object] | None = None
+    meta: dict[str, object] | None = None
+
+
+def _error(code: str, message: str, *, degraded: bool = False) -> PresubmitResponse:
+    return PresubmitResponse(
+        ok=False, report=None,
+        error={"code": code, "message": message, "degraded": degraded},
+    )
+
+
+@router.post("/presubmit", response_model=PresubmitResponse)
+async def presubmit_review(
+    file: UploadFile = File(..., description="待审稿 PDF"),
+    target_journal: str = Form("", description="目标期刊（可选，影响格式类意见）"),
+) -> PresubmitResponse:
+    settings = get_settings()
+
+    filename = file.filename or "paper.pdf"
+    if not filename.lower().endswith(".pdf"):
+        return _error("VALIDATION", "仅支持 PDF 文件")
+
+    content = await file.read()
+    if not content:
+        return _error("VALIDATION", "上传文件为空")
+    if len(content) > settings.max_pdf_bytes:
+        return _error("VALIDATION", "PDF 超过 50MB 上限")
+
+    # ---- 解析（vstore 8094）----
+    try:
+        text = await paper_parse.parse_pdf_bytes(content, filename=filename)
+    except paper_parse.ParseError as exc:
+        logger.warning("presubmit: 解析失败：%s", exc)
+        return _error("PARSE_FAILED", str(exc), degraded=True)
+
+    truncated = len(text) > settings.max_text_chars
+    feed_text, dropped_sections = _fit_feed_text(text, settings.max_text_chars)
+
+    # ---- LLM 结构化自审（植物基因组学六维清单）----
+    # 第二层保护：HTTP 400/413（疑似超长/形态拒绝）→ 降 80K 字符重试一次
+    user_prompt = self_review.build_user_prompt(feed_text, (target_journal or "").strip())
+    try:
+        try:
+            payload = await llm.complete_json(
+                self_review.SYSTEM_PROMPT,
+                user_prompt,
+                temperature=0.2,
+                max_tokens=8000,
+                timeout=settings.presubmit_read_timeout,
+            )
+        except llm.LLMError as exc:
+            msg = str(exc)
+            if ("HTTP 400" in msg or "HTTP 413" in msg) and len(feed_text) > _LLM_REJECT_RETRY_CHARS:
+                logger.warning("presubmit: LLM 拒绝输入（%s），降到 %d 字符重试",
+                               msg[:120], _LLM_REJECT_RETRY_CHARS)
+                feed_text, dropped_sections = pack_feed_text(text, _LLM_REJECT_RETRY_CHARS)
+                truncated = True
+                payload = await llm.complete_json(
+                    self_review.SYSTEM_PROMPT,
+                    self_review.build_user_prompt(feed_text, (target_journal or "").strip()),
+                    temperature=0.2,
+                    max_tokens=8000,
+                    timeout=settings.presubmit_read_timeout,
+                )
+            else:
+                raise
+    except llm.LLMError as exc:
+        logger.error("presubmit: LLM 审稿失败：%s", exc)
+        return _error("UPSTREAM_DOWN", f"审稿模型调用失败：{exc}", degraded=True)
+
+    report = self_review.coerce_report(payload)
+
+    # ---- 关键词扫描器：证伪 LLM 的硬性缺项（有 X 却报缺 X → 真降级至 minor）----
+    # A2（2026-10-12）：被冲突的 major 不再留在 major 列表里只剥标签，而是移出
+    # major、append 到 minor（scanner_downgraded=True）——major_count/引擎输入真实
+    # 减少；fatal 条目例外（只记冲突不降级，须人工过目）。
+    signals = paper_scanner.scan_paper_signals(feed_text)
+    kept_majors, demoted_minors, scanner_conflicts = paper_scanner.reconcile_hard_rules(
+        report.major_weaknesses, signals
+    )
+    report.major_weaknesses = kept_majors
+    if demoted_minors:
+        report.minor_weaknesses = list(report.minor_weaknesses) + list(demoted_minors)
+
+    # recommendation 由规则引擎计算（LLM 输出的同名字段已被 coerce 忽略）
+    tier, tier_source = resolve_tier((target_journal or "").strip())
+    decision = decide_recommendation(
+        majors=report.major_weaknesses,
+        minors=report.minor_weaknesses,
+        presentations=report.presentation_format,
+        tier=tier,
+    )
+    rationale = decision["rationale"]
+    rationale["scanner_conflicts"] = scanner_conflicts
+    if scanner_conflicts:
+        rationale["explanation"] += (
+            f" 关键词扫描器与审稿意见存在 {len(scanner_conflicts)} 处冲突，"
+            f"已降级为小修级问题，请人工核对。"
+        )
+    report.recommendation = decision["recommendation"]
+    report.recommendation_rationale = rationale
+    return PresubmitResponse(
+        ok=True,
+        report=report,
+        meta={
+            "filename": filename,
+            "target_journal": (target_journal or "").strip(),
+            "text_chars": len(feed_text),
+            "truncated": truncated,
+            "dropped_sections": dropped_sections,
+            "scanner": {
+                "accession_found": bool((signals.get("accession") or {}).get("found")),
+                "busco_level": (signals.get("busco") or {}).get("level"),
+                "hic_found": bool((signals.get("hic") or {}).get("found")),
+            },
+            "model": llm._llm_config()["model"],
+            "tier": tier,
+            "tier_label": decision["rationale"]["tier_label"],
+            "tier_source": tier_source,
+        },
+    )
@@ -0,0 +1,288 @@
+"""routers/rebuttal.py —— Rebuttal Phase 1（审稿回复助手，10 端点）。
+
+信封与其余 review 端点一致：业务错误 = HTTP 200 + {ok:false,error:{code,message,degraded}}。
+- 文本粘贴主入口 / PDF 次要入口（PDF 经 vstore 8094 解析）；
+- 逐条 response → draft（校验C前置）→ confirm（后端重算 human_ack）→ letter 拼装；
+- letter.md 下载门槛 = human_ack；DELETE 手动清（无 TTL，决策 5）。
+"""
+from __future__ import annotations
+
+import logging
+from typing import Any, Literal
+
+from fastapi import APIRouter, File, UploadFile
+from fastapi.responses import PlainTextResponse
+from pydantic import BaseModel, Field
+
+from ..config import get_settings
+from ..services import llm, paper_parse
+from ..services.rebuttal_draft import PART_TYPES, assemble_letter, generate_draft, validate_parts
+from ..services.rebuttal_parse import parse_review_text
+from ..services import rebuttal_store
+
+logger = logging.getLogger(__name__)
+
+router = APIRouter(prefix="/api/review/rebuttal", tags=["review-rebuttal"])
+
+_MAX_RAW_CHARS = 200_000  # 粘贴文本上限（审稿意见通常 <20K，保守给大）
+
+
+# ---------- 信封 ----------
+class RebuttalResponse(BaseModel):
+    ok: bool
+    job: dict[str, Any] | None = None
+    error: dict[str, Any] | None = None
+    meta: dict[str, Any] | None = None
+
+
+def _error(code: str, message: str) -> RebuttalResponse:
+    return RebuttalResponse(ok=False, error={"code": code, "message": message, "degraded": False})
+
+
+def _ok(job: dict[str, Any], **meta: Any) -> RebuttalResponse:
+    return RebuttalResponse(ok=True, job=job, meta=meta or None)
+
+
+# ---------- 请求体 ----------
+class JobCreateBody(BaseModel):
+    text: str = Field(min_length=1)
+
+
+class PartBody(BaseModel):
+    type: Literal["new_data", "reanalysis", "location", "clarification", "rebuttal"]
+    content: str = ""
+    location_hint: str | None = None
+
+
+class ResponseBody(BaseModel):
+    parts: list[PartBody] = Field(default_factory=list)
+
+
+class StructureBody(BaseModel):
+    action: Literal["merge", "split"]
+    # merge: comment_ids（含当前 cid，≥2 条）；split: items [{title, body}]
+    comment_ids: list[str] | None = None
+    items: list[dict[str, str]] | None = None
+
+
+class ConfirmBody(BaseModel):
+    confirmed: bool
+
+
+# ---------- 内部工具 ----------
+async def _messages_llm(messages: list[dict[str, str]], *, temperature: float = 0.3) -> dict[str, Any]:
+    """适配 rebuttal_parse/draft 的 messages 形态 → llm.complete_json。"""
+    system = next((m["content"] for m in messages if m.get("role") == "system"), "")
+    user = next((m["content"] for m in messages if m.get("role") == "user"), "")
+    return await llm.complete_json(system, user, temperature=temperature)
+
+
+def _find_comment(job: dict[str, Any], cid: str) -> tuple[dict, dict] | None:
+    for r in job["reviewers"]:
+        for c in r["comments"]:
+            if c["id"] == cid:
+                return r, c
+    return None
+
+
+async def _build_job(raw_text: str, *, kind: str, filename: str | None) -> RebuttalResponse:
+    raw_text = (raw_text or "").strip()
+    if not raw_text:
+        return _error("VALIDATION", "审稿意见文本为空")
+    if len(raw_text) > _MAX_RAW_CHARS:
+        return _error("VALIDATION", f"文本超过 {_MAX_RAW_CHARS} 字符上限")
+    reviewers = await parse_review_text(raw_text, _messages_llm)
+    if not reviewers:
+        return _error("PARSE_FAILED", "未能从文本中解析出任何审稿意见条目")
+    job = {
+        "id": rebuttal_store.new_id("rbt_"),
+        "status": "ready",
+        "source": {"kind": kind, "filename": filename, "raw_text": raw_text},
+        "template": "generic",
+        "reviewers": reviewers,
+        "letter_md": None,
+        "validation": None,
+        "human_ack": False,
+    }
+    rebuttal_store.insert_job(job)
+    n_comments = sum(len(r["comments"]) for r in reviewers)
+    return _ok(job, reviewers=len(reviewers), comments=n_comments)
+
+
+# ---------- 端点 ----------
+@router.post("/jobs", response_model=RebuttalResponse)
+async def create_job(body: JobCreateBody) -> RebuttalResponse:
+    """文本粘贴主入口。"""
+    return await _build_job(body.text, kind="text", filename=None)
+
+
+@router.post("/jobs/pdf", response_model=RebuttalResponse)
+async def create_job_pdf(file: UploadFile = File(...)) -> RebuttalResponse:
+    """PDF 次要入口（批注版审稿 PDF；经 vstore 8094 解析）。"""
+    settings = get_settings()
+    filename = file.filename or "review.pdf"
+    if not filename.lower().endswith(".pdf"):
+        return _error("VALIDATION", "仅支持 PDF 文件（推荐直接粘贴文本）")
+    data = await file.read()
+    if not data:
+        return _error("VALIDATION", "上传文件为空")
+    if len(data) > settings.max_pdf_bytes:
+        return _error("VALIDATION", f"PDF 超过 {settings.max_pdf_bytes // (1024 * 1024)}MB 上限")
+    try:
+        text = await paper_parse.parse_pdf_bytes(data, filename=filename)
+    except Exception as exc:  # noqa: BLE001
+        return _error("UPSTREAM_DOWN", f"PDF 解析失败：{exc}")
+    return await _build_job(text, kind="pdf", filename=filename)
+
+
+@router.get("/jobs/{job_id}", response_model=RebuttalResponse)
+async def get_job(job_id: str) -> RebuttalResponse:
+    job = rebuttal_store.get_job(job_id)
+    if job is None:
+        return _error("NOT_FOUND", f"job {job_id} 不存在或已删除")
+    return _ok(job)
+
+
+@router.patch("/jobs/{job_id}/comments/{cid}/response", response_model=RebuttalResponse)
+async def patch_response(job_id: str, cid: str, body: ResponseBody) -> RebuttalResponse:
+    job = rebuttal_store.get_job(job_id)
+    if job is None:
+        return _error("NOT_FOUND", f"job {job_id} 不存在或已删除")
+    found = _find_comment(job, cid)
+    if found is None:
+        return _error("NOT_FOUND", f"comment {cid} 不存在")
+    _, comment = found
+    for p in body.parts:
+        if p.type not in PART_TYPES:
+            return _error("VALIDATION", f"未知 part.type: {p.type}")
+    comment["response"] = {"parts": [p.model_dump() for p in body.parts]}
+    # 改回复 → 旧 draft/validation 作废（保守：不保留过期草稿）
+    comment["draft"] = None
+    comment["validation"] = None
+    job = rebuttal_store.update_job(job_id, reviewers=job["reviewers"]) or job
+    return _ok(job)
+
+
+@router.post("/jobs/{job_id}/comments/{cid}/draft", response_model=RebuttalResponse)
+async def post_draft(job_id: str, cid: str) -> RebuttalResponse:
+    job = rebuttal_store.get_job(job_id)
+    if job is None:
+        return _error("NOT_FOUND", f"job {job_id} 不存在或已删除")
+    found = _find_comment(job, cid)
+    if found is None:
+        return _error("NOT_FOUND", f"comment {cid} 不存在")
+    _, comment = found
+    parts = (comment.get("response") or {}).get("parts") or []
+    if not parts or not any(str(p.get("content") or "").strip() for p in parts):
+        # 决策 4：生成前必须填 user_response；LLM 调用次数=0
+        return _error("MISSING_RESPONSE", "请先填写回复要点（user_response）再生成草稿")
+    validation = validate_parts(parts)
+    comment["validation"] = validation
+    if not validation["passed"]:
+        job = rebuttal_store.update_job(job_id, reviewers=job["reviewers"]) or job
+        return RebuttalResponse(
+            ok=False, job=job,
+            error={"code": "VALIDATION_FAILED", "message": "反幻觉校验未通过",
+                   "degraded": False},
+            meta={"validation": validation},
+        )
+    comment["draft"] = await generate_draft(_messages_llm, comment)
+    job = rebuttal_store.update_job(job_id, reviewers=job["reviewers"]) or job
+    return _ok(job, validation=validation)
+
+
+@router.patch("/jobs/{job_id}/comments/{cid}/structure", response_model=RebuttalResponse)
+async def patch_structure(job_id: str, cid: str, body: StructureBody) -> RebuttalResponse:
+    job = rebuttal_store.get_job(job_id)
+    if job is None:
+        return _error("NOT_FOUND", f"job {job_id} 不存在或已删除")
+    found = _find_comment(job, cid)
+    if found is None:
+        return _error("NOT_FOUND", f"comment {cid} 不存在")
+    reviewer, comment = found
+    comments = reviewer["comments"]
+    idx = comments.index(comment)
+    if body.action == "merge":
+        ids = body.comment_ids or []
+        if cid not in ids:
+            ids = [cid] + ids
+        if len(ids) < 2:
+            return _error("VALIDATION", "merge 至少需要 2 条 comment")
+        targets = [c for c in comments if c["id"] in ids]
+        if len(targets) < 2:
+            return _error("VALIDATION", "merge 目标中有效 comment 不足 2 条")
+        merged_body = "\n\n".join(c["body"] for c in targets)
+        comment["body"] = merged_body
+        comment["title"] = f"{comment['title']} (+{len(targets) - 1} merged)"
+        reviewer["comments"] = [
+            c for c in comments
+            if c is comment or c["id"] not in ids
+        ]
+    else:  # split
+        items = body.items or []
+        items = [i for i in items if str(i.get("body") or "").strip()]
+        if len(items) < 2:
+            return _error("VALIDATION", "split 至少需要 2 个非空子项")
+        group_id = comment.get("group_id") or f"g_{cid}"
+        new_comments = []
+        for n, it in enumerate(items, start=1):
+            c = dict(comment)
+            c["id"] = rebuttal_store.new_id(f"{cid}s{n}")
+            c["group_id"] = group_id
+            c["title"] = str(it.get("title") or f"{comment['title']} ({n})")
+            c["body"] = str(it.get("body") or "").strip()
+            c["sub_items"] = []
+            c["response"] = {"parts": []}
+            c["draft"] = None
+            c["validation"] = None
+            c["human_confirmed"] = False
+            new_comments.append(c)
+        comments[idx:idx + 1] = new_comments
+    job = rebuttal_store.update_job(job_id, reviewers=job["reviewers"]) or job
+    return _ok(job)
+
+
+@router.patch("/jobs/{job_id}/comments/{cid}/confirm", response_model=RebuttalResponse)
+async def patch_confirm(job_id: str, cid: str, body: ConfirmBody) -> RebuttalResponse:
+    job = rebuttal_store.get_job(job_id)
+    if job is None:
+        return _error("NOT_FOUND", f"job {job_id} 不存在或已删除")
+    found = _find_comment(job, cid)
+    if found is None:
+        return _error("NOT_FOUND", f"comment {cid} 不存在")
+    _, comment = found
+    comment["human_confirmed"] = bool(body.confirmed)
+    # human_ack 由 store 重算（决策 4：全勾才置位，不信前端）
+    job = rebuttal_store.update_job(job_id, reviewers=job["reviewers"]) or job
+    return _ok(job, human_ack=job["human_ack"])
+
+
+@router.post("/jobs/{job_id}/letter", response_model=RebuttalResponse)
+async def post_letter(job_id: str) -> RebuttalResponse:
+    job = rebuttal_store.get_job(job_id)
+    if job is None:
+        return _error("NOT_FOUND", f"job {job_id} 不存在或已删除")
+    job = rebuttal_store.update_job(job_id, letter_md=assemble_letter(job)) or job
+    return _ok(job)
+
+
+@router.get("/jobs/{job_id}/letter.md")
+async def download_letter(job_id: str) -> PlainTextResponse:
+    job = rebuttal_store.get_job(job_id)
+    if job is None:
+        return PlainTextResponse(
+            "job not found", status_code=404, media_type="text/plain; charset=utf-8")
+    if not job.get("human_ack"):
+        # 信封口径与下载端点适配：GET 下载返回纯文本，业务拒绝用 400 + 明文
+        return PlainTextResponse(
+            "HUMAN_ACK_REQUIRED: 请逐条勾选确认后再下载 letter.md",
+            status_code=400, media_type="text/plain; charset=utf-8")
+    md = job.get("letter_md") or assemble_letter(job)
+    return PlainTextResponse(md, media_type="text/markdown; charset=utf-8")
+
+
+@router.delete("/jobs/{job_id}", response_model=RebuttalResponse)
+async def delete_job(job_id: str) -> RebuttalResponse:
+    if not rebuttal_store.delete_job(job_id):
+        return _error("NOT_FOUND", f"job {job_id} 不存在或已删除")
+    return RebuttalResponse(ok=True, job=None, meta={"deleted": job_id})
@@ -0,0 +1,165 @@
+"""routers/reformat.py —— 论文自动排版 P1（.tex 源码级重排版，不编译）。
+
+端点：
+  POST /api/review/reformat          multipart 上传 .tex + target_journal →
+                                     修改后源码 + 逐行 diff 报告（job 落盘）
+  GET  /api/review/reformat/{id}     取完整报告（重启后仍在）
+  GET  /api/review/reformat/{id}/file 下载修改后的 .tex
+
+信封与其余 review 端点一致：业务错误 = HTTP 200 + {ok:false,error:{code,message,degraded:false}}，
+前端经 review.js unwrap 归一为 ApiError。本次改动无上游依赖（零 LLM/零 vstore），
+degraded 恒 false。
+"""
+from __future__ import annotations
+
+import hashlib
+import json
+import logging
+import re
+import uuid
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Any
+
+from fastapi import APIRouter, File, Form, UploadFile
+from fastapi.responses import FileResponse, JSONResponse
+from pydantic import BaseModel
+
+from ..config import get_settings
+from ..services.reformat import ReformatError, reformat_tex, resolve_rules
+
+logger = logging.getLogger(__name__)
+
+router = APIRouter(prefix="/api/review", tags=["review-reformat"])
+
+_JOB_ID_RE = re.compile(r"^[0-9a-f]{12}$")
+_ENGINE = "reformat-p1/1.0"
+
+
+class ReformatResponse(BaseModel):
+    ok: bool
+    job_id: str | None = None
+    modified_tex: str | None = None
+    changes: list[dict[str, Any]] | None = None
+    warnings: list[dict[str, Any]] | None = None
+    meta: dict[str, Any] | None = None
+    error: dict[str, Any] | None = None
+
+
+def _error(code: str, message: str) -> ReformatResponse:
+    return ReformatResponse(
+        ok=False,
+        error={"code": code, "message": message, "degraded": False},
+    )
+
+
+def _jobs_dir() -> Path:
+    d = get_settings().reformat_dir_abs
+    d.mkdir(parents=True, exist_ok=True)
+    return d
+
+
+@router.post("/reformat", response_model=ReformatResponse)
+async def reformat(
+    file: UploadFile = File(..., description="LaTeX 源码（.tex 单文件）"),
+    target_journal: str = Form("", description="目标期刊 id/名称，或 default=通用规则"),
+) -> ReformatResponse:
+    settings = get_settings()
+
+    # ---- 入参校验（拍板 5：只收 .tex，docx/pdf 走 format-check 审核不重排）----
+    filename = file.filename or "paper.tex"
+    if not filename.lower().endswith(".tex"):
+        return _error("VALIDATION", "仅支持 .tex 文件（docx/pdf 请走格式审核）")
+    target = (target_journal or "").strip()
+    if not target:
+        return _error("VALIDATION", "必须指定目标期刊（或选择「通用规则」）")
+
+    content = await file.read()
+    if not content:
+        return _error("VALIDATION", "上传文件为空")
+    if len(content) > settings.max_tex_bytes:
+        return _error("VALIDATION", "源码超过 2MB 上限")
+    try:
+        source = content.decode("utf-8")
+    except UnicodeDecodeError:
+        return _error("VALIDATION", "源码必须为 UTF-8 编码")
+
+    # ---- 规则解析（journals.json / format_cache / journal_directory 只读回链）----
+    resolved = await resolve_rules(target)
+
+    # ---- 变换（纯规则引擎；结构畸形 → PARSER_FAILED）----
+    try:
+        result = reformat_tex(source, resolved["rules"])
+    except ReformatError as exc:
+        logger.warning("reformat: 结构守卫拒收 %s: %s", filename, exc)
+        return _error(exc.code, str(exc))
+
+    # ---- 落盘（.tex + .json 报告；重启后 GET 仍可用）----
+    job_id = uuid.uuid4().hex[:12]
+    base = _jobs_dir()
+    (base / f"{job_id}.tex").write_text(result["modified_tex"], encoding="utf-8")
+
+    meta: dict[str, Any] = {
+        "journal_id": resolved["journal_id"],
+        "journal_name": resolved["journal_name"],
+        "rules": resolved["rules"],
+        "rules_source": resolved["rules_source"],
+        "rules_note": resolved["rules_note"],
+        "filename": filename,
+        "original_sha256": hashlib.sha256(content).hexdigest(),
+        "engine": _ENGINE,
+        "generated_at": datetime.now(timezone.utc).isoformat(timespec="seconds"),
+    }
+    payload = {
+        "ok": True,
+        "job_id": job_id,
+        "modified_tex": result["modified_tex"],
+        "changes": result["changes"],
+        "warnings": result["warnings"],
+        "meta": meta,
+    }
+    (base / f"{job_id}.json").write_text(
+        json.dumps(payload, ensure_ascii=False, indent=2), encoding="utf-8"
+    )
+    logger.info(
+        "reformat: %s → job %s（%d 处修改, %d 条提示, 规则 %s）",
+        filename, job_id,
+        sum(1 for c in result["changes"] if c["action"] == "modified"),
+        sum(1 for c in result["changes"] if c["action"] == "warning"),
+        resolved["rules_source"],
+    )
+    return ReformatResponse(**payload)
+
+
+def _load_job(job_id: str) -> dict[str, Any] | None:
+    if not _JOB_ID_RE.fullmatch(job_id or ""):
+        return None
+    path = _jobs_dir() / f"{job_id}.json"
+    try:
+        payload = json.loads(path.read_text("utf-8"))
+    except (OSError, ValueError):
+        return None
+    return payload if isinstance(payload, dict) and payload.get("ok") else None
+
+
+_NOT_FOUND = {"ok": False, "error": {"code": "NOT_FOUND",
+                                     "message": "任务不存在或已过期，请重新上传源码",
+                                     "degraded": False}}
+
+
+@router.get("/reformat/{job_id}", response_model=ReformatResponse)
+async def get_reformat_job(job_id: str) -> ReformatResponse:
+    payload = _load_job(job_id)
+    if payload is None:
+        return _error("NOT_FOUND", "任务不存在或已过期，请重新上传源码")
+    return ReformatResponse(**payload)
+
+
+@router.get("/reformat/{job_id}/file", response_model=None)
+async def download_reformat_file(job_id: str) -> FileResponse | JSONResponse:
+    """下载修改后的 .tex；缺件/非法 id → 200 信封（前端单一错误口径）。"""
+    valid = bool(_JOB_ID_RE.fullmatch(job_id or ""))
+    tex = _jobs_dir() / f"{job_id}.tex" if valid else None
+    if tex is None or not tex.is_file():
+        return JSONResponse(status_code=200, content=_NOT_FOUND)
+    return FileResponse(tex, media_type="application/x-tex", filename=f"{job_id}.tex")
@@ -0,0 +1 @@
+"""review 服务服务层包。"""
@@ -0,0 +1,788 @@
+"""services/format_check.py —— 版式与规范规则引擎（⑤ 论文排版与规范）。
+
+纯规则、无 LLM、无 vstore、同步执行（通常 <1s）：
+- PDF   → pymupdf 本地解档（AGENTS.md 约束 6 例外：vstore 只回文本，字体/边距/
+  行距/页数等版式元数据拿不到；正文提取仍走 vstore，本服务不碰正文语义）；
+- Word  → python-docx（页边距/行距精确，页数取 docProps/app.xml 的 <Pages>）；
+- 规则集 → data/journals/journals.json：
+    顶层 format_rules_default（通用默认值，rules_source="default"）
+    每条目可选 format_rules（按期刊覆盖，必须带 rules_source: placeholder|official|default）
+  ⚠ 诚实原则：不知道期刊真实投稿指南 → 该条只写 {"rules_source": "placeholder"}，
+  所有具体数字回退 default 通用值，绝不编造期刊专属数字。
+
+输出：{checks[{name,key,status,detail,suggestion}], summary{pass,warn,fail}, meta{...}}
+status ∈ pass|warn|fail。参考文献样式宽容化：仅"明确不符"（如 [J] 标引但规则要求 APA）
+才 fail，"疑似但不确定/检测不到"一律 warn，避免误伤。
+"""
+from __future__ import annotations
+
+import io
+import json
+import re
+import statistics
+import zipfile
+from pathlib import Path
+from typing import Any
+
+import fitz  # pymupdf（venv 已装 1.28.x）
+from docx import Document
+from docx.shared import Length
+
+# review_service/app/services/ → parents[2] = review_service
+_JOURNALS_PATH = Path(__file__).resolve().parents[2] / "data" / "journals" / "journals.json"
+
+_MAX_SCAN_PAGES = 80   # 版式扫描页数上限（正文/字体/边距；稿件通常远小于此）
+_MAX_REFS_SCAN = 40    # 从文末向前找参考文献标题的页数窗口
+_MAX_PARAS = 8000      # docx 段落扫描上限
+_PT_TO_MM = 25.4 / 72.0
+_EMU_TO_MM = 1.0 / 36000.0
+
+_HEADING_RE = re.compile(
+    r"^\s*(references|bibliography|literature cited|works cited|参考文献|文献)\s*[:：]?\s*$",
+    re.IGNORECASE,
+)
+_FIG_RE = re.compile(r"(?im)^\s*(figure|fig\.?|图)\s*\d+")
+_TAB_RE = re.compile(r"(?im)^\s*(table|表)\s*\d+")
+_GB_TAG_RE = re.compile(r"\[[A-Z]{1,3}\d*\]")          # [J] [M] [D] [C] …（GB/T 7714 标引）
+_PAREN_YEAR_RE = re.compile(r"\((?:19|20)\d{2}\)")      # (2024) 作者-年份制
+_BRACKET_NUM_RE = re.compile(r"^\[\d+\]")               # [1] 编号制
+_DOI_RE = re.compile(r"doi:?\.?org|doi:\s*1\.", re.IGNORECASE)
+
+_STYLE_LABEL = {
+    "gb7714": "GB/T 7714",
+    "author_year": "作者-年份制（类 APA）",
+    "numbered": "编号制（顺序编码）",
+    "unknown": "无法确定",
+}
+
+
+class FormatCheckError(Exception):
+    """解档/规则加载失败（路由器转 PARSE_FAILED）。"""
+
+
+# ---------------------------------------------------------------- 规则集加载
+
+def load_ruleset(target_journal: str) -> tuple[dict[str, Any], dict[str, Any]]:
+    """返回 (rules, ruleset_meta)。target_journal 传 id 或 name 均可；未知 → default。"""
+    try:
+        data = json.loads(_JOURNALS_PATH.read_text("utf-8"))
+    except Exception as exc:  # noqa: BLE001
+        raise FormatCheckError(f"规则集加载失败：{exc}") from exc
+
+    default = data.get("format_rules_default") or {}
+    jid = (target_journal or "").strip()
+    entry = None
+    if jid:
+        for j in data.get("journals") or []:
+            if j.get("id") == jid or j.get("name") == jid:
+                entry = j
+                break
+
+    if entry is None:
+        rules = dict(default)
+        meta = {
+            "journal_id": None,
+            "journal_name": None,
+            "ruleset_source": "default",
+            "rules_source": str(default.get("rules_source", "default")),
+        }
+    else:
+        journal_rules = entry.get("format_rules") or {}
+        rules = {**default, **journal_rules}
+        meta = {
+            "journal_id": entry.get("id"),
+            "journal_name": entry.get("name"),
+            "ruleset_source": "journal",
+            # 占位规则（无官方核验）→ 前端黄字提示
+            "rules_source": str(journal_rules.get("rules_source", "placeholder")),
+        }
+    rules.setdefault("rules_source", "default")
+    return rules, meta
+
+
+# ---------------------------------------------------------------- PDF 解档（pymupdf）
+
+def _norm_font(name: str) -> str:
+    n = (name or "").split("+")[-1].strip()
+    return n or "unknown"
+
+
+def extract_profile_pdf(data: bytes) -> dict[str, Any]:
+    try:
+        doc = fitz.open(stream=data, filetype="pdf")
+    except Exception as exc:  # noqa: BLE001
+        raise FormatCheckError(f"PDF 解档失败：{exc}") from exc
+    if getattr(doc, "needs_pass", False):
+        doc.close()
+        raise FormatCheckError("PDF 已加密，无法解析")
+
+    pages_total = doc.page_count
+    scan = min(pages_total, _MAX_SCAN_PAGES)
+    margin_rows: list[tuple[float, float, float, float]] = []  # t r b l (mm)
+    font_w: dict[str, int] = {}
+    size_w: dict[float, int] = {}
+    ratios: list[float] = []
+    img_ids: set[int] = set()
+    fig_caps = tab_caps = 0
+
+    for pno in range(scan):
+        page = doc[pno]
+        rect = page.rect
+        blocks = page.get_text("blocks")
+        content = [b for b in blocks if b[4].strip()]
+        if content:
+            left = min(b[0] for b in content)
+            top = min(b[1] for b in content)
+            right = rect.width - max(b[2] for b in content)
+            bottom = rect.height - max(b[3] for b in content)
+            margin_rows.append(
+                (
+                    max(0.0, top) * _PT_TO_MM,
+                    max(0.0, right) * _PT_TO_MM,
+                    max(0.0, bottom) * _PT_TO_MM,
+                    max(0.0, left) * _PT_TO_MM,
+                )
+            )
+
+        for img in page.get_images(full=True):
+            img_ids.add(img[0])
+
+        text = page.get_text()
+        fig_caps += len(_FIG_RE.findall(text))
+        tab_caps += len(_TAB_RE.findall(text))
+
+        d = page.get_text("dict")
+        for block in d.get("blocks", []):
+            if block.get("type") != 0:
+                continue
+            line_meta: list[tuple[float, float]] = []  # (基线 y, 字号)
+            for line in block.get("lines", []):
+                spans = [s for s in line.get("spans", []) if s.get("text", "").strip()]
+                if not spans:
+                    continue
+                row_size = max(s.get("size", 0.0) for s in spans)
+                if row_size <= 0:
+                    continue
+                for s in spans:
+                    size = round(float(s.get("size", 0.0)), 1)
+                    chars = len(s.get("text", ""))
+                    if size > 0:
+                        norm = _norm_font(s.get("font", ""))
+                        font_w[norm] = font_w.get(norm, 0) + chars
+                        size_w[size] = size_w.get(size, 0) + chars
+                # 行距基准用 span.origin 基线 y，不用 bbox 顶缘：bbox 顶随字形高低
+                # 漂移，表格/图注等同基线并列文本会产出假性小 delta，混入中位数会把
+                # 行距拉成 0.1x 的不可能值。
+                origin = spans[0].get("origin")
+                line_meta.append((origin[1] if origin else line["bbox"][1], row_size))
+            for i in range(1, len(line_meta)):
+                delta = line_meta[i][0] - line_meta[i - 1][0]
+                size = line_meta[i][1]
+                # 行距倍数 = 相邻行基线 y 差 / 当前行字号；
+                # 过滤物理不可能值：<0.5（行重叠/同基线并列表格）、>4.0（异常结构）
+                ratio = delta / size
+                if 0.5 <= ratio <= 4.0:
+                    ratios.append(ratio)
+
+    refs_text, refs_found = _find_refs_pdf(doc, pages_total)
+    doc.close()
+
+    if margin_rows:
+        med = [statistics.median(col) for col in zip(*margin_rows)]
+        margins = {"top": med[0], "right": med[1], "bottom": med[2], "left": med[3]}
+    else:
+        margins = None
+
+    return {
+        "source_kind": "pdf",
+        "pages": pages_total,
+        "margins_mm": margins,
+        "font_weights": font_w,
+        "size_weights": size_w,
+        "line_spacing_median": statistics.median(ratios) if ratios else None,
+        "figures": max(len(img_ids), fig_caps),
+        "tables": tab_caps,
+        "refs_text": refs_text,
+        "refs_found": refs_found,
+    }
+
+
+def _find_refs_pdf(doc: "fitz.Document", pages_total: int) -> tuple[str | None, bool]:
+    """从文末向前找参考文献标题行；找到 → 标题行至文末文本；找不到 → (None, False)。"""
+    buf: list[str] = []
+    start = max(0, pages_total - _MAX_REFS_SCAN)
+    for pno in range(pages_total - 1, start - 1, -1):
+        page_text = doc[pno].get_text()
+        lines = page_text.splitlines()
+        for idx in range(len(lines) - 1, -1, -1):
+            if _HEADING_RE.match(lines[idx].strip()):
+                tail = "\n".join(lines[idx + 1:])
+                joined = "\n".join([tail] + buf).strip()
+                return (joined if len(joined) >= 50 else None), bool(joined)
+        buf.insert(0, page_text)
+    return None, False
+
+
+# ---------------------------------------------------------------- Word 解档（python-docx）
+
+def _docx_app_pages(data: bytes) -> int | None:
+    try:
+        with zipfile.ZipFile(io.BytesIO(data)) as zf:
+            xml = zf.read("docProps/app.xml").decode("utf-8", "ignore")
+        m = re.search(r"<Pages>(\d+)</Pages>", xml)
+        return int(m.group(1)) if m else None
+    except Exception:  # noqa: BLE001
+        return None
+
+
+def extract_profile_docx(data: bytes) -> dict[str, Any]:
+    try:
+        doc = Document(io.BytesIO(data))
+    except Exception as exc:  # noqa: BLE001
+        raise FormatCheckError(f"Word 文件解析失败：{exc}") from exc
+
+    side_lists: dict[str, list[float]] = {"top": [], "right": [], "bottom": [], "left": []}
+    for sec in doc.sections:
+        for k, v in (
+            ("top", sec.top_margin),
+            ("right", sec.right_margin),
+            ("bottom", sec.bottom_margin),
+            ("left", sec.left_margin),
+        ):
+            if v is not None:
+                side_lists[k].append(float(v) * _EMU_TO_MM)
+    margins = None
+    if all(side_lists.values()):
+        margins = {k: statistics.median(v) for k, v in side_lists.items()}
+
+    try:
+        normal = doc.styles["Normal"].font
+        default_name = normal.name
+        default_size = float(normal.size.pt) if normal.size is not None else None
+    except Exception:  # noqa: BLE001
+        default_name, default_size = None, None
+
+    font_w: dict[str, int] = {}
+    size_w: dict[float, int] = {}
+    ratios: list[float] = []
+    fig_caps = tab_caps = 0
+    paras = doc.paragraphs
+    scan_count = min(len(paras), _MAX_PARAS)
+
+    for i in range(scan_count):
+        para = paras[i]
+        text = para.text
+        if not text.strip():
+            continue
+        ls = para.paragraph_format.line_spacing
+        if isinstance(ls, Length):
+            # 精确行距（exactly）以 EMU 存储，Length 是 int 子类——直接当倍数会得出
+            # 十万级的假值；用正文默认字号换算成倍数
+            if default_size:
+                r = float(ls.pt) / default_size
+                if 0.5 <= r <= 4.0:
+                    ratios.append(r)
+        elif isinstance(ls, (int, float)) and not isinstance(ls, bool) and ls > 0:
+            r = float(ls)  # multiple 行距本身就是倍数
+            if 0.5 <= r <= 4.0:
+                ratios.append(r)
+        if _FIG_RE.match(text):
+            fig_caps += 1
+        elif _TAB_RE.match(text):
+            tab_caps += 1
+        for run in para.runs:
+            if not run.text:
+                continue
+            name = run.font.name or default_name or "unknown"
+            pt = run.font.size.pt if run.font.size is not None else default_size
+            chars = len(run.text)
+            font_w[str(name)] = font_w.get(str(name), 0) + chars
+            if pt:
+                size_w[round(float(pt), 1)] = size_w.get(round(float(pt), 1), 0) + chars
+
+    # 参考文献节：标题段落之后全部文本
+    refs_text, refs_found = None, False
+    for i, para in enumerate(paras):
+        if _HEADING_RE.match((para.text or "").strip()):
+            tail = "\n".join(p.text for p in paras[i + 1:] if (p.text or "").strip())
+            if len(tail) >= 50:
+                refs_text, refs_found = tail, True
+            break
+
+    return {
+        "source_kind": "docx",
+        "pages": _docx_app_pages(data),  # Word 未记录 → None（检查项降级为 warn）
+        "margins_mm": margins,
+        "font_weights": font_w,
+        "size_weights": size_w,
+        "line_spacing_median": statistics.median(ratios) if ratios else None,
+        "figures": max(len(doc.inline_shapes), fig_caps),
+        "tables": max(len(doc.tables), tab_caps),
+        "refs_text": refs_text,
+        "refs_found": refs_found,
+    }
+
+
+# ---------------------------------------------------------------- LaTeX 解档（正则+状态机，零新依赖）
+#
+# 决策前提：只做"解析 + 检查 + 建议代码片段"，不自动改写 LaTeX（用户可能有自定义宏，
+# 自动改写会引错；LaTeX 应由用户自己编辑）。不引入 pylatexenc/texsoup。
+
+# 会相互覆盖的字体类宏包：≥2 个同时引入 → warn（times + mathptmx 类冲突）
+_TEX_FONT_PKGS = {"times", "mathptmx", "newtx", "newpx", "txfonts", "pxfonts", "mathpazo"}
+
+
+def _strip_tex_comments(src: str) -> str:
+    r"""去行内 % 注释（r-string，避免 \% 被解释为转义序列）。"""
+    return re.sub(r"(?<!\\)%.*", "", src)
+
+
+def _parse_geometry(src: str) -> dict[str, float] | None:
+    """\\usepackage[...]{geometry} 或 \\geometry{...} → {边: mm}（可缺边，检查端容缺）。"""
+    m = re.search(r"\\usepackage\s*\[([^\]]*)\]\s*\{\s*geometry\s*\}", src)
+    if not m:
+        m = re.search(r"\\geometry\s*\{([^}]*)\}", src)
+        if not m:
+            return None
+    opts = m.group(1)
+
+    def to_mm(val: str) -> float | None:
+        mm = re.match(r"\s*([\d.]+)\s*(mm|cm|in|pt)?\s*$", val)
+        if not mm:
+            return None
+        x = float(mm.group(1))
+        unit = mm.group(2) or "pt"  # geometry 裸数字按 TeX 惯例为 pt
+        return {"mm": x, "cm": x * 10, "in": x * 25.4, "pt": x * 25.4 / 72.0}[unit]
+
+    kv = {}
+    for pair in opts.split(","):
+        if "=" in pair:
+            k, v = pair.split("=", 1)
+            kv[k.strip().lower()] = v.strip()
+    out: dict[str, float] = {}
+    if "margin" in kv:
+        v = to_mm(kv["margin"])
+        if v is not None:
+            return {"top": v, "right": v, "bottom": v, "left": v}
+    for k in ("top", "right", "bottom", "left"):
+        if k in kv:
+            v = to_mm(kv[k])
+            if v is not None:
+                out[k] = v
+    if "inner" in kv:
+        v = to_mm(kv["inner"])
+        if v is not None:
+            out.setdefault("left", v)
+    if "outer" in kv:
+        v = to_mm(kv["outer"])
+        if v is not None:
+            out.setdefault("right", v)
+    return out or None
+
+
+def extract_tex_profile(data: bytes) -> dict[str, Any]:
+    """正则 + 轻量状态机解析 .tex 源文件 → 与 DocProfile 同构（+tex 扩展字段）。"""
+    try:
+        text = data.decode("utf-8")
+    except UnicodeDecodeError:
+        text = data.decode("latin-1", errors="replace")
+    src = _strip_tex_comments(text)
+
+    # \documentclass[10pt,a4paper]{article}
+    m_cls = re.search(r"\\documentclass\s*(?:\[[^\]]*\])?\s*\{\s*([\w*]+)\s*\}", src)
+    cls = m_cls.group(1) if m_cls else None
+    m_opt = re.search(r"\\documentclass\s*\[([^\]]*)\]", src)
+    cls_opts = m_opt.group(1) if m_opt else ""
+    m_pt = re.search(r"(\d+)\s*pt", cls_opts)
+    # 标准类未写选项时 LaTeX 默认 10pt；无 documentclass → None（检查项降级 warn）
+    fontsize = int(m_pt.group(1)) if m_pt else (10 if cls else None)
+    paper = "a4paper" if "a4paper" in cls_opts else ("letterpaper" if "letterpaper" in cls_opts else None)
+
+    # \usepackage 列表（支持 {a,b} 逗号多包）
+    packages: list[str] = []
+    for m in re.finditer(r"\\usepackage\s*(?:\[[^\]]*\])?\s*\{\s*([^}]+?)\s*\}", src):
+        packages += [p.strip().lower() for p in m.group(1).split(",") if p.strip()]
+
+    # 行距：\linespread{...} 或 \setstretch{...}（值直接按"行距倍数"口径评估——
+    # 按步骤4 规格：低于 min_line_spacing 即 fail；LaTeX 实际倍数还含 baselinestretch
+    # 的字号比，本引擎取显式设置值做保守判定）
+    line_spread: float | None = None
+    m = re.search(r"\\linespread\s*\{\s*([\d.]+)\s*\}", src)
+    if not m:
+        m = re.search(r"\\setstretch\s*\{\s*([\d.]+)\s*\}", src)
+    if m:
+        line_spread = float(m.group(1))
+
+    # 页边距（geometry）
+    margins = _parse_geometry(src)
+
+    # 计数
+    figures = len(re.findall(r"\\begin\s*\{\s*figure\*?\s*\}", src))
+    tables = len(re.findall(r"\\begin\s*\{\s*table\*?\s*\}", src))
+    cites = len(re.findall(r"\\cite\w*\s*\{", src))
+
+    # 参考文献：\bibliography{...}（BibTeX）/ \printbibliography（biblatex）/ thebibliography
+    has_bibtex = bool(re.search(r"\\bibliography\s*\{", src))
+    has_printbib = bool(re.search(r"\\printbibliography", src))
+    has_thebib = bool(re.search(r"\\begin\s*\{\s*thebibliography\s*\}", src))
+    has_bibstyle = bool(re.search(r"\\bibliographystyle\s*\{", src))  # BibTeX 必需；biblatex 不需要
+    has_bib = has_bibtex or has_printbib or has_thebib
+    refs_text: str | None = None
+    m_bib = re.search(r"\\begin\s*\{\s*thebibliography\s*\}[\s\S]*?\\end\s*\{\s*thebibliography\s*\}", src)
+    if m_bib:
+        refs_text = m_bib.group(0)
+
+    # 宏表（\newcommand{\xxx} / \renewcommand）——用于解析准确性（识别自定义宏）
+    macros = re.findall(r"\\(?:new|re)command\s*\{\s*\\(\w+)\s*\}", src)
+
+    # 匿名评审命令探测（规则集 anonymous:true 时检查）
+    m_anon = re.search(r"\\(?:anonymi[sz]e|anon\b|hideauthor|ifdoubleblind)", src, re.IGNORECASE)
+
+    return {
+        "source_kind": "tex",
+        "pages": None,  # LaTeX 源文件页数需编译后才有 → 检查项降级 warn（宽容化）
+        "margins_mm": margins,
+        "font_weights": {},
+        "size_weights": {float(fontsize): 100} if fontsize else {},
+        "line_spacing_median": line_spread,
+        "figures": figures,
+        "tables": tables,
+        "refs_text": refs_text,
+        "refs_found": has_bib,
+        "tex": {
+            "class": cls,
+            "fontsize_pt": fontsize,
+            "paper": paper,
+            "packages": packages,
+            "cites": cites,
+            "macros": macros,
+            "anon_cmd": m_anon.group(0) if m_anon else None,
+            "bib_bibtex": has_bibtex,
+            "bib_style": has_bibstyle,
+        },
+    }
+
+
+# ---------------------------------------------------------------- 参考文献样式检测
+
+def detect_refs_style(text: str | None) -> tuple[str, str]:
+    """宽容化检测：返回 (detected, sample_line)。含糊 → unknown（后续只 warn）。"""
+    if not text:
+        return "unknown", ""
+    lines = [l.strip() for l in text.splitlines() if l.strip()][:40]
+    if not lines:
+        return "unknown", ""
+    n = len(lines)
+    gb = sum(1 for l in lines if _GB_TAG_RE.search(l))
+    year = sum(1 for l in lines if _PAREN_YEAR_RE.search(l))
+    num = sum(1 for l in lines if _BRACKET_NUM_RE.match(l))
+    doi = sum(1 for l in lines if _DOI_RE.search(l))
+    sample = lines[0][:80]
+
+    if gb / n >= 0.4:
+        return "gb7714", sample
+    if num / n >= 0.4 and year / n < 0.3:
+        return "numbered", sample
+    if year / n >= 0.3 or doi / n >= 0.3:
+        return "author_year", sample
+    return "unknown", sample
+
+
+# ---------------------------------------------------------------- 检查项构建
+
+def _chk(key: str, name: str, status: str, detail: str, suggestion: str = "") -> dict[str, str]:
+    return {"key": key, "name": name, "status": status, "detail": detail, "suggestion": suggestion}
+
+
+def _check_pages(profile: dict[str, Any], rules: dict[str, Any]) -> dict[str, str]:
+    limit = int(rules.get("max_pages", 10))
+    pages = profile.get("pages")
+    kind = profile.get("source_kind") or "doc"
+    if pages is None:
+        # 宽容化：Word/LaTeX 页数缺失绝不 fail
+        if kind == "tex":
+            return _chk(
+                "pages", "页数", "warn",
+                f"LaTeX 源无法直接统计页数（规则上限 {limit} 页），需编译后核对",
+                "编译后确认（如 xelatex main.tex）总页数 ≤ 上限",
+            )
+        return _chk(
+            "pages", "页数", "warn",
+            "Word 未记录页数，请自行核对",
+            f"在 Word 中按 Ctrl+End 查看总页数，或导出 PDF 后重查（规则上限 {limit} 页）",
+        )
+    if pages <= limit:
+        return _chk("pages", "页数", "pass", f"共 {pages} 页，规则上限 {limit} 页")
+    return _chk(
+        "pages", "页数", "fail", f"共 {pages} 页，超出规则上限 {limit} 页",
+        f"压缩至 ≤{limit} 页，或将方法/图表移入补充材料",
+    )
+
+
+def _check_fonts(profile: dict[str, Any], rules: dict[str, Any]) -> dict[str, str]:
+    min_font = float(rules.get("min_font_pt", 9))
+    # LaTeX：字号来自 \documentclass 选项（10/11/12pt，粒度粗）
+    if profile.get("source_kind") == "tex":
+        tex = profile.get("tex") or {}
+        cls = tex.get("class") or "documentclass"
+        fs = tex.get("fontsize_pt")
+        pkgs = tex.get("packages") or []
+        font_pkgs = sorted(p for p in pkgs if p in _TEX_FONT_PKGS or p in ("helvet", "courier", "charter", "fourier"))
+        detail = (
+            f"\\documentclass 选项字号 {fs}pt（类 {cls}）；"
+            f"字体宏包：{'、'.join(font_pkgs) if font_pkgs else '未引入'}"
+            + (f"；纸张 {tex['paper']}" if tex.get("paper") else "")
+        )
+        if fs is None:
+            return _chk("fonts", "字体字号", "warn", detail + "\n建议：\n  \\documentclass[11pt]{article}", "补充 \\documentclass 声明")
+        if fs < min_font:
+            # LaTeX 粒度粗 → 按步骤4 规格降为 warn（非 fail）
+            return _chk(
+                "fonts", "字体字号", "warn", detail + f"\n建议：\n  \\documentclass[11pt]{{{cls}}}",
+                f"正文字号低于下限 {min_font:.0f}pt，请改用 11pt/12pt 选项",
+            )
+        return _chk("fonts", "字体字号", "pass", detail)
+
+    size_w: dict[float, int] = profile.get("size_weights") or {}
+    font_w: dict[str, int] = profile.get("font_weights") or {}
+    if not size_w:
+        return _chk("fonts", "字体字号", "warn", "未能提取字体信息", "确认文档含可选中文本（扫描件无法检查字体）")
+    min_font = float(rules.get("min_font_pt", 9))
+    max_fonts = int(rules.get("max_fonts", 6))
+    total = sum(size_w.values())
+    body_pt = max(size_w, key=size_w.get)
+    body_ratio = int(size_w[body_pt] / total * 100)
+    distinct = len(font_w)
+    top_fonts = sorted(font_w.items(), key=lambda kv: -kv[1])[:3]
+    top_text = "、".join(f"{k}({v}字)" for k, v in top_fonts)
+    detail = f"主要字号 {body_pt}pt（约 {body_ratio}%），共 {distinct} 种字体；高频字体：{top_text}"
+    if body_pt < min_font:
+        return _chk(
+            "fonts", "字体字号", "fail", detail,
+            f"将正文字号提高至 ≥{min_font}pt（当前主字号 {body_pt}pt）",
+        )
+    if distinct > max_fonts:
+        return _chk(
+            "fonts", "字体字号", "warn", detail,
+            f"字体种类偏多（{distinct} > {max_fonts}），建议全文统一为 1–2 种正文字体",
+        )
+    return _chk("fonts", "字体字号", "pass", detail)
+
+
+def _check_margins(profile: dict[str, Any], rules: dict[str, Any]) -> dict[str, str]:
+    limit = float(rules.get("min_margin_mm", 15))
+    margins = profile.get("margins_mm")
+    # LaTeX：页边距来自 geometry；低于下限按步骤4 规格给 warn（非 fail），附建议片段
+    if profile.get("source_kind") == "tex":
+        if not margins:
+            return _chk(
+                "margins", "页边距", "warn",
+                "未通过 geometry 设置页边距（按类默认评估）"
+                + f"\n建议：\n  \\usepackage[margin=25mm]{{geometry}}",
+                "在导言区显式声明页边距",
+            )
+        lo = min(margins.values())
+        detail = f"geometry 页边距最小 {lo:.0f}mm（" + "、".join(f"{k}{v:.0f}" for k, v in margins.items()) + f"），规则下限 {limit:.0f}mm"
+        if lo < limit:
+            return _chk(
+                "margins", "页边距", "warn",
+                detail + f"\n建议：\n  \\usepackage[margin={limit:.0f}mm]{{geometry}}",
+                f"调大页边距至 ≥{limit:.0f}mm",
+            )
+        return _chk("margins", "页边距", "pass", detail)
+    if not margins:
+        return _chk("margins", "页边距", "warn", "未能提取页边距信息", "检查文档是否含可定位文本")
+    vals = [margins.get(k) for k in ("top", "right", "bottom", "left")]
+    vals = [v for v in vals if v is not None]
+    if not vals:
+        return _chk("margins", "页边距", "warn", "未能提取页边距信息", "检查文档是否含可定位文本")
+    t, r = margins.get("top"), margins.get("right")
+    b, l = margins.get("bottom"), margins.get("left")
+    lo = min(vals)
+    sides = "、".join(
+        f"{name}{v:.0f}" for name, v in (("上", t), ("右", r), ("下", b), ("左", l)) if v is not None
+    )
+    detail = f"四边最小 {lo:.0f}mm（{sides}），规则下限 {limit:.0f}mm"
+    if lo >= limit:
+        return _chk("margins", "页边距", "pass", detail)
+    if lo >= limit * 0.8:
+        return _chk("margins", "页边距", "warn", detail, f"将页边距调大至 ≥{limit:.0f}mm")
+    return _chk("margins", "页边距", "fail", detail, f"页边距过小，请调至 ≥{limit:.0f}mm（版式设置）")
+
+
+def _check_spacing(profile: dict[str, Any], rules: dict[str, Any]) -> dict[str, str]:
+    lo = float(rules.get("min_line_spacing", 1.15))
+    ratio = profile.get("line_spacing_median")
+    # LaTeX：\linespread/\setstretch 显式设置值；低于下限按步骤4 规格直接 fail
+    if profile.get("source_kind") == "tex":
+        if ratio is None:
+            return _chk(
+                "spacing", "行距", "pass",
+                "未显式设置 \\linespread/\\setstretch，LaTeX 类默认约 1.2 倍（如 10pt→12pt baselineskip）",
+            )
+        detail = f"\\linespread/\\setstretch = {ratio:.2f}，规则下限 {lo:.2f}"
+        if ratio < lo:
+            return _chk(
+                "spacing", "行距", "fail",
+                detail + f"\n建议：\n  \\linespread{{{lo:.2f}}}   % 或 \\setstretch{{{lo:.2f}}}（导言区）",
+                "在导言区调大行距设置",
+            )
+        return _chk("spacing", "行距", "pass", detail)
+    if ratio is None:
+        return _chk("spacing", "行距", "warn", "未能提取行距信息", "确认段落使用固定/多倍行距设置")
+    lo = float(rules.get("min_line_spacing", 1.15))
+    detail = f"正文中位行距约 {ratio:.2f} 倍，规则下限 {lo:.2f} 倍"
+    if ratio >= lo:
+        return _chk("spacing", "行距", "pass", detail)
+    if ratio >= lo * 0.9:
+        return _chk("spacing", "行距", "warn", detail, f"段落行距设为 ≥{lo:.2f} 倍（如 1.5 倍行距）")
+    return _chk("spacing", "行距", "fail", detail, f"行距过密，请设为 ≥{lo:.2f} 倍行距")
+
+
+def _check_figures(profile: dict[str, Any], rules: dict[str, Any]) -> dict[str, str]:
+    figures = int(profile.get("figures") or 0)
+    tables = int(profile.get("tables") or 0)
+    min_f = int(rules.get("min_figures", 1))
+    detail = f"检测到图 {figures} 张、表 {tables} 个（图注/表注正则 + 内嵌对象启发式）"
+    if figures >= min_f:
+        return _chk("figures", "图表数量", "pass", detail)
+    # 启发式检测不可靠 → 低于阈值只 warn 不 fail
+    return _chk(
+        "figures", "图表数量", "warn", detail,
+        f"常规研究论文建议 ≥{min_f} 图；若为综述/短文可忽略（本项为启发式检测）",
+    )
+
+
+# 仅"明确不符"才 fail 的 (expected, detected) 组合（宽容化：其余含糊组合一律 warn）
+_REF_FAIL_PAIRS = {
+    ("apa", "gb7714"),        # 找到 [J] 标引但规则要求 APA
+    ("gb7714", "author_year"),  # 无 [J] 标引的作者-年份制，但规则要求 GB/T 7714
+    ("apa", "numbered"),      # 编号制引文但规则要求 APA
+}
+
+
+def _check_refs(profile: dict[str, Any], rules: dict[str, Any]) -> dict[str, str]:
+    expected = str(rules.get("refs_style", "apa")).lower()
+    exp_label = _STYLE_LABEL.get(expected, expected)
+    if not profile.get("refs_found"):
+        return _chk(
+            "refs", "参考文献格式", "warn",
+            "未找到参考文献节（References/参考文献 / \\bibliography / thebibliography）",
+            "确认存在参考文献声明后重查",
+        )
+    if profile.get("source_kind") == "tex":
+        tex = profile.get("tex") or {}
+        # BibTeX：\bibliography 存在但缺 \bibliographystyle → warn（样式引擎未知）
+        if tex.get("bib_bibtex") and not tex.get("bib_style"):
+            return _chk(
+                "refs", "参考文献格式", "warn",
+                f"规则要求 {exp_label}；检测到 \\bibliography 但缺少 \\bibliographystyle（BibTeX 无法确定引用样式）"
+                + "\n建议：\n  \\bibliographystyle{plain}   % 按期刊/模板指定实际样式",
+                "在 \\bibliography 前补 \\bibliographystyle",
+            )
+        if not profile.get("refs_text"):
+            # 条目在 .bbl/编译产物，源文件无文本 → 宽容化只 warn
+            return _chk(
+                "refs", "参考文献格式", "warn",
+                f"规则要求 {exp_label}；检测到参考文献声明（条目由编译生成，源文件无条目文本）",
+                "编译后核对参考文献条目样式",
+            )
+    detected, sample = detect_refs_style(profile.get("refs_text"))
+    det_label = _STYLE_LABEL[detected]
+    detail = f"规则要求 {exp_label}；检测到 {det_label}；样例：{sample}"
+    # 宽容化：仅"明确不符"（_REF_FAIL_PAIRS）才 fail；含糊/不确定一律 warn
+    if (expected, detected) in _REF_FAIL_PAIRS:
+        return _chk("refs", "参考文献格式", "fail", detail, f"按 {exp_label} 调整全部文献条目（可用文献管理工具一键转换）")
+    if detected == "unknown":
+        return _chk("refs", "参考文献格式", "warn", detail, f"请人工核对是否符合 {exp_label}")
+    if expected == "gb7714" and detected == "numbered":
+        return _chk("refs", "参考文献格式", "warn", detail, "GB/T 7714 顺序编码制也用编号，需人工确认条目含 [J] 等类型标引")
+    if expected == "author-year-journal" and detected in ("gb7714", "numbered"):
+        return _chk("refs", "参考文献格式", "warn", detail, f"请对照期刊投稿指南核对是否符合 {exp_label}")
+    return _chk("refs", "参考文献格式", "pass", detail)
+
+
+def _check_font_packages(profile: dict[str, Any], rules: dict[str, Any]) -> dict[str, str]:
+    """LaTeX 特有：多个相互覆盖的字体宏包（times + mathptmx 类）→ warn。"""
+    pkgs = set((profile.get("tex") or {}).get("packages") or [])
+    clash = sorted(pkgs & _TEX_FONT_PKGS)
+    if len(clash) >= 2:
+        detail = (
+            f"检测到多个相互覆盖的字体宏包：{'、'.join(clash)}（后加载者覆盖前者，易产生冲突）"
+            + "\n建议：\n  %只保留一套字体方案，例如：\n  \\usepackage{newtx}   % newtxtext + newtxmath 一体"
+        )
+        return _chk("fontpkgs", "字体包兼容", "warn", detail, "移除重复/冲突的字体宏包，只保留一套")
+    return _chk(
+        "fontpkgs", "字体包兼容", "pass",
+        "字体宏包：" + ("、".join(clash) if clash else "未引入冲突类字体包"),
+    )
+
+
+def _check_anonymous(profile: dict[str, Any], rules: dict[str, Any]) -> dict[str, str]:
+    """LaTeX 特有且规则集 anonymous:true 时才出：源文件需含匿名处理命令。"""
+    tex = profile.get("tex") or {}
+    cmd = tex.get("anon_cmd")
+    if cmd:
+        return _chk("anonymous", "匿名评审", "pass", f"检测到匿名处理命令 {cmd}")
+    return _chk(
+        "anonymous", "匿名评审", "warn",
+        "规则要求匿名评审，源文件未检测到匿名处理命令"
+        + "\n建议：\n  %隐去作者/致谢/自引，或定义匿名宏：\n  \\newcommand{\\anon}[1]{[ANON]}",
+        "按期刊要求对作者信息做匿名处理",
+    )
+
+
+def build_checks(profile: dict[str, Any], rules: dict[str, Any]) -> list[dict[str, str]]:
+    checks = [
+        _check_pages(profile, rules),
+        _check_fonts(profile, rules),
+        _check_margins(profile, rules),
+        _check_spacing(profile, rules),
+    ]
+    if profile.get("source_kind") == "tex":
+        checks.append(_check_font_packages(profile, rules))
+    checks.append(_check_figures(profile, rules))
+    checks.append(_check_refs(profile, rules))
+    if profile.get("source_kind") == "tex" and rules.get("anonymous"):
+        checks.append(_check_anonymous(profile, rules))
+    return checks
+
+
+# ---------------------------------------------------------------- 入口
+
+def check_document(data: bytes, kind: str, target_journal: str) -> dict[str, Any]:
+    """kind ∈ pdf|docx|tex。返回 {checks, summary, meta}（filename 由路由器补入 meta）。"""
+    if kind == "pdf":
+        profile = extract_profile_pdf(data)
+    elif kind == "docx":
+        profile = extract_profile_docx(data)
+    elif kind == "tex":
+        profile = extract_tex_profile(data)
+    else:
+        raise FormatCheckError(f"不支持的文件类型：{kind}")
+
+    rules, ruleset_meta = load_ruleset(target_journal)
+    checks = build_checks(profile, rules)
+    summary = {"pass": 0, "warn": 0, "fail": 0}
+    for c in checks:
+        summary[c["status"]] = summary.get(c["status"], 0) + 1
+
+    detected, _ = detect_refs_style(profile.get("refs_text")) if profile.get("refs_found") else ("unknown", "")
+    meta = {
+        **ruleset_meta,
+        "file_type": kind,
+        "pages": profile.get("pages"),
+        "refs_style_expected": str(rules.get("refs_style", "apa")).lower(),
+        "refs_style_detected": detected,
+    }
+    if kind == "tex":
+        tex = profile.get("tex") or {}
+        meta["tex"] = {
+            "class": tex.get("class"),
+            "fontsize_pt": tex.get("fontsize_pt"),
+            "paper": tex.get("paper"),
+            "packages": tex.get("packages"),
+            "cites": tex.get("cites"),
+            "macros": (tex.get("macros") or [])[:10],
+        }
+    return {"checks": checks, "summary": summary, "meta": meta}
@@ -0,0 +1,232 @@
+"""services/format_extractor.py —— 投稿指南 → 格式规则 JSON（LLM 抽取，第一批）。
+
+- 调 services/llm.py 的 complete_json（DeepSeek json_object + 修复重试，零新依赖）
+- Prompt = 「格式规则抽取器」模板：目标字段与 journals.json format_rules_default
+  同构（max_pages / min_font_pt / min_margin_mm / min_line_spacing / min_figures /
+  max_fonts / refs_style / anonymous），强制每字段带 source_quotes + confidence
+- 诚实原则：正文没写 → null，绝不编造（与 format_check 诚实原则一致）
+- 解析/校验失败 → {"ok": False, "error": ...}
+
+返回：
+  成功 {"ok": True, "rules": {...}, "source_quotes": {...},
+        "confidence": {...}, "notes": str, "raw": LLM原始JSON, "error": None}
+  失败 {"ok": False, "error": "...", 其余键为 None}
+source_url 由调用方（scripts/fetch_format_rules.py）在落盘时补入结果文件。
+"""
+from __future__ import annotations
+
+import logging
+import re
+from typing import Any
+
+from .llm import LLMError, complete_json
+
+logger = logging.getLogger(__name__)
+
+# 「格式规则抽取器」模板（system prompt）
+_SYSTEM = """你是「格式规则抽取器」：从期刊官方投稿指南的 Markdown 正文中抽取格式规则，供投稿排版检查引擎使用。
+
+# 目标字段（rules 对象，严格用以下字段名）
+- max_pages：正文页数上限（整数；原文无明确上限 → null）
+- min_font_pt：最小字号（数字，单位 pt；原文若用 cm/mm/inch 给出则换算为 pt）
+- min_margin_mm：最小页边距（数字，单位 mm；原文若用 inch 给出则 ×25.4 换算）
+- min_line_spacing：最小行距倍数（数字；如 "double-spaced" → 2.0，"1.5 spacing" → 1.5）
+- min_figures：研究论文最少图数（整数；无明确要求 → null）
+- max_fonts：全文最多字体种类（整数；无明确要求 → null）
+- refs_style：参考文献样式，枚举 apa | gb7714 | author_year | numbered | vancouver | mla | chicago | other（无法判断 → null）
+- anonymous：是否要求匿名/双盲评审（true / false / null）
+
+# 凭证（强制）
+- 每个非 null 字段必须给 source_quotes[字段名]：从正文【逐字】摘录的 1-3 句原文，
+  不改写、不翻译、不丢掉含关键数字的句子。
+- source_quotes["_general"]：整体最有凭证价值的 1-3 条原文摘录。
+- confidence：{"overall": 0-1, "per_field": {"字段名": 0-1}}。
+  直接原文命中 ≥0.9；单位换算 0.6-0.9；靠上下文推断 <0.6。
+
+# 诚实原则
+- 正文没写到的字段一律 null，绝不用常识或训练记忆补值。
+- 单位换算允许做，但该字段 confidence 不得超过 0.9。
+- 换算过程、拿不准的点、页面疑似不完整，写进 notes。
+
+# 输出
+只输出一个 JSON 对象，不要代码块、不要解释文字：
+{"rules": {"max_pages": null, "min_font_pt": null, "min_margin_mm": null,
+  "min_line_spacing": null, "min_figures": null, "max_fonts": null,
+  "refs_style": null, "anonymous": null},
+ "source_quotes": {"字段名": ["原文1", "..."], "_general": ["原文1", "..."]},
+ "confidence": {"overall": 0.0, "per_field": {"字段名": 0.0}},
+ "notes": "一句话说明抽取依据与不确定点"}"""
+
+_USER_TMPL = """期刊：{journal_name}
+
+=== 官方投稿指南正文（Markdown，已截断） ===
+{markdown}"""
+
+_RULE_INT_KEYS = ("max_pages", "min_figures", "max_fonts")
+_REFS_ALLOWED = {"apa", "gb7714", "author_year", "numbered", "vancouver",
+                 "mla", "chicago", "other"}
+_REFS_ALIAS = {
+    "apa-7": "apa", "apa7": "apa", "apa 7th": "apa", "apa_7th": "apa",
+    "harvard": "author_year", "author-year": "author_year", "authoryear": "author_year",
+    "gb/t 7714": "gb7714", "gb/t-7714": "gb7714", "gb7714-2015": "gb7714",
+    "gb/t7714": "gb7714", "chicago author-date": "chicago",
+}
+
+
+# 字符串值带显式单位时的目标单位换算表（LLM 若回传原文单位的兜底；无单位=数值即目标单位）
+_UNIT_TO_MM = {"mm": 1.0, "cm": 10.0, "in": 25.4, "inch": 25.4, "inches": 25.4, "pt": 25.4 / 72}
+_UNIT_TO_PT = {"pt": 1.0, "mm": 72 / 25.4, "cm": 72 / 2.54, "in": 72.0, "inch": 72.0, "inches": 72.0}
+
+
+def _to_int(v: Any) -> int | None:
+    if isinstance(v, bool) or v is None:
+        return None
+    if isinstance(v, int):
+        return v
+    if isinstance(v, float):
+        return int(round(v))
+    if isinstance(v, str):
+        m = re.search(r"-?\d+", v)
+        if m:
+            return int(m.group(0))
+    return None
+
+
+def _to_float(v: Any, units: dict[str, float] | None = None) -> float | None:
+    if isinstance(v, bool) or v is None:
+        return None
+    if isinstance(v, (int, float)):
+        return float(v)
+    if isinstance(v, str):
+        m = re.search(r"(-?\d+(?:\.\d+)?)\s*([a-zA-Z]+)?", v)
+        if not m:
+            return None
+        x = float(m.group(1))
+        unit = (m.group(2) or "").lower()
+        if units and unit:
+            factor = units.get(unit)
+            if factor is None:
+                return None  # 未知单位不猜
+            x *= factor
+        return x
+    return None
+
+
+def _to_bool(v: Any) -> bool | None:
+    if isinstance(v, bool):
+        return v
+    if isinstance(v, (int, float)) and not isinstance(v, bool):
+        if v in (0, 1):
+            return bool(v)
+    if isinstance(v, str):
+        low = v.strip().lower()
+        if low in ("true", "yes", "required"):
+            return True
+        if low in ("false", "no", "not required"):
+            return False
+    return None
+
+
+def _norm_refs(v: Any) -> str | None:
+    if not isinstance(v, str) or not v.strip():
+        return None
+    low = v.strip().lower()
+    low = _REFS_ALIAS.get(low, low)
+    return low if low in _REFS_ALLOWED else "other"
+
+
+def _norm_conf(v: Any) -> float | None:
+    if isinstance(v, bool) or not isinstance(v, (int, float)):
+        return None
+    return max(0.0, min(1.0, float(v)))
+
+
+def _normalize(raw: dict[str, Any]) -> dict[str, Any]:
+    """白名单归一：类型错的值置 null（宁缺勿错，raw 全量保留在结果里）。"""
+    src = raw.get("rules")
+    src = src if isinstance(src, dict) else {}
+    rules: dict[str, Any] = {}
+    for k in _RULE_INT_KEYS:
+        rules[k] = _to_int(src.get(k))
+    rules["min_font_pt"] = _to_float(src.get("min_font_pt"), _UNIT_TO_PT)
+    rules["min_margin_mm"] = _to_float(src.get("min_margin_mm"), _UNIT_TO_MM)
+    rules["min_line_spacing"] = _to_float(src.get("min_line_spacing"))
+    rules["refs_style"] = _norm_refs(src.get("refs_style"))
+    rules["anonymous"] = _to_bool(src.get("anonymous"))
+
+    sq_src = raw.get("source_quotes")
+    sq_src = sq_src if isinstance(sq_src, dict) else {}
+    quotes: dict[str, list[str]] = {}
+    for key, val in sq_src.items():
+        if key != "_general" and key not in rules:
+            continue
+        items = val if isinstance(val, list) else [val]
+        cleaned = [str(x).strip() for x in items if isinstance(x, (str, int, float))
+                   and str(x).strip()]
+        if cleaned:
+            quotes[key] = cleaned
+
+    conf_src = raw.get("confidence")
+    conf_src = conf_src if isinstance(conf_src, dict) else {}
+    pf_src = conf_src.get("per_field")
+    pf_src = pf_src if isinstance(pf_src, dict) else {}
+    per_field: dict[str, float] = {}
+    for k, v in pf_src.items():
+        c = _norm_conf(v)
+        if c is not None and (k in rules or k == "_general"):
+            per_field[k] = c
+    overall = _norm_conf(conf_src.get("overall"))
+    if overall is None and per_field:
+        overall = sum(per_field.values()) / len(per_field)
+    confidence = {"overall": overall, "per_field": per_field}
+
+    notes = raw.get("notes")
+    return {
+        "rules": rules,
+        "source_quotes": quotes,
+        "confidence": confidence,
+        "notes": str(notes) if notes else "",
+    }
+
+
+def _validation_error(norm: dict[str, Any]) -> str | None:
+    """强制凭证：任一非 null 字段缺 source_quotes → 拒收（ok=False）。"""
+    missing = [k for k, v in norm["rules"].items()
+               if v is not None and k not in norm["source_quotes"]]
+    if missing:
+        return f"LLM 输出缺少非 null 字段的 source_quotes：{', '.join(missing)}"
+    if not norm["source_quotes"].get("_general"):
+        return "LLM 输出缺少 source_quotes._general 整体引证"
+    if any(v is not None for v in norm["rules"].values()):
+        return None
+    return "LLM 未抽出任何非 null 字段（rules 全空）"
+
+
+async def extract_format_rules(markdown: str, journal_name: str) -> dict:
+    """markdown（≤30000 字符）+ 期刊名 → 抽取结果（schema 见模块 docstring）。"""
+    if not markdown or not markdown.strip():
+        return {"ok": False, "error": "markdown 为空", "rules": None,
+                "source_quotes": None, "confidence": None, "notes": None, "raw": None}
+    user = _USER_TMPL.format(journal_name=journal_name, markdown=markdown)
+    try:
+        raw = await complete_json(_SYSTEM, user, temperature=0.1, max_tokens=8000)
+    except LLMError as exc:
+        return {"ok": False, "error": f"LLM 调用失败：{exc}", "rules": None,
+                "source_quotes": None, "confidence": None, "notes": None, "raw": None}
+    if not isinstance(raw, dict):
+        return {"ok": False, "error": f"LLM 输出非 JSON 对象：{type(raw).__name__}",
+                "rules": None, "source_quotes": None, "confidence": None,
+                "notes": None, "raw": None}
+
+    norm = _normalize(raw)
+    err = _validation_error(norm)
+    if err:
+        logger.warning("[extract] %s 校验失败：%s", journal_name, err)
+        return {"ok": False, "error": err, "rules": None,
+                "source_quotes": norm["source_quotes"], "confidence": norm["confidence"],
+                "notes": norm["notes"], "raw": raw}
+    filled = sum(1 for v in norm["rules"].values() if v is not None)
+    logger.info("[extract] %s → 8 字段中 %d 个非 null", journal_name, filled)
+    return {"ok": True, "error": None, "rules": norm["rules"],
+            "source_quotes": norm["source_quotes"],
+            "confidence": norm["confidence"], "notes": norm["notes"], "raw": raw}
@@ -0,0 +1,356 @@
+"""services/format_fetcher.py —— 投稿指南页面抓取（格式规则自动获取·第一批）。
+
+约束（用户拍板 2026-10-10）：
+- 零新依赖：httpx + beautifulsoup4（venv 已装 4.15.0，用户明确指定使用；
+  lxml 6.1.2 在 requirements.lock 内，作 bs4 解析器）
+- 同域限速 ≥ 2s（robots.txt 与正文请求共用计时器）
+- 抓正文前先 GET /robots.txt，命中 Disallow → ok=False 跳过
+- UA: "PlantAI-RAG-Bot/1.0 (+contact: admin@example.com)"
+- 只提取正文（去导航/页脚/脚本），截断至 30000 字符
+
+返回固定四键：{"ok": bool, "markdown": str, "error": str | None, "fetched_at": str}
+"""
+from __future__ import annotations
+
+import asyncio
+import logging
+import re
+import time
+from datetime import datetime, timezone
+from urllib.parse import urlparse
+
+import httpx
+from bs4 import BeautifulSoup, NavigableString
+
+logger = logging.getLogger(__name__)
+
+USER_AGENT = "PlantAI-RAG-Bot/1.0 (+contact: admin@example.com)"
+TIMEOUT = 30.0
+MAX_CHARS = 30_000
+MIN_INTERVAL_PER_HOST = 2.0  # 同域请求间隔 ≥ 2s（robots 与正文共用）
+_MIN_TEXT_CHARS = 200        # 正文短于此 → 疑似 JS 渲染/反爬页
+_HEADERS = {
+    "User-Agent": USER_AGENT,
+    "Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8",
+    "Accept-Language": "en-US,en;q=0.9",
+}
+
+# 同域限速：host → 上次请求完成时刻（monotonic）
+_last_hit: dict[str, float] = {}
+_throttle_lock = asyncio.Lock()
+
+
+def _now_iso() -> str:
+    return datetime.now(timezone.utc).isoformat(timespec="seconds")
+
+
+def _fail(error: str) -> dict:
+    return {"ok": False, "markdown": "", "error": error, "fetched_at": _now_iso()}
+
+
+async def _throttle(host: str) -> None:
+    """同域串行 + ≥2s 间隔（全局锁：本批抓取量小，简单可靠优先）。"""
+    async with _throttle_lock:
+        now = time.monotonic()
+        wait = _last_hit.get(host, now) + MIN_INTERVAL_PER_HOST - now
+        if wait > 0:
+            await asyncio.sleep(wait)
+        _last_hit[host] = time.monotonic()
+
+
+# ---------------------------------------------------------------- robots.txt
+
+def _parse_robots(text: str) -> list[tuple[list[str], list[tuple[str, str]]]]:
+    """→ [(agents, [(kind, pattern)...]), ...]（连续 UA 行同组；规则行后出现 UA=新组）。"""
+    groups: list[tuple[list[str], list[tuple[str, str]]]] = []
+    agents: list[str] = []
+    rules: list[tuple[str, str]] = []
+    for raw in text.splitlines():
+        line = raw.split("#", 1)[0].strip()
+        if not line or ":" not in line:
+            continue
+        key, _, value = line.partition(":")
+        key, value = key.strip().lower(), value.strip()
+        if key == "user-agent":
+            if agents and rules:  # 上一组已出规则 → 当前 UA 行开新组
+                groups.append((agents, rules))
+                agents, rules = [], []
+            agents.append(value)
+        elif key in ("allow", "disallow"):
+            if not agents:  # 无前置 UA 的规则按 * 组处理
+                agents = ["*"]
+            rules.append((key, value))
+    if agents:
+        groups.append((agents, rules))
+    return groups
+
+
+def _robots_path_allowed(groups, path: str) -> tuple[bool, str]:
+    """最长匹配决胜（同长 Allow 优先；`$` 结尾=精确匹配；空 Disallow 跳过）。"""
+
+    def matched_by(pat: str) -> bool:
+        if pat.endswith("$"):
+            return path == pat[:-1]
+        return path.startswith(pat)
+
+    token = "plantai-rag-bot"
+    matched = [rules for agents, rules in groups
+               if any(token in a.lower() for a in agents)]
+    if not matched:
+        matched = [rules for agents, rules in groups
+                   if any(a.lower() == "*" for a in agents)]
+    if not matched:
+        return True, "robots.txt 无匹配组（本 bot 不受限）"
+
+    best_len, best_allow, best_pat = -1, False, ""
+    for rules in matched:
+        for kind, pat in rules:
+            if not pat:  # "Disallow:" 空值 = 放行一切（该组无需处理）
+                continue
+            if not matched_by(pat):
+                continue
+            length = len(pat)
+            allow = kind == "allow"
+            if length > best_len or (length == best_len and allow and not best_allow):
+                best_len, best_allow, best_pat = length, allow, pat
+    if best_len < 0:
+        return True, "robots.txt 允许（无路径匹配）"
+    if best_allow:
+        return True, f"robots.txt Allow 命中（{best_pat}）"
+    return False, f"robots.txt Disallow 命中（{best_pat}）"
+
+
+async def _robots_allows(client: httpx.AsyncClient, url: str) -> tuple[bool, str]:
+    p = urlparse(url)
+    robots_url = f"{p.scheme}://{p.netloc}/robots.txt"
+    await _throttle(p.netloc.lower())
+    try:
+        resp = await client.get(robots_url, headers=_HEADERS)
+    except httpx.HTTPError as exc:
+        return True, f"robots.txt 获取失败（{type(exc).__name__}），按允许处理"
+    if resp.status_code != 200:
+        return True, f"robots.txt HTTP {resp.status_code}，按允许处理"
+    groups = _parse_robots(resp.text)
+    return _robots_path_allowed(groups, p.path or "/")
+
+
+# ---------------------------------------------------------------- 正文提取
+
+_STRIP_TAGS = ("script", "style", "noscript", "iframe", "form", "nav",
+               "footer", "aside", "button", "select", "textarea", "input", "svg")
+_STRIP_ROLES = ("navigation", "contentinfo", "complementary", "search")
+# 正文容器候选（按优先级；首个文本 ≥500 字符者胜出）
+_CONTENT_SELECTORS = (
+    "main", "article", '[role="main"]', "#content", "#main", "#main-content",
+    ".article-body", "#article-body", ".article__body", ".hub-article-body",
+    ".page-content", ".main-content", ".content-area",
+)
+_CHALLENGE_MARKERS = ("just a moment", "attention required", "captcha",
+                      "access denied", "ddos protection", "verify you are human")
+
+
+def _decode_html(resp: httpx.Response) -> str:
+    """header charset → <meta charset> → utf-8（errors=replace），防 OUP/Wiley 无 header 乱码。"""
+    enc = None
+    m = re.search(r"charset=([\w.-]+)", resp.headers.get("content-type", ""), re.I)
+    if m:
+        enc = m.group(1)
+    if not enc:
+        m = re.search(rb"""charset\s*=\s*["']?([\w.-]+)""", resp.content[:4096], re.I)
+        if m:
+            enc = m.group(1).decode("ascii", "ignore")
+    try:
+        return resp.content.decode(enc or "utf-8", errors="replace")
+    except LookupError:
+        return resp.content.decode("utf-8", errors="replace")
+
+
+def _squeeze(s: str) -> str:
+    """行内空白压缩 + 去空行（保留单换行）。"""
+    lines = [re.sub(r"[ \t\r\f\v]+", " ", line).strip() for line in s.split("\n")]
+    return "\n".join(line for line in lines if line)
+
+
+def _inline(el) -> str:
+    """行内渲染：a→md链接 / strong→** / em→* / code→` / br→换行；跳过列表与图片。"""
+    parts: list[str] = []
+    for child in el.children:
+        name = getattr(child, "name", None)
+        if name is None:  # NavigableString
+            parts.append(str(child))
+            continue
+        if name in ("ul", "ol", "img", "picture", "figure"):
+            continue
+        if name == "a":
+            href = (child.get("href") or "").strip()
+            txt = _inline(child).strip()
+            if not txt:
+                continue
+            parts.append(f"[{txt}]({href})" if href.startswith(("http://", "https://")) else txt)
+        elif name in ("strong", "b"):
+            parts.append(f"**{_inline(child)}**")
+        elif name in ("em", "i"):
+            parts.append(f"*{_inline(child)}*")
+        elif name == "code":
+            parts.append(f"`{_inline(child).strip()}`")
+        elif name == "br":
+            parts.append("\n")
+        else:
+            parts.append(_inline(child))
+    return "".join(parts)
+
+
+def _list_md(el, ordered: bool) -> str:
+    lines: list[str] = []
+    idx = 1
+    for li in el.find_all("li", recursive=False):
+        # li 文本不含嵌套列表（嵌套列表随后缩进输出）
+        buf = []
+        for child in li.children:
+            if getattr(child, "name", None) in ("ul", "ol"):
+                continue
+            buf.append(_inline(child) if getattr(child, "name", None) else str(child))
+        txt = " ".join("".join(buf).split())
+        if txt:
+            lines.append(f"{idx}. {txt}" if ordered else f"- {txt}")
+            idx += 1
+        for nested in li.find_all(("ul", "ol"), recursive=False):
+            sub = _list_md(nested, nested.name == "ol")
+            if sub:
+                lines.extend("  " + line for line in sub.split("\n"))
+    return "\n".join(lines)
+
+
+def _table_md(table) -> str | None:
+    rows: list[list[str]] = []
+    for tr in table.find_all("tr"):
+        cells = [" ".join(_squeeze(_inline(c)).split())
+                 for c in tr.find_all(("td", "th"))]
+        if cells:
+            rows.append(cells)
+    if not rows:
+        return None
+    out = ["| " + " | ".join(rows[0]) + " |"]
+    if table.find("th"):  # 首行含表头 → 补分隔行（合法 GFM 表）
+        out.append("| " + " | ".join(["---"] * len(rows[0])) + " |")
+    out += ["| " + " | ".join(r) + " |" for r in rows[1:]]
+    return "\n".join(out)
+
+
+def _blocks(el, out: list[str]) -> None:
+    for child in el.children:
+        name = getattr(child, "name", None)
+        if name is None:  # 裸文本
+            txt = _squeeze(str(child))
+            if txt:
+                out.append(txt)
+            continue
+        if name in _STRIP_TAGS:
+            continue
+        if name in ("h1", "h2", "h3", "h4", "h5", "h6"):
+            txt = " ".join(_squeeze(_inline(child)).split())
+            if txt:
+                out.append("#" * int(name[1]) + " " + txt)
+        elif name == "p":
+            txt = _squeeze(_inline(child))
+            if txt:
+                out.append(txt)
+        elif name in ("ul", "ol"):
+            md = _list_md(child, name == "ol")
+            if md:
+                out.append(md)
+        elif name == "table":
+            md = _table_md(child)
+            if md:
+                out.append(md)
+        elif name == "blockquote":
+            txt = _squeeze(_inline(child))
+            if txt:
+                out.append("\n".join("> " + line for line in txt.split("\n")))
+        elif name == "pre":
+            code = child.get_text().strip("\n")
+            if code.strip():
+                out.append("```\n" + code + "\n```")
+        elif name == "hr":
+            out.append("---")
+        else:  # div/section/article/main/figure/dl/details/… 容器递归
+            _blocks(child, out)
+
+
+def _html_to_markdown(html: str) -> tuple[str, str | None]:
+    """→ (markdown, error)。选正文容器 → 去壳 → DOM 递归转 Markdown。"""
+    soup = BeautifulSoup(html, "lxml")  # lxml 在 lock 内；缺时 bs4 自动回退 html.parser
+
+    title = (soup.title.get_text() if soup.title else "") or ""
+    for tag in soup.find_all(_STRIP_TAGS):
+        tag.decompose()
+    for tag in soup.find_all(attrs={"role": _STRIP_ROLES}):
+        tag.decompose()
+
+    container = None
+    fallback_hits = []
+    for sel in _CONTENT_SELECTORS:
+        for node in soup.select(sel):
+            text_len = len(node.get_text(" ", strip=True))
+            fallback_hits.append((text_len, node))
+            if text_len >= 500:
+                container = node
+                break
+        if container is not None:
+            break
+    if container is None:
+        if fallback_hits:
+            container = max(fallback_hits, key=lambda x: x[0])[1]
+        else:
+            container = soup.body or soup
+
+    blocks: list[str] = []
+    _blocks(container, blocks)
+    md = "\n\n".join(blocks)
+
+    probe = (title + " " + md[:500]).lower()
+    marker = next((m for m in _CHALLENGE_MARKERS if m in probe), None)
+    if marker:
+        return "", f"疑似反爬/挑战页（命中 {marker!r}，title={title[:80]!r}）"
+    if len(md) < _MIN_TEXT_CHARS:
+        return "", f"正文提取过短（{len(md)} < {_MIN_TEXT_CHARS} 字符），疑似 JS 渲染或空壳页"
+    if len(md) > MAX_CHARS:
+        md = md[:MAX_CHARS - 1] + "…"
+    return md, None
+
+
+# ---------------------------------------------------------------- 入口
+
+async def fetch_submission_guidelines(url: str) -> dict:
+    """抓投稿指南页面 → 正文 Markdown。
+
+    流程：robots.txt 检查（≥2s 限速）→ 禁止即跳过 → GET 正文（≥2s 限速）
+    → 状态/类型校验 → 正文提取 → 截断 30000 字符。
+    """
+    parsed = urlparse(url)
+    if parsed.scheme not in ("http", "https") or not parsed.netloc:
+        return _fail(f"非法 URL：{url!r}")
+    host = parsed.netloc.lower()
+
+    async with httpx.AsyncClient(follow_redirects=True, timeout=TIMEOUT) as client:
+        allowed, robots_reason = await _robots_allows(client, url)
+        if not allowed:
+            logger.info("[fetch] robots 禁止，跳过 %s（%s）", url, robots_reason)
+            return _fail(robots_reason)
+
+        await _throttle(host)
+        try:
+            resp = await client.get(url, headers=_HEADERS)
+        except httpx.HTTPError as exc:
+            return _fail(f"请求失败（{type(exc).__name__}）：{exc}")
+        if resp.status_code != 200:
+            return _fail(f"HTTP {resp.status_code}")
+        ctype = resp.headers.get("content-type", "")
+        if "html" not in ctype and "xhtml" not in ctype:
+            return _fail(f"非 HTML 响应：{ctype or '无 Content-Type'}")
+
+        markdown, err = _html_to_markdown(_decode_html(resp))
+        if err:
+            return _fail(f"{err}（robots: {robots_reason}）")
+        logger.info("[fetch] %s → %d 字符（robots: %s）", url, len(markdown), robots_reason)
+        return {"ok": True, "markdown": markdown, "error": None, "fetched_at": _now_iso()}
@@ -0,0 +1,223 @@
+"""services/journal_kb.py —— 期刊 scope_desc → vstore 入库 + 向量匹配（只读消费 8094）。
+
+链路（全部复用 vstore 既有 API，零改动）：
+1. ensure_scope_docs：各期刊 scope_desc 以 .txt 入库（category=journal_scope，
+   name=期刊名），document_id 回写 journals.vstore_doc_id（幂等：已有 id 不重灌）。
+2. match：GET /api/vstore/search-chunks?q=<摘要截断>&doc_ids=<id 白名单>&top_k=N
+   → 按 doc_id 映射回期刊，取该期刊最高 chunk 分数为 similarity。
+3. 自愈：白名单命中 0 条 → GET /documents/{id} 探活 → 失效的重灌（vstore 去重
+   语义下同内容重灌会换 doc_id，需回写）→ 重试一次 → 仍 0 视为语义低相似。
+
+错误语义：连通性/上游异常抛 MatchError（路由降级为全量候选）；
+返回 ([], False) 表示检索成功但无有效匹配（路由同样降级）。
+"""
+from __future__ import annotations
+
+import logging
+from typing import Any
+
+import httpx
+
+from ..config import get_settings
+from ..db import set_vstore_doc_id
+
+logger = logging.getLogger(__name__)
+
+SCOPE_CATEGORY = "journal_scope"
+
+
+class MatchError(Exception):
+    """vstore 向量匹配失败（不可达/响应异常）。"""
+
+
+def _timeout() -> httpx.Timeout:
+    t = get_settings().vstore_match_timeout
+    return httpx.Timeout(connect=5.0, read=t, write=t, pool=5.0)
+
+
+def _err_body(resp: httpx.Response) -> str:
+    try:
+        payload = resp.json()
+    except ValueError:
+        return (resp.text or "").strip()[:500] or "（空响应体）"
+    if isinstance(payload, dict):
+        err = payload.get("error")
+        if isinstance(err, dict) and err.get("message"):
+            return str(err["message"])
+        if isinstance(err, str):
+            return err
+    return str(payload)[:500]
+
+
+async def _ingest_scope(client: httpx.AsyncClient, base: str, journal: dict[str, Any]) -> str:
+    """单本期刊 scope_desc 入库，返回 document_id。"""
+    content = str(journal.get("scope_desc") or "").strip()
+    if not content:
+        raise MatchError(f"期刊 scope_desc 为空：{journal.get('id')}")
+    jid = str(journal.get("id") or "")
+    try:
+        resp = await client.post(
+            f"{base}/api/vstore/ingest",
+            files={"file": (f"{jid}.txt", content.encode("utf-8"), "text/plain")},
+            data={
+                "name": str(journal.get("name") or jid),
+                "category": SCOPE_CATEGORY,
+                "description": "review_service 期刊范围种子（scope_desc 向量匹配）",
+            },
+        )
+    except httpx.HTTPError as exc:
+        raise MatchError(f"vstore 不可达（{base}）：{exc}") from exc
+    if resp.status_code >= 400:
+        raise MatchError(f"vstore ingest 失败（HTTP {resp.status_code}）：{_err_body(resp)}")
+    try:
+        payload = resp.json()
+    except ValueError as exc:
+        raise MatchError(f"vstore ingest 响应非 JSON：{exc}") from exc
+    if not isinstance(payload, dict) or not payload.get("ok"):
+        raise MatchError(
+            str((payload.get("error") or {}).get("message") if isinstance(payload, dict) else "") or "vstore ingest 失败"
+        )
+    doc_id = str((payload.get("item") or {}).get("document_id") or "")
+    if not doc_id:
+        raise MatchError("vstore ingest 响应缺少 document_id")
+    return doc_id
+
+
+async def ensure_scope_docs(journals: list[dict[str, Any]]) -> list[dict[str, Any]]:
+    """补齐缺失的 scope 入库映射（就地回写 vstore_doc_id 并持久到 DB）。"""
+    settings = get_settings()
+    missing = [j for j in journals if not j.get("vstore_doc_id")]
+    if not missing:
+        return journals
+    async with httpx.AsyncClient(timeout=_timeout()) as client:
+        for j in missing:
+            try:
+                doc_id = await _ingest_scope(client, settings.vstore_base, j)
+            except MatchError as exc:
+                # 单本失败不阻断其余（该期刊将不进白名单，由路由降级兜底）
+                logger.warning("journal_kb: scope 入库失败（%s）：%s", j.get("id"), exc)
+                continue
+            j["vstore_doc_id"] = doc_id
+            await set_vstore_doc_id(str(j["id"]), doc_id)
+    return journals
+
+
+async def _search(
+    client: httpx.AsyncClient, base: str, query: str, doc_ids: list[str]
+) -> list[dict[str, Any]]:
+    """chunk 级白名单检索。连通/上游错误抛 MatchError。"""
+    if not doc_ids:
+        # doc_ids 为空时 vstore 侧等于不过滤 → 会命中用户私有库，必须拦死
+        raise MatchError("白名单为空，拒绝全库检索")
+    try:
+        resp = await client.get(
+            f"{base}/api/vstore/search-chunks",
+            params={
+                "q": query,
+                "top_k": get_settings().recommend_scope_top_k,
+                "doc_ids": ",".join(doc_ids),
+            },
+        )
+    except httpx.HTTPError as exc:
+        raise MatchError(f"vstore search-chunks 不可达：{exc}") from exc
+    if resp.status_code >= 400:
+        raise MatchError(f"vstore search-chunks 失败（HTTP {resp.status_code}）：{_err_body(resp)}")
+    try:
+        payload = resp.json()
+    except ValueError as exc:
+        raise MatchError(f"vstore search-chunks 响应非 JSON：{exc}") from exc
+    if not isinstance(payload, dict) or not payload.get("ok"):
+        raise MatchError(
+            str((payload.get("error") or {}).get("message") if isinstance(payload, dict) else "") or "vstore search-chunks 失败"
+        )
+    items = payload.get("items")
+    return items if isinstance(items, list) else []
+
+
+async def _doc_alive(client: httpx.AsyncClient, base: str, doc_id: str) -> bool:
+    try:
+        resp = await client.get(f"{base}/api/vstore/documents/{doc_id}")
+    except httpx.HTTPError:
+        return False
+    if resp.status_code != 200:
+        return False
+    try:
+        payload = resp.json()
+    except ValueError:
+        return False
+    return bool(isinstance(payload, dict) and payload.get("ok"))
+
+
+async def _refresh_dead_docs(
+    client: httpx.AsyncClient, base: str, journals: list[dict[str, Any]]
+) -> None:
+    """白名单 0 命中时探活：失效文档重灌并回写新 id。"""
+    for j in journals:
+        doc_id = str(j.get("vstore_doc_id") or "")
+        if not doc_id or await _doc_alive(client, base, doc_id):
+            continue
+        try:
+            new_id = await _ingest_scope(client, base, j)
+        except MatchError as exc:
+            logger.warning("journal_kb: scope 重灌失败（%s）：%s", j.get("id"), exc)
+            continue
+        j["vstore_doc_id"] = new_id
+        await set_vstore_doc_id(str(j["id"]), new_id)
+
+
+async def match(
+    abstract: str, journals: list[dict[str, Any]]
+) -> tuple[list[dict[str, Any]], bool]:
+    """摘要 vs scope_desc 向量匹配。
+
+    返回 (candidates, vector_ok)；candidates 元素：
+      {"journal": <journals 行>, "similarity": float}
+    按 similarity 降序。MatchError → 路由降级；([], False) → 语义低相似。
+    """
+    settings = get_settings()
+    query = abstract.strip()[: settings.recommend_query_chars]
+    if not query:
+        return [], False
+
+    await ensure_scope_docs(journals)
+    whitelisted = [j for j in journals if j.get("vstore_doc_id")]
+    if not whitelisted:
+        raise MatchError("无任何期刊 scope 入库成功（vstore_doc_id 为空）")
+
+    doc_map = {str(j["vstore_doc_id"]): j for j in whitelisted}
+    timeout = _timeout()
+    async with httpx.AsyncClient(timeout=timeout) as client:
+        items = await _search(client, settings.vstore_base, query, list(doc_map))
+        if not items:
+            await _refresh_dead_docs(client, settings.vstore_base, whitelisted)
+            doc_map = {str(j["vstore_doc_id"]): j for j in whitelisted if j.get("vstore_doc_id")}
+            if not doc_map:
+                return [], False
+            items = await _search(client, settings.vstore_base, query, list(doc_map))
+
+    # 聚合：每本期刊取最高 chunk 分
+    best: dict[str, float] = {}
+    for item in items:
+        if not isinstance(item, dict):
+            continue
+        j = doc_map.get(str(item.get("doc_id") or ""))
+        if j is None:
+            continue
+        try:
+            score = float(item.get("score"))
+        except (TypeError, ValueError):
+            continue
+        jid = str(j["id"])
+        if jid not in best or score > best[jid]:
+            best[jid] = score
+    if not best:
+        return [], False
+
+    by_id = {str(j["id"]): j for j in journals}
+    candidates = [
+        {"journal": by_id[jid], "similarity": score}
+        for jid, score in best.items()
+        if jid in by_id
+    ]
+    candidates.sort(key=lambda c: c["similarity"], reverse=True)
+    return candidates, bool(candidates)
@@ -0,0 +1,210 @@
+"""services/journal_rank.py —— LLM 重排 + 幻觉防护 + 三档归类。
+
+职责：
+1. rerank：把带语义分的候选期刊（来自 journal_kb）+ 用户偏好交给 LLM，
+   要求按 id 白名单返回 {rankings:[{id, tier, match_reason, risk_note}]}。
+2. validate：硬校验——白名单外 id 丢弃（幻觉拦截）；tier 非法/LLM 缺漏的
+   期刊按规则补位（绝不因 LLM 输出丢失候选期刊）；期刊名称/指标一律不采信
+   LLM，最终展示全部用 DB 字段（防止改名型幻觉）。
+3. fallback_rankings：LLM 不可用时的确定性规则分档（按 impact_factor）。
+
+三档语义：challenge 挑战型（高影响/慢审稿）、fit 适配型（均衡）、
+safe 稳妥型（快速/门槛低）。
+"""
+from __future__ import annotations
+
+import json
+from dataclasses import dataclass
+from typing import Any
+
+from ..config import get_settings
+from . import llm
+
+TIERS = ("challenge", "fit", "safe")
+TIER_LABELS = {
+    "challenge": "挑战型（高影响因子/慢审稿）",
+    "fit": "适配型（中等影响/周期适中）",
+    "safe": "稳妥型（快速发表/门槛较低）",
+}
+
+# 规则分档阈值（近似值，可后续配置化）
+_CHALLENGE_MIN_IF = 9.0
+_SAFE_MAX_IF = 4.0
+
+# tier 同义词归一（LLM 偶发中文标签）
+_TIER_ALIASES = {
+    "挑战": "challenge",
+    "挑战型": "challenge",
+    "高风险": "challenge",
+    "适配": "fit",
+    "适配型": "fit",
+    "稳妥": "safe",
+    "稳妥型": "safe",
+    "低风险": "safe",
+}
+
+SYSTEM_PROMPT = """你是学术投稿推荐专家（植物基因组学方向）。根据给定候选期刊、论文摘要与用户偏好，为**每一个**候选期刊输出推荐分档与理由。
+
+硬规则（违反即视为无效输出）：
+1. id 白名单：只能使用输入 candidates 中出现的 id；绝对禁止添加、替换或臆造列表之外的任何期刊。
+2. 每个输入 id 恰好输出一次，不得遗漏、不得重复；期刊名称等元数据由系统填充，你只输出 id。
+3. tier 只能取 challenge | fit | safe：
+   - challenge（挑战型）：高影响因子、审稿较慢或竞争激烈的期刊
+   - fit（适配型）：影响力与发表周期均衡、与论文契合的期刊
+   - safe（稳妥型）：审稿较快、门槛较低、命中概率较高的期刊
+4. match_reason：中文，1-2 句，结合摘要的研究主题与该刊 scope_desc 及指标（如有 similarity 一并参考），说明为何匹配/不匹配。
+5. risk_note：中文，1-2 句，指出投稿风险（超出用户偏好、IF 门槛偏高、范围匹配偏弱、审稿周期长等）；无明显风险写「无」。
+6. 用户 preferences 为软约束：不满足偏好的期刊仍必须输出，并在 risk_note 中明确说明。
+7. 不确定时宁可保守陈述，禁止编造统计数据（录用率、审稿天数等）。
+
+输出：仅一个 JSON 对象，格式：
+{"rankings":[{"id":"...","tier":"challenge","match_reason":"...","risk_note":"..."}]}
+不要输出任何 JSON 之外的内容。"""
+
+
+class RankError(Exception):
+    """LLM 输出形态异常（无法按 JSON 解析/结构非法）。"""
+
+
+@dataclass
+class Ranking:
+    journal_id: str
+    tier: str
+    match_reason: str
+    risk_note: str
+
+
+def rule_tier(journal: dict[str, Any]) -> str:
+    """确定性分档规则（LLM 缺漏/不可用时兜底）。"""
+    inf = journal.get("impact_factor")
+    weeks = journal.get("review_time_weeks")
+    if isinstance(inf, (int, float)):
+        if inf >= _CHALLENGE_MIN_IF:
+            return "challenge"
+        if inf <= _SAFE_MAX_IF:
+            return "safe"
+    elif isinstance(weeks, (int, float)) and weeks <= 4:
+        return "safe"
+    return "fit"
+
+
+def build_user_prompt(
+    abstract: str,
+    candidates: list[dict[str, Any]],
+    preferences: dict[str, Any],
+) -> str:
+    """候选 + 偏好 + 摘要 → 用户消息（JSON）。"""
+    payload = {
+        "abstract": abstract.strip()[:4000],
+        "preferences": preferences or {},
+        "candidates": [
+            {
+                "id": str(c["journal"]["id"]),
+                "name": str(c["journal"].get("name") or ""),
+                "impact_factor": c["journal"].get("impact_factor"),
+                "review_time_weeks": c["journal"].get("review_time_weeks"),
+                "acceptance_rate": c["journal"].get("acceptance_rate"),
+                "similarity": c.get("similarity"),
+                "scope_desc": str(c["journal"].get("scope_desc") or "")[:400],
+            }
+            for c in candidates
+        ],
+    }
+    return json.dumps(payload, ensure_ascii=False)
+
+
+def _normalize_tier(raw: Any) -> str | None:
+    tier = str(raw or "").strip().lower()
+    tier = _TIER_ALIASES.get(str(raw or "").strip(), tier)
+    return tier if tier in TIERS else None
+
+
+def validate_rankings(
+    payload: Any, candidates: list[dict[str, Any]]
+) -> tuple[list[Ranking], int, int]:
+    """校验 LLM 输出。
+
+    返回 (rankings, dropped_hallucinated, repaired)：
+    - 白名单外 id / 重复 id → 丢弃并计数（repaired 中重复不计）；
+    - tier 非法、LLM 缺漏的 id → 按规则补位（repaired 计数）。
+    """
+    if not isinstance(payload, dict) or not isinstance(payload.get("rankings"), list):
+        raise RankError("LLM 输出缺少 rankings 数组")
+
+    by_id = {str(c["journal"]["id"]): c["journal"] for c in candidates}
+    input_ids = list(by_id)
+    seen: set[str] = set()
+    rankings: list[Ranking] = []
+    dropped = 0
+    repaired = 0
+
+    for entry in payload["rankings"]:
+        if not isinstance(entry, dict):
+            dropped += 1
+            continue
+        jid = str(entry.get("id") or "").strip()
+        if jid in seen:
+            continue
+        if jid not in by_id:
+            dropped += 1  # 幻觉期刊：绝不进输出
+            continue
+        seen.add(jid)
+        tier = _normalize_tier(entry.get("tier"))
+        if tier is None:
+            tier = rule_tier(by_id[jid])
+            repaired += 1
+        reason = str(entry.get("match_reason") or "").strip() or "基于期刊范围与指标的匹配"
+        risk = str(entry.get("risk_note") or "").strip() or "无"
+        rankings.append(Ranking(journal_id=jid, tier=tier, match_reason=reason, risk_note=risk))
+
+    for jid in input_ids:
+        if jid in seen:
+            continue
+        rankings.append(
+            Ranking(
+                journal_id=jid,
+                tier=rule_tier(by_id[jid]),
+                match_reason="LLM 未给出该期刊条目，已按影响因子/周期规则补位",
+                risk_note="未提供（LLM 输出缺漏，规则兜底）",
+            )
+        )
+        repaired += 1
+    return rankings, dropped, repaired
+
+
+async def rerank(
+    abstract: str,
+    candidates: list[dict[str, Any]],
+    preferences: dict[str, Any],
+) -> tuple[list[Ranking], int, int]:
+    """LLM 重排 + 校验。LLMError / RankError 上抛（路由降级为规则分档）。"""
+    settings = get_settings()
+    payload = await llm.complete_json(
+        SYSTEM_PROMPT,
+        build_user_prompt(abstract, candidates, preferences),
+        temperature=0.2,
+        max_tokens=3000,
+        timeout=settings.recommend_read_timeout,
+    )
+    return validate_rankings(payload, candidates)
+
+
+def fallback_rankings(candidates: list[dict[str, Any]]) -> list[Ranking]:
+    """LLM 不可用时的确定性分档（不丢任何候选期刊）。"""
+    rankings: list[Ranking] = []
+    for c in candidates:
+        j = c["journal"]
+        inf = j.get("impact_factor")
+        weeks = j.get("review_time_weeks")
+        rankings.append(
+            Ranking(
+                journal_id=str(j["id"]),
+                tier=rule_tier(j),
+                match_reason=(
+                    f"规则分档：影响因子 {inf if inf is not None else '未收录'}、"
+                    f"审稿约 {weeks if weeks is not None else '未收录'} 周"
+                ),
+                risk_note="LLM 不可用，本条按影响因子/周期规则估算",
+            )
+        )
+    return rankings
@@ -0,0 +1,520 @@
+"""app/services/journal_seed.py —— journal_directory 核心导入逻辑（CLI 与启动 seed 共享）。
+
+数据流（schema 仍由本模块独家拥有，app 路由层只读不建表）：
+  openpyxl 非 read_only 加载（读 cell.hyperlink.target 来源链接）
+  → 「国际期刊」「中文期刊」两 sheet 按【列名】映射
+  → 行级清洗（空→None 绝不填 0；分区数字→"N区"；JCR学科→JSON 数组）
+  → 按 id 幂等 upsert（ON CONFLICT DO UPDATE，重跑 count 不变）
+
+两个入口：
+  - scripts/import_journals.py（CLI）：extract_rows_from_xlsx + upsert_to_db
+    + 对账报告（exit code 语义见脚本 docstring）
+  - ensure_journal_directory_seeded()：服务启动自动 seed（main.py lifespan），
+    仅当表不存在或为空才导入；任何失败收敛为 dict 返回值，绝不抛异常。
+
+v4 源（2026-10-10）：JIF=2025 统计年/2026 JCR 发布；中文 IF=2024 统计年/
+年报 2025 版。源 xlsx 路径走 settings.journal_directory_seed_abs
+（REVIEW_JOURNAL_DIRECTORY_SEED_PATH 覆盖）。
+
+id 策略：有 ISSN → "{lang}:{ISSN}"; 无 ISSN → "{lang}:{slug(name)}"；
+同 lang 内冲突 → 抛 JournalSeedError（CLI 中止导入 / startup 返回 error）。
+"""
+from __future__ import annotations
+
+import json
+import re
+import sqlite3
+import unicodedata
+from collections import Counter
+from datetime import datetime
+from pathlib import Path
+from typing import Any
+
+import openpyxl
+
+from ..config import get_settings
+
+SHEET_INTL = "国际期刊"
+SHEET_ZH = "中文期刊"
+EXPECT_INTL = 779  # 口径 sheet 声明（v4 不变）
+EXPECT_ZH = 277
+
+# 官网列（v4 实际列名「官网网址」在首位；其余为历史/备用别名）
+OFFICIAL_URL_HEADERS = ("官网网址", "官网", "官方网址", "期刊官网")
+# JCR 学科列别名：v4 改名「JCR学科（2024源表）」，v2 为「JCR学科（源表）」
+JCR_DISCIPLINE_HEADERS = ("JCR学科（2024源表）", "JCR学科（源表）")
+
+# 既有表缺列时的幂等迁移（缺哪加哪，重复跑不报错）
+MIGRATE_COLS = (
+    ("official_url", "TEXT"),
+    ("official_check_status", "TEXT"),
+    ("jcr_release_year", "INTEGER"),
+)
+
+SCHEMA_SQL = """
+CREATE TABLE IF NOT EXISTS journal_directory (
+    id                          TEXT PRIMARY KEY,
+    lang                        TEXT NOT NULL,
+    name                        TEXT NOT NULL,
+    research_direction          TEXT,
+    cas_partition               TEXT,
+    cas_partition_note          TEXT,
+    cas_partition_year          INTEGER,
+    jif                        REAL,
+    jif_year                    INTEGER,
+    jif_note                    TEXT,
+    jif_check_status            TEXT,
+    composite_impact_factor     REAL,
+    comprehensive_impact_factor REAL,
+    metric_year                 INTEGER,
+    metric_report_year          INTEGER,
+    metric_caliber              TEXT,
+    annual_report_page          INTEGER,
+    top_flag                    TEXT,
+    publisher_series            TEXT,
+    journal_mark                TEXT,
+    article_type                TEXT,
+    issn                        TEXT,
+    eissn                       TEXT,
+    jcr_disciplines             TEXT,
+    supplement_note             TEXT,
+    evidence_note               TEXT,
+    official_url                TEXT,
+    official_check_status       TEXT,
+    jcr_release_year            INTEGER,
+    partition_source            TEXT,
+    jif_source                  TEXT,
+    jif_source_url              TEXT,
+    partition_source_url        TEXT,
+    data_source_label           TEXT,
+    data_source_url             TEXT,
+    imported_at                 TEXT
+);
+CREATE INDEX IF NOT EXISTS idx_dir_lang_name    ON journal_directory(lang, name);
+CREATE INDEX IF NOT EXISTS idx_dir_lang_jif     ON journal_directory(lang, jif);
+CREATE INDEX IF NOT EXISTS idx_dir_lang_cif     ON journal_directory(lang, composite_impact_factor);
+CREATE INDEX IF NOT EXISTS idx_dir_lang_part    ON journal_directory(lang, cas_partition);
+CREATE INDEX IF NOT EXISTS idx_dir_lang_domain  ON journal_directory(lang, research_direction);
+"""
+
+# upsert 列序（除 id 外全部 ON CONFLICT DO UPDATE）
+COLS = (
+    "lang", "name", "research_direction", "cas_partition", "cas_partition_note",
+    "cas_partition_year", "jif", "jif_year", "jif_note", "jif_check_status",
+    "composite_impact_factor", "comprehensive_impact_factor", "metric_year",
+    "metric_report_year", "metric_caliber", "annual_report_page", "top_flag",
+    "publisher_series", "journal_mark", "article_type", "issn", "eissn",
+    "jcr_disciplines", "supplement_note", "evidence_note", "official_url",
+    "official_check_status", "jcr_release_year",
+    "partition_source", "jif_source", "jif_source_url", "partition_source_url",
+    "data_source_label", "data_source_url", "imported_at",
+)
+UPSERT_SQL = (
+    "INSERT INTO journal_directory (id, " + ", ".join(COLS) + ") VALUES ("
+    + ", ".join("?" for _ in range(len(COLS) + 1)) + ") "
+    + "ON CONFLICT(id) DO UPDATE SET "
+    + ", ".join(f"{c}=excluded.{c}" for c in COLS)
+)
+
+
+class JournalSeedError(Exception):
+    """xlsx 缺失/结构错误/口径不符/id 冲突（不写库）。
+
+    exit_code 对齐 CLI 语义：1=id 冲突中止；2=行数与口径不符；3=文件/结构错误。
+    """
+
+    def __init__(
+        self,
+        message: str,
+        *,
+        exit_code: int = 3,
+        stage: str = "读取失败",
+        conflicts: list[str] | None = None,
+    ) -> None:
+        super().__init__(message)
+        self.exit_code = exit_code
+        self.stage = stage
+        self.conflicts = conflicts or []
+
+
+def new_stats() -> dict[str, Any]:
+    """对账统计骨架（CLI 报告与解析共享）。"""
+    return {
+        "read_intl": 0, "read_zh": 0, "success": 0, "skipped": 0, "failed": 0,
+        "jif_missing": [], "cif_missing": [], "part_blank": [], "part_notfound": [],
+        "part_dist": Counter(), "hl_jif": 0, "hl_part": 0, "hl_zh": 0,
+        "id_issn": 0, "id_slug": 0, "official_url_detected": False,
+        "migrated_cols": [], "migrated_skipped": [],
+        "official_total": 0, "official_filled": 0, "official_check_filled": 0,
+        "jcr_filled": 0, "official_missing": [],
+    }
+
+
+def migrate(conn: sqlite3.Connection) -> tuple[list[str], list[str]]:
+    """幂等加列：PRAGMA 探测现有列，缺哪个 ALTER ADD 哪个。"""
+    existing = {r[1] for r in conn.execute("PRAGMA table_info(journal_directory)")}
+    added: list[str] = []
+    skipped: list[str] = []
+    for col, decl in MIGRATE_COLS:
+        if col in existing:
+            skipped.append(col)
+        else:
+            conn.execute(f"ALTER TABLE journal_directory ADD COLUMN {col} {decl}")
+            added.append(col)
+    conn.commit()
+    return added, skipped
+
+
+# ---- 清洗原语 ----
+
+def text(v: Any) -> str | None:
+    """单元格 → strip 后的文本；空/纯空白 → None（绝不填 0/空串）。"""
+    if v is None:
+        return None
+    s = str(v).strip()
+    return s or None
+
+
+def to_float(v: Any) -> float | None:
+    if v is None or (isinstance(v, str) and not v.strip()):
+        return None
+    try:
+        return float(v)
+    except (TypeError, ValueError):
+        return None
+
+
+def to_int(v: Any) -> int | None:
+    f = to_float(v)
+    if f is None:
+        return None
+    return int(f)
+
+
+def slugify(name: str) -> str:
+    """小写 + 非词字符折叠为连字符；\\w 含 CJK（中文期刊无 ISSN 时的 id 兜底）。"""
+    s = unicodedata.normalize("NFC", name.strip().casefold())
+    s = re.sub(r"[^\w]+", "-", s, flags=re.UNICODE)
+    s = re.sub(r"-{2,}", "-", s)
+    return s.strip("-")
+
+
+def make_id(lang: str, name: str, issn: str | None) -> str:
+    if issn:
+        return f"{lang}:{issn}"
+    return f"{lang}:{slugify(name)}"
+
+
+def parse_partition(raw: Any) -> tuple[str | None, str | None]:
+    """分区 → (cas_partition, note)。数字 1-4 → 'N区'；'未检得' → note；空白 → 双 None。"""
+    if raw is None:
+        return None, None
+    if isinstance(raw, (int, float)) and not isinstance(raw, bool):
+        n = int(raw)
+        if 1 <= n <= 4:
+            return f"{n}区", None
+        return None, None
+    s = str(raw).strip()
+    if not s:
+        return None, None
+    if "未检得" in s:
+        return None, "未检得"
+    m = re.fullmatch(r"([1-4])\s*区?", s)
+    if m:
+        return f"{m.group(1)}区", None
+    return s, None  # 未知文本：原样保留（不丢信息）
+
+
+def split_disciplines(raw: Any) -> str | None:
+    """'A(SCIE);B(SCIE)' → JSON 数组字符串。"""
+    s = text(raw)
+    if not s:
+        return None
+    parts = [p.strip() for p in s.split(";") if p.strip()]
+    return json.dumps(parts, ensure_ascii=False) if parts else None
+
+
+def hyperlink_target(cell) -> str | None:
+    """超链接单元格 → target URL；无链接 → None（需要非 read_only 模式）。"""
+    try:
+        target = cell.hyperlink.target if cell.hyperlink is not None else None
+    except Exception:  # noqa: BLE001
+        return None
+    return text(target)
+
+
+# ---- sheet 解析 ----
+
+def header_index(ws) -> dict[str, int]:
+    headers = [text(c.value) for c in ws[1]]
+    return {h: i for i, h in enumerate(headers) if h is not None}
+
+
+def read_intl(ws, imported_at: str, stats: dict) -> list[tuple]:
+    """国际期刊 sheet → 行元组（顺序同 COLS 前置 id）。"""
+    ix = header_index(ws)
+    for req in ("期刊名称", "研究方向", "中科院分区", "JIF影响因子"):
+        if req not in ix:
+            raise JournalSeedError(
+                f"{SHEET_INTL} 缺列：{req}（实际列：{list(ix)}）",
+                exit_code=3, stage="结构错误",
+            )
+    url_col = next((ix[h] for h in OFFICIAL_URL_HEADERS if h in ix), None)
+    jcr_hdr = next((h for h in JCR_DISCIPLINE_HEADERS if h in ix), None)
+    stats["official_url_detected"] = url_col is not None
+    if url_col is not None:
+        stats["official_url_headers"] = next(h for h in OFFICIAL_URL_HEADERS if h in ix)
+
+    rows: list[tuple] = []
+    for row in ws.iter_rows(min_row=2):
+        if not any(c.value is not None for c in row):
+            continue  # 尾部幻影空行：不计入 skipped
+        name = text(row[ix["期刊名称"]].value) if ix["期刊名称"] < len(row) else None
+        if not name:
+            stats["skipped"] += 1
+            continue
+        issn = text(row[ix["ISSN"]].value) if "ISSN" in ix else None
+        jif = to_float(row[ix["JIF影响因子"]].value)
+        check_status = text(row[ix["JIF核对状态"]].value) if "JIF核对状态" in ix else None
+        official_check = text(row[ix["官网核对状态"]].value) if "官网核对状态" in ix else None
+        jcr_year = to_int(row[ix["JCR发布年"]].value) if "JCR发布年" in ix else None
+        part, part_note = parse_partition(row[ix["中科院分区"]].value)
+
+        # JIF 空 → note = 核对状态原文（"未检得"/"源表标N/A" 等说明）
+        jif_note = check_status if jif is None else None
+
+        jif_url = hyperlink_target(row[ix["JIF数据来源"]]) if "JIF数据来源" in ix else None
+        part_url = hyperlink_target(row[ix["分区数据来源"]]) if "分区数据来源" in ix else None
+        official = None
+        if url_col is not None and url_col < len(row):
+            official = text(row[url_col].value) or hyperlink_target(row[url_col])
+
+        rows.append((
+            make_id("en", name, issn), "en", name,
+            text(row[ix["研究方向"]].value),
+            part, part_note,
+            to_int(row[ix["分区版本年"]].value) if "分区版本年" in ix else None,
+            jif,
+            to_int(row[ix["JIF统计年"]].value) if "JIF统计年" in ix else None,
+            jif_note, check_status,
+            None, None, None, None, None, None,
+            text(row[ix["Top（源表）"]].value) if "Top（源表）" in ix else None,
+            text(row[ix["出版系列"]].value) if "出版系列" in ix else None,
+            text(row[ix["期刊标记"]].value) if "期刊标记" in ix else None,
+            text(row[ix["文章类型"]].value) if "文章类型" in ix else None,
+            issn,
+            text(row[ix["eISSN"]].value) if "eISSN" in ix else None,
+            split_disciplines(row[ix[jcr_hdr]].value) if jcr_hdr else None,
+            text(row[ix["补充说明"]].value) if "补充说明" in ix else None,
+            text(row[ix["补充证据"]].value) if "补充证据" in ix else None,
+            official,
+            official_check,
+            jcr_year,
+            "official", "official",
+            jif_url, part_url,
+            text(row[ix["JIF数据来源"]].value) if "JIF数据来源" in ix else None,
+            None,  # data_source_url（国际表来源即 jif/partition 两链接）
+            imported_at,
+        ))
+        # 统计
+        stats["official_total"] += 1
+        stats["official_filled"] += 1 if official else 0
+        stats["official_check_filled"] += 1 if official_check else 0
+        stats["jcr_filled"] += 1 if jcr_year else 0
+        if not official:
+            stats["official_missing"].append(("en", name))
+        if jif is None:
+            stats["jif_missing"].append((name, check_status or ""))
+        if part is None and part_note == "未检得":
+            stats["part_notfound"].append(name)
+        elif part is None:
+            stats["part_blank"].append(name)
+        stats["hl_jif"] += 1 if jif_url else 0
+        stats["hl_part"] += 1 if part_url else 0
+        stats["id_issn" if issn else "id_slug"] += 1
+    return rows
+
+
+def read_zh(ws, imported_at: str, stats: dict) -> list[tuple]:
+    """中文期刊 sheet → 行元组。"""
+    ix = header_index(ws)
+    for req in ("中文期刊名称", "复合影响因子", "综合影响因子"):
+        if req not in ix:
+            raise JournalSeedError(
+                f"{SHEET_ZH} 缺列：{req}（实际列：{list(ix)}）",
+                exit_code=3, stage="结构错误",
+            )
+    url_col = next((ix[h] for h in OFFICIAL_URL_HEADERS if h in ix), None)
+    stats["official_url_detected_zh"] = url_col is not None
+
+    rows: list[tuple] = []
+    for row in ws.iter_rows(min_row=2):
+        if not any(c.value is not None for c in row):
+            continue  # 尾部幻影空行：不计入 skipped
+        name = text(row[ix["中文期刊名称"]].value)
+        if not name:
+            stats["skipped"] += 1
+            continue
+        composite = to_float(row[ix["复合影响因子"]].value)
+        comprehensive = to_float(row[ix["综合影响因子"]].value)
+        check_status = text(row[ix["核对状态"]].value) if "核对状态" in ix else None
+
+        src_label = text(row[ix["数据来源"]].value) if "数据来源" in ix else None
+        src_url = hyperlink_target(row[ix["数据来源"]]) if "数据来源" in ix else None
+        official = None
+        if url_col is not None and url_col < len(row):
+            official = text(row[url_col].value) or hyperlink_target(row[url_col])
+        official_check = text(row[ix["官网核对状态"]].value) if "官网核对状态" in ix else None
+
+        rows.append((
+            make_id("zh", name, None), "zh", name,
+            text(row[ix["研究方向"]].value),
+            # 中文分区原样（常量"不按此口径列示"），不分区 → partition_source=None
+            text(row[ix["中科院分区"]].value) if "中科院分区" in ix else None,
+            None,  # cas_partition_note：中文表无"未检得"语义（口径=不按此口径列示）
+            None,  # cas_partition_year
+            None, None, None, check_status,
+            composite, comprehensive,
+            to_int(row[ix["指标统计年"]].value) if "指标统计年" in ix else None,
+            to_int(row[ix["年报版本年"]].value) if "年报版本年" in ix else None,
+            text(row[ix["指标口径"]].value) if "指标口径" in ix else None,
+            to_int(row[ix["年报PDF页码"]].value) if "年报PDF页码" in ix else None,
+            None, None, None, None, None, None, None,
+            text(row[ix["备注"]].value) if "备注" in ix else None,
+            None,  # evidence_note（中文表无此列）
+            official,
+            official_check,
+            None,  # jcr_release_year：中文表无 JCR 发布年列（前端中文 Tab 不显示）
+            None,  # partition_source：中文不按中科院口径
+            "official",  # jif_source：国内年报（official）
+            None, None,
+            src_label, src_url,
+            imported_at,
+        ))
+        stats["official_total"] += 1
+        stats["official_filled"] += 1 if official else 0
+        stats["official_check_filled"] += 1 if official_check else 0
+        if not official:
+            stats["official_missing"].append(("zh", name))
+        if composite is None:
+            stats["cif_missing"].append((name, check_status or ""))
+        stats["hl_zh"] += 1 if src_url else 0
+        stats["id_slug"] += 1
+    return rows
+
+
+# ---- 共享主流程 ----
+
+def extract_rows_from_xlsx(
+    source: Path,
+    *,
+    imported_at: str | None = None,
+    stats: dict | None = None,
+) -> tuple[list[tuple], list[tuple], dict]:
+    """xlsx → (rows_en, rows_zh, stats)。口径不符/id 冲突抛 JournalSeedError（不写库）。"""
+    stats = stats if stats is not None else new_stats()
+    imported_at = imported_at or datetime.now().isoformat(timespec="seconds")
+
+    try:
+        wb = openpyxl.load_workbook(source, data_only=True)
+    except FileNotFoundError as exc:
+        raise JournalSeedError(
+            f"源文件不存在: {source}", exit_code=3, stage="读取失败"
+        ) from exc
+    except Exception as exc:  # noqa: BLE001
+        raise JournalSeedError(
+            f"无法打开 Excel: {exc}", exit_code=3, stage="读取失败"
+        ) from exc
+    if SHEET_INTL not in wb.sheetnames or SHEET_ZH not in wb.sheetnames:
+        raise JournalSeedError(
+            f"缺少 sheet：需要 {SHEET_INTL}/{SHEET_ZH}，实际 {wb.sheetnames}",
+            exit_code=3, stage="结构错误",
+        )
+
+    rows_en = read_intl(wb[SHEET_INTL], imported_at, stats)
+    rows_zh = read_zh(wb[SHEET_ZH], imported_at, stats)
+    stats["read_intl"], stats["read_zh"] = len(rows_en), len(rows_zh)
+    for r in rows_en:
+        stats["part_dist"][r[4] or ("未检得" if r[5] else "空白")] += 1
+
+    # 口径行数校验（不符 → 抛错，不写库）
+    if len(rows_en) != EXPECT_INTL or len(rows_zh) != EXPECT_ZH:
+        raise JournalSeedError(
+            f"行数与口径不符：国际 {len(rows_en)}/{EXPECT_INTL}、"
+            f"中文 {len(rows_zh)}/{EXPECT_ZH}，中止导入",
+            exit_code=2, stage="行数校验失败",
+        )
+
+    # id 冲突检测（同 lang 内重复 → 抛错，不写库）
+    ids = [r[0] for r in rows_en + rows_zh]
+    dup = [i for i, c in Counter(ids).items() if c > 1]
+    if dup:
+        conflicts = [f"{i} × {Counter(ids)[i]}" for i in sorted(dup)]
+        raise JournalSeedError(
+            f"发现 {len(conflicts)} 个重复 id，中止导入（未写库）",
+            exit_code=1, stage="id 冲突中止", conflicts=conflicts,
+        )
+
+    return rows_en, rows_zh, stats
+
+
+def upsert_to_db(db_path: Path, rows_en: list[tuple], rows_zh: list[tuple]) -> dict[str, int]:
+    """建表(IF NOT EXISTS)+幂等加列+upsert → {"en","zh","total"}。"""
+    db_path = Path(db_path)
+    db_path.parent.mkdir(parents=True, exist_ok=True)
+    conn = sqlite3.connect(str(db_path))
+    try:
+        conn.executescript(SCHEMA_SQL)
+        migrate(conn)
+        conn.executemany(UPSERT_SQL, list(rows_en) + list(rows_zh))
+        conn.commit()
+        d = dict(conn.execute(
+            "SELECT lang, COUNT(*) FROM journal_directory GROUP BY lang").fetchall())
+        return {"en": d.get("en", 0), "zh": d.get("zh", 0), "total": sum(d.values())}
+    finally:
+        conn.close()
+
+
+def ensure_journal_directory_seeded(
+    db_path: Path | None = None,
+    source_xlsx: Path | None = None,
+) -> dict:
+    """启动自动 seed：空表才导入；任何失败收敛为 dict，绝不抛异常。
+
+    返回统一四键：seeded/reason/error/rows（另有 counts 仅成功时给出 en/zh 明细）。
+    - 已有数据（只认空/非空，不做补差）→ seeded=False, reason="already has N rows, skip"
+    - 空表导入成功 → seeded=True, rows=1056
+    - xlsx 缺失/结构错误/口径不符/id 冲突 → seeded=False, error="..."
+    """
+    settings = get_settings()
+    db = Path(db_path) if db_path is not None else settings.db_path_abs
+    source = Path(source_xlsx) if source_xlsx is not None else settings.journal_directory_seed_abs
+
+    try:
+        if db.exists():
+            conn = sqlite3.connect(str(db))
+            try:
+                row = conn.execute("SELECT COUNT(*) FROM journal_directory").fetchone()
+            except sqlite3.OperationalError:
+                row = None  # 表不存在 → 视为空
+            finally:
+                conn.close()
+        else:
+            row = None
+        if row is not None and int(row[0]) > 0:
+            n = int(row[0])
+            return {
+                "seeded": False, "reason": f"already has {n} rows, skip",
+                "error": None, "rows": n,
+            }
+
+        rows_en, rows_zh, _ = extract_rows_from_xlsx(source)
+        counts = upsert_to_db(db, rows_en, rows_zh)
+        return {
+            "seeded": True, "reason": None, "error": None,
+            "rows": counts["total"], "counts": counts,
+        }
+    except JournalSeedError as exc:
+        return {"seeded": False, "reason": None, "error": str(exc), "rows": None}
+    except Exception as exc:  # noqa: BLE001
+        return {"seeded": False, "reason": None, "error": str(exc), "rows": None}
@@ -0,0 +1,869 @@
+"""services/latex_compile.py —— tectonic 编译 .tex → PDF（P3a + P4 项目 zip）。
+
+隔离与安全（对齐设计清单）：
+  1. 一编译一目录：{reformat_dir}/{anchor_id}/compile/（input.tex/output.pdf/output.log/meta.json）
+  2. 文件名永不落盘：用户文件名只做后缀校验，写入一律 input.tex
+  3. tectonic --untrusted（官方旗标：禁用已知不安全特性，含 shell escape 路径）
+  4. 子进程 start_new_session + 超时 killpg(SIGKILL)（整进程组）
+  5. 单槽队列：asyncio.Lock + pending 计数，超出 compile_queue_limit → QueueFullError
+  6. 产物 PDF > max_compile_pdf_bytes → 删文件 + OutputTooLargeError
+  7. 启动/每次编译前机会性清扫 retention_days 天前的 job 目录（只删 12 位 hex 锚点目录）
+
+P4 项目 zip（两段式 inspect + run，与 P3a 共享单槽队列/清扫/错误类）：
+  - inspect_zip：安全解压（zip_safety）→ 主文件识别 → compile_inspect/{job_id}/（1h TTL）
+  - compile_project_job：原子 rename 消费 inspect → compile_jobs/{cid}/ → tectonic →
+    finally 删 project 树（只留 output.pdf/output.log/meta.json）
+  - 失败也保证 output.log 落盘（补充 3）；classify_compile_error 给出用户友好文案
+  - P3a 单文件路径（prepare_input/compile_tex/_run_once）零改动
+
+tectonic 二进制缺失 → ToolUnavailableError（路由层回安装指引）。
+"""
+from __future__ import annotations
+
+import asyncio
+import json
+import logging
+import os
+import re
+import shutil
+import signal
+import subprocess
+import time
+import uuid
+from dataclasses import dataclass
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Any
+
+from ..config import get_settings
+
+logger = logging.getLogger(__name__)
+
+_ANCHOR_ID_RE = re.compile(r"^[0-9a-f]{12}$")
+_ENGINE = "tectonic-p3/0.17.0"
+_LOG_TAIL_LINES = 200
+
+# 单槽并发控制（进程内；重启归零可接受——本服务无持久队列需求）
+_lock = asyncio.Lock()
+_pending = 0
+
+
+class CompileError(Exception):
+    """编译失败（含 log 尾）。code ∈ {COMPILE_FAILED, TIMEOUT, OUTPUT_TOO_LARGE}。"""
+    # compile_id：P4 项目编译失败时由 compile_project_job 附加（P3a 单文件为 None），
+    # 路由层据此在失败信封里回 compile_id + log_url（补充 3）。
+    compile_id: str | None = None
+
+    def __init__(self, code: str, message: str, log_tail: str = "") -> None:
+        super().__init__(message)
+        self.code = code
+        self.log_tail = log_tail
+
+
+class QueueFullError(Exception):
+    """等待槽位超限。"""
+
+
+class ToolUnavailableError(Exception):
+    """tectonic 二进制缺失/不可执行。"""
+
+
+def _tectonic_bin() -> Path:
+    return get_settings().tectonic_abs
+
+
+def _ensure_tool() -> Path:
+    bin_path = _tectonic_bin()
+    if not (bin_path.is_file() and os.access(bin_path, os.X_OK)):
+        raise ToolUnavailableError(
+            f"tectonic 未安装（{bin_path}）。"
+            "请执行：cd review_service && bash tools/install_tectonic.sh"
+        )
+    return bin_path
+
+
+def _log_tail(path: Path, lines: int = _LOG_TAIL_LINES) -> str:
+    try:
+        text = path.read_text("utf-8", errors="replace")
+    except OSError:
+        return ""
+    return "\n".join(text.splitlines()[-lines:])
+
+
+def compile_dir(anchor_id: str) -> Path:
+    """{reformat_dir}/{anchor_id}/compile/（存在性由调用方按需 mkdir）。"""
+    return get_settings().reformat_dir_abs / anchor_id / "compile"
+
+
+def prepare_input(anchor_id: str, source: str) -> Path:
+    """写入隔离目录 input.tex；返回其路径。"""
+    cdir = compile_dir(anchor_id)
+    cdir.mkdir(parents=True, exist_ok=True)
+    input_tex = cdir / "input.tex"
+    input_tex.write_text(source, encoding="utf-8")
+    return input_tex
+
+
+async def compile_tex(anchor_id: str) -> dict[str, Any]:
+    """同步编译 anchor 的 input.tex（须先 prepare_input）。
+
+    → {compile_id: anchor_id, pdf_path, log_path, seconds, pdf_bytes}
+    失败抛 CompileError / QueueFullError / ToolUnavailableError。
+    """
+    global _pending
+    settings = get_settings()
+    _ensure_tool()  # 快速失败：不占队列
+    sweep_expired()
+
+    if _pending >= settings.compile_queue_limit:
+        raise QueueFullError(
+            f"编译队列已满（{_pending} 个任务排队），请稍后重试"
+        )
+    _pending += 1
+    try:
+        async with _lock:
+            return await _run_once(anchor_id)
+    finally:
+        _pending -= 1
+
+
+async def _run_once(anchor_id: str) -> dict[str, Any]:
+    settings = get_settings()
+    cdir = compile_dir(anchor_id)
+    input_tex = cdir / "input.tex"
+    pdf_path = cdir / "output.pdf"
+    log_path = cdir / "output.log"
+    if not input_tex.is_file():
+        raise CompileError("COMPILE_FAILED", "编译输入不存在，请重新上传源码")
+
+    env = dict(os.environ)
+    env["TECTONIC_CACHE_DIR"] = str(settings.tectonic_cache_abs)
+    cmd = [
+        str(_tectonic_bin()), "-X", "compile", input_tex.name,
+        "--untrusted", "--keep-logs", "--outdir", ".",
+    ]
+    started = time.monotonic()
+    try:
+        proc = await asyncio.create_subprocess_exec(
+            *cmd, cwd=cdir, env=env,
+            stdout=asyncio.subprocess.PIPE, stderr=asyncio.subprocess.STDOUT,
+            start_new_session=True,
+        )
+        try:
+            await asyncio.wait_for(
+                proc.communicate(), timeout=settings.compile_timeout_s
+            )
+        except asyncio.TimeoutError:
+            _kill_group(proc)
+            try:
+                await asyncio.wait_for(proc.wait(), timeout=5.0)
+            except asyncio.TimeoutError:
+                pass
+            log_path.write_text(_log_tail(log_path) + "\n[timeout] 编译超时，进程已终止",
+                                 encoding="utf-8")
+            raise CompileError(
+                "TIMEOUT",
+                f"编译超过 {settings.compile_timeout_s:g} 秒未完成，已终止",
+                _log_tail(log_path),
+            ) from None
+    except FileNotFoundError as exc:
+        raise ToolUnavailableError(f"tectonic 不可执行：{exc}") from exc
+    finally:
+        seconds = round(time.monotonic() - started, 2)
+
+    # tectonic --keep-logs 把日志写在 cwd 的 input.log
+    produced_log = cdir / "input.log"
+    if produced_log.is_file():
+        shutil.move(str(produced_log), str(log_path))
+    if not log_path.is_file():
+        log_path.write_text("", encoding="utf-8")
+
+    produced_pdf = cdir / "input.pdf"
+    if not produced_pdf.is_file():
+        raise CompileError(
+            "COMPILE_FAILED",
+            "编译失败（未产出 PDF），请查看日志定位 LaTeX 错误",
+            _log_tail(log_path),
+        )
+    pdf_bytes = produced_pdf.stat().st_size
+    if pdf_bytes > settings.max_compile_pdf_bytes:
+        produced_pdf.unlink(missing_ok=True)
+        raise CompileError(
+            "OUTPUT_TOO_LARGE",
+            f"产出 PDF 超过 {settings.max_compile_pdf_bytes // (1024 * 1024)}MB 上限，已删除",
+            _log_tail(log_path),
+        )
+    produced_pdf.rename(pdf_path)
+
+    meta = {
+        "compile_id": anchor_id,
+        "engine": _ENGINE,
+        "seconds": seconds,
+        "pdf_bytes": pdf_bytes,
+        "returncode": 0,
+        "compiled_at": datetime.now(timezone.utc).isoformat(timespec="seconds"),
+    }
+    (cdir / "meta.json").write_text(
+        json.dumps(meta, ensure_ascii=False, indent=2), encoding="utf-8"
+    )
+    logger.info("compile: %s → PDF %d bytes, %.2fs", anchor_id, pdf_bytes, seconds)
+    return {
+        "compile_id": anchor_id,
+        "pdf_path": pdf_path,
+        "log_path": log_path,
+        "seconds": seconds,
+        "pdf_bytes": pdf_bytes,
+    }
+
+
+def _kill_group(proc: asyncio.subprocess.Process) -> None:
+    try:
+        os.killpg(os.getpgid(proc.pid), signal.SIGKILL)
+    except (ProcessLookupError, PermissionError, OSError):
+        try:
+            proc.kill()
+        except ProcessLookupError:
+            pass
+
+
+def sweep_expired() -> int:
+    """删除 mtime 超 retention_days 的 12-hex 锚点目录（编译产物+P1 落盘一并清）。"""
+    settings = get_settings()
+    base = settings.reformat_dir_abs
+    if not base.is_dir():
+        return 0
+    cutoff = time.time() - settings.compile_retention_days * 86400
+    removed = 0
+    for child in base.iterdir():
+        if not child.is_dir() or not _ANCHOR_ID_RE.fullmatch(child.name):
+            continue
+        try:
+            if child.stat().st_mtime < cutoff:
+                shutil.rmtree(child, ignore_errors=True)
+                removed += 1
+        except OSError:
+            continue
+    if removed:
+        logger.info("compile sweep: 清理 %d 个过期任务目录（>%d 天）",
+                    removed, settings.compile_retention_days)
+    return removed
+
+
+# ================================================================ P4：项目 zip（inspect + run）
+#
+# 与 P3a 共用：_lock/_pending 单槽队列、_ensure_tool、CompileError/QueueFullError/
+# ToolUnavailableError、_kill_group、_log_tail、12-hex 目录与 mtime sweep 约定。
+# P3a 函数（prepare_input/compile_tex/_run_once）零改动。
+
+
+class InspectError(Exception):
+    """inspect/消费阶段业务失败。
+    code ∈ {VALIDATION, ZIP_UNSAFE, ZIP_BOMB, ZIP_INVALID, ZIP_TOO_LARGE}。
+    """
+
+    def __init__(self, code: str, message: str) -> None:
+        super().__init__(message)
+        self.code = code
+        self.message = message
+
+
+_DOCCLASS_RE = re.compile(r"(?<!\\)\\documentclass\s*(\[|\{)")
+_IMG_LIKE_EXT = {".png", ".jpg", ".jpeg", ".pdf", ".eps", ".svg"}
+
+
+def inspect_root() -> Path:
+    """data/compile_inspect/（1 小时 TTL 暂存根，存在性由调用方按需 mkdir）。"""
+    return get_settings().inspect_dir_abs
+
+
+def compile_job_dir(cid: str) -> Path:
+    """data/compile_jobs/{cid}/（产物根；不走 reformat_dir，P4 独立清扫）。"""
+    return get_settings().compile_jobs_dir_abs / cid
+
+
+def _strip_tex_comments(text: str) -> str:
+    """粗剥注释：行内 % 截断（\\% 误伤可接受，MVP 设计决策）。"""
+    return "\n".join(ln.split("%", 1)[0] for ln in text.splitlines())
+
+
+def _read_tex(path: Path) -> str:
+    """utf-8 → gb18030 → latin-1 降级读（中文模板常见 GBK）。"""
+    raw = path.read_bytes()
+    for enc in ("utf-8", "gb18030", "latin-1"):
+        try:
+            return raw.decode(enc)
+        except UnicodeDecodeError:
+            continue
+    return raw.decode("utf-8", errors="replace")
+
+
+def find_main_tex(project_dir: Path) -> tuple[str | None, list[str], int]:
+    """主文件识别（补充 2）→ (main_rel | None, 含 documentclass 的相对路径清单, .tex 总数)。
+
+    场景：唯一候选 → main；0 个 .tex / 0 候选 / ≥2 候选 → None + 清单（调用方报错）。
+    返回的相对路径用 posix 分隔符（与 zip 条目名一致）。
+    """
+    tex_files = sorted(
+        p for p in project_dir.rglob("*")
+        if p.is_file() and p.suffix.lower() == ".tex"
+    )
+    if not tex_files:
+        return None, [], 0
+    candidates: list[str] = []
+    for p in tex_files:
+        if _DOCCLASS_RE.search(_strip_tex_comments(_read_tex(p))):
+            candidates.append(p.relative_to(project_dir).as_posix())
+    if len(candidates) == 1:
+        return candidates[0], candidates, len(tex_files)
+    return None, candidates, len(tex_files)
+
+
+_MISSING_FILE_RE = re.compile(
+    r"LaTeX Error: File [`']([^`']+)' not found"
+    r"|I can't find file [`']([^`']+)'"
+)
+_IMG_INCLUSION_RE = re.compile(r"""image inclusion failed for ["']([^"']+)["']""")
+
+_EPS_CONVERTED_SUFFIX = "-eps-converted-to.pdf"
+_REF_TEXT_EXTS = {".tex", ".cls", ".sty", ".cfg", ".def"}
+
+# EPS 现场转换 v2（约束 1-4）：xdvipdfmx 无法内嵌 EPS → 解压后批量转同名 .pdf
+_EPS_CONVERT_TIMEOUT_S = 15                      # 约束2：单文件转换超时（秒）
+_EPS_CONVERT_MAX_FILE = 20 * 1024 * 1024         # 约束3：单文件转换后上限（warning）
+_EPS_CONVERT_MAX_TOTAL = 100 * 1024 * 1024       # 约束3：转换产物总上限（中止）
+
+
+def _eps_tool_commands(eps: Path, pdf: Path) -> list[tuple[str, list[str]]]:
+    """转换工具优先级：gs（约束1 必须 -dSAFER）→ epstopdf → ps2pdf；只列 PATH 里可用的。"""
+    tools: list[tuple[str, list[str]]] = []
+    gs = shutil.which("gs")
+    if gs:
+        tools.append(("gs", [
+            gs, "-dSAFER", "-dNOPAUSE", "-dBATCH", "-sDEVICE=pdfwrite",
+            "-dPDFSETTINGS=/prepress",
+            f"-sOutputFile={pdf}", str(eps),
+        ]))
+    epstopdf = shutil.which("epstopdf")
+    if epstopdf:
+        # epstopdf 默认输出到同目录同名 .pdf（即 pdf 路径）
+        tools.append(("epstopdf", [epstopdf, str(eps)]))
+    ps2pdf = shutil.which("ps2pdf")
+    if ps2pdf:
+        tools.append(("ps2pdf", [ps2pdf, str(eps), str(pdf)]))
+    return tools
+
+
+def _convert_eps_file(eps: Path, pdf: Path) -> tuple[str, str]:
+    """逐工具尝试把 eps 转成同名 pdf → ("ok", tool) | ("timeout", tool) | ("fail", "")。
+
+    约束2：单工具 15s 超时 → 放弃该文件（继续下一个 eps，不再试后续工具）。
+    成功判定：退出后 pdf 存在且非空（防半成品）。
+    """
+    tools = _eps_tool_commands(eps, pdf)
+    if not tools:
+        return "fail", ""
+    for tool, cmd in tools:
+        pdf.unlink(missing_ok=True)  # 清上一个工具的半成品
+        try:
+            subprocess.run(
+                cmd, timeout=_EPS_CONVERT_TIMEOUT_S,
+                stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL,
+                check=False,
+            )
+        except subprocess.TimeoutExpired:
+            pdf.unlink(missing_ok=True)
+            return "timeout", tool
+        except OSError:
+            continue
+        if pdf.is_file() and pdf.stat().st_size > 0:
+            return "ok", tool
+    pdf.unlink(missing_ok=True)
+    return "fail", ""
+
+
+def process_eps_images(project: Path) -> list[str]:
+    """EPS 兼容 v2：解压后**批量转换项目内所有 .eps**（不依赖 zip 自带预转换版）。
+
+    对每个 X.eps（原 .eps 保留）：
+      1. 已有同名 X.pdf → 跳过转换（引用照常切换为 .pdf）；
+      2. zip 自带 X-eps-converted-to.pdf 预转换版 → 复制为 X.pdf（免转换）；
+      3. 否则现场转换：gs(-dSAFER) → epstopdf → ps2pdf 逐个 fallback（约束1），
+         单文件 15s 超时 → warning 后继续下一个（约束2）。
+    转换成功 → 显式 `X.eps` 引用字节替换为 `X.pdf`（.tex/.cls/.sty/.cfg/.def 全扫，
+    纯字节 ASCII/UTF-8 替换不碰编码）；无扩展名引用 `{.../X}` 由 graphicx 直接
+    命中新生成的 X.pdf（解析顺序 .pdf→…→.eps）。
+    约束3：单文件转换后 >20MB → warning；转换产物累计 >100MB → 抛
+    InspectError("ZIP_TOO_LARGE") 中止；约束4：返回值为写入 output.log 的
+    "[eps-convert]" 日志行（由 _run_project 落盘）。
+    → 日志行列表（无 .eps 项目 → 空）。
+    """
+    eps_files = sorted(
+        p for p in project.rglob("*")
+        if p.is_file() and p.suffix.lower() == ".eps"
+    )
+    if not eps_files:
+        return []
+    lines: list[str] = []
+    handled: list[tuple[bytes, bytes]] = []
+    total_out = 0
+
+    def _rel(p: Path) -> str:
+        return p.relative_to(project).as_posix()
+
+    for eps in eps_files:
+        pdf = eps.with_suffix(".pdf")
+        src_rel, dst_rel = _rel(eps), _rel(pdf)
+        if pdf.is_file():
+            handled.append((eps.name.encode("utf-8"), pdf.name.encode("utf-8")))
+            continue
+        converted = eps.with_name(eps.stem + _EPS_CONVERTED_SUFFIX)
+        if converted.is_file():
+            t0 = time.monotonic()
+            shutil.copyfile(converted, pdf)
+            elapsed = time.monotonic() - t0
+            tool = "preset"
+        else:
+            t0 = time.monotonic()
+            status, tool = _convert_eps_file(eps, pdf)
+            elapsed = time.monotonic() - t0
+            if status == "timeout":
+                lines.append(f"[eps-convert] {src_rel} 转换超时")  # 约束2
+                continue
+            if status != "ok":
+                lines.append(
+                    f"[eps-convert] 全部工具失败，图片 {src_rel} 未转换")
+                continue
+        # 约束4：转换日志（成功路径）
+        lines.append(
+            f"[eps-convert] {src_rel} → {dst_rel} "
+            f"({eps.stat().st_size} → {pdf.stat().st_size}, "
+            f"{elapsed:.2f}s, {tool})")
+        size_out = pdf.stat().st_size
+        if size_out > _EPS_CONVERT_MAX_FILE:                        # 约束3
+            lines.append(
+                f"[eps-convert] 警告：{dst_rel} 转换后 {size_out} 字节"
+                f"超过 {_EPS_CONVERT_MAX_FILE // (1024 * 1024)}MB 上限")
+        total_out += size_out
+        if total_out > _EPS_CONVERT_MAX_TOTAL:                      # 约束3
+            raise InspectError(
+                "ZIP_TOO_LARGE",
+                f"EPS 转换后总大小超过 {_EPS_CONVERT_MAX_TOTAL // (1024 * 1024)}MB 上限"
+                f"（已达 {total_out // (1024 * 1024)}MB），请压缩图片后重试")
+        handled.append((eps.name.encode("utf-8"), pdf.name.encode("utf-8")))
+
+    # 显式 .eps 引用 → .pdf（仅对转换成功者；失败的保持 .eps → 编译兜底友好报错）
+    changed = 0
+    if handled:
+        for f in project.rglob("*"):
+            if not (f.is_file() and f.suffix.lower() in _REF_TEXT_EXTS):
+                continue
+            data = f.read_bytes()
+            new = data
+            for old_b, new_b in handled:
+                new = new.replace(old_b, new_b)
+            if new != data:
+                f.write_bytes(new)
+                changed += 1
+    if changed:
+        lines.append(f"[eps-convert] {changed} 个文件的显式 .eps 引用已改写为 .pdf")
+    if lines:
+        logger.info("eps v2: %s", " | ".join(lines))
+    return lines
+
+
+def _append_eps_lines(log_path: Path, lines: list[str] | None) -> None:
+    """约束4：把 [eps-convert] 转换日志写入 output.log（引擎 log 之后、chatter 之前）。"""
+    if not lines:
+        return
+    with log_path.open("a", encoding="utf-8") as fh:
+        fh.write("\n".join(lines) + "\n")
+
+
+def classify_compile_error(log_tail: str) -> str:
+    """COMPILE_FAILED 的日志 → 用户友好文案（Q4/§4.4）。"""
+    m = _MISSING_FILE_RE.search(log_tail)
+    if m:
+        name = next(g for g in m.groups() if g)
+        ext = Path(name).suffix.lower()
+        if ext == ".cls":
+            return f"项目缺少 {name}，请从期刊官网下载模板后重新上传"
+        if ext in (".sty", ".def", ".clo"):
+            return f"缺少 LaTeX 宏包 {name}，可能是模板不完整"
+        if ext in _IMG_LIKE_EXT:
+            return f"图片 {name} 未在 zip 里，请检查引用路径与大小写"
+        if ext == ".bib":
+            return f"缺少文献库 {name}，请确认 .bib 已包含在 zip 中"
+        return f"编译找不到文件 {name}，请检查 zip 内文件路径"
+    m = _IMG_INCLUSION_RE.search(log_tail)
+    if m:
+        name = m.group(1)
+        if Path(name).suffix.lower() == ".eps":
+            # EPS v2 已现场转换；仍失败 = 服务器转换没成功（工具缺失/超时/格式怪异）
+            return "项目包含 EPS 图片，服务器转换失败，请转成 PDF/PNG 后重试"
+        return f"图片 {name} 无法内嵌，请检查图片格式与路径（建议使用 PDF/PNG）"
+    if re.search(r"Emergency stop|Undefined control sequence", log_tail):
+        return "LaTeX 源码有语法错误，请展开日志定位出错行"
+    return "编译失败，请查看日志定位 LaTeX 错误"
+
+
+async def inspect_zip(zip_bytes: bytes) -> dict[str, Any]:
+    """两段式之①：安全解压 + 主文件识别 + 落盘 inspect 暂存（1h TTL）。
+
+    → {job_id, main, stats{files,tex,images,cls,bib,other,bytes}, skipped[], skipped_count}
+    失败抛 InspectError（路由层转信封）；任何失败 → rmtree 暂存目录，磁盘零残留。
+    """
+    from .zip_safety import ZipSafetyError, safe_extract
+
+    settings = get_settings()
+    sweep_inspect_expired()          # 机会性清扫（同 P3a 模式）
+    job_id = uuid.uuid4().hex[:12]
+    jdir = inspect_root() / job_id
+    project = jdir / "project"
+    try:
+        try:
+            result = await asyncio.to_thread(safe_extract, zip_bytes, project, settings)
+        except ZipSafetyError as exc:
+            raise InspectError(exc.code, exc.message) from exc
+        main, candidates, tex_total = find_main_tex(project)
+        if tex_total == 0:
+            raise InspectError("VALIDATION", "zip 中没有 .tex 文件")
+        if not candidates:
+            raise InspectError(
+                "VALIDATION", "未找到含 \\documentclass 的 .tex 文件")
+        if main is None:
+            shown = ", ".join(Path(c).name for c in candidates)
+            raise InspectError(
+                "VALIDATION",
+                f"检测到多个主文件（{shown}），请合并为单一入口后重新上传")
+        meta = {
+            "job_id": job_id,
+            "main": main,
+            "stats": {
+                "files": result.files, "tex": result.tex, "images": result.images,
+                "cls": result.cls, "bib": result.bib, "other": result.other,
+                "bytes": result.bytes,
+            },
+            "skipped": [{"name": s.name, "reason": s.reason} for s in result.skipped],
+            "skipped_count": result.skipped_count,
+            "created_at": datetime.now(timezone.utc).isoformat(timespec="seconds"),
+        }
+        jdir.mkdir(parents=True, exist_ok=True)
+        (jdir / "inspect.json").write_text(
+            json.dumps(meta, ensure_ascii=False, indent=2), encoding="utf-8")
+        return meta
+    except BaseException:
+        shutil.rmtree(jdir, ignore_errors=True)
+        raise
+
+
+def consume_inspect(job_id: str, cid: str) -> tuple[Path, dict[str, Any]]:
+    """两段式之②前置：**原子 rename 消费** inspect 暂存 → compile_jobs/{cid}/project。
+
+    并发正确性（防同一 job 双跑）：
+      os.rename(src, dst) 在同一文件系统内是原子的，且 src 不存在 → FileNotFoundError。
+      两个并发 run 拿同一 job_id 时，只有一个能成功 rename；后到者拿到
+      FileNotFoundError → 路由层转 VALIDATION"已过期/不存在"，**绝不可能双编译**。
+      inspect 残壳（inspect.json）在 rename 成功后立即删除，也杜绝二跑读到半状态。
+    """
+    settings = get_settings()
+    if not _ANCHOR_ID_RE.fullmatch(job_id or ""):
+        raise InspectError("VALIDATION", "job_id 格式非法（应为 12 位 hex）")
+    src_root = inspect_root() / job_id
+    meta_path = src_root / "inspect.json"
+    src_project = src_root / "project"
+    if not (meta_path.is_file() and src_project.is_dir()):
+        raise InspectError(
+            "VALIDATION", "上传任务不存在或已过期（1 小时），请重新上传 zip")
+    try:
+        meta = json.loads(meta_path.read_text("utf-8"))
+    except (OSError, ValueError) as exc:
+        raise InspectError(
+            "VALIDATION", "上传任务数据损坏，请重新上传 zip") from exc
+    dst_root = compile_job_dir(cid)
+    dst_project = dst_root / "project"
+    dst_root.mkdir(parents=True, exist_ok=True)
+    try:
+        os.rename(src_project, dst_project)
+    except FileNotFoundError as exc:
+        raise InspectError(
+            "VALIDATION", "上传任务不存在或已过期（1 小时），请重新上传 zip") from exc
+    except OSError as exc:  # 跨设备等罕见失败 → 保持 inspect 原样可重试
+        raise InspectError(
+            "VALIDATION", "任务消费失败，请重试或重新上传") from exc
+    shutil.rmtree(src_root, ignore_errors=True)  # 消费成功 → 删残壳
+    return dst_project, meta
+
+
+async def compile_project_job(job_id: str) -> dict[str, Any]:
+    """两段式之②：原子消费 inspect → tectonic 编译 → 产物留 pdf/log/meta。
+
+    队列/工具检查**先于消费**（inspect 保留 → 失败可直接重试）；
+    EPS v2：解压后批量转换所有 .eps → 同名 .pdf（gs -dSAFER → epstopdf → ps2pdf，
+    单文件 15s 超时；产物累计 >100MB → ZIP_TOO_LARGE 中止），转换日志进 output.log；
+    成功 → 立即删 project/；失败（COMPILE_FAILED/TIMEOUT）→ **保留 project/ 现场 24h**
+    供诊断（sweep_compile_jobs_expired 按 failed_project_ttl_s 清理；
+    KEEP_FAILED_PROJECTS=1 永久保留）；
+    失败必落完整 output.log（含 --print 的 XDV→PDF 阶段输出，补充 3）。
+
+    → {compile_id, pdf_path, log_path, seconds, pdf_bytes}
+    """
+    global _pending
+    settings = get_settings()
+    _ensure_tool()                    # 快速失败：不消费 inspect、不占队列
+    sweep_inspect_expired()
+    sweep_compile_jobs_expired()
+    if _pending >= settings.compile_queue_limit:
+        raise QueueFullError(
+            f"编译队列已满（{_pending} 个任务排队），请稍后重试")
+    _pending += 1                     # 占位先于消费：QUEUE_FULL 时 inspect 未动
+    cid = uuid.uuid4().hex[:12]
+    project: Path | None = None
+    meta: dict[str, Any] = {}
+    try:
+        project, meta = await asyncio.to_thread(consume_inspect, job_id, cid)
+        try:
+            # EPS v2：解压后批量转换所有 .eps → 同名 .pdf 并切换显式引用
+            # （不依赖 zip 自带预转换版；失败现场保留转换后的改写结果）
+            eps_lines = await asyncio.to_thread(process_eps_images, project)
+            async with _lock:
+                result = await _run_project(
+                    cid, project, str(meta.get("main", "")), eps_lines)
+            # 成功 → 立即清理 project 树（失败路径在 finally 保留现场）
+            shutil.rmtree(project, ignore_errors=True)
+            project = None
+            return result
+        except CompileError as exc:
+            # 补充 3：失败信封也要能下载 log → 异常携带产物 cid（log 落盘于 compile_jobs/{cid}/）
+            exc.compile_id = cid
+            raise
+    finally:
+        _pending -= 1
+        if project is not None:
+            # 编译失败 → 保留 compile_jobs/{cid}/project/ 现场供诊断；
+            # touch 目录使 24h 保留窗从失败时刻起算
+            try:
+                os.utime(project, None)
+            except OSError:
+                pass
+
+
+async def _run_project(
+    cid: str,
+    project: Path,
+    main_rel: str,
+    eps_log_lines: list[str] | None = None,
+) -> dict[str, Any]:
+    """单槽内执行项目编译：cwd=main 所在目录（相对路径解析），outdir=compile_jobs/{cid}。
+
+    eps_log_lines：EPS v2 的 [eps-convert] 转换日志（约束4），正常/超时两条路径
+    都会写进 output.log（引擎 log 之后、chatter/[timeout] 之前）。
+    """
+    settings = get_settings()
+    outdir = compile_job_dir(cid)
+    outdir.mkdir(parents=True, exist_ok=True)
+    main_path = project / main_rel
+    if not main_rel or not main_path.is_file():
+        raise InspectError("VALIDATION", "主文件缺失，请重新上传 zip")
+    cwd = main_path.parent
+    stem = main_path.stem
+
+    env = dict(os.environ)
+    env["TECTONIC_CACHE_DIR"] = str(settings.tectonic_cache_abs)
+    # --print：打印引擎完整 chatter（含 XDV→PDF/xdvipdfmx 阶段输出）；
+    # 不加时 xdvipdfmx 报错只进 tectonic stderr、不落 {stem}.log，导致"LaTeX 成功但
+    # 无 PDF"且 log 无错误行（MDPI 模板实测）。stdout/stderr 统一落盘 output.log。
+    cmd = [
+        str(_tectonic_bin()), "-X", "compile", main_path.name,
+        "--untrusted", "--keep-logs", "--print", "--outdir", str(outdir),
+    ]
+    timeout = settings.compile_project_timeout_s
+    log_path = outdir / "output.log"
+    started = time.monotonic()
+    try:
+        proc = await asyncio.create_subprocess_exec(
+            *cmd, cwd=str(cwd), env=env,
+            stdout=asyncio.subprocess.PIPE, stderr=asyncio.subprocess.STDOUT,
+            start_new_session=True,
+        )
+        try:
+            stdout_bytes, _ = await asyncio.wait_for(
+                proc.communicate(), timeout=timeout)
+        except asyncio.TimeoutError:
+            _kill_group(proc)
+            try:
+                await asyncio.wait_for(proc.wait(), timeout=5.0)
+            except asyncio.TimeoutError:
+                pass
+            # 超时后 communicate 已取消，chatter 不可取；.log（--keep-logs）仍完整
+            _ensure_project_log(outdir, stem, cwd)
+            # 约束4：转换日志先落（转换发生在编译之前），再追加超时标记
+            _append_eps_lines(log_path, eps_log_lines)
+            # 追加而非覆盖：保留完整引擎输出（诊断 XDV→PDF 阶段必需）
+            with log_path.open("a", encoding="utf-8") as fh:
+                fh.write(f"\n[timeout] 编译超时（{timeout:g}s），进程已终止\n")
+            raise CompileError(
+                "TIMEOUT",
+                f"编译超过 {timeout:g} 秒未完成，已终止"
+                "（项目首次编译需下载宏包，可能较慢，请重试）",
+                _log_tail(log_path),
+            ) from None
+    except FileNotFoundError as exc:
+        raise ToolUnavailableError(f"tectonic 不可执行：{exc}") from exc
+    finally:
+        seconds = round(time.monotonic() - started, 2)
+
+    _ensure_project_log(outdir, stem, cwd)
+
+    # 产物归一：{stem}.pdf/.log → output.pdf/.log（补充 3：失败也必有 output.log）
+    produced_pdf = outdir / f"{stem}.pdf"
+    produced_log = outdir / f"{stem}.log"
+    if produced_log.is_file():
+        shutil.move(str(produced_log), str(log_path))
+    if not log_path.is_file():
+        log_path.write_text(
+            "[no log] tectonic 未产出日志（进程异常退出）", encoding="utf-8")
+    # 约束4：[eps-convert] 转换日志（引擎 log 之后、chatter 之前）
+    _append_eps_lines(log_path, eps_log_lines)
+    # --print 的进程输出（含 XDV→PDF 阶段）追加到 output.log 全文之后；
+    # 信封 detail 仍只取尾 200 行，磁盘保留完整 log 供"查看完整 log"下载
+    _append_chatter(log_path, stdout_bytes)
+
+    if not produced_pdf.is_file():
+        raise CompileError(
+            "COMPILE_FAILED",
+            classify_compile_error(_log_tail(log_path)),
+            _log_tail(log_path),
+        )
+    pdf_bytes = produced_pdf.stat().st_size
+    if pdf_bytes > settings.max_compile_pdf_bytes:
+        produced_pdf.unlink(missing_ok=True)
+        raise CompileError(
+            "OUTPUT_TOO_LARGE",
+            f"产出 PDF 超过 {settings.max_compile_pdf_bytes // (1024 * 1024)}MB 上限，已删除",
+            _log_tail(log_path),
+        )
+    produced_pdf.rename(outdir / "output.pdf")
+
+    meta = {
+        "compile_id": cid,
+        "project": True,
+        "main": main_rel,
+        "engine": _ENGINE,
+        "seconds": seconds,
+        "pdf_bytes": pdf_bytes,
+        "returncode": 0,
+        "compiled_at": datetime.now(timezone.utc).isoformat(timespec="seconds"),
+    }
+    (outdir / "meta.json").write_text(
+        json.dumps(meta, ensure_ascii=False, indent=2), encoding="utf-8")
+    logger.info("compile(project): %s main=%s → PDF %d bytes, %.2fs",
+                cid, main_rel, pdf_bytes, seconds)
+    return {
+        "compile_id": cid,
+        "pdf_path": outdir / "output.pdf",
+        "log_path": log_path,
+        "seconds": seconds,
+        "pdf_bytes": pdf_bytes,
+    }
+
+
+def _ensure_project_log(outdir: Path, stem: str, cwd: Path) -> None:
+    """tectonic 落 log 到 outdir 或 cwd → 统一挪到 outdir/output.log；都没有则占位。"""
+    log_path = outdir / "output.log"
+    if log_path.is_file():
+        return
+    for cand in (outdir / f"{stem}.log", cwd / f"{stem}.log"):
+        if cand.is_file():
+            shutil.move(str(cand), str(log_path))
+            return
+
+
+def _append_chatter(log_path: Path, stdout_bytes: bytes | None) -> None:
+    """把 tectonic --print 的进程 stdout（含 XDV→PDF/xdvipdfmx 阶段）追加到 output.log。
+
+    {stem}.log 只有 LaTeX 引擎内容（止于 "Output written on … .xdv"）；
+    XDV→PDF 转换错误只出现在进程 chatter 里——不落盘则"无 PDF 且 log 无错误行"。
+    """
+    if not stdout_bytes:
+        return
+    chatter = stdout_bytes.decode("utf-8", errors="replace").strip()
+    if not chatter:
+        return
+    with log_path.open("a", encoding="utf-8") as fh:
+        fh.write("\n\n===== tectonic --print（进程输出，含 XDV→PDF 阶段）=====\n")
+        fh.write(chatter)
+        fh.write("\n")
+
+
+def sweep_inspect_expired() -> int:
+    """删 mtime 超 inspect_ttl_s（默认 1h）的 12-hex inspect 暂存目录。"""
+    settings = get_settings()
+    base = settings.inspect_dir_abs
+    if not base.is_dir():
+        return 0
+    cutoff = time.time() - settings.inspect_ttl_s
+    removed = 0
+    for child in base.iterdir():
+        if not child.is_dir() or not _ANCHOR_ID_RE.fullmatch(child.name):
+            continue
+        try:
+            if child.stat().st_mtime < cutoff:
+                shutil.rmtree(child, ignore_errors=True)
+                removed += 1
+        except OSError:
+            continue
+    if removed:
+        logger.info("inspect sweep: 清理 %d 个过期 inspect 暂存（>%d 秒）",
+                    removed, settings.inspect_ttl_s)
+    return removed
+
+
+def _keep_failed_projects() -> bool:
+    """失败现场是否永久保留（调试）：REVIEW_KEEP_FAILED_PROJECTS=1 或裸 KEEP_FAILED_PROJECTS=1。"""
+    if get_settings().keep_failed_projects:
+        return True
+    return os.environ.get("KEEP_FAILED_PROJECTS", "").strip() == "1"
+
+
+def sweep_compile_jobs_expired() -> int:
+    """编译产物清扫，两级：
+      ① 失败现场 project/ 子目录：mtime 超 failed_project_ttl_s（默认 24h）→ 删子目录
+         （compile_jobs/{cid} 本体与 output.log/meta 保留，供"查看完整 log"）；
+         KEEP_FAILED_PROJECTS=1 跳过（永久保留，调试用）。
+      ② 整个 compile_jobs/{cid}：mtime 超 compile_retention_days（7 天）→ 整目录删。
+    """
+    settings = get_settings()
+    base = settings.compile_jobs_dir_abs
+    if not base.is_dir():
+        return 0
+    removed = 0
+    keep_failed = _keep_failed_projects()
+    # ① 失败现场 24h 清理（成功编译的 project/ 已在 compile_project_job 立即删）
+    if not keep_failed:
+        proj_cutoff = time.time() - settings.failed_project_ttl_s
+        for child in base.iterdir():
+            if not child.is_dir() or not _ANCHOR_ID_RE.fullmatch(child.name):
+                continue
+            proj = child / "project"
+            if not proj.is_dir():
+                continue
+            try:
+                if proj.stat().st_mtime < proj_cutoff:
+                    shutil.rmtree(proj, ignore_errors=True)
+                    removed += 1
+            except OSError:
+                continue
+    # ② 整目录 7 天清理
+    cutoff = time.time() - settings.compile_retention_days * 86400
+    for child in base.iterdir():
+        if not child.is_dir() or not _ANCHOR_ID_RE.fullmatch(child.name):
+            continue
+        try:
+            if child.stat().st_mtime < cutoff:
+                shutil.rmtree(child, ignore_errors=True)
+                removed += 1
+        except OSError:
+            continue
+    if removed:
+        logger.info("compile_jobs sweep: 清理 %d 个过期项目产物/失败现场", removed)
+    return removed
@@ -0,0 +1,203 @@
+"""services/llm.py —— LLM 调用（httpx 裸调 DeepSeek，模式同 paper_writer_service）。
+
+- complete_text(system, user, *, temperature=0.3, max_tokens=8000, timeout=None) -> str
+- complete_json(...)（response_format json_object + 一次 JSON 修复重试）
+- 4 次尝试（1.5s / 3s / 6s 指数退避，429 / 5xx / 超时）
+- env 键（优先 REVIEW_LLM_*，回退 DOCGEN_LLM_*，再回退内置默认）：
+  *_LLM_BASE_URL / *_LLM_API_KEY / *_LLM_MODEL / *_LLM_TIMEOUT
+"""
+from __future__ import annotations
+
+import asyncio
+import json
+import logging
+import os
+from typing import Any
+
+import httpx
+
+logger = logging.getLogger(__name__)
+
+DEFAULT_LLM_BASE_URL = "https://api.deepseek.com/v1"
+DEFAULT_LLM_MODEL = "deepseek-chat"
+DEFAULT_LLM_TIMEOUT = 300.0
+BACKOFF_SECONDS = (1.5, 3.0, 6.0)
+MAX_ATTEMPTS = 4
+
+
+class LLMError(Exception):
+    """LLM 调用失败（重试尽/响应异常）。"""
+
+
+def _env(keys: tuple[str, ...], default: str = "") -> str:
+    for key in keys:
+        val = os.environ.get(key)
+        if val:
+            return val
+    return default
+
+
+def _llm_config() -> dict[str, Any]:
+    return {
+        "base_url": _env(
+            ("REVIEW_LLM_BASE_URL", "DOCGEN_LLM_BASE_URL"), DEFAULT_LLM_BASE_URL
+        ).rstrip("/"),
+        "api_key": _env(("REVIEW_LLM_API_KEY", "DOCGEN_LLM_API_KEY"), ""),
+        "model": _env(("REVIEW_LLM_MODEL", "DOCGEN_LLM_MODEL"), DEFAULT_LLM_MODEL),
+        "timeout": float(
+            _env(("REVIEW_LLM_TIMEOUT", "DOCGEN_LLM_TIMEOUT"), str(DEFAULT_LLM_TIMEOUT))
+        ),
+    }
+
+
+def _extract_text(payload: dict[str, Any]) -> str:
+    try:
+        choices = payload.get("choices") or []
+        if choices:
+            content = choices[0].get("message", {}).get("content")
+            if isinstance(content, str):
+                return content
+            if isinstance(content, list):
+                return "".join(
+                    str(c.get("text", "")) if isinstance(c, dict) else str(c) for c in content
+                )
+    except Exception:
+        pass
+    return ""
+
+
+async def _chat_once(
+    client: httpx.AsyncClient,
+    cfg: dict[str, Any],
+    system: str,
+    user: str,
+    *,
+    temperature: float,
+    max_tokens: int,
+    json_mode: bool,
+    timeout: float | None,
+) -> str:
+    headers = {"Content-Type": "application/json"}
+    if cfg["api_key"]:
+        headers["Authorization"] = f"Bearer {cfg['api_key']}"
+    body: dict[str, Any] = {
+        "model": cfg["model"],
+        "messages": [
+            {"role": "system", "content": system},
+            {"role": "user", "content": user},
+        ],
+        "temperature": temperature,
+        "max_tokens": max_tokens,
+    }
+    if json_mode:
+        body["response_format"] = {"type": "json_object"}
+    resp = await client.post(
+        f"{cfg['base_url']}/chat/completions",
+        headers=headers,
+        json=body,
+        timeout=timeout if timeout is not None else cfg["timeout"],
+    )
+    resp.raise_for_status()
+    payload = resp.json()
+    if not isinstance(payload, dict):
+        raise LLMError("LLM 响应形态异常（非 JSON 对象）")
+    text = _extract_text(payload)
+    if not text:
+        raise LLMError("LLM 响应缺少 choices[0].message.content")
+    return text
+
+
+async def _complete(
+    system: str,
+    user: str,
+    *,
+    temperature: float,
+    max_tokens: int,
+    json_mode: bool,
+    timeout: float | None,
+) -> str:
+    cfg = _llm_config()
+    last_exc: BaseException | None = None
+    async with httpx.AsyncClient() as client:
+        for attempt in range(MAX_ATTEMPTS):
+            try:
+                return await _chat_once(
+                    client, cfg, system, user,
+                    temperature=temperature, max_tokens=max_tokens, json_mode=json_mode,
+                    timeout=timeout,
+                )
+            except LLMError:
+                raise
+            except (httpx.HTTPStatusError, httpx.HTTPError, httpx.TimeoutException) as exc:
+                last_exc = exc
+                status = getattr(getattr(exc, "response", None), "status_code", None)
+                retryable = status is None or status == 429 or status >= 500
+                if not retryable or attempt == MAX_ATTEMPTS - 1:
+                    raise LLMError(f"LLM 调用失败（HTTP {status or '网络'}）：{exc}") from exc
+                await asyncio.sleep(BACKOFF_SECONDS[min(attempt, len(BACKOFF_SECONDS) - 1)])
+    raise LLMError(f"LLM 调用失败：{last_exc}")
+
+
+async def complete_text(
+    system: str,
+    user: str,
+    *,
+    temperature: float = 0.3,
+    max_tokens: int = 8000,
+    timeout: float | None = None,
+) -> str:
+    """文本补全。失败抛 LLMError。"""
+    return await _complete(
+        system, user, temperature=temperature, max_tokens=max_tokens, json_mode=False,
+        timeout=timeout,
+    )
+
+
+def _repair_json(text: str) -> str:
+    text = text.strip()
+    if text.startswith("```"):
+        text = text.strip("`")
+        if text.lower().startswith("json"):
+            text = text[4:]
+        text = text.strip()
+    if not text:
+        raise LLMError("LLM 返回空内容")
+    if text.startswith("{"):
+        return text
+    start = text.find("{")
+    end = text.rfind("}")
+    if start >= 0 and end > start:
+        return text[start:end + 1]
+    raise LLMError("LLM 输出中未找到 JSON 对象")
+
+
+async def complete_json(
+    system: str,
+    user: str,
+    *,
+    temperature: float = 0.3,
+    max_tokens: int = 8000,
+    timeout: float | None = None,
+) -> dict[str, Any]:
+    """JSON 补全（json_object + 一次修复重试）。"""
+    text = await _complete(
+        system, user, temperature=temperature, max_tokens=max_tokens, json_mode=True,
+        timeout=timeout,
+    )
+    try:
+        return json.loads(text)
+    except ValueError:
+        pass
+    text2 = await _complete(
+        system + "\n（重要：你的回答必须是单个合法 JSON 对象，不要输出其他任何内容）",
+        user,
+        temperature=temperature,
+        max_tokens=max_tokens,
+        json_mode=True,
+        timeout=timeout,
+    )
+    try:
+        return json.loads(text2)
+    except ValueError:
+        repaired = _repair_json(text2)
+        return json.loads(repaired)
@@ -0,0 +1,139 @@
+"""paper_parse.py —— PDF → 纯文本（经 vstore 8094 现有解析接口，零改动复用）。
+
+链路（全部只读消费 vstore 既有 API，不修改 vstore 代码）：
+1. POST {vstore}/api/vstore/ingest      multipart file（vstore 内部 pymupdf 解析）
+2. GET  {vstore}/api/vstore/documents/{doc_id}   → document.paragraphs 拼接纯文本
+3. DELETE {vstore}/api/vstore/documents/{doc_id} （临时解析件 best-effort 清理，
+   REVIEW_PARSE_DELETE_AFTER=0 可关闭——保留文档便于人工排查）
+
+为何不用 methodology 8092：其 /extract-upload 是 MinerU 分钟级异步 job
+（MinerU 子进程 + LLM 抽取两阶段），不适配同步自审稿；vstore 段落解析秒级
+返回，满足 presubmit 场景。methodology 地址在 config 中预留供后续扩展。
+"""
+from __future__ import annotations
+
+import logging
+from typing import Any
+
+import httpx
+
+from ..config import get_settings
+
+logger = logging.getLogger(__name__)
+
+
+class ParseError(Exception):
+    """PDF 解析失败（上游不可达/响应异常/空文本）。"""
+
+
+async def parse_pdf(path: str) -> str:
+    """接收 PDF 文件路径，返回拼接后的纯文本。失败抛 ParseError。"""
+    try:
+        with open(path, "rb") as fh:
+            file_bytes = fh.read()
+    except OSError as exc:
+        raise ParseError(f"读取 PDF 失败：{exc}") from exc
+    return await parse_pdf_bytes(file_bytes, filename=str(path).rsplit("/", 1)[-1] or "paper.pdf")
+
+
+async def parse_pdf_bytes(file_bytes: bytes, filename: str = "paper.pdf") -> str:
+    """接收 PDF 字节流，返回拼接后的纯文本。失败抛 ParseError。"""
+    if not file_bytes:
+        raise ParseError("PDF 内容为空")
+
+    settings = get_settings()
+    base = settings.vstore_base
+    timeout = httpx.Timeout(
+        connect=5.0, read=settings.parse_timeout, write=settings.parse_timeout, pool=5.0
+    )
+
+    async with httpx.AsyncClient(timeout=timeout) as client:
+        # ---- 1) ingest（vstore 内部 pymupdf 解析 + 嵌入 + 加密落盘）----
+        try:
+            resp = await client.post(
+                f"{base}/api/vstore/ingest",
+                files={"file": (filename, file_bytes, "application/pdf")},
+                data={
+                    "name": filename,
+                    "category": "review_presubmit",
+                    "description": "review_service 临时解析件",
+                },
+            )
+        except httpx.HTTPError as exc:
+            raise ParseError(f"vstore 不可达（{base}）：{exc}") from exc
+
+        if resp.status_code >= 400:
+            # 读上游错误体（信封 JSON 或裸文本），区分“不可达”与“上游报错”
+            raise ParseError(f"vstore ingest 失败（HTTP {resp.status_code}）：{_err_body(resp)}")
+
+        try:
+            payload = resp.json()
+        except ValueError as exc:
+            raise ParseError(f"vstore ingest 响应非 JSON：{exc}") from exc
+
+        if not isinstance(payload, dict) or not payload.get("ok"):
+            message = _err_message(payload) or "vstore ingest 失败"
+            raise ParseError(message)
+        doc_id = str((payload.get("item") or {}).get("document_id") or "")
+        if not doc_id:
+            raise ParseError("vstore ingest 响应缺少 document_id")
+
+        # ---- 2) 取明文全文（paragraphs 拼接）+ 3) 清理临时件 ----
+        try:
+            text = await _fetch_text(client, base, doc_id)
+        finally:
+            if settings.parse_delete_after:
+                await _best_effort_delete(client, base, doc_id)
+
+    text = text.strip()
+    if not text:
+        raise ParseError("PDF 解析结果为空（可能是扫描件/图片型 PDF，vstore 无 OCR）")
+    return text
+
+
+async def _fetch_text(client: httpx.AsyncClient, base: str, doc_id: str) -> str:
+    """取 vstore 文档明文并按段落拼接纯文本。"""
+    try:
+        resp = await client.get(f"{base}/api/vstore/documents/{doc_id}")
+    except httpx.HTTPError as exc:
+        raise ParseError(f"vstore 取文档失败（{doc_id}）：{exc}") from exc
+    if resp.status_code >= 400:
+        raise ParseError(
+            f"vstore 取文档失败（{doc_id}，HTTP {resp.status_code}）：{_err_body(resp)}"
+        )
+    try:
+        payload = resp.json()
+    except ValueError as exc:
+        raise ParseError(f"vstore 取文档响应非 JSON（{doc_id}）：{exc}") from exc
+    if not isinstance(payload, dict) or not payload.get("ok"):
+        raise ParseError(_err_message(payload) or f"vstore 取文档失败（{doc_id}）")
+
+    document: dict[str, Any] = payload.get("document") or {}
+    paragraphs = document.get("paragraphs") or []
+    return "\n".join(str(p) for p in paragraphs if str(p).strip())
+
+
+async def _best_effort_delete(client: httpx.AsyncClient, base: str, doc_id: str) -> None:
+    try:
+        await client.delete(f"{base}/api/vstore/documents/{doc_id}")
+    except Exception:  # noqa: BLE001 - 清理失败不阻断（文档级 secure_delete 已尽力）
+        logger.warning("paper_parse: vstore 临时文档清理失败（%s）", doc_id, exc_info=True)
+
+
+def _err_message(payload: Any) -> str:
+    if isinstance(payload, dict):
+        err = payload.get("error")
+        if isinstance(err, dict):
+            return str(err.get("message") or "")
+        if isinstance(err, str):
+            return err
+    return ""
+
+
+def _err_body(resp: httpx.Response) -> str:
+    """上游错误体：优先 JSON 信封 message，回退裸文本（截断 500 字符）。"""
+    try:
+        payload = resp.json()
+    except ValueError:
+        return (resp.text or "").strip()[:500] or "（空响应体）"
+    return _err_message(payload) or str(payload)[:500]
@@ -0,0 +1,226 @@
+"""services/paper_scanner.py —— 关键词兜底扫描器（纯 stdlib，零 LLM）。
+
+背景（2026-10-12）：hard_rule 标签由 LLM 输出，存在"正文明明有 accession/BUSCO/挂载率
+却报缺失"的漏检风险（真实案例 s41588 Nature Genetics：正文有 PRJCA038097 等 +
+BUSCO 98.57% + 94.18% anchored，仍被判 busco/accession/hic_missing → 大修）。
+本模块做**程序层证伪**：LLM 说缺某项、扫描器在文中找到该项 → 剥掉 hard_rule
+降级为非硬性 major，并在 rationale 记录冲突（前端黄色提示，请人工核对）。
+
+边界（刻意保守，不引入新误判）：
+- 只做"证伪硬性缺项"，不做"证实"——扫不到不等于真缺（可能同义表述），不升级任何条目
+- accession 只在 Data Availability 段内扫（用户指令）：正文引用他人数据的
+  accession 不得误认为"自己有"
+"""
+from __future__ import annotations
+
+import re
+from typing import Any
+
+# ---- accession（只在 DA 段扫）----
+ACCESSION_RE = re.compile(
+    r"\b(PRJNA|PRJEB|PRJCA|SRP|ERP|DRP|CRA|SRR|ERR|DRR|GCA_|GCF_)\s?(\d[\d._]*)",
+    re.IGNORECASE,
+)
+
+# ---- DA 段定位：标题多变体（行首允许编号前缀）----
+_DA_START_RE = re.compile(
+    r"^[ \t]*(?:\d+(?:\.\d+)*\.?\s+)?"
+    r"(?:Data\s+(?:and\s+(?:code\s+)?)?[Aa]vailability"
+    r"|Availability\s+of\s+(?:data|Data)"
+    r"|Data\s+and\s+[Mm]aterials\s+[Aa]vailability"
+    r"|Data\s+availability\s+statement)",
+    re.MULTILINE,
+)
+# DA 段结束 = 下一个一级节标题
+_NEXT_HEADER_RE = re.compile(
+    r"^[ \t]*(?:\d+(?:\.\d+)*\.?\s+)?"
+    r"(?:Abstract|Summary|Introduction|Results|Discussion|Methods"
+    r"|Materials\s+and\s+Methods|References|Acknowledg(?:e)?ments?"
+    r"|Author\s+[Ii]nformation|Rights\s+and\s+permissions|Change\s+history"
+    r"|Data\s+(?:and\s+(?:code\s+)?)?[Aa]vailability"
+    r"|Availability\s+of\s+[Dd]ata|Data\s+and\s+[Mm]aterials\s+[Aa]vailability)"
+    r"\s*$",
+    re.MULTILINE,
+)
+# 回退窗：DA 无行首标题时，短语出现处 + 上下文
+_DA_PHRASE_RE = re.compile(r"data\s+availability", re.IGNORECASE)
+_DA_FALLBACK_WINDOW = 3000
+
+# ---- BUSCO（全文）----
+_BUSCO_MENTION_RE = re.compile(r"\bBUSCO\b", re.IGNORECASE)
+_BUSCO_FULL_RE = re.compile(
+    r"(?:\bS\s*:\s*\d|\bSingle[- ]copy)"
+    r".{0,200}?"
+    r"(?:\bD\s*:\s*\d|\bDuplicat)",
+    re.IGNORECASE | re.DOTALL,
+)
+
+# ---- Hi-C 挂载率（全文）----
+HIC_RE = re.compile(
+    r"(anchored\s+to\s+chromosomes?"
+    r"|anchoring\s+rate"
+    r"|pseudo[- ]?chromosomes?"
+    r"|chromosome[- ]level"
+    r"|%[^.\n]{0,40}anchored)",
+    re.IGNORECASE,
+)
+
+_MAX_HITS = 20
+
+
+def _extract_da_section(text: str) -> str:
+    """定位 Data Availability 段正文（标题后 → 下一个一级节标题）。
+
+    无行首标题时回退：短语出现处向后 3000 字符窗。均未命中 → ""。
+    """
+    m = _DA_START_RE.search(text)
+    if m:
+        nxt = _NEXT_HEADER_RE.search(text, m.end())
+        end = nxt.start() if nxt else min(len(text), m.end() + _DA_FALLBACK_WINDOW)
+        return text[m.start():end]
+    m2 = _DA_PHRASE_RE.search(text)
+    if m2:
+        return text[m2.start():min(len(text), m2.start() + _DA_FALLBACK_WINDOW)]
+    return ""
+
+
+def _scan_accession(da_text: str) -> dict[str, Any]:
+    if not da_text:
+        return {"found": False, "hits": [], "in_da_section": False}
+    hits: list[str] = []
+    seen: set[str] = set()
+    for m in ACCESSION_RE.finditer(da_text):
+        token = (m.group(1) + m.group(2)).upper()
+        if token not in seen:
+            seen.add(token)
+            hits.append(token)
+            if len(hits) >= _MAX_HITS:
+                break
+    return {"found": bool(hits), "hits": hits, "in_da_section": True}
+
+
+def _scan_busco(text: str) -> dict[str, Any]:
+    m = _BUSCO_MENTION_RE.search(text)
+    if not m:
+        return {"level": "none", "excerpt": ""}
+    excerpt = text[m.start():m.start() + 200]
+    if _BUSCO_FULL_RE.search(text):
+        level = "full"
+    else:
+        level = "partial"  # 只有百分比、无 S/D 分项 → prompt 已定为 minor
+    return {"level": level, "excerpt": excerpt}
+
+
+def _scan_hic(text: str) -> dict[str, Any]:
+    m = HIC_RE.search(text)
+    if not m:
+        return {"found": False, "excerpt": ""}
+    start = max(0, m.start() - 40)
+    return {"found": True, "excerpt": text[start:m.end() + 80]}
+
+
+def scan_paper_signals(text: str) -> dict[str, Any]:
+    """全文 → 结构化信号。accession 只在 DA 段；busco/hic 全文。"""
+    if not text:
+        return {
+            "accession": {"found": False, "hits": [], "in_da_section": False},
+            "busco": {"level": "none", "excerpt": ""},
+            "hic": {"found": False, "excerpt": ""},
+        }
+    return {
+        "accession": _scan_accession(_extract_da_section(text)),
+        "busco": _scan_busco(text),
+        "hic": _scan_hic(text),
+    }
+
+
+def _get_hr(item: Any) -> Any:
+    if isinstance(item, dict):
+        return item.get("hard_rule")
+    return getattr(item, "hard_rule", None)
+
+
+def _item_fatal(item: Any) -> bool:
+    if isinstance(item, dict):
+        return bool(item.get("fatal"))
+    return bool(getattr(item, "fatal", False))
+
+
+def _set_downgraded(item: Any) -> None:
+    if isinstance(item, dict):
+        item["scanner_downgraded"] = True
+    else:
+        try:
+            item.scanner_downgraded = True
+        except Exception:  # pydantic 严格模式等极端场景：吞掉，冲突记录仍保留
+            pass
+
+
+def _set_hr_none(item: Any) -> None:
+    if isinstance(item, dict):
+        item["hard_rule"] = None
+    else:
+        try:
+            item.hard_rule = None
+        except Exception:  # pydantic 严格模式等极端场景：吞掉，冲突记录仍保留
+            pass
+
+
+def _item_title(item: Any) -> str:
+    if isinstance(item, dict):
+        return str(item.get("title") or "")
+    return str(getattr(item, "title", "") or "")
+
+
+# 冲突映射：hard_rule 标签 → (信号检查, 冲突描述)
+def _conflict_for(tag: str, signals: dict[str, Any]) -> str | None:
+    acc = signals.get("accession") or {}
+    busco = signals.get("busco") or {}
+    hic = signals.get("hic") or {}
+    if tag == "accession_missing" and acc.get("found"):
+        hits = ", ".join(acc.get("hits") or [])[:120]
+        return f"Data Availability 段已检出 accession（{hits}）"
+    if tag == "busco_missing" and busco.get("level") in ("partial", "full"):
+        return f"正文已提及 BUSCO（{busco.get('level')} 格式）"
+    if tag == "hic_missing" and hic.get("found"):
+        excerpt = (hic.get("excerpt") or "").strip()[:80]
+        return f"正文已检出挂载率描述（{excerpt}）"
+    return None
+
+
+def reconcile_hard_rules(
+    majors: list[Any], signals: dict[str, Any]
+) -> tuple[list[Any], list[Any], list[dict[str, Any]]]:
+    """对带 hard_rule 的 major 做扫描器证伪：命中 → 剥标签 + **移出 major 降级至
+    minor**（A2 语义，2026-10-12）→ 记冲突。
+
+    返回 (kept_majors, demoted_minors, conflicts)：
+    - kept_majors：未冲突/未处理的 major（原序）
+    - demoted_minors：被冲突降级的条目（hard_rule 置 None、scanner_downgraded=True）
+    - conflicts：{hard_rule, title, reason}——fatal 条目只记冲突不降级
+      （拒稿级问题须人工过目，扫描器证伪不了伦理判断）。
+    """
+    kept: list[Any] = []
+    demoted: list[Any] = []
+    conflicts: list[dict[str, Any]] = []
+    for m in majors:
+        tag = _get_hr(m)
+        if not isinstance(tag, str):
+            kept.append(m)
+            continue
+        reason = _conflict_for(tag, signals)
+        if reason is None:
+            kept.append(m)
+            continue
+        conflicts.append({
+            "hard_rule": tag,
+            "title": _item_title(m),
+            "reason": reason,
+        })
+        if _item_fatal(m):
+            kept.append(m)  # fatal 保留原位（含其 hard_rule 供引擎 R1/R0 使用）
+            continue
+        _set_hr_none(m)
+        _set_downgraded(m)
+        demoted.append(m)
+    return kept, demoted, conflicts
@@ -0,0 +1,264 @@
+"""services/ppt_figure_index.py —— 论文真实图表清单扫描（P5 增强 1）。
+
+问题根因：LLM 不知道论文里真实图编号与位置，suggested_figures 全靠编。
+修复：用正则从论文全文扫描 Figure/Fig./图 + Table/表 编号 → figure_index
+（[{label, para_id, caption, kind}]），注入 reduce prompt 供 LLM「只选不编」，
+代码侧再按清单校验：不在清单里的图引用直接丢弃（而非标 unverified）。
+
+para_id 与 ppt_outline.build_index 的分段完全一致（复用同一套分段逻辑），
+因此 figure_index 的 para_id 可直接用于证据链与前端展示「Fig 1（论文 S1-P12）」。
+"""
+from __future__ import annotations
+
+import logging
+import re
+from pathlib import Path
+from typing import Any
+
+logger = logging.getLogger(__name__)
+
+FIG_RE = re.compile(r"(?:Figure|Fig\.?|图)\s*(\d+)")
+TABLE_RE = re.compile(r"(?:Table|表)\s*(\d+)")
+_CAPTION_MARK = re.compile(r"\s*[:：.]")     # 紧跟编号的冒号/句点 → caption 形态
+_SENT_SPLIT = re.compile(r"(?<=[.!?。！？;；])\s*")
+_MAX_CAPTION = 120
+
+# label → 规约键：("fig", n) / ("table", n)（"Figure 2"/"Fig. 2"/"图 2"/"Fig 2" 同键）
+_LABEL_KIND = re.compile(r"^\s*(figure|fig|图|table|表)", re.IGNORECASE)
+
+# 行首 caption（借 paper-skills pdf_snap 的分隔符全集：:：. 与 |；pdf_snap MIT）
+_CAPTION_LINE = re.compile(
+    r"^\s*(Figure|Fig\.?|Table|Tab\.?|图|表|Algorithm|算法)\s*"
+    r"([0-9]+[a-z]?|[A-Z]\.?[0-9]+)\s*[:：.|]\s*(\S.*)$", re.IGNORECASE,
+)
+
+
+def canon_label(label: Any) -> tuple[str, int] | None:
+    """图/表 label 归一化 → (kind, number)；无法解析返回 None。"""
+    s = str(label or "").strip()
+    m = _LABEL_KIND.match(s)
+    digits = re.search(r"(\d+)", s)
+    if not m or not digits:
+        return None
+    kind = "table" if m.group(1).lower() in ("table", "表") else "fig"
+    return (kind, int(digits.group(1)))
+
+
+def figure_map(figure_index: list[dict[str, Any]] | None) -> dict[tuple[str, int], dict[str, Any]]:
+    """figure_index → {("fig",2): entry} 查找表（校验用）。"""
+    out: dict[tuple[str, int], dict[str, Any]] = {}
+    for entry in figure_index or []:
+        key = canon_label(entry.get("label"))
+        if key and key not in out:
+            out[key] = entry
+    return out
+
+
+def _sentence(paragraph: str, span: tuple[int, int]) -> str:
+    """取包含命中的句子（截 120 字符）作为 caption。"""
+    start = 0
+    best = paragraph
+    for part in _SENT_SPLIT.split(paragraph):
+        end = start + len(part)
+        if start <= span[0] < end:
+            best = part
+            break
+        start = end
+    return best.strip()[:_MAX_CAPTION]
+
+
+def _scan(index: dict[str, str]) -> list[dict[str, Any]]:
+    """para_id→原文 索引 → 真实图表清单（按 (kind,编号) 去重）。"""
+    found: dict[tuple[str, int], tuple[int, dict[str, Any]]] = {}
+    for para_id, para_text in index.items():
+        for regex, kind in ((FIG_RE, "figure"), (TABLE_RE, "table")):
+            for m in regex.finditer(para_text):
+                key = (kind, int(m.group(1)))
+                # caption 形态（"Figure 2: ..."）优先于顺带提及；同分先到先得
+                score = 2 if _CAPTION_MARK.match(para_text[m.end(): m.end() + 4]) else 1
+                hit = {
+                    "label": f"Fig {m.group(1)}" if kind == "figure" else f"Table {m.group(1)}",
+                    "para_id": para_id,
+                    "caption": _sentence(para_text, m.span()),
+                    "kind": kind,
+                }
+                if key not in found or score > found[key][0]:
+                    found[key] = (score, hit)
+    return [entry for _, entry in found.values()]
+
+
+def scan_figure_index(index: dict[str, str]) -> list[dict[str, Any]]:
+    """para_id→原文 索引 → 图表清单（纯函数，可单测）。"""
+    return _scan(index)
+
+
+def build_figure_index(text: str) -> list[dict[str, Any]]:
+    """论文全文 → 图表清单（与证据链共用同一套段落分段，para_id 一致）。"""
+    from .ppt_outline import build_index  # 局部导入避免与 ppt_outline 循环依赖
+    _, index = build_index(text)
+    return _scan(index)
+
+
+# ---------- PDF 原图提取（P5 增强 2.3；AGENTS 例外：vstore 只回文本，图片须本地解档） ----------
+
+_BAND_ABOVE_PT = 300.0   # caption 上方搜索带（图底边距 caption 的最大距离，pt）
+_BAND_PAD_X_PT = 40.0    # caption 左右扩展（横向重叠判定）
+_MIN_PX = (60, 40)       # 裁切结果最小像素（过滤图标/装饰线）
+_DPI = 300
+
+
+def extract_figures(pdf_bytes: bytes, out_dir: Path) -> list[dict[str, Any]]:
+    """PDF → 与 caption 配对的原图 PNG（out_dir/Fig_1.png…）+ 清单。
+
+    策略（自 paper-skills pdf_snap「页渲染+裁图」与 paper-ppt-skill Step5 裁剪规则
+    自动化而来）：同页 caption 行上方 band 内「嵌入位图 ∪ 矢量绘图」联合包围盒
+    → clip 渲染 300dpi。Table 跳过（表格不出栅格图，由占位/表格版式承接）。
+    配对失败/过小 → 跳过（build 侧回落文字占位），绝不抛错阻塞建 job。
+    """
+    out = Path(out_dir)
+    out.mkdir(parents=True, exist_ok=True)
+    results: dict[str, dict[str, Any]] = {}
+    try:
+        import pymupdf  # lock 中已有（format_check 同款）
+    except ImportError:  # pragma: no cover
+        logger.warning("pymupdf 不可用，跳过图表原图提取")
+        return []
+    try:
+        doc = pymupdf.open(stream=pdf_bytes, filetype="pdf")
+    except Exception as exc:  # noqa: BLE001
+        logger.warning("PDF 打开失败，跳过图表原图提取：%s", exc)
+        return []
+    try:
+        for pno in range(doc.page_count):
+            page = doc[pno]
+            caps = _caption_lines(page)
+            if not caps:
+                continue
+            img_rects = _image_rects(page)
+            for cap in caps:
+                if cap["kind"] != "fig":
+                    continue
+                key = f"Fig {cap['num']}"
+                if key in results:
+                    continue
+                box = _figure_box(page, cap, img_rects)
+                if box is None:
+                    continue
+                try:
+                    pix = page.get_pixmap(clip=box, dpi=_DPI)
+                except Exception:  # noqa: BLE001 - clip 越界等
+                    continue
+                if pix.width < _MIN_PX[0] or pix.height < _MIN_PX[1]:
+                    continue
+                fname = f"Fig_{cap['num']}.png"
+                try:
+                    pix.save(str(out / fname))
+                except OSError:
+                    continue
+                results[key] = {
+                    "label": key, "file": fname, "page": pno + 1,
+                    "caption": cap["text"][:_MAX_CAPTION],
+                    "width": pix.width, "height": pix.height,
+                }
+    finally:
+        doc.close()
+    ordered = sorted(results.values(), key=lambda r: int(r["label"].split()[1]))
+    logger.info("图表原图提取：%d 张 → %s", len(ordered), out)
+    return ordered
+
+
+def _caption_lines(page: Any) -> list[dict[str, Any]]:
+    """页内行首 caption → [{kind, num, text, x0, x1, y0}]（每编号取最先一行）。"""
+    caps: dict[str, dict[str, Any]] = {}
+    try:
+        data = page.get_text("dict")
+    except Exception:  # noqa: BLE001
+        return []
+    for block in data.get("blocks", []):
+        if block.get("type") != 0:
+            continue
+        for line in block.get("lines", []):
+            text = "".join(sp.get("text", "") for sp in line.get("spans", []))
+            m = _CAPTION_LINE.match(text)
+            if not m:
+                continue
+            raw_kind = m.group(1).rstrip(".").lower()   # "Fig." → "fig"（v3：剥尾点）
+            if raw_kind in ("figure", "fig", "图"):
+                kind = "fig"
+            elif raw_kind in ("table", "tab", "表"):
+                kind = "table"
+            else:
+                continue  # Algorithm 等：清单不含，原图也跳过
+            num = m.group(2)
+            digits = re.match(r"(\d+)", num)
+            if not digits:
+                continue
+            key = f"{kind}{digits.group(1)}"
+            if key in caps:
+                continue
+            x0, y0, x1, y1 = line["bbox"]
+            caps[key] = {
+                "kind": kind, "num": int(digits.group(1)),
+                "text": m.group(3).strip(),
+                "x0": float(x0), "x1": float(x1), "y0": float(y0),
+            }
+    return list(caps.values())
+
+
+def _image_rects(page: Any) -> list[Any]:
+    """页内嵌入位图的 rect 列表（失败返回空）。"""
+    rects = []
+    try:
+        for info in page.get_image_info(xrefs=True):
+            xref = info.get("xref")
+            if not xref:
+                continue
+            for r in page.get_image_rects(xref):
+                rects.append(r)
+    except Exception:  # noqa: BLE001
+        return []
+    return rects
+
+
+def _figure_box(page: Any, cap: dict[str, Any], img_rects: list[Any]) -> Any | None:
+    """caption 上方 band 内「位图 ∪ 矢量绘图」联合包围盒（含 6pt 内边距）。"""
+    import pymupdf  # 局部导入（extract_figures 已保证可用）
+
+    page_rect = page.rect
+    band_y0 = cap["y0"] - _BAND_ABOVE_PT
+    band_y1 = cap["y0"] - 1.0
+    bx0 = cap["x0"] - _BAND_PAD_X_PT
+    bx1 = cap["x1"] + _BAND_PAD_X_PT
+
+    def _in_band(r: Any) -> bool:
+        return band_y0 <= float(r.y1) <= band_y1 and not (float(r.x1) < bx0 or float(r.x0) > bx1)
+
+    union = None
+
+    def _merge(r: Any) -> None:
+        nonlocal union
+        r = r & page_rect
+        if r.is_empty:
+            return
+        union = r if union is None else (union | r)
+
+    for r in img_rects:
+        if _in_band(r):
+            _merge(r)
+    try:
+        drawings = page.get_drawings()
+    except Exception:  # noqa: BLE001
+        drawings = []
+    for d in drawings:
+        r = d.get("rect")
+        if r is None or r.is_empty:
+            continue
+        # 细长规则线（页眉横线/表格线）不进联合，避免整页宽条
+        if float(r.height) < 1.5 or (float(r.width) < 1.5):
+            continue
+        if _in_band(r):
+            _merge(r)
+    if union is None:
+        return None
+    box = pymupdf.Rect(union.x0 - 6, union.y0 - 6, union.x1 + 6, union.y1 + 6) & page_rect
+    return None if box.is_empty else box
@@ -0,0 +1,917 @@
+"""services/ppt_outline.py —— P5 科研汇报大纲生成（map-reduce + 证据程序化校验）。
+
+管线（全 LLM 只负责引用与措辞，结构/页数/证据状态由代码裁决）：
+  纯文本 → 段落索引（para_id 形如 S4-P1，figure 引用 S4-P1-Fig2）
+  → 图表清单扫描（ppt_figure_index 正则扫 Figure/图/Table/表，非 LLM）
+  → map：分块（≤5 块）抽 claims/figures（quote 逐字 + para_id 标注，LLM；
+     figures 先过真实清单，不在清单的丢弃）
+  → reduce：按 page_plan 配额生成页大纲（1 或 2 次调用；>14 页分两片，
+    第二片带上一片页标题维持连贯；deepseek-chat 输出上限 8K，必须分片；
+    真实图表清单注入 prompt，suggested_figures 只选不编）
+  → 后校验（纯函数、可单测）：
+      ① 页数：PAGE_TARGETS 决策 2（10→8-10/15→11-14/20→15-18/30→22-26），
+         超上限从尾部可删页裁掉（section/reference 先删）；低于下限不凑页 + warning
+      ② bullets（补充 3）：内容页 <2 条 → 一次按页扩充重试；>8 条 → 拆成两页
+      ③ evidence：quote 归一化后必须是某段落的子串 → 反查真实 para_id
+         （repair_evidence_para_ids，修复 LLM 编造段落ID）→ verified；
+         找不到段落 → unverified；result/conclusion 页未核实占比 >50% → warning
+      ④ suggested_figures：label 必须在真实图表清单内（否则丢弃而非标
+         unverified）；para_id 以清单扫描出的真实位置为准 → verified
+
+错误：OutlineError(code=VALIDATION|LLM_ERROR|LLM_INVALID) → 路由映射信封。
+LLM 调用次数：map ≤5 + reduce 1~2 + expand ≤1 ≈ 4~8 次/篇。
+"""
+from __future__ import annotations
+
+import asyncio
+import json
+import math
+import re
+import unicodedata
+from typing import Any
+
+from ..config import get_settings
+from . import llm
+from .llm import LLMError
+from .ppt_figure_index import canon_label, figure_map, scan_figure_index
+
+# ---------- 枚举与决策常量 ----------
+
+SCENARIOS = (
+    "group_meeting",
+    "proposal",
+    "conclusion_report",
+    "defense",
+    "conference_talk",
+)
+SCENARIO_LABELS = {
+    "group_meeting": "组会",
+    "proposal": "开题",
+    "conclusion_report": "结题",
+    "defense": "答辩",
+    "conference_talk": "学术会议",
+}
+# P5 增强 2：风格 3 → 8 → 14（与 data/ppt_styles/*.json 一一对应）。
+# 其中 domestic/international/systems-talk/theory-beamer/jp-gothic/editorial
+# 移植自开源 paper-skills styles/tokens.json（MIT），色/字号映射进自有 schema。
+STYLE_IDS = (
+    "academic-minimal", "botanic-forest", "classic-defense",
+    "academic-blue", "nature-green", "tech-dark", "monochrome", "warm-earth",
+    "domestic", "international", "systems-talk", "theory-beamer",
+    "jp-gothic", "editorial",
+)
+
+# section = 章节分隔页（P5 增强 3：大标题居中 + 色块背景，由代码定骨架、LLM 只起标题）
+PAGE_TYPES = (
+    "title", "outline", "section", "background", "method", "result", "conclusion", "reference",
+)
+CONTENT_TYPES = ("background", "method", "result", "conclusion")
+
+# 决策 2：时长 → [下限, 上限]（含封面/目录，defense 含参考文献页）
+PAGE_TARGETS: dict[int, tuple[int, int]] = {
+    10: (8, 10),
+    15: (11, 14),
+    20: (15, 18),
+    30: (22, 26),
+}
+MINUTES_CHOICES = tuple(sorted(PAGE_TARGETS))
+
+# 场景骨架：内容页权重（reference 只有答辩要）；代码算配额，LLM 只填内容
+_SKELETONS: dict[str, dict[str, Any]] = {
+    "group_meeting":     {"weights": {"background": 0.25, "method": 0.40, "result": 0.35}, "reference": False},
+    "proposal":          {"weights": {"background": 0.40, "method": 0.45, "result": 0.15}, "reference": False},
+    "conclusion_report": {"weights": {"background": 0.20, "method": 0.30, "result": 0.50}, "reference": False},
+    "defense":           {"weights": {"background": 0.25, "method": 0.35, "result": 0.40}, "reference": True},
+    "conference_talk":   {"weights": {"background": 0.25, "method": 0.35, "result": 0.40}, "reference": False},
+}
+
+# 索引切块（正文 ≤150K 字符 → 块数 ≤5，控制 map 调用次数）
+_MAX_SECTIONS = 5
+_PARAS_PER_SECTION = 40
+_PARA_CHAR_CAP = 1000     # 单段送 map 的截断（pymupdf 块通常 <1000 字符）
+_SECTION_CHAR_CAP = 30000 # 单块送 map 的总预算
+_MAX_CLAIMS_TOTAL = 50
+_MAX_FIGURES_TOTAL = 15
+_REDUCE_PAGE_SLICE = 14   # 单次 reduce 页数上限（>14 页分两片，守住 8K 输出）
+
+_MAP_TIMEOUT = 75.0
+_REDUCE_TIMEOUT = 200.0
+_EXPAND_TIMEOUT = 75.0
+_MAP_CONCURRENCY = 2      # BFF 读超时 360s 硬顶：map 并发压总时长
+
+
+class OutlineError(Exception):
+    """大纲生成失败（VALIDATION | LLM_ERROR | LLM_INVALID）。"""
+
+    def __init__(self, code: str, message: str) -> None:
+        super().__init__(message)
+        self.code = code
+        self.message = message
+
+
+# ---------- 决策 2：页数配额（纯函数） ----------
+
+def page_plan(scenario: str, minutes: int) -> dict[str, tuple[int, int]]:
+    """时长目标页数 + 场景骨架 → 每 type 配额 (min, max)。
+
+    固定页：title=1、outline=1、conclusion=1（defense +reference=1）；
+    其余按场景权重最大余数法分配（每内容页保底 1）。LLM 只能在配额内填，
+    总页数另外夹在 PAGE_TARGETS[minutes] 区间内。
+    """
+    if scenario not in _SKELETONS:
+        raise ValueError(f"未知场景: {scenario}")
+    if minutes not in PAGE_TARGETS:
+        raise ValueError(f"不支持的时长: {minutes}（可选 {list(MINUTES_CHOICES)}）")
+    lo, hi = PAGE_TARGETS[minutes]
+    target = (lo + hi) // 2
+    weights = _SKELETONS[scenario]["weights"]
+    n_ref = 1 if _SKELETONS[scenario]["reference"] else 0
+    # 章节分隔页：≥15 分钟（target≥11）每个内容组一张；10 分钟小 deck 不放分隔页
+    n_sec = len(weights) if target >= 11 else 0
+    rest = max(target - (3 + n_ref + n_sec), len(weights))  # 3 = title+outline+conclusion
+
+    raw = {t: w * rest for t, w in weights.items()}
+    alloc = {t: int(v) for t, v in raw.items()}
+    for t in sorted(raw, key=lambda k: raw[k] - alloc[k], reverse=True)[: rest - sum(alloc.values())]:
+        alloc[t] += 1
+    for t in alloc:
+        alloc[t] = max(1, alloc[t])  # 内容页保底
+
+    plan: dict[str, tuple[int, int]] = {
+        "title": (1, 1), "outline": (1, 1), "conclusion": (1, 1),
+    }
+    if n_sec:
+        plan["section"] = (n_sec, n_sec)
+    if n_ref:
+        plan["reference"] = (1, 1)
+    for t, a in alloc.items():
+        plan[t] = (a, a + 1)
+    return plan
+
+
+# ---------- 段落索引（para_id：S{块}-P{段}） ----------
+
+def build_index(text: str) -> tuple[list[dict[str, Any]], dict[str, str]]:
+    """纯文本 → (blocks, index)。blocks 含段落ID标注文本（map 输入），index 为
+    para_id → 原文（evidence 校验用）。块按固定段数均分（不做标题猜测，
+    确定性可测；S 编号 = 块序号，P 编号 = 块内段序）。"""
+    paras = [ln.strip() for ln in text.splitlines() if ln.strip()]
+    paras = [p[:_PARA_CHAR_CAP] for p in paras]
+    if not paras:
+        return [], {}
+    n_sections = max(1, min(_MAX_SECTIONS, math.ceil(len(paras) / _PARAS_PER_SECTION)))
+    size = math.ceil(len(paras) / n_sections)
+    blocks: list[dict[str, Any]] = []
+    index: dict[str, str] = {}
+    for si in range(0, len(paras), size):
+        sec_no = si // size + 1
+        lines = paras[si : si + size]
+        paras_out = []
+        for pi, p in enumerate(lines, 1):
+            pid = f"S{sec_no}-P{pi}"
+            paras_out.append({"para_id": pid, "text": p})
+            index[pid] = p
+        blocks.append({
+            "section_id": f"S{sec_no}",
+            "paras": paras_out,
+            "text": "\n".join(f"[{v['para_id']}] {v['text']}" for v in paras_out),
+        })
+    return blocks, index
+
+
+# ---------- map：分块抽 claims / figures ----------
+
+_MAP_SYSTEM = """你是植物学论文精读助手。输入是一个论文文本块，每段以 [段落ID] 标注。
+只输出单个 JSON 对象：
+{"claims": [{"claim": "一句话事实陈述", "para_id": "S1-P2", "quote": "支撑该事实的原文逐字引用"}],
+ "figures": [{"label": "Fig 2", "para_id": "S1-P5-Fig2"}]}
+硬性要求：
+- claim 必须能被同条 quote 直接支撑；quote 必须逐字来自对应段落（≤60字、单句、不得跨段拼接、不得改写）；
+- para_id 必须照抄输入标注；figure 的 para_id = 其 caption 所在段落ID + "-FigN"（N 为图序号）；
+- 每块最多 8 条 claims、4 个 figures；没有实质内容就返回空数组；严禁编造引用、数据、图号；
+- 不要输出 JSON 以外的任何文字。"""
+
+
+async def _map_block(block: dict[str, Any]) -> tuple[list[dict], list[dict]]:
+    payload = await llm.complete_json(
+        _MAP_SYSTEM, _map_block_user(block), temperature=0.2,
+        max_tokens=4000, timeout=_MAP_TIMEOUT,
+    )
+    claims = [c for c in (payload.get("claims") or []) if isinstance(c, dict)][:8]
+    figures = [f for f in (payload.get("figures") or []) if isinstance(f, dict)][:4]
+    return claims, figures
+
+
+def _map_block_user(block: dict[str, Any]) -> str:
+    body = block["text"]
+    if len(body) > _SECTION_CHAR_CAP:
+        body = body[:_SECTION_CHAR_CAP]
+    return f"论文文本块 {block['section_id']}：\n{body}"
+
+
+# ---------- reduce：页大纲（配额内填内容） ----------
+
+_REDUCE_SYSTEM = """你是学术汇报策划。根据给出的论文摘要卡片（claims/figures 已带逐字引用）、
+论文真实图表清单与页数配额，生成 PPT 大纲。只输出单个 JSON 对象：
+{"pages": [{"type": "...", "title": "...", "subtitle": "...", "bullets": ["..."],
+            "evidence": [{"quote": "..."}],
+            "speaker_notes": "...", "suggested_figures": [{"label": "Fig 2", "para_id": "S1-P12"}],
+            "highlight": {"value": "+0.82 cm", "label": "体长增长"},
+            "table": {"headers": ["处理", "株高(cm)"], "rows": [["对照", "10.2"]]}}]}
+硬性要求：
+- type 只能取：title, outline, section, background, method, result, conclusion, reference；
+- 结构顺序固定：title → outline →（section → 对应内容组）×3 → conclusion（→ reference，若配额里有）；
+  type=section 表示章节分隔页：放在 background、method、result 各组第一张之前，
+  title 只用组名（如「研究背景」，2~6 字，末尾不得带「是/的/了」等虚词，不要写成句子），
+  subtitle 必给（分隔页副标题，渲染在主标题下方）：照抄该章第一张内容页的 title
+  （如「黄瓜遗传改良亟需高精度泛基因组」，≤20 字、一句话、与该页标题逐字一致），
+  bullets 用空数组（副标题走 subtitle 字段，不要再塞进 bullets），
+  evidence/speaker_notes 可省略；
+- 每个 type 的页数必须落在给定配额 [min,max] 内，不得自创结构；
+- 标题即结论：内容页 title 写成一句话结论或核心问题（≤20 字，看标题就懂这页讲什么），
+  「背景/方法/结果」这类栏目词只允许出现在 section 分隔页；
+- 叙事：方法页讲机制与做法，结果页说明「证明了什么」而不是罗列做了什么；
+- bullets 每页 3-5 条（title 页放作者/单位/来源，outline 页列各部分标题，
+  reference 页列 5-8 条文献）；单条 ≤40 字、名词短语化、不写整句；
+  关键词强调用 **双星号** 包裹（如 **盐胁迫**）；子要点写成独立数组元素并以「- 」开头
+  （如 "- 子要点"，其 evidence 填 null）；
+- 版面标记（生成端只按此写法，渲染端自动识别，勿在同一页混用多种）：
+  · 并列短要点：方法/结果/结论页若内容就是 2-4 个并列短语，每条 ≤16 字、不带任何标记，
+    直接写成这样的短句条目（会渲染为卡片网格）；
+  · 关键词行：背景/方法概述页 ≥3 条统一用「关键词：说明」句式（如「靶基因：SOS1」）；
+  · 流程：步骤页 ≥3 条统一以「→ 」开头（如「→ 提取 RNA」），会渲染为流程卡；
+  · 强调框：全篇最多 1-2 条最核心结论，以「> 」开头单独成条放在该页最后，
+    其 evidence 填 null（会渲染为底部强调引用框）；
+  · 表格：结果对比页优先用 table 字段（headers ≤5 列、rows ≤4 行、单元格 ≤18 字）
+    代替 bullets；该页 bullets 最多 2 条导读，表格里的数据引用写进 speaker_notes；
+- evidence 与 bullets 等长对齐（一一对齐，没有来源的位置填 null）；
+  每条 evidence 只需要 "quote" 字段：从摘要卡片里逐字照抄 quote 原文；
+  **不需要写 para_id，后端会按 quote 自动反查真实段落ID**（你写错会干扰校验）；
+  卡片里找不到对应 quote 的一律填 null，严禁改写或编造；
+- speaker_notes 是讲稿口吻（80-160 字），可自然转述 quote 但不得出现段落ID；
+- suggested_figures 只能从用户消息给出的「论文真实图表清单」里照抄 label 与 para_id，
+  清单为空则一律给空数组；你只决定"哪个图放哪页"，绝不发明图号；
+- result 组最后 1-2 页若呈现对比数据，给该页加 "highlight": {"value": "≤12字符的数字",
+  "label": "≤16字符的说明"}（如 {"value": "+0.82 cm", "label": "体长增长"}）；
+  没有可突出的数字对比就省略 highlight 字段；
+- 严禁编造引用、数据、图表编号。不要输出 JSON 以外的任何文字。"""
+
+
+def _plan_table(plan: dict[str, tuple[int, int]], types: tuple[str, ...] | list[str]) -> str:
+    return "\n".join(f"- {t}: {plan[t][0]}~{plan[t][1]} 页" for t in types)
+
+
+def _narrow_figure_index(
+    figure_index: list[dict], available: list[str] | None,
+) -> list[dict]:
+    """v3 修复2：把注入 prompt 的图表清单收窄到「已提取原图」的 label。
+
+    available 为空/None → 不收窄（text 模式保持全清单占位框）；
+    交集为空（提取 label 与扫描不一致等意外）→ 回退全清单，绝不把图清空。
+    匹配按 canon_label（kind+编号）进行，且把 entry.label 统一成磁盘文件名形态
+    （"Fig. 6b" → "Fig 6"，子图后缀无对应文件），同编号去重只留首个。
+    """
+    if not available or not figure_index:
+        return figure_index
+    by_key: dict[tuple[str, int], str] = {}
+    for lbl in available:
+        key = canon_label(lbl)
+        if key and key not in by_key:
+            by_key[key] = str(lbl).strip()
+    if not by_key:
+        return figure_index
+    narrowed: list[dict] = []
+    seen: set[tuple[str, int]] = set()
+    for f in figure_index:
+        key = canon_label(f.get("label"))
+        if key in by_key and key not in seen:
+            entry = dict(f)
+            entry["label"] = by_key[key]   # LLM 所见 = 磁盘可嵌形态
+            narrowed.append(entry)
+            seen.add(key)
+    return narrowed or figure_index
+
+
+def _claims_block(claims: list[dict], figures: list[dict]) -> str:
+    # para_id 不下发给 reduce/expand（LLM 会照抄编造；quote 由后端反查真实段落ID）
+    compact = [
+        {"claim": str(c.get("claim") or "")[:200],
+         "quote": str(c.get("quote") or "")[:80]}
+        for c in claims
+    ]
+    figs = [
+        {"label": str(f.get("label") or "")[:40], "para_id": str(f.get("para_id") or "")}
+        for f in figures
+    ]
+    return json.dumps({"claims": compact, "figures": figs}, ensure_ascii=False)
+
+
+def _reduce_user(
+    scenario: str, minutes: int, plan: dict[str, tuple[int, int]],
+    claims: list[dict], figures: list[dict],
+    types: list[str], *, prior_titles: list[str] | None = None, total_hint: int | None = None,
+    figure_index: list[dict] | None = None,
+) -> str:
+    parts = [
+        f"场景：{SCENARIO_LABELS[scenario]}（{scenario}），汇报时长 {minutes} 分钟，"
+        f"目标总页数 {PAGE_TARGETS[minutes][0]}~{PAGE_TARGETS[minutes][1]} 页。",
+        f"本次生成的页类型与配额（按顺序）：\n{_plan_table(plan, types)}",
+    ]
+    if total_hint is not None:
+        parts.append(f"本次需生成 {total_hint} 页。")
+    if prior_titles:
+        parts.append("前半部分已生成的页标题（保持连贯，不要重复）：" + "；".join(prior_titles))
+    parts.append(f"摘要卡片：\n{_claims_block(claims, figures)}")
+    # P5 增强 1：论文真实图表清单注入（LLM 只选不编）
+    if figure_index:
+        compact = [
+            {"label": f.get("label"), "para_id": f.get("para_id"),
+             "caption": str(f.get("caption") or "")[:80]}
+            for f in figure_index
+        ]
+        parts.append(
+            "论文中真实存在的图表清单（suggested_figures 只能从这里选，label 与 para_id 照抄）：\n"
+            + json.dumps(compact, ensure_ascii=False)
+        )
+    else:
+        parts.append("论文中未扫描到任何图表编号：suggested_figures 一律给空数组。")
+    return "\n\n".join(parts)
+
+
+# ---------- 结构裁决（纯函数） ----------
+
+def coerce_outline(payload: Any) -> list[dict]:
+    """LLM 返回 → 规范化 pages（枚举/字段/bullets-evidence 对齐/slide_number）。"""
+    pages_raw = payload.get("pages") if isinstance(payload, dict) else None
+    if not isinstance(pages_raw, list):
+        raise OutlineError("LLM_INVALID", "LLM 输出缺少 pages 列表")
+    pages: list[dict] = []
+    for raw in pages_raw:
+        if not isinstance(raw, dict):
+            continue
+        ptype = str(raw.get("type") or "")
+        if ptype not in PAGE_TYPES:
+            continue
+        title = str(raw.get("title") or "").strip() or ptype
+        if ptype == "section":
+            # v3 修复3：LLM 偶发把「是」等虚词缀进组名（如「研究方法是」）
+            title = re.sub(r"[是的了]$", "", title) or title
+        bullets = [
+            str(b).strip() for b in (raw.get("bullets") or [])
+            if isinstance(b, (str, int, float)) and str(b).strip()
+        ]
+        ev_raw = raw.get("evidence")
+        evidence: list[dict | None] = []
+        for i in range(len(bullets)):
+            item = ev_raw[i] if isinstance(ev_raw, list) and i < len(ev_raw) else None
+            if isinstance(item, dict) and str(item.get("quote") or "").strip():
+                evidence.append({
+                    "para_id": str(item.get("para_id") or ""),
+                    "quote": str(item.get("quote") or "").strip(),
+                    "status": "unverified",
+                })
+            else:
+                evidence.append(None)
+        figs_raw = raw.get("suggested_figures")
+        figs = []
+        if isinstance(figs_raw, list):
+            for f in figs_raw[:6]:
+                if isinstance(f, dict) and str(f.get("para_id") or "").strip():
+                    figs.append({
+                        "label": str(f.get("label") or "").strip(),
+                        "para_id": str(f.get("para_id") or "").strip(),
+                        "status": "unverified",
+                    })
+        # P5 增强 3：大数字突出页标记（result 组对比数据页，可选）
+        hl_raw = raw.get("highlight")
+        highlight = None
+        if isinstance(hl_raw, dict) and str(hl_raw.get("value") or "").strip():
+            highlight = {
+                "value": str(hl_raw.get("value") or "").strip()[:24],
+                "label": str(hl_raw.get("label") or "").strip()[:32],
+            }
+        # P5 二次开发 2.2：对比表格（可选；rows 超限截断，坏结构直接丢弃）
+        table = None
+        tbl_raw = raw.get("table")
+        if isinstance(tbl_raw, dict) and isinstance(tbl_raw.get("rows"), list):
+            headers = [
+                str(h).strip()[:24] for h in (tbl_raw.get("headers") or [])
+                if isinstance(h, (str, int, float)) and str(h).strip()
+            ][:8]
+            rows: list[list[str]] = []
+            for r in tbl_raw["rows"][:12]:
+                if not isinstance(r, (list, tuple)):
+                    continue
+                cells = [
+                    str(c).strip()[:60] for c in r
+                    if isinstance(c, (str, int, float))
+                ][:8]
+                if any(cells):
+                    rows.append(cells)
+            if rows:
+                table = {"headers": headers, "rows": rows}
+        page = {
+            "slide_number": 0,
+            "type": ptype,
+            "title": title,
+            "bullets": bullets,
+            "evidence": evidence,
+            "speaker_notes": str(raw.get("speaker_notes") or "").strip(),
+            "suggested_figures": figs,
+        }
+        if ptype == "section":
+            # P5 改进 2：分隔页副标题独立字段（LLM 给 subtitle；旧大纲仍在 bullets[0]，
+            # 编辑器改 bullets[0] 也算数 → bullets 优先，避免编辑被旧 subtitle 覆盖）
+            page["subtitle"] = (bullets[0] if bullets else "") or str(
+                raw.get("subtitle") or ""
+            ).strip()
+        if highlight:
+            page["highlight"] = highlight
+        if table:
+            page["table"] = table
+        pages.append(page)
+    if not pages:
+        raise OutlineError("LLM_INVALID", "LLM 输出中没有可用页（type 全部非法）")
+    return pages
+
+
+# 超页裁剪优先级：section/reference 可整页删（floor 0），内容页保底 1 页；
+# title/outline/conclusion 永不删
+_DROP_PRIORITY = ("section", "reference", "background", "method", "result")
+_FLOOR_ZERO = ("section", "reference")
+
+
+def trim_to_max(
+    pages: list[dict], hi: int, warnings: list[str],
+    floors: dict[str, int] | None = None,
+) -> list[dict]:
+    """总页数超上限：按 _DROP_PRIORITY 优先级删该类型的最后一页；不凑下限。
+
+    floors（v3 修复3）：按配额给类型设保底（如 section=(3,3) → 传 {"section": 3}）。
+    有保底时先删「超配额的内容页/文献页」，section 不再被一刀清空；
+    全部 floor 都满足却仍超页 → 才回退到 section/reference 整页删（原语义兜底）。
+    """
+    floors = floors or {}
+    floor_of = lambda t: floors.get(t, 0 if t in _FLOOR_ZERO else 1)  # noqa: E731
+    while len(pages) > hi:
+        counts: dict[str, int] = {}
+        for p in pages:
+            counts[p["type"]] = counts.get(p["type"], 0) + 1
+        drop_type = next(
+            (t for t in _DROP_PRIORITY if counts.get(t, 0) > floor_of(t)),
+            None,
+        )
+        if drop_type is None:
+            # 配额 floor 全满足仍超页 → 兜底砍可整删类型（section/reference 优先）
+            drop_type = next(
+                (t for t in _DROP_PRIORITY
+                 if t in _FLOOR_ZERO and counts.get(t, 0) > 0),
+                None,
+            )
+        if drop_type is None:
+            break
+        idx = max(i for i, p in enumerate(pages) if p["type"] == drop_type)
+        removed = pages.pop(idx)
+        warnings.append(
+            f"页数超过 {hi} 页上限，已移除 {removed['type']} 页「{removed['title']}」"
+        )
+    return pages
+
+
+def split_oversized(pages: list[dict], warnings: list[str]) -> list[dict]:
+    """内容页 bullets >8：拆成两页（续页 title+"（续）"），递归直到全 ≤8。"""
+    out: list[dict] = []
+    for page in pages:
+        todo = [page]
+        while todo:
+            cur = todo.pop(0)
+            bullets = cur.get("bullets") or []
+            if cur["type"] in CONTENT_TYPES and len(bullets) > 8:
+                k = math.ceil(len(bullets) / 2)
+                ev_full = list(cur.get("evidence") or [])
+                if len(ev_full) < len(bullets):
+                    ev_full += [None] * (len(bullets) - len(ev_full))
+                nxt = json.loads(json.dumps(cur))  # 深拷贝
+                nxt["bullets"] = bullets[k:]
+                nxt["evidence"] = ev_full[k:]
+                nxt["title"] = f"{cur['title']}（续）"
+                nxt["suggested_figures"] = []   # 图占位只放首页
+                nxt["speaker_notes"] = ""
+                cur["bullets"] = bullets[:k]
+                cur["evidence"] = ev_full[:k]
+                warnings.append(f"「{cur['title'].removesuffix('（续）')}」要点超过 8 条，已拆成两页")
+                todo.insert(0, nxt)
+                todo.insert(0, cur)
+                continue
+            out.append(cur)
+    return out
+
+
+def renumber(pages: list[dict]) -> list[dict]:
+    for i, p in enumerate(pages, 1):
+        p["slide_number"] = i
+    return pages
+
+
+# ---------- 证据程序化校验（纯函数） ----------
+
+_FIG_RE = re.compile(r"^(S\d+-P\d+)(?:-Fig(\d+))?$", re.IGNORECASE)
+
+
+def _norm(s: str) -> str:
+    """归一化：NFKC + 小写 + 去掉全部空白与标点（只留字母数字/CJK）。"""
+    s = unicodedata.normalize("NFKC", s).lower()
+    return re.sub(r"[\W_]+", "", s, flags=re.UNICODE)
+
+
+def _concat_segments(norm_index: dict[str, str]) -> tuple[str, dict[str, tuple[int, int]]]:
+    """按 document 顺序把各段归一化文本拼成一条，并给出每段在拼接串中的 [start, end)。
+
+    LLM 照抄的 quote 常横跨两个段落边界 → 任何单段都不含它，但整篇文档含。
+    repair/validate 据此做跨段宽松反查（v3 修复4）。
+    """
+    offsets: dict[str, tuple[int, int]] = {}
+    chunks: list[str] = []
+    pos = 0
+    for pid, nt in norm_index.items():
+        offsets[pid] = (pos, pos + len(nt))
+        chunks.append(nt)
+        pos += len(nt)
+    return "".join(chunks), offsets
+
+
+def _locate_span(
+    nq: str, concat: str, offsets: dict[str, tuple[int, int]],
+) -> str | None:
+    """跨段定位：nq 起点落在哪个段（取起点所在段为归属）。≥10 归一化字符才启用。"""
+    if len(nq) < 10:
+        return None
+    i = concat.find(nq)
+    if i < 0:
+        return None
+    for pid, (start, end) in offsets.items():
+        if start <= i < end:
+            return pid
+    return None
+
+
+def repair_evidence_para_ids(pages: list[dict], index: dict[str, str]) -> int:
+    """按 quote 归一化子串反查真实 para_id（P5 修复：LLM 常编 para_id，quote 往往逐字正确）。
+
+    LLM reduce/expand 只需给 quote（prompt 已声明后端反查）；这里按 document
+    顺序找第一个包含该 quote 的段落填回 para_id，后续 validate_evidence 据此标
+    verified。找不到 → 不动，留给 validate_evidence 标 unverified（真幻觉）。
+    返回修复条数。
+    """
+    norm_index = {pid: _norm(t) for pid, t in index.items()}
+    concat, offsets = _concat_segments(norm_index)
+    repaired = 0
+    for page in pages:
+        for ev in page.get("evidence") or []:
+            if not isinstance(ev, dict):
+                continue
+            quote = str(ev.get("quote") or "")
+            nq = _norm(quote)
+            if not nq:
+                continue
+            pid = str(ev.get("para_id") or "")
+            if pid and nq in norm_index.get(pid, ""):
+                continue  # 标注已正确，不动
+            hit = next((p for p, nt in norm_index.items() if nq in nt), None)
+            if not hit:
+                # 跨段 quote：任何单段都不含，但在整篇拼接串里 → 归属起点所在段
+                hit = _locate_span(nq, concat, offsets)
+            if hit:
+                ev["para_id"] = hit
+                repaired += 1
+    return repaired
+
+
+def validate_evidence(
+    pages: list[dict], index: dict[str, str],
+    figure_index: list[dict] | None = None,
+) -> list[str]:
+    """逐条校验 evidence / suggested_figures → status + warnings。
+
+    figure_index（论文真实图表清单）非空时，图引用按清单裁决：
+      - label 不在清单 → 直接丢弃（不是标 unverified，结果里不会出现论文没有的图）；
+      - label 在清单 → 以清单里的真实 para_id 为准，status=verified。
+    为 None 时保持旧路径（格式 + 原文 fig{N} 子串校验），兼容无清单的调用方。
+    """
+    warnings: list[str] = []
+    norm_index = {pid: _norm(t) for pid, t in index.items()}
+    doc_all = "".join(norm_index.values())
+    concat, offsets = _concat_segments(norm_index)
+    fmap = figure_map(figure_index) if figure_index is not None else None
+    for page in pages:
+        sn = page["slide_number"]
+        evs = page.get("evidence") or []
+        ver = unver = 0
+        for ev in evs:
+            if ev is None:
+                continue
+            quote = str(ev.get("quote") or "")
+            pid = str(ev.get("para_id") or "")
+            nq, np_ = _norm(quote), norm_index.get(pid)
+            if quote and np_ is not None and nq and nq in np_:
+                ev["status"] = "verified"
+                ver += 1
+            elif quote and nq and pid and _locate_span(nq, concat, offsets) == pid:
+                # 跨段 quote：repair 已把 para_id 指到起点段 → 等同逐字命中
+                ev["status"] = "verified"
+                ver += 1
+            else:
+                ev["status"] = "unverified"
+                unver += 1
+                if nq and nq in doc_all:
+                    warnings.append(
+                        f"第{sn}页：引用真实存在，但段落标注 {pid or '（空）'} 不符（已标 unverified）"
+                    )
+        total = ver + unver
+        if page["type"] in ("result", "conclusion") and total and unver / total > 0.5:
+            warnings.append(
+                f"第{sn}页（{page['type']}）证据未核实占比超过 50%（{unver}/{total}），请人工复核"
+            )
+        kept: list[dict] = []
+        for fig in page.get("suggested_figures") or []:
+            if fmap is not None:
+                key = canon_label(fig.get("label"))
+                entry = fmap.get(key) if key else None
+                if entry is None:
+                    warnings.append(
+                        f"第{sn}页：图引用 {fig.get('label') or '（空）'} 不在论文真实图表清单，已丢弃"
+                    )
+                    continue
+                fig["para_id"] = entry["para_id"]   # 以扫描出的真实位置为准
+                fig["status"] = "verified"
+                kept.append(fig)
+                continue
+            m = _FIG_RE.match(str(fig.get("para_id") or ""))
+            if not m:
+                fig["status"] = "unverified"
+                warnings.append(f"第{sn}页：图引用 {fig.get('para_id')} 格式不合法")
+                kept.append(fig)
+                continue
+            base, num = m.group(1).upper(), m.group(2)
+            base_norm = norm_index.get(base)
+            fig_ok = base_norm is not None and (
+                num is None or f"fig{num}" in base_norm or f"figure{num}" in base_norm
+            )
+            fig["status"] = "verified" if fig_ok else "unverified"
+            if not fig_ok:
+                warnings.append(
+                    f"第{sn}页：图引用 {fig['para_id']} 未在原文对应段落找到（已标 unverified）"
+                )
+            kept.append(fig)
+        page["suggested_figures"] = kept
+    return warnings
+
+
+# ---------- 扩充重试（内容页 bullets <2 → 一次按页补齐） ----------
+
+_EXPAND_SYSTEM = """你是学术汇报编辑。某几页幻灯片的要点不足（少于 2 条）。
+基于给出的页信息与摘要卡片（claims 已带逐字引用），为每页补齐到 3-6 条要点。
+只输出单个 JSON 对象：
+{"pages": [{"index": 0, "bullets": ["..."], "evidence": [{"quote": "..."}]}]}
+硬性要求：
+- index 是给定页在列表中的下标；bullets 保留原有要点（可精炼改写）并补充同主题新要点；
+- evidence 与 bullets 等长对齐；每条 evidence 只需要 "quote" 字段，从卡片里逐字照抄，
+  **不需要写 para_id，后端会按 quote 自动反查**；没有依据填 null；
+- 单条 ≤60 字；严禁编造。不要输出 JSON 以外的任何文字。"""
+
+
+async def _expand_thin(
+    pages: list[dict], thin_idx: list[int],
+    claims: list[dict], figures: list[dict], warnings: list[str],
+) -> None:
+    """一次 LLM 调用补齐所有薄弱页；失败仅 warning，不阻断。"""
+    page_info = [
+        {
+            "index": i,
+            "type": pages[i]["type"],
+            "title": pages[i]["title"],
+            "bullets": pages[i]["bullets"],
+            "speaker_notes": pages[i]["speaker_notes"],
+        }
+        for i in thin_idx
+    ]
+    user = (
+        f"待补齐页（下标即列表位置）：\n{json.dumps(page_info, ensure_ascii=False)}\n\n"
+        f"摘要卡片：\n{_claims_block(claims, figures)}"
+    )
+    try:
+        payload = await llm.complete_json(
+            _EXPAND_SYSTEM, user, temperature=0.3,
+            max_tokens=4000, timeout=_EXPAND_TIMEOUT,
+        )
+    except LLMError as exc:
+        warnings.append(f"薄弱页扩充重试失败（保留原状）：{exc}")
+        return
+    for item in payload.get("pages") or []:
+        if not isinstance(item, dict):
+            continue
+        idx = item.get("index")
+        if not isinstance(idx, int) or not (0 <= idx < len(pages)) or idx not in thin_idx:
+            continue
+        page = pages[idx]
+        bullets = [
+            str(b).strip() for b in (item.get("bullets") or [])
+            if isinstance(b, (str, int, float)) and str(b).strip()
+        ][:8]
+        if len(bullets) < 2:
+            continue
+        ev_raw = item.get("evidence")
+        evidence: list[dict | None] = []
+        for i in range(len(bullets)):
+            e = ev_raw[i] if isinstance(ev_raw, list) and i < len(ev_raw) else None
+            if isinstance(e, dict) and str(e.get("quote") or "").strip():
+                evidence.append({
+                    "para_id": str(e.get("para_id") or ""),
+                    "quote": str(e.get("quote") or "").strip(),
+                    "status": "unverified",
+                })
+            else:
+                evidence.append(None)
+        page["bullets"] = bullets
+        page["evidence"] = evidence
+
+
+# ---------- 主编排 ----------
+
+async def generate_outline(
+    text: str, scenario: str, minutes: int, style_id: str,
+    *,
+    available_figures: list[str] | None = None,
+) -> tuple[list[dict], list[str], dict[str, Any]]:
+    """生成完整大纲。返回 (pages, warnings, meta)；失败抛 OutlineError。
+
+    available_figures（v3 修复2）：PDF 入口已提取到磁盘的原图 label 列表。
+    非空时只把「已提取」的图注入 reduce/expand（LLM 选了 build 就能 add_picture
+    嵌入，不再出虚线占位）；None/空 → 保持全清单（text 模式占位框不变）。
+    """
+    if scenario not in SCENARIOS:
+        raise OutlineError("VALIDATION", f"未知场景 scenario={scenario}")
+    if minutes not in PAGE_TARGETS:
+        raise OutlineError("VALIDATION", f"不支持的时长 {minutes} 分钟（可选 {list(MINUTES_CHOICES)}）")
+    if style_id not in STYLE_IDS:
+        raise OutlineError("VALIDATION", f"未知风格 style_id={style_id}")
+
+    text = (text or "").strip()
+    if len(text) < 300:
+        raise OutlineError("VALIDATION", "正文过短（<300 字），无法生成汇报大纲")
+    settings = get_settings()
+    if len(text) > settings.max_text_chars:
+        text = text[: settings.max_text_chars]
+
+    blocks, index = build_index(text)
+    if not blocks:
+        raise OutlineError("VALIDATION", "正文解析为空，无法生成汇报大纲")
+
+    # P5 增强 1：论文真实图表清单（正则扫描，非 LLM）——供 reduce 只选不编
+    figure_index = scan_figure_index(index)
+    # v3 修复2：有已提取原图 → 注入清单收窄到「磁盘上有图」的条目（交集空则回退全清单）
+    inject_index = _narrow_figure_index(figure_index, available_figures)
+    fmap_pick = figure_map(inject_index)
+
+    plan = page_plan(scenario, minutes)
+    lo, hi = PAGE_TARGETS[minutes]
+    warnings: list[str] = []
+    llm_calls = 0
+
+    # ---- map（并发 2，控总时长压在 BFF 360s 内） ----
+    claims: list[dict] = []
+    figures: list[dict] = []
+    sem = asyncio.Semaphore(_MAP_CONCURRENCY)
+
+    async def _map_one(block: dict[str, Any]) -> tuple[list[dict], list[dict]]:
+        async with sem:
+            return await _map_block(block)
+
+    try:
+        results = await asyncio.gather(*(_map_one(b) for b in blocks))
+    except LLMError as exc:
+        raise OutlineError("LLM_ERROR", f"章节摘要失败：{exc}") from exc
+    llm_calls += len(results)
+    for cs, fs in results:
+        for c in cs:
+            if len(claims) < _MAX_CLAIMS_TOTAL:
+                claims.append(c)
+        for f in fs:
+            if len(figures) < _MAX_FIGURES_TOTAL:
+                figures.append(f)
+    # P5 增强 1：map 抽到的图先过一遍注入清单（不在清单 → 丢弃；在 → 用真实 para_id）
+    if fmap_pick:
+        filtered: list[dict] = []
+        for f in figures:
+            key = canon_label(f.get("label"))
+            entry = fmap_pick.get(key) if key else None
+            if entry:
+                f = dict(f, para_id=entry["para_id"])
+                filtered.append(f)
+        if len(filtered) != len(figures):
+            warnings.append(
+                f"map 阶段 {len(figures) - len(filtered)} 个图引用不在论文真实图表清单，已丢弃"
+            )
+        figures = filtered
+    else:
+        if figures:
+            warnings.append(f"论文未扫描到图表编号，丢弃 map 阶段 {len(figures)} 个图引用")
+        figures = []
+    if not claims:
+        raise OutlineError("LLM_INVALID", "未能从正文抽取到任何可引用事实（claims 为空）")
+
+    # ---- reduce（>14 页分两片，第二片带上一片标题连贯） ----
+    full_types = [t for t in PAGE_TYPES if t in plan]
+    split_at = len(full_types)
+    acc = 0
+    for i, t in enumerate(full_types):
+        acc += plan[t][1]
+        if acc >= _REDUCE_PAGE_SLICE:
+            split_at = i + 1
+            break
+    first_types, second_types = full_types[:split_at], full_types[split_at:]
+
+    def _types_quota(ts: list[str]) -> int:
+        return sum(plan[t][0] for t in ts)
+
+    pages: list[dict] = []
+    try:
+        payload = await llm.complete_json(
+            _REDUCE_SYSTEM,
+            _reduce_user(scenario, minutes, plan, claims, figures, first_types,
+                         figure_index=inject_index),
+            temperature=0.4, max_tokens=8000, timeout=_REDUCE_TIMEOUT,
+        )
+        llm_calls += 1
+        pages = coerce_outline(payload)
+        if second_types:
+            prior_titles = [p["title"] for p in pages]
+            payload2 = await llm.complete_json(
+                _REDUCE_SYSTEM,
+                _reduce_user(
+                    scenario, minutes, plan, claims, figures, second_types,
+                    prior_titles=prior_titles, total_hint=_types_quota(second_types),
+                    figure_index=inject_index,
+                ),
+                temperature=0.4, max_tokens=8000, timeout=_REDUCE_TIMEOUT,
+            )
+            llm_calls += 1
+            pages.extend(coerce_outline(payload2))
+    except LLMError as exc:
+        msg = str(exc)
+        if "JSON" in msg or "json" in msg:
+            raise OutlineError("LLM_INVALID", f"LLM 大纲输出无法解析：{msg}") from exc
+        raise OutlineError("LLM_ERROR", f"大纲生成失败：{msg}") from exc
+
+    # ---- 后校验：拆页 → 夹页数 → 扩充 → 证据 → 重编号 ----
+    pages = split_oversized(pages, warnings)
+    renumber(pages)
+    # v3 修复3：按配额给全类型设保底（先删超配额的页；section/reference 不再被一刀清空）
+    floors = {t: mn for t, (mn, _mx) in plan.items() if mn}
+    pages = trim_to_max(pages, hi, warnings, floors=floors)
+    renumber(pages)
+    if len(pages) < lo:
+        warnings.append(
+            f"生成 {len(pages)} 页，低于 {minutes} 分钟目标下限 {lo} 页（不凑页，请人工补足）"
+        )
+    # 类型顺序归一：保持 LLM 输出顺序即可，但至少保证 title 在首位
+    pages.sort(key=lambda p: (0 if p["type"] == "title" else 1))
+    renumber(pages)
+
+    thin_idx = [
+        i for i, p in enumerate(pages)
+        if p["type"] in CONTENT_TYPES and len(p["bullets"]) < 2
+    ]
+    if thin_idx:
+        await _expand_thin(pages, thin_idx, claims, figures, warnings)
+        for i in thin_idx:
+            if len(pages[i]["bullets"]) < 2:
+                warnings.append(f"第{pages[i]['slide_number']}页要点不足 2 条（扩充后仍不足）")
+
+    # P5 修复：LLM 只给 quote（或编 para_id）→ 按 quote 反查真实段落ID，再进校验
+    repaired = repair_evidence_para_ids(pages, index)
+    if repaired:
+        warnings.append(f"{repaired} 条 evidence 的段落标注已按 quote 反查修正")
+    warnings.extend(validate_evidence(pages, index, inject_index))
+    renumber(pages)
+
+    unverified_total = sum(
+        1 for p in pages for e in (p.get("evidence") or []) if e and e.get("status") == "unverified"
+    )
+    meta = {
+        "scenario": scenario,
+        "minutes": minutes,
+        "style_id": style_id,
+        "paragraphs": len(index),
+        "sections": len(blocks),
+        "claims": len(claims),
+        "figures": len(figure_index),          # 真实图表清单规模（扫描所得）
+        "figures_used": sum(                   # 大纲里实际引用且通过校验的图数
+            1 for p in pages for f in (p.get("suggested_figures") or [])
+            if f.get("status") == "verified"
+        ),
+        "llm_calls": llm_calls,
+        "target_pages": [lo, hi],
+        "unverified_evidence": unverified_total,
+    }
+    return pages, warnings, meta
@@ -0,0 +1,230 @@
+"""services/ppt_preview.py —— pptx → PNG 页预览（PIL 自渲染，读回 python-pptx 对象）。
+
+移植自交付脚本 /tmp/opencode/render_pptx_preview.py（本项目自有验证脚本），
+用途：build 后给前端缩略图条 / 大图预览（浏览器内直接目检版式）。
+非 PowerPoint 截图：几何/颜色/字体色忠实还原，字形以 Noto CJK 近似（预览够用）。
+
+依赖仅 Pillow + python-pptx（均已在 tooling/requirements.lock），零新依赖。
+约定：输出 out_dir/slide_{i:02d}.png（i 从 1 起），1280×720 @96dpi；
+损坏/空 pptx → 返回 []（调用方降级，不抛）。
+"""
+from __future__ import annotations
+
+import logging
+import tempfile
+from io import BytesIO
+from pathlib import Path
+
+from PIL import Image, ImageDraw, ImageFont
+from pptx import Presentation
+from pptx.enum.shapes import MSO_SHAPE_TYPE
+from pptx.util import Emu
+
+logger = logging.getLogger(__name__)
+
+DPI = 96
+SLIDE_W_IN, SLIDE_H_IN = 13.333, 7.5
+
+# 字体 fallback 链：Noto CJK（中英混排）→ DejaVu（兜底，缺 CJK 也不崩）
+_FONT_CANDIDATES_REG = (
+    "/usr/share/fonts/opentype/noto/NotoSansCJK-Regular.ttc",
+    "/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf",
+)
+_FONT_CANDIDATES_BOLD = (
+    "/usr/share/fonts/opentype/noto/NotoSansCJK-Bold.ttc",
+    "/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf",
+)
+
+
+def _first_existing(paths: tuple[str, ...]) -> str:
+    for p in paths:
+        if Path(p).is_file():
+            return p
+    return paths[-1]
+
+
+_FONT_REG = _first_existing(_FONT_CANDIDATES_REG)
+_FONT_BOLD = _first_existing(_FONT_CANDIDATES_BOLD)
+
+
+def px(emu: int) -> int:
+    return int(Emu(emu).inches * DPI)
+
+
+def font_for(pt: float, bold: bool) -> ImageFont.FreeTypeFont:
+    path = _FONT_BOLD if bold else _FONT_REG
+    return ImageFont.truetype(path, max(int(pt * DPI / 72), 6))
+
+
+def run_style(run) -> tuple[float, bool, tuple[int, int, int]]:
+    f = run.font
+    pt = (f.size.pt if f.size else 18)
+    bold = bool(f.bold)
+    color = (0, 0, 0)
+    try:
+        if f.color and f.color.rgb is not None:
+            color = tuple(f.color.rgb)
+    except Exception:  # noqa: BLE001 - 主题色等非直接 RGB，回退黑
+        pass
+    return pt, bold, color
+
+
+def wrap_text(draw: ImageDraw.ImageDraw, text: str, font: ImageFont.ImageFont, max_w: float) -> list[str]:
+    lines: list[str] = []
+    cur = ""
+    for ch in text:
+        if ch == "\n":
+            lines.append(cur)
+            cur = ""
+            continue
+        if draw.textlength(cur + ch, font=font) > max_w and cur:
+            lines.append(cur)
+            cur = ch
+        else:
+            cur += ch
+    if cur:
+        lines.append(cur)
+    return lines or [""]
+
+
+def draw_text_frame(draw, tf, box, *, v_anchor: str = "top") -> None:
+    """box = (x, y, w, h)；按段落逐 run 画（粗体分段 / level 缩进 / 居中）。"""
+    x, y, w, h = box
+    lines_all: list[tuple[str, ImageFont.ImageFont, tuple, int, str]] = []
+    for p in tf.paragraphs:
+        runs = p.runs
+        if not runs:
+            lines_all.append(("", font_for(14, False), (0, 0, 0), 0, str(p.alignment or "left")))
+            continue
+        segs = []
+        for r in runs:
+            pt, bold, col = run_style(r)
+            segs.append((r.text, pt, bold, col))
+        # 预览够用：整段拼接，取最大字号 + 任一粗体，色随首 run
+        joined = "".join(s[0] for s in segs)
+        max_pt = max(s[1] for s in segs)
+        any_bold = any(s[2] for s in segs)
+        col = segs[0][3]
+        indent = (p.level or 0) * 24
+        align = str(p.alignment or "left")
+        fnt = font_for(max_pt, any_bold)
+        for line in wrap_text(draw, joined, fnt, max(w - indent - 8, 20)):
+            lines_all.append((line, fnt, col, indent, align))
+    total_h = sum(int(f.size * 1.35) for _, f, _, _, _ in lines_all)
+    if v_anchor == "middle":
+        y = y + max((h - total_h) // 2, 0)
+    for line, fnt, col, indent, align in lines_all:
+        lw = draw.textlength(line, font=fnt)
+        if "CENTER" in align:
+            lx = x + (w - lw) / 2
+        elif "RIGHT" in align:
+            lx = x + w - lw - 6
+        else:
+            lx = x + indent + 4
+        draw.text((lx, y), line, font=fnt, fill=col)
+        y += int(fnt.size * 1.35)
+
+
+def slide_bg_color(slide) -> tuple[int, int, int]:
+    try:
+        fill = slide.background.fill
+        if fill.type is not None and fill.fore_color and fill.fore_color.rgb is not None:
+            return tuple(fill.fore_color.rgb)
+    except Exception:  # noqa: BLE001 - 无背景填充 → 白底
+        pass
+    return (255, 255, 255)
+
+
+def render_slide(slide) -> Image.Image:
+    img = Image.new("RGB", (int(SLIDE_W_IN * DPI), int(SLIDE_H_IN * DPI)), slide_bg_color(slide))
+    d = ImageDraw.Draw(img)
+    for sh in slide.shapes:
+        try:
+            x, y, w, h = px(sh.left), px(sh.top), px(sh.width), px(sh.height)
+        except Exception:  # noqa: BLE001 - 无定位形状（组合件等）跳过
+            continue
+        if sh.shape_type == MSO_SHAPE_TYPE.AUTO_SHAPE:
+            # 色块（分隔页横幅 / 封面强调条 / 引用框）
+            fc = None
+            try:
+                if sh.fill.type is not None and sh.fill.fore_color.rgb is not None:
+                    fc = tuple(sh.fill.fore_color.rgb)
+            except Exception:  # noqa: BLE001
+                fc = None
+            if fc:
+                d.rectangle([x, y, x + w, y + h], fill=fc)
+            else:
+                d.rectangle([x, y, x + w, y + h], outline=(150, 150, 150), width=2)
+            if sh.has_text_frame and sh.text_frame.text.strip():
+                draw_text_frame(d, sh.text_frame, (x, y, w, h), v_anchor="middle")
+        elif sh.shape_type == MSO_SHAPE_TYPE.PICTURE:
+            # 真图（Tier B contain 插入的原图）
+            try:
+                pic = Image.open(BytesIO(sh.image.blob)).convert("RGB")
+                img.paste(pic.resize((max(w, 1), max(h, 1))), (x, y))
+            except Exception:  # noqa: BLE001 - 损坏图 → 灰块占位
+                d.rectangle([x, y, x + w, y + h], fill=(205, 205, 205))
+        elif getattr(sh, "has_table", False):
+            # 原生表格
+            tbl = sh.table
+            cw = [px(tbl.columns[c].width) for c in range(len(tbl.columns))]
+            rh = [px(tbl.rows[r].height) for r in range(len(tbl.rows))]
+            cy = y
+            for r, row_h in enumerate(rh):
+                cx = x
+                for c, col_w in enumerate(cw):
+                    cell = tbl.cell(r, c)
+                    try:
+                        fc = tuple(cell.fill.fore_color.rgb)
+                    except Exception:  # noqa: BLE001
+                        fc = (245, 245, 245)
+                    d.rectangle([cx, cy, cx + col_w, cy + row_h], fill=fc, outline=(170, 170, 170))
+                    draw_text_frame(d, cell.text_frame, (cx + 3, cy + 2, col_w - 6, row_h - 4))
+                    cx += col_w
+                cy += row_h
+        elif sh.has_text_frame:
+            # 占位符 / 文本框：虚线图框判定
+            txt = sh.text_frame.text
+            if "请插入" in txt:
+                d.rectangle([x, y, x + w, y + h], outline=(150, 150, 150), width=3)
+                for i in range(x, x + w, 12):  # 近似虚线
+                    d.line([i, y, min(i + 6, x + w), y], fill=(150, 150, 150), width=3)
+                    d.line([i, y + h, min(i + 6, x + w), y + h], fill=(150, 150, 150), width=3)
+                d.line([x, y, x, y + h], fill=(150, 150, 150), width=3)
+                d.line([x + w, y, x + w, y + h], fill=(150, 150, 150), width=3)
+            anchor = "middle" if "请插入" in txt else "top"
+            draw_text_frame(d, sh.text_frame, (x, y, w, h), v_anchor=anchor)
+    return img
+
+
+def render_previews(pptx_path: Path, out_dir: Path) -> list[Path]:
+    """draft.pptx → out_dir/slide_{i:02d}.png；失败/空/损坏 → []（绝不抛）。"""
+    if not pptx_path.is_file():
+        return []
+    try:
+        prs = Presentation(str(pptx_path))
+    except Exception as exc:  # noqa: BLE001 - 坏文件降级（调用方 warning）
+        logger.warning("预览渲染：pptx 打开失败 %s：%s", pptx_path, exc)
+        return []
+    try:
+        out_dir.mkdir(parents=True, exist_ok=True)
+        # 清旧页：重建后页数变少时不留 slide_{n}.png 残影（懒渲染 GET 同样受益）
+        for stale in out_dir.glob("slide_*.png"):
+            stale.unlink(missing_ok=True)
+        written: list[Path] = []
+        for i, slide in enumerate(prs.slides, 1):
+            img = render_slide(slide)
+            final = out_dir / f"slide_{i:02d}.png"
+            # 原子写：先临时文件再 replace，避免并发 GET 读到半张图
+            with tempfile.NamedTemporaryFile(dir=out_dir, suffix=".png", delete=False) as tmp:
+                tmp_path = Path(tmp.name)
+            try:
+                img.save(tmp_path, format="PNG")
+                tmp_path.replace(final)
+            finally:
+                tmp_path.unlink(missing_ok=True)
+            written.append(final)
+        return written
+    except Exception as exc:  # noqa: BLE001 - 渲染异常不阻断构建
+        logger.warning("预览渲染失败（该 job 无缩略图）：%s", exc)
+        return []
@@ -0,0 +1,155 @@
+"""services/ppt_store.py —— P5 科研汇报 job 持久化（SQLite，自含连接）。
+
+模式同 rebuttal_store：表 ppt_jobs 落 review_service/review.db（同库不同表），
+自开短连接 + WAL；pages/warnings 全量 JSON 列整读整写（单进程串行足够）。
+raw_text 只落库不回 API（150K 正文进 job dict 会把 GET 撑爆；重生成场景
+才需要它，经 DB 直读）。DDL 按 2026-10-14 决策 3 定稿。
+"""
+from __future__ import annotations
+
+import json
+import sqlite3
+import uuid
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Any
+
+from ..config import get_settings
+
+_SCHEMA = """
+CREATE TABLE IF NOT EXISTS ppt_jobs (
+  id TEXT PRIMARY KEY,
+  status TEXT NOT NULL,
+  source_kind TEXT,
+  filename TEXT,
+  raw_text TEXT,
+  scenario TEXT,
+  minutes INTEGER,
+  style_id TEXT,
+  pages_json TEXT,
+  pptx_path TEXT,
+  warnings_json TEXT,
+  created_at TEXT,
+  updated_at TEXT
+);
+"""
+
+_STATUS_VALUES = ("outline_ready", "building", "done", "error")
+_JSON_COLS = {"pages": "pages_json", "warnings": "warnings_json"}
+_SCALAR_COLS = ("status", "scenario", "minutes", "style_id", "pptx_path",
+                "source_kind", "filename")
+
+
+def _now() -> str:
+    return datetime.now(timezone.utc).isoformat(timespec="seconds")
+
+
+def new_id(prefix: str = "") -> str:
+    return prefix + uuid.uuid4().hex[:12]
+
+
+def _connect() -> sqlite3.Connection:
+    db_path: Path = get_settings().db_path_abs
+    db_path.parent.mkdir(parents=True, exist_ok=True)
+    conn = sqlite3.connect(str(db_path), timeout=5)
+    conn.row_factory = sqlite3.Row
+    conn.execute("PRAGMA journal_mode=WAL")
+    return conn
+
+
+def ensure_table() -> None:
+    with _connect() as conn:
+        conn.executescript(_SCHEMA)
+
+
+def _row_to_job(row: sqlite3.Row) -> dict[str, Any]:
+    status = row["status"]
+    pptx_path = row["pptx_path"]
+    return {
+        "id": row["id"],
+        "status": status,
+        "source": {
+            "kind": row["source_kind"] or "text",
+            "filename": row["filename"],
+            "text_chars": len(row["raw_text"] or ""),
+        },
+        "scenario": row["scenario"],
+        "minutes": row["minutes"],
+        "style_id": row["style_id"],
+        "pages": json.loads(row["pages_json"]) if row["pages_json"] else [],
+        "warnings": json.loads(row["warnings_json"]) if row["warnings_json"] else [],
+        "pptx_ready": bool(pptx_path) and Path(pptx_path).exists(),
+        "created_at": row["created_at"],
+        "updated_at": row["updated_at"],
+    }
+
+
+def insert_job(job: dict[str, Any], raw_text: str = "") -> None:
+    now = job.get("created_at") or _now()
+    status = job.get("status") or "outline_ready"
+    if status not in _STATUS_VALUES:
+        raise ValueError(f"非法 status: {status}")
+    with _connect() as conn:
+        conn.execute(
+            "INSERT INTO ppt_jobs (id, status, source_kind, filename, raw_text,"
+            " scenario, minutes, style_id, pages_json, pptx_path, warnings_json,"
+            " created_at, updated_at) VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?)",
+            (
+                job["id"], status,
+                (job.get("source") or {}).get("kind"),
+                (job.get("source") or {}).get("filename"),
+                raw_text,
+                job.get("scenario"), job.get("minutes"), job.get("style_id"),
+                json.dumps(job.get("pages") or [], ensure_ascii=False),
+                job.get("pptx_path"),
+                json.dumps(job.get("warnings") or [], ensure_ascii=False),
+                now, now,
+            ),
+        )
+
+
+def get_job(job_id: str) -> dict[str, Any] | None:
+    with _connect() as conn:
+        row = conn.execute("SELECT * FROM ppt_jobs WHERE id=?", (job_id,)).fetchone()
+    return _row_to_job(row) if row else None
+
+
+def update_job(job_id: str, **fields: Any) -> dict[str, Any] | None:
+    """局部更新（省略的列不动；pages/warnings 传对象自动序列化）。"""
+    sets: list[str] = []
+    vals: list[Any] = []
+    for key, value in fields.items():
+        if key in _JSON_COLS:
+            sets.append(f"{_JSON_COLS[key]}=?")
+            vals.append(json.dumps(value, ensure_ascii=False) if value is not None else None)
+        elif key in _SCALAR_COLS:
+            if key == "status" and value not in _STATUS_VALUES:
+                raise ValueError(f"非法 status: {value}")
+            sets.append(f"{key}=?")
+            vals.append(value)
+        else:
+            raise TypeError(f"update_job 不支持的字段: {key}")
+    if not sets:
+        return get_job(job_id)
+    sets.append("updated_at=?")
+    vals.extend([_now(), job_id])
+    with _connect() as conn:
+        cur = conn.execute(f"UPDATE ppt_jobs SET {', '.join(sets)} WHERE id=?", vals)
+        if cur.rowcount == 0:
+            return None
+    return get_job(job_id)
+
+
+def delete_job(job_id: str) -> bool:
+    with _connect() as conn:
+        cur = conn.execute("DELETE FROM ppt_jobs WHERE id=?", (job_id,))
+    return cur.rowcount > 0
+
+
+def get_raw_text(job_id: str) -> str:
+    """raw_text 只在 evidence 重验时直读（不进 API job dict，避免 GET 撑爆）。"""
+    with _connect() as conn:
+        row = conn.execute(
+            "SELECT raw_text FROM ppt_jobs WHERE id=?", (job_id,)
+        ).fetchone()
+    return (row["raw_text"] or "") if row else ""
@@ -0,0 +1,153 @@
+"""services/rebuttal_draft.py —— 5 类回复片段 Prompt + 反幻觉校验 + letter 拼装。
+
+- part.type 枚举（决策 2，无 auto）：new_data | reanalysis | location | clarification | rebuttal。
+- 反幻觉校验（补充 2 收窄版，只做负向证伪，不做泛化打分）：
+  * location：出现 "shows that / as shown" 但无 "added/新增" 迹证 → FAIL
+    （"S3 shows that..." 红 FAIL；"we have added ... in S3" 过）。
+  * rebuttal：命中负向词表 we agree / we accept / we concede / you are right /
+    we were wrong → FAIL；无立场词（maintain/disagree/respectfully/坚持/不同意…）
+    → FAIL；"respectfully maintain" 过。
+  * 其他三类：Phase 1 仅查非空。
+- 校验前置（决策：校验C前置）：draft 生成前先跑校验，FAIL 则不调 LLM。
+- letter 拼装：按 reviewer → comment 顺序，原文 + 草稿；无草稿留 "[待补充]"。
+"""
+from __future__ import annotations
+
+import re
+from typing import Any, Callable
+
+LLMCallable = Callable[..., Any]
+
+PART_TYPES = ("new_data", "reanalysis", "location", "clarification", "rebuttal")
+
+_TYPE_FRAGMENTS: dict[str, str] = {
+    "new_data": (
+        "你的回复属于【补充新数据】类：说明新增了哪些实验/数据（图/表编号、关键数值），"
+        "并明确回应原审稿关切。不得虚构未提供的数据——只用 user_response 给出的事实。"
+    ),
+    "reanalysis": (
+        "你的回复属于【重新分析】类：说明重跑了哪些分析、方法/参数变化与新结论要点。"
+        "不得虚构未提供的结果——只用 user_response 给出的事实。"
+    ),
+    "location": (
+        "你的回复属于【定位/指出位置】类：明确指出修改或证据在稿件中的位置"
+        "（如 Section 3 / Fig. S2 / Methods 段落），与 user_response 给出的位置一致。"
+        "不得虚构未提供的位置。"
+    ),
+    "clarification": (
+        "你的回复属于【澄清说明】类：针对误解给出准确、简洁的解释，"
+        "只用 user_response 与原评论内容，不引入新主张。"
+    ),
+    "rebuttal": (
+        "你的回复属于【礼貌反驳】类：礼貌但明确地表达不同立场（maintain/disagree），"
+        "给出理由（基于 user_response 与原文），不得虚构证据。"
+    ),
+}
+
+_BASELINE = (
+    "通用底线：只基于原评论与 user_response 起草；不得编造数据、图表编号、"
+    "统计结果或已做修改；不确定处用占位（[XX]）而非猜测。"
+    "输出 JSON：{\"draft_md\": \"英文正式回复正文（markdown，≤200词）\"}。只输出 JSON。"
+)
+
+_STANCE = re.compile(
+    r"\b(maintain|disagree|respectfully|cannot\s+agree|dispute|stand\s+by|"
+    r"hold\s+to)\b|坚持|不同意|保留|异议",
+    re.IGNORECASE,
+)
+_NEGATIVE = re.compile(
+    r"\bwe\s+agree\b|\bwe\s+accept\b|\bwe\s+concede\b|\byou\s+are\s+right\b|"
+    r"\bwe\s+were\s+wrong\b",
+    re.IGNORECASE,
+)
+_LOC_SHOWS = re.compile(r"shows?\s+that|as\s+shown|表明", re.IGNORECASE)
+_LOC_ADDED = re.compile(r"\badded\b|新增|have\s+added|we\s+have\s+added", re.IGNORECASE)
+
+
+def validate_parts(parts: list[dict[str, Any]]) -> dict[str, Any]:
+    """反幻觉校验 → {passed: bool, findings: [{part_index, code, message}]}。"""
+    findings: list[dict[str, Any]] = []
+    for i, p in enumerate(parts):
+        ptype = str(p.get("type") or "")
+        content = str(p.get("content") or "").strip()
+        if not content:
+            findings.append({"part_index": i, "code": "EMPTY_CONTENT",
+                             "message": "回复内容不能为空"})
+            continue
+        if ptype == "location":
+            if _LOC_SHOWS.search(content) and not _LOC_ADDED.search(content):
+                findings.append({
+                    "part_index": i, "code": "LOCATION_EVIDENCE_WEAK",
+                    "message": "location 类回复出现“shows that/如所示”但未给出新增位置；"
+                               "请写明“we have added … in S{n}”式定位",
+                })
+        elif ptype == "rebuttal":
+            if _NEGATIVE.search(content):
+                findings.append({
+                    "part_index": i, "code": "REBUTTAL_NEGATIVE",
+                    "message": "rebuttal 类回复出现让步词（we agree/accept/concede…）；"
+                               "该类应礼貌但明确地表达不同立场",
+                })
+            elif not _STANCE.search(content):
+                findings.append({
+                    "part_index": i, "code": "REBUTTAL_NO_STANCE",
+                    "message": "rebuttal 类回复缺少立场词（maintain/disagree/respectfully…）",
+                })
+        # new_data / reanalysis / clarification：Phase 1 仅非空
+    return {"passed": not findings, "findings": findings}
+
+
+def _draft_system(parts: list[dict[str, Any]]) -> str:
+    frags = [_TYPE_FRAGMENTS.get(str(p.get("type") or ""), "") for p in parts]
+    frags = [f for f in frags if f]
+    return " ".join(frags) + " " + _BASELINE if frags else _BASELINE
+
+
+async def generate_draft(llm: LLMCallable, comment: dict[str, Any]) -> str:
+    """按 comment.response.parts 起草 draft_md（调用方须先过 validate_parts）。"""
+    parts = (comment.get("response") or {}).get("parts") or []
+    user_lines = []
+    for p in parts:
+        hint = str(p.get("location_hint") or "").strip()
+        line = f"- [{p.get('type')}] {p.get('content')}"
+        if hint:
+            line += f" (location_hint: {hint})"
+        user_lines.append(line)
+    user_msg = (
+        f"原审稿意见：\n{comment.get('body') or comment.get('title') or ''}\n\n"
+        f"作者拟回复要点（user_response）：\n" + "\n".join(user_lines)
+    )
+    try:
+        data = await llm(
+            [{"role": "system", "content": _draft_system(parts)},
+             {"role": "user", "content": user_msg}],
+            temperature=0.2,
+        )
+        draft = str((data or {}).get("draft_md") or "").strip()
+        return draft or "[draft generation returned empty]"
+    except Exception:  # noqa: BLE001
+        return "[draft generation failed — 请重试]"
+
+
+def assemble_letter(job: dict[str, Any]) -> str:
+    """拼装整封 response letter markdown（Phase 1 纯 .md，docx 放 Phase 2）。"""
+    lines: list[str] = ["# Response to Reviewers", ""]
+    lines.append(f"_Job: {job.get('id')} · template: {job.get('template') or 'generic'}_")
+    lines.append("")
+    for r in job.get("reviewers") or []:
+        lines.append(f"## {r.get('label') or 'Reviewer'}")
+        lines.append("")
+        for c in r.get("comments") or []:
+            title = c.get("title") or c.get("id") or "Comment"
+            lines.append(f"### {title}")
+            lines.append("")
+            lines.append("**Original comment:**")
+            lines.append("")
+            lines.append(str(c.get("body") or "").strip())
+            lines.append("")
+            lines.append("**Our response:**")
+            lines.append("")
+            draft = str(c.get("draft") or "").strip()
+            lines.append(draft if draft else "[待补充]")
+            lines.append("")
+    return "\n".join(lines)
@@ -0,0 +1,207 @@
+"""services/rebuttal_parse.py —— 审稿意见文本 → 结构化 Comment 树。
+
+流程（保守：正则先切骨架，LLM 只做分类/拆子条，行数交叉核对不匹配则回退正则）：
+1. 归一化换行；正则识别 Reviewer 段头（Reviewer 1 / 审稿人 2 / Review A 等），
+   无段头 → 单 Reviewer（label=Reviewer）。
+2. 每个 Reviewer 段内按编号行切 comment 段（"1." "2)" "（3）" 等）；
+   切不出编号 → 整段作 1 条。
+3. LLM complete_json 对每段做：{title, severity, sub_items:[{title,body,confidence}]}。
+   - LLM 返回段数 != 提交段数 → 全量回退正则（title=首 60 字，severity 默认 major）。
+   - sub_items ≥ 2 且最高 confidence ≥ 0.7 → 拆多条（共享 group_id）；否则单条。
+4. cross_refs：正文里 "see comment 3 / 参见第 2 条" → 解析目标；解析不到
+   target_id=null 保留 raw（决策：不猜）。
+
+不做：auto 分类（已砍）；severity 以外的任何 LLM 自由发挥字段。
+"""
+from __future__ import annotations
+
+import re
+from typing import Any, Callable
+
+# LLM 依赖注入（测试打桩）：async (messages, temperature=..) -> dict
+LLMCallable = Callable[..., Any]
+
+_REVIEWER_HEADER = re.compile(
+    r"^(?:reviewers?\s*#?\s*([0-9]+|[A-Z])|审稿人\s*#?\s*([0-9A-Z]+)|review\s+([A-Z]))\s*[:：.）)]?",
+    re.IGNORECASE | re.MULTILINE,
+)
+_COMMENT_NUM = re.compile(
+    r"(?:(?<=\n)|(?<=\.\s)|^)\s*(?:[#(（]?\s*(\d{1,2})\s*[)）.:、]|[（(]\s*([ivx]{1,4}|[a-z])\s*[)）])\s+",
+    re.IGNORECASE | re.MULTILINE,
+)
+_CROSS_REF = re.compile(
+    r"(?:see|noted\s+in|refer(?:ring)?\s+to|per)\s+comment\s*#?\s*(\d+)|"
+    r"(?:please\s+)?refer\s+to\s+comment\s*#?\s*(\d+)|"
+    r"参见\s*第?\s*(\d+)\s*条|见\s*comment\s*#?\s*(\d+)|同上(?:一条)?评论",
+    re.IGNORECASE,
+)
+
+_SPLIT_CONFIDENCE = 0.7  # 决策 3：confidence ≥ 0.7 才拆
+
+
+def _norm(text: str) -> str:
+    return text.replace("\r\n", "\n").replace("\r", "\n").strip()
+
+
+def split_reviewers(text: str) -> list[tuple[str, str]]:
+    """→ [(label, block_text)]；无段头 → [(Reviewer, 全文)]。"""
+    text = _norm(text)
+    matches = list(_REVIEWER_HEADER.finditer(text))
+    if not matches:
+        return [("Reviewer", text)]
+    out: list[tuple[str, str]] = []
+    for i, m in enumerate(matches):
+        raw = next(g for g in m.groups() if g is not None)
+        label = raw.upper() if raw.isalpha() else f"Reviewer {raw}"
+        start = m.end()
+        end = matches[i + 1].start() if i + 1 < len(matches) else len(text)
+        block = text[start:end].strip()
+        if block:
+            out.append((label, block))
+    if not out:  # 段头全空块 → 兜底
+        return [("Reviewer", text)]
+    # 段头前的引言（无段头内容）丢弃——保守：不猜归属
+    return out
+
+
+def split_comments(block: str) -> list[str]:
+    """段内按编号行切 comment 块；无编号 → [整段]。"""
+    block = _norm(block)
+    matches = list(_COMMENT_NUM.finditer(block))
+    if len(matches) < 2:  # 单个编号或无编号 → 整段一条
+        return [block] if block else []
+    out: list[str] = []
+    for i, m in enumerate(matches):
+        start = m.end()
+        end = matches[i + 1].start() if i + 1 < len(matches) else len(block)
+        chunk = block[start:end].strip()
+        if chunk:
+            out.append(chunk)
+    return out or [block]
+
+
+def _fallback_segment(seg: str) -> dict[str, Any]:
+    title = re.sub(r"\s+", " ", seg)[:60]
+    return {
+        "title": title,
+        "severity": "major",
+        "sub_items": [{"title": title, "body": seg, "confidence": 1.0}],
+    }
+
+
+_SEG_SYSTEM = (
+    "你是学术审稿意见解析助手。输入是一段审稿意见原文。输出 JSON："
+    '{"title": "≤12词标题", "severity": "major|minor|question", '
+    '"sub_items": [{"title": "...", "body": "该子问题完整原文", "confidence": 0.0-1.0}]}。'
+    "severity：major=要求补实验/补数据/重分析；minor=格式/表述小问题；"
+    "question=仅提问、无需修改稿件。"
+    "若该段含多个可独立回复的子问题则拆成多个 sub_items（confidence 给拆分把握度），"
+    "否则 1 个 sub_items（confidence=1.0）。只输出 JSON。"
+)
+
+
+async def _ask_llm_segment(llm: LLMCallable, seg: str) -> dict[str, Any] | None:
+    try:
+        data = await llm(
+            [{"role": "system", "content": _SEG_SYSTEM},
+             {"role": "user", "content": seg}],
+            temperature=0.0,
+        )
+        if not isinstance(data, dict) or not isinstance(data.get("sub_items"), list):
+            return None
+        sev = str(data.get("severity", "")).lower()
+        title = str(data.get("title") or "").strip() or seg[:60]
+        subs: list[dict[str, Any]] = []
+        for s in data["sub_items"][:8]:
+            if not isinstance(s, dict):
+                continue
+            body = str(s.get("body") or "").strip()
+            if not body:
+                continue
+            try:
+                conf = float(s.get("confidence", 1.0))
+            except (TypeError, ValueError):
+                conf = 0.0
+            subs.append({
+                "title": str(s.get("title") or "").strip() or title,
+                "body": body,
+                "confidence": max(0.0, min(1.0, conf)),
+            })
+        if not subs:
+            return None
+        return {"title": title,
+                "severity": sev if sev in ("major", "minor", "question") else "major",
+                "sub_items": subs}
+    except Exception:  # noqa: BLE001 — LLM 失败即回退正则，不猜测
+        return None
+
+
+def _resolve_cross_refs(body: str, ordinal_map: dict[int, str]) -> list[dict[str, Any]]:
+    refs: list[dict[str, Any]] = []
+    for m in _CROSS_REF.finditer(body):
+        raw = m.group(0).strip()
+        num = next((int(g) for g in m.groups() if g and g.isdigit()), None)
+        if num is None and "同上" in raw:
+            num = _prev_ordinal(ordinal_map, m.start())  # 同上 → 上一条，保守仅前一条
+        target = ordinal_map.get(num) if num is not None else None
+        refs.append({"raw": raw, "target_id": target})
+    return refs
+
+
+def _prev_ordinal(ordinal_map: dict[int, str], _pos: int) -> int | None:
+    # 简化：同上 → 已知最大编号（即前一条）
+    return max(ordinal_map) if ordinal_map else None
+
+
+async def parse_review_text(text: str, llm: LLMCallable) -> list[dict[str, Any]]:
+    """→ reviewers=[{id, label, ordinal, comments:[Comment]}]（不含 job 包装）。"""
+    reviewers_out: list[dict[str, Any]] = []
+    cid_seq = 0
+    for r_ord, (label, block) in enumerate(split_reviewers(text), start=1):
+        segs = split_comments(block)
+        if not segs:
+            continue
+        comments: list[dict[str, Any]] = []
+        ordinal_map: dict[int, str] = {}
+        parsed_seg: list[dict[str, Any]] = []
+        for seg in segs:
+            llm_res = await _ask_llm_segment(llm, seg)
+            # 交叉核对：LLM 无法给出结构 → 该段回退正则
+            parsed_seg.append(llm_res if llm_res else _fallback_segment(seg))
+        for seg_idx, (seg, p) in enumerate(zip(segs, parsed_seg), start=1):
+            subs = p["sub_items"]
+            split = len(subs) >= 2 and max(s["confidence"] for s in subs) >= _SPLIT_CONFIDENCE
+            group_id = f"g{r_ord}-{seg_idx}"
+            items = subs if split else [subs[0]]
+            if not split and len(subs) > 1:
+                # 未达阈值 → 多子问题并回一条（body 用整段原文）
+                items = [{"title": p["title"], "body": seg, "confidence": 1.0}]
+            for it in items:
+                cid_seq += 1
+                cid = f"c{cid_seq:04d}"
+                # 保守：不拆时 body 保留该段原文（不采信 LLM 改写）；拆时用子项 body
+                body = it["body"] if split else seg
+                ordinal_map[seg_idx] = cid
+                comments.append({
+                    "id": cid,
+                    "group_id": group_id if split else None,
+                    "severity": p["severity"],
+                    "title": it["title"],
+                    "body": body,
+                    "sub_items": [s["title"] for s in subs] if split else [],
+                    "cross_refs": _resolve_cross_refs(body, ordinal_map),
+                    "response": {"parts": []},
+                    "draft": None,
+                    "validation": None,
+                    "human_confirmed": False,
+                    "scanner_downgraded": False,
+                })
+        # cross_refs 需全量 comment id 后再扫一遍（前面扫时 map 未齐）
+        for c in comments:
+            c["cross_refs"] = _resolve_cross_refs(c["body"], ordinal_map)
+        if comments:
+            reviewers_out.append({
+                "id": f"r{r_ord}", "label": label, "ordinal": r_ord,
+                "comments": comments,
+            })
+    return reviewers_out
@@ -0,0 +1,162 @@
+"""services/rebuttal_store.py —— Rebuttal Phase 1 任务持久化（SQLite，自含连接）。
+
+设计（2026-10-12 定稿）：
+- 表 rebuttal_jobs 落在 review_service/review.db（与 journals 同库不同表）；
+  本模块自开短连接（低频 CRUD，WAL 下足够），不改既有 app/db.py。
+- Job/Comment 全量以 JSON 存 reviewers_json 列（Phase 1 规模 ≤ 数十条，
+  整读整写最简单且可测；并发写靠 updated_at + 单进程串行）。
+- human_ack 不信前端置位：confirm 端点改完 comment 后由本模块重算——
+  所有 comment.human_confirmed 全 true 才置 1（决策 4）。
+- 不做 TTL 自动清理（决策 5）；DELETE 端点手动删。
+"""
+from __future__ import annotations
+
+import json
+import sqlite3
+import uuid
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Any
+
+from ..config import get_settings
+
+_SCHEMA = """
+CREATE TABLE IF NOT EXISTS rebuttal_jobs (
+  id TEXT PRIMARY KEY,
+  status TEXT NOT NULL,
+  source_kind TEXT,
+  filename TEXT,
+  raw_text TEXT,
+  template TEXT DEFAULT 'generic',
+  reviewers_json TEXT NOT NULL,
+  letter_md TEXT,
+  validation_json TEXT,
+  human_ack INTEGER DEFAULT 0,
+  created_at TEXT,
+  updated_at TEXT
+);
+"""
+
+
+def _now() -> str:
+    return datetime.now(timezone.utc).isoformat(timespec="seconds")
+
+
+def new_id(prefix: str = "") -> str:
+    return prefix + uuid.uuid4().hex[:12]
+
+
+def _connect() -> sqlite3.Connection:
+    db_path: Path = get_settings().db_path_abs
+    db_path.parent.mkdir(parents=True, exist_ok=True)
+    conn = sqlite3.connect(str(db_path), timeout=5)
+    conn.row_factory = sqlite3.Row
+    conn.execute("PRAGMA journal_mode=WAL")
+    return conn
+
+
+def ensure_table() -> None:
+    with _connect() as conn:
+        conn.executescript(_SCHEMA)
+
+
+def _row_to_job(row: sqlite3.Row) -> dict[str, Any]:
+    return {
+        "id": row["id"],
+        "status": row["status"],
+        "source": {
+            "kind": row["source_kind"] or "text",
+            "filename": row["filename"],
+            "raw_text": row["raw_text"] or "",
+        },
+        "template": row["template"] or "generic",
+        "reviewers": json.loads(row["reviewers_json"] or "[]"),
+        "letter_md": row["letter_md"],
+        "validation": json.loads(row["validation_json"]) if row["validation_json"] else None,
+        "human_ack": bool(row["human_ack"]),
+        "created_at": row["created_at"],
+        "updated_at": row["updated_at"],
+    }
+
+
+def insert_job(job: dict[str, Any]) -> None:
+    """写入完整 job（reviewers 等结构由调用方构造好）。"""
+    now = job.get("created_at") or _now()
+    with _connect() as conn:
+        conn.execute(
+            "INSERT INTO rebuttal_jobs (id, status, source_kind, filename, raw_text,"
+            " template, reviewers_json, letter_md, validation_json, human_ack,"
+            " created_at, updated_at) VALUES (?,?,?,?,?,?,?,?,?,?,?,?)",
+            (
+                job["id"], job.get("status") or "ready",
+                (job.get("source") or {}).get("kind"),
+                (job.get("source") or {}).get("filename"),
+                (job.get("source") or {}).get("raw_text"),
+                job.get("template") or "generic",
+                json.dumps(job.get("reviewers") or [], ensure_ascii=False),
+                job.get("letter_md"),
+                json.dumps(job.get("validation"), ensure_ascii=False)
+                if job.get("validation") is not None else None,
+                1 if job.get("human_ack") else 0,
+                now, now,
+            ),
+        )
+
+
+def get_job(job_id: str) -> dict[str, Any] | None:
+    with _connect() as conn:
+        row = conn.execute(
+            "SELECT * FROM rebuttal_jobs WHERE id=?", (job_id,)
+        ).fetchone()
+    return _row_to_job(row) if row else None
+
+
+def update_job(job_id: str, *, reviewers: list[dict[str, Any]] | None = None,
+               letter_md: str | None = None, status: str | None = None) -> dict[str, Any] | None:
+    """局部更新；reviewers 变更时重算 human_ack（全勾才 true）。"""
+    job = get_job(job_id)
+    if job is None:
+        return None
+    if reviewers is not None:
+        job["reviewers"] = reviewers
+    if letter_md is not None:
+        job["letter_md"] = letter_md
+    if status is not None:
+        job["status"] = status
+    job["human_ack"] = all_comments_confirmed(job["reviewers"])
+    job["updated_at"] = _now()
+    with _connect() as conn:
+        conn.execute(
+            "UPDATE rebuttal_jobs SET reviewers_json=?, letter_md=?, status=?,"
+            " human_ack=?, updated_at=? WHERE id=?",
+            (
+                json.dumps(job["reviewers"], ensure_ascii=False),
+                job.get("letter_md"),
+                job["status"],
+                1 if job["human_ack"] else 0,
+                job["updated_at"],
+                job_id,
+            ),
+        )
+    return job
+
+
+def delete_job(job_id: str) -> bool:
+    with _connect() as conn:
+        cur = conn.execute("DELETE FROM rebuttal_jobs WHERE id=?", (job_id,))
+    return cur.rowcount > 0
+
+
+def all_comments(reviewers: list[dict[str, Any]]) -> list[dict[str, Any]]:
+    out: list[dict[str, Any]] = []
+    for r in reviewers or []:
+        out.extend(r.get("comments") or [])
+    return out
+
+
+def all_comments_confirmed(reviewers: list[dict[str, Any]]) -> bool:
+    comments = all_comments(reviewers)
+    # 空 job（未解析出任何 comment）不置位 human_ack，避免"全勾"平凡真
+    if not comments:
+        return False
+    return all(bool(c.get("human_confirmed")) for c in comments)
@@ -0,0 +1,232 @@
+"""services/recommend_engine.py —— presubmit recommendation 规则引擎（纯函数，零 LLM）。
+
+背景（2026-10-12 诊断）：旧链路由 LLM 直接输出 recommendation，且 SYSTEM_PROMPT 配额
+强制 "major_weaknesses 3-8 条"，导致 accept/minor_revision 几乎不可达（对照实验中
+强稿——BUSCO 96.8%/Hi-C 98.7%/accession 齐/UFBoot 1000——仍被凑出 6 条 major）。
+新链路：LLM 只如实列 weakness（major 带 hard_rule/fatal 标签），本引擎按可测规则
+计算 recommendation + rationale（模板拼装，可复现，不经 LLM）。
+
+判定链（自上而下首条命中）：
+  R0    任一 major 带 fatal=true              → reject（须人工复核）
+  R1    H = 硬性 major 数 ≥ 1                 → major_revision（与 tier 无关，不可协商）
+  R2'   tier==3 且 1≤S≤2 且 H==0              → minor_revision（入门刊仅 soft 可降）
+  R2    S = soft major 数 ≥ 1                 → major_revision（S≥5 标 severe，仍非 reject）
+  R4    S == 0 且 minor ≤ accept_max_minor[tier] → accept
+  R5    S == 0                                → minor_revision
+其中 S = 总 major 数 − 硬性标签数（标签漏打时 S 变大，只会更严不会漏放）。
+"""
+from __future__ import annotations
+
+import json
+import re
+import sqlite3
+from functools import lru_cache
+from pathlib import Path
+from typing import Any, Iterable
+
+from ..config import get_settings
+
+# 硬性规则标签（SYSTEM_PROMPT 与 coerce 共用白名单；未知标签一律置 None）
+HARD_RULE_TAGS = (
+    "busco_missing",      # 组装类论文缺 BUSCO 完整格式
+    "hic_missing",        # 宣称 chromosome-level/Hi-C 但缺挂载率
+    "accession_missing",  # 缺数据 Accession（"will be deposited" 视为缺）
+    "voucher_missing",    # 野生材料缺凭证标本
+    "abs_missing",        # 缺 ABS/名古屋合规声明
+)
+
+HARD_RULE_LABELS = {
+    "busco_missing": "BUSCO 完整度缺失",
+    "hic_missing": "Hi-C 挂载率缺失",
+    "accession_missing": "数据 Accession 缺失",
+    "voucher_missing": "凭证标本缺失",
+    "abs_missing": "ABS/名古屋合规声明缺失",
+}
+
+TIER_LABELS = {1: "顶刊", 2: "主流期刊", 3: "入门期刊"}
+
+# tier 参数：accept 门槛（minor 上限）；tier3 额外允许 ≤2 条 soft major 降为小修
+TIER_ACCEPT_MAX_MINOR = {1: 1, 2: 2, 3: 3}
+TIER3_SOFT_MAJOR_AS_MINOR_MAX = 2
+
+# ---- tier 查找优先级（2026-10-12）：override → featured → jif → 默认 ----
+# ① 用户高频投稿顶刊硬编码（精确名匹配，不受 jif/综述刊启发式影响；
+#    "The " 前缀归一化，"Plant Cell"/"The Plant Cell" 互认）
+TIER1_OVERRIDES = frozenset(
+    re.sub(r"^the\s+", "", name.casefold()) for name in (
+        "Nature", "Nature Genetics", "Nature Plants", "Nature Biotechnology",
+        "Nature Methods", "Cell", "Science", "Genome Biology", "Molecular Plant",
+        "The Plant Cell", "Nature Communications", "Science Advances", "Cell Research",
+    )
+)
+# 综述刊不因高 jif 升 tier1（Annual Review of… / Trends in… / …Reviews）
+_REVIEW_JOURNAL_RE = re.compile(r"reviews?\b|\btrends\b|annual\s+review", re.IGNORECASE)
+_JIF_TIER1_MIN = 15.0  # jif >= 15 → tier1；5 ≤ jif < 15 → tier2；<5/NULL → 默认 tier2
+
+
+@lru_cache(maxsize=1)
+def _tier_by_name() -> dict[str, int]:
+    """journals.json 精选期刊 name(casefold) → review_tier（读文件一次，缓存）。"""
+    path = get_settings().journals_seed_abs
+    try:
+        payload = json.loads(Path(path).read_text(encoding="utf-8"))
+    except (OSError, ValueError):
+        return {}
+    out: dict[str, int] = {}
+    for j in payload.get("journals") or []:
+        if not isinstance(j, dict):
+            continue
+        name = str(j.get("name") or "").strip().casefold()
+        tier = j.get("review_tier")
+        if name and isinstance(tier, int) and tier in (1, 2, 3):
+            out[name] = tier
+    return out
+
+
+@lru_cache(maxsize=256)
+def _jif_by_name(name_bare_cf: str) -> float | None:
+    """journal_directory 按名查 jif（只读一列；表缺失/查不到 → None）。"""
+    db = get_settings().db_path_abs
+    if not Path(db).exists():
+        return None
+    try:
+        conn = sqlite3.connect(f"file:{db}?mode=ro", uri=True, timeout=2)
+        try:
+            row = conn.execute(
+                "SELECT jif FROM journal_directory WHERE lang='en' "
+                "AND (lower(name)=? OR lower(name)=?) "
+                "ORDER BY jif DESC LIMIT 1",
+                (name_bare_cf, "the " + name_bare_cf),
+            ).fetchone()
+        finally:
+            conn.close()
+    except sqlite3.Error:
+        return None
+    if not row or row[0] is None:
+        return None
+    try:
+        return float(row[0])
+    except (TypeError, ValueError):
+        return None
+
+
+def resolve_tier(target_journal: str) -> tuple[int, str]:
+    """目标期刊 → (tier, source)。source ∈ override/featured/jif/默认。
+
+    查找优先级：① 硬编码 13 本顶刊 ② journals.json review_tier
+    ③ journal_directory jif 启发式（综述刊除外）④ 默认 tier 2。
+    """
+    raw = (target_journal or "").strip()
+    if not raw:
+        return 2, "默认"
+    key = raw.casefold()
+    bare = re.sub(r"^the\s+", "", key)
+    if bare in TIER1_OVERRIDES:
+        return 1, "override"
+    featured = _tier_by_name()
+    tier = featured.get(key, featured.get(bare))
+    if isinstance(tier, int) and tier in (1, 2, 3):
+        return tier, "featured"
+    if not _REVIEW_JOURNAL_RE.search(bare):
+        jif = _jif_by_name(bare)
+        if jif is not None:
+            return (1 if jif >= _JIF_TIER1_MIN else 2), "jif"
+    return 2, "默认"
+
+
+def _item_field(item: Any, key: str) -> Any:
+    if isinstance(item, dict):
+        return item.get(key)
+    return getattr(item, key, None)
+
+
+def decide_recommendation(
+    majors: Iterable[Any],
+    minors: Iterable[Any] = (),
+    presentations: Iterable[Any] = (),
+    tier: int = 2,
+) -> dict[str, Any]:
+    """规则引擎入口。majors 项可为 dict 或带 hard_rule/fatal 属性的对象。
+
+    返回 {"recommendation": ..., "rationale": {...}}；
+    rationale 含 rule/hard_hits/计数/tier/tier_label/explanation（模板拼装）。
+    """
+    del presentations  # 呈现类不参与判定（仅归档展示）
+    majors = list(majors)
+    minors = list(minors)
+    if tier not in (1, 2, 3):
+        tier = 2
+
+    hard_hits: list[str] = []
+    fatal = False
+    for m in majors:
+        if bool(_item_field(m, "fatal")):
+            fatal = True
+        hr = _item_field(m, "hard_rule")
+        if hr in HARD_RULE_LABELS:
+            hard_hits.append(hr)
+
+    m_count = len(majors)
+    h_count = len(hard_hits)
+    s_count = m_count - h_count  # soft major（标签漏打 → 计入 S，只会更严）
+    minor_count = len(minors)
+    tier_label = TIER_LABELS[tier]
+
+    # tier3 降级通道提示（对作者可见：同稿投不同档结果不同）
+    tier_note = ""
+    if h_count == 0 and 1 <= s_count <= TIER3_SOFT_MAJOR_AS_MINOR_MAX and tier != 3:
+        tier_note = f"当前判定基于 tier {tier} 档；tier 3 入门刊此稿可能判 minor_revision。"
+
+    def _result(rec: str, rule: str, explanation: str) -> dict[str, Any]:
+        return {
+            "recommendation": rec,
+            "rationale": {
+                "rule": rule,
+                "hard_hits": hard_hits,
+                "major_count": m_count,
+                "hard_count": h_count,
+                "soft_count": s_count,
+                "minor_count": minor_count,
+                "tier": tier,
+                "tier_label": tier_label,
+                "explanation": explanation + tier_note,
+            },
+        }
+
+    # R0：fatal → reject（前端须配"建议人工复核"）
+    if fatal:
+        return _result(
+            "reject", "R0",
+            "存在 fatal 级问题（数据可靠性/伦理，须人工复核）→ 建议拒稿。")
+
+    # R1：硬性 major 不可协商
+    if h_count >= 1:
+        labels = "、".join(HARD_RULE_LABELS.get(t, t) for t in dict.fromkeys(hard_hits))
+        return _result(
+            "major_revision", "R1",
+            f"命中硬性缺陷（{labels}）→ 大修（不可协商）；"
+            f"另有大修级 {s_count} 条、小修级 {minor_count} 条。")
+
+    # R2'：入门刊 1-2 条 soft major 可降为小修
+    if tier == 3 and 1 <= s_count <= TIER3_SOFT_MAJOR_AS_MINOR_MAX:
+        return _result(
+            "minor_revision", "R2'",
+            f"无硬性缺陷，大修级（soft）{s_count} 条；"
+            f"入门刊（tier 3）可将 ≤{TIER3_SOFT_MAJOR_AS_MINOR_MAX} 条 soft 降为小修 → 建议小修。")
+
+    # R2/R3：soft major ≥ 1（S≥5 标 severe）
+    if s_count >= 1:
+        sev = "，severe" if s_count >= 5 else ""
+        return _result(
+            "major_revision", "R2",
+            f"大修级问题 {s_count} 条（均非硬性{sev}）→ 建议大修。")
+
+    # R4/R5：无 major
+    accept_max = TIER_ACCEPT_MAX_MINOR[tier]
+    if minor_count <= accept_max:
+        return _result(
+            "accept", "R4",
+            f"无大修级问题，小修级 {minor_count} 条（≤{accept_max}）→ 建议接收。")
+    return _result(
+        "minor_revision", "R5",
+        f"无大修级问题，小修级 {minor_count} 条 → 建议小修。")
@@ -0,0 +1,553 @@
+r"""services/reformat.py —— P1 论文重排版（.tex 源码级规则变换，不编译）。
+
+链路：resolve_rules（三级规则解析）→ reformat_tex（4 变换器 + 结构守卫）
+      → 路由层落盘 data/reformat_jobs/{job_id}.tex/.json。
+纯规则、零 LLM、零执行用户内容、不碰 docx/pdf（那两个只在 FormatPanel 审核）。
+
+拍板（用户 4 点确认，2026-10-10）：
+1. changes[] 每条带 rule_key ∈ {font_pt, margin, line_spacing, bib_style}、
+   action ∈ {modified, inserted, warning}（P1 只产生 modified/warning，
+   inserted 留给后续阶段）；前端按 rule_key 着色、按 action 计数。
+2. 保守插入策略：命令/选项缺失一律【不改源码】→ changes 里 action=warning，
+   reason 附"建议手动添加"的代码片段；warning 不计入"已修改"计数。
+   （warnings[] 顶层数组只放结构级提示，如多处 \documentclass。）
+3. target_journal 必填；"default"= 通用规则（min_font_pt=11, min_margin_mm=20,
+   min_line_spacing=1.5, refs_style=apa），前端下拉首项即通用。
+4. P1 仅 .tex；结构畸形宁拒不猜（PARSER_FAILED）。
+
+铁律：
+① 只在违反规则时改（合规零触碰 → 重跑幂等，changes=[]）
+② 只收紧不放松：字号/行距/边距只调大、绝不调小
+③ 每条修改必须能回答"为什么"：reason 带原值/目标值/规则
+
+规则解析链（resolve_rules）：
+  "default"                                  → 内置通用规则
+  journals.json id/name 命中                 → data/format_cache/{id}.json ok → fetched
+                                             → 否则 format_rules 非 placeholder → official
+                                             → 否则通用规则 + 占位说明
+  形如 "en:xxx"/"zh:xxx"（journal_directory）→ 只读查目录拿 name → 回链上一步
+  其他字符串（期刊名）                       → 回链 journals.json → 未中 → 通用 + 未匹配说明
+"""
+from __future__ import annotations
+
+import json
+import re
+from pathlib import Path
+from typing import Any
+
+# review_service/app/services/ → parents[2] = review_service/
+_ROOT = Path(__file__).resolve().parents[2]
+_SEED_PATH = _ROOT / "data" / "journals" / "journals.json"
+_CACHE_DIR = _ROOT / "data" / "format_cache"
+
+_EPS = 1e-9
+
+# 通用规则（拍板 3：与 journals.json format_rules_default 的 9/15/1.15 不同，
+# 这是重排版自己的"通用规则"口径，勿混用）
+RULES_DEFAULT: dict[str, Any] = {
+    "rules_source": "default",
+    "max_pages": 10,
+    "min_font_pt": 11,
+    "min_margin_mm": 20.0,
+    "min_line_spacing": 1.5,
+    "min_figures": 1,
+    "max_fonts": 6,
+    "refs_style": "apa",
+    "anonymous": None,
+}
+
+# 参考文献样式 → 经典 .bst（均为发行版基础件）。
+# 修正（2026-10-10）：author_year 旧映射 plain 是错的——plain.bst 是编号制 [1]；
+# author-year 制应映射 apalike.bst（Author, 2020）。apa 同理。
+REFS_BST_MAP: dict[str, str] = {
+    "apa": "apalike",
+    "author_year": "apalike",
+    "numbered": "unsrt",
+    "vancouver": "unsrt",
+    "gb7714": "gb7714",
+}
+# biblatex 工作流的 style= 建议名（与 .bst 是两套体系）
+BIBLATEX_STYLE_MAP: dict[str, str] = {
+    "apa": "apa",
+    "author_year": "authoryear",
+    "numbered": "numeric",
+    "vancouver": "numeric",
+    "gb7714": "gb7714",
+}
+
+_DOCCLASS_RE = re.compile(r"(\\documentclass)\s*(\[[^\]]*\])?\s*\{([^}]*)\}")
+_PKG_RE = re.compile(r"\\(?:usepackage|RequirePackage)\s*(\[[^\]]*\])?\s*\{([^}]*)\}")
+_SPACING_RE = re.compile(r"\\(?:linespread|setstretch)\s*\{\s*(\d+(?:\.\d+)?)\s*\}")
+_BIBSTYLE_RE = re.compile(r"\\bibliographystyle\s*\{\s*([^}]+?)\s*\}")
+_PT_RE = re.compile(r"(\d+(?:\.\d+)?)\s*pt\b")
+_BEGIN_DOC_RE = re.compile(r"\\begin\s*\{\s*document\s*\}")
+_BIBLATEX_RE = re.compile(r"\\(?:printbibliography|addbibresource)")
+
+_MM_FACTORS = {"mm": 1.0, "cm": 10.0, "in": 25.4, "inch": 25.4, "pt": 25.4 / 72.0}
+_SIDE_KEYS = ("left", "right", "top", "bottom")
+_MARGIN_ATTRS = ("margin", "hmargin", "vmargin", "left", "right", "top", "bottom",
+                 "inner", "outer")
+
+
+class ReformatError(Exception):
+    """结构畸形无法安全处理（code: PARSER_FAILED）。"""
+
+    def __init__(self, code: str, message: str) -> None:
+        super().__init__(message)
+        self.code = code
+
+
+# ================================================================ 规则解析链
+
+def _seed_entries() -> list[dict[str, Any]]:
+    try:
+        data = json.loads(_SEED_PATH.read_text("utf-8"))
+        entries = data.get("journals")
+        return [e for e in entries if isinstance(e, dict)] if isinstance(entries, list) else []
+    except (OSError, ValueError):
+        return []
+
+
+def _find_seed(text: str) -> dict[str, Any] | None:
+    low = text.strip().casefold()
+    if not low:
+        return None
+    for e in _seed_entries():
+        if str(e.get("id", "")).casefold() == low or str(e.get("name", "")).casefold() == low:
+            return e
+    return None
+
+
+def _cache_rules(journal_id: str) -> dict[str, Any] | None:
+    """data/format_cache/{id}.json（抓取+LLM 抽取产物）；ok=false/缺失 → None。"""
+    try:
+        payload = json.loads((_CACHE_DIR / f"{journal_id}.json").read_text("utf-8"))
+    except (OSError, ValueError):
+        return None
+    if not isinstance(payload, dict) or not payload.get("ok"):
+        return None
+    rules = payload.get("format_rules")
+    return rules if isinstance(rules, dict) and rules.get("rules_source") else None
+
+
+def _merged(rules: dict[str, Any]) -> dict[str, Any]:
+    """专属规则叠加在通用规则上（缺失键/显式 null 保留——fetched 的 null 是诚实未知）。"""
+    return {**RULES_DEFAULT, **rules}
+
+
+async def _directory_name(journal_id: str) -> str | None:
+    """journal_directory id → name（只读；表未连/不存在 → None，绝不抛错）。"""
+    try:
+        from ..db import db  # 惰性导入：resolver 可在无 lifespan 的测试中工作
+        row = await db.fetchone(
+            "SELECT name FROM journal_directory WHERE id = ?", (journal_id,)
+        )
+        return str(row["name"]) if row and row.get("name") else None
+    except Exception:  # noqa: BLE001 —— 查不到/未连接都按未匹配处理
+        return None
+
+
+async def resolve_rules(target: str) -> dict[str, Any]:
+    """→ {journal_id, journal_name, rules, rules_source, rules_note}（永不失败）。"""
+    target = (target or "").strip()
+
+    if target == "default":
+        return {
+            "journal_id": "default",
+            "journal_name": "通用规则",
+            "rules": dict(RULES_DEFAULT),
+            "rules_source": "default",
+            "rules_note": "通用规则（APA + 通用论文规范）",
+        }
+
+    display_name = target
+    entry = _find_seed(target)
+    if entry is None and ":" in target:
+        # journal_directory id（en:0028-0836 / zh:slug）→ 目录查 name → 再回链种子
+        name = await _directory_name(target)
+        if name:
+            display_name = name
+            entry = _find_seed(name)
+    elif entry is None:
+        display_name = target  # 直接当期刊名回链
+
+    if entry is not None:
+        jid = str(entry.get("id") or "")
+        jname = str(entry.get("name") or display_name)
+        cached = _cache_rules(jid)
+        if cached:
+            return {
+                "journal_id": jid, "journal_name": jname, "rules": _merged(cached),
+                "rules_source": "fetched",
+                "rules_note": "该刊规则来自官网抓取 + LLM 抽取（data/format_cache，待人工核验）",
+            }
+        fr = entry.get("format_rules") if isinstance(entry.get("format_rules"), dict) else {}
+        if fr and fr.get("rules_source") not in (None, "placeholder", "default"):
+            return {
+                "journal_id": jid, "journal_name": jname, "rules": _merged(fr),
+                "rules_source": str(fr.get("rules_source")),
+                "rules_note": "journals.json 期刊专属规则",
+            }
+        return {
+            "journal_id": jid, "journal_name": jname, "rules": dict(RULES_DEFAULT),
+            "rules_source": "default",
+            "rules_note": f"「{jname}」在 journals.json 中仅有占位规则（placeholder），已用通用规则",
+        }
+
+    return {
+        "journal_id": None,
+        "journal_name": display_name or target,
+        "rules": dict(RULES_DEFAULT),
+        "rules_source": "default",
+        "rules_note": f"未匹配到「{display_name or target}」的专属格式规则，已用通用规则",
+    }
+
+
+# ================================================================ 变换器工具
+
+def _change(line_no: int, original: str, modified: str, reason: str,
+            rule_key: str, action: str) -> dict[str, Any]:
+    return {
+        "line": line_no,
+        "original": original.rstrip("\n"),
+        "modified": modified.rstrip("\n"),
+        "reason": reason,
+        "rule_key": rule_key,
+        "action": action,
+    }
+
+
+def _warning_change(line_no: int, original: str, reason: str, rule_key: str) -> dict[str, Any]:
+    return _change(line_no, original, "", reason, rule_key, "warning")
+
+
+def _parse_mm(raw: str) -> float | None:
+    """geometry 长度值 → mm；裸数字按 TeX 惯例 pt（同 format_check 先例）；未知 → None。"""
+    m = re.fullmatch(r"\s*(\d+(?:\.\d+)?)\s*([A-Za-z]*)\s*", raw or "")
+    if not m:
+        return None
+    unit = (m.group(2) or "pt").lower()
+    factor = _MM_FACTORS.get(unit)
+    if factor is None:
+        return None
+    return float(m.group(1)) * factor
+
+
+def _fmt(v: float) -> str:
+    return f"{v:g}"
+
+
+# ================================================================ ① 字号 font_pt
+
+def _transform_font(lines: list[str], orig: list[str], rules: dict[str, Any],
+                    doc_idx: int) -> list[dict[str, Any]]:
+    min_pt = rules.get("min_font_pt")
+    if min_pt is None:
+        return []
+    min_pt = float(min_pt)
+    line = lines[doc_idx]
+    m = _DOCCLASS_RE.search(line)
+    if not m:  # 守卫已保证，理论不可达
+        return []
+    opts = m.group(2)  # "[...]" 或 None
+    cls = m.group(3).strip()
+    opts_inner = opts[1:-1] if opts else ""
+    pt_m = _PT_RE.search(opts_inner)
+
+    if pt_m is None:
+        # 拍板 2：选项缺失不自动加 → warning + 建议片段
+        if opts_inner:
+            suggestion = f"\\documentclass[{opts_inner}, {_fmt(min_pt)}pt]{{{cls}}}"
+        else:
+            suggestion = f"\\documentclass[{_fmt(min_pt)}pt]{{{cls}}}"
+        return [_warning_change(
+            doc_idx + 1, orig[doc_idx],
+            f"未检测到字号选项，无法核验正文字号（目标下限 {_fmt(min_pt)}pt），"
+            f"建议手动声明：{suggestion}",
+            "font_pt",
+        )]
+
+    cur = float(pt_m.group(1))
+    if cur >= min_pt - _EPS:
+        return []
+    target = next((s for s in (10, 11, 12) if s >= min_pt - _EPS), min_pt)
+    new_inner = opts_inner[:pt_m.start(1)] + _fmt(target) + opts_inner[pt_m.end(1):]
+    new_line = line[:m.start(2) + 1] + new_inner + line[m.start(2) + 1 + len(opts_inner):]
+    lines[doc_idx] = new_line
+    return [_change(
+        doc_idx + 1, orig[doc_idx], new_line,
+        f"正文字号 {_fmt(cur)}pt 低于目标下限 {_fmt(min_pt)}pt，改为 {_fmt(target)}pt",
+        "font_pt", "modified",
+    )]
+
+
+# ================================================================ ② 页边距 margin
+
+def _find_geometry(lines: list[str]) -> tuple[int, re.Match] | None:
+    for i, line in enumerate(lines):
+        for m in _PKG_RE.finditer(line):
+            pkgs = [p.strip().lower() for p in m.group(2).split(",")]
+            if "geometry" in pkgs:
+                return i, m
+    return None
+
+
+def _patch_attr(line: str, key: str, new_val: str) -> str:
+    """geometry 选项里 key=old → key=new（首个匹配）。
+
+    值止于 `,` 或 `]`——绝不能吞掉 `]{geometry}` 尾巴（否则下一轮就找不到
+    geometry 宏包，破坏幂等）。key 带 \\b 防 hmargin/margin 互撞。
+    """
+    return re.sub(rf"(\b{key}\s*=\s*)([^,\]]+)", lambda m: m.group(1) + new_val,
+                  line, count=1)
+
+
+def _transform_margin(lines: list[str], orig: list[str], rules: dict[str, Any],
+                      doc_idx: int) -> list[dict[str, Any]]:
+    min_mm = rules.get("min_margin_mm")
+    if min_mm is None:
+        return []
+    min_mm = float(min_mm)
+    out: list[dict[str, Any]] = []
+    found = _find_geometry(lines)
+
+    if found is None:
+        return [_warning_change(
+            doc_idx + 1, orig[doc_idx],
+            f"未检测到 geometry 宏包，无法核验页边距（目标下限 {_fmt(min_mm)}mm），"
+            f"建议手动添加：\\usepackage[margin={_fmt(min_mm)}mm]{{geometry}}"
+            f"（置于 \\documentclass 之后）",
+            "margin",
+        )]
+
+    gi, gm = found
+    opts = gm.group(1)
+    if opts is None:
+        # \usepackage{geometry} 裸用 → 建议加选项（拍板 2 不自动改）
+        return [_warning_change(
+            gi + 1, orig[gi],
+            f"geometry 未设置边距选项，无法核验页边距（目标下限 {_fmt(min_mm)}mm），"
+            f"建议手动改为：\\usepackage[margin={_fmt(min_mm)}mm]{{geometry}}",
+            "margin",
+        )]
+    opts_inner = opts[1:-1]
+    attrs: dict[str, str] = {}
+    for part in opts_inner.split(","):
+        if "=" in part:
+            k, _, v = part.partition("=")
+            attrs[k.strip().lower()] = v.strip()
+
+    present = [k for k in _MARGIN_ATTRS if k in attrs]
+    if not present:
+        return [_warning_change(
+            gi + 1, orig[gi],
+            f"geometry 未设置边距相关选项（目标下限 {_fmt(min_mm)}mm），"
+            f"建议在现有选项中添加：margin={_fmt(min_mm)}mm",
+            "margin",
+        )]
+
+    # 逐边解析提供者（side > h/vmargin > margin；inner/outer 单独按自身长度评）
+    def provider_for(side: str) -> str | None:
+        if side in attrs:
+            return side
+        if side in ("left", "right") and "hmargin" in attrs:
+            return "hmargin"
+        if side in ("top", "bottom") and "vmargin" in attrs:
+            return "vmargin"
+        if "margin" in attrs:
+            return "margin"
+        if side in ("left", "right") and "inner" in attrs:
+            return "inner"  # 见下：inner/outer 单独评估，此处不按边处理
+        if side in ("left", "right") and "outer" in attrs:
+            return "outer"
+        return None
+
+    patch_keys: dict[str, str] = {}      # attr → 新值（同键只抬一次）
+    reasons: list[str] = []
+    unresolved: list[str] = []
+
+    for side in _SIDE_KEYS:
+        pkey = provider_for(side)
+        if pkey in ("inner", "outer"):
+            continue  # 由下方 inner/outer 评估负责
+        if pkey is None:
+            unresolved.append(side)
+            continue
+        mm = _parse_mm(attrs.get(pkey, ""))
+        if mm is None:
+            unresolved.append(side)
+            continue
+        if mm < min_mm - _EPS and pkey not in patch_keys:
+            patch_keys[pkey] = f"{_fmt(min_mm)}mm"
+            reasons.append(f"页边距 {side}({_fmt(mm)}mm) 低于下限 {_fmt(min_mm)}mm → {_fmt(min_mm)}mm")
+
+    for key in ("inner", "outer"):
+        if key in attrs:
+            mm = _parse_mm(attrs[key])
+            if mm is None:
+                unresolved.append(key)
+            elif mm < min_mm - _EPS and key not in patch_keys:
+                patch_keys[key] = f"{_fmt(min_mm)}mm"
+                reasons.append(f"页边距 {key}({_fmt(mm)}mm) 低于下限 {_fmt(min_mm)}mm → {_fmt(min_mm)}mm")
+
+    out: list[dict[str, Any]] = []
+    if patch_keys:
+        new_line = lines[gi]
+        for key, val in patch_keys.items():
+            new_line = _patch_attr(new_line, key, val)
+        lines[gi] = new_line
+        out.append(_change(
+            gi + 1, orig[gi], new_line, "；".join(reasons), "margin", "modified",
+        ))
+
+    if unresolved:
+        uniq = "、".join(dict.fromkeys(unresolved))
+        out.append(_warning_change(
+            gi + 1, orig[gi],
+            f"geometry 未设置/无法解析 {uniq} 边（沿用类默认，无法核验），"
+            f"建议显式声明：{uniq}={_fmt(min_mm)}mm",
+            "margin",
+        ))
+    return out
+
+
+# ================================================================ ③ 行距 line_spacing
+
+def _transform_spacing(lines: list[str], orig: list[str], rules: dict[str, Any],
+                       doc_idx: int) -> list[dict[str, Any]]:
+    min_ls = rules.get("min_line_spacing")
+    if min_ls is None:
+        return []
+    min_ls = float(min_ls)
+
+    # 只看导言区（\begin{document} 之前）；正文中的 \setstretch 是局部覆盖，不碰
+    end = len(lines)
+    for i, line in enumerate(lines):
+        if _BEGIN_DOC_RE.search(line):
+            end = i
+            break
+    records: list[tuple[int, re.Match]] = []
+    for i in range(end):
+        for m in _SPACING_RE.finditer(lines[i]):
+            records.append((i, m))
+
+    if not records:
+        return [_warning_change(
+            doc_idx + 1, orig[doc_idx],
+            f"未在导言区检测到 \\linespread 或 \\setstretch，无法核验行距"
+            f"（目标下限 {_fmt(min_ls)}），建议手动添加到导言区："
+            f"\\linespread{{{_fmt(min_ls)}}}",
+            "line_spacing",
+        )]
+
+    i, m = records[-1]  # 最后一次出现者生效（LaTeX 后设覆盖前设）
+    cur = float(m.group(1))
+    if cur >= min_ls - _EPS:
+        return []
+    new_line = lines[i][:m.start(1)] + _fmt(min_ls) + lines[i][m.end(1):]
+    lines[i] = new_line
+    return [_change(
+        i + 1, orig[i], new_line,
+        f"行距 {_fmt(cur)} 低于目标下限 {_fmt(min_ls)}，改为 {_fmt(min_ls)}",
+        "line_spacing", "modified",
+    )]
+
+
+# ================================================================ ④ 参考文献 bib_style
+
+def _transform_bib(lines: list[str], orig: list[str], rules: dict[str, Any],
+                   doc_idx: int) -> list[dict[str, Any]]:
+    style = str(rules.get("refs_style") or "").strip().lower()
+    if not style:
+        # 规则未提供已确认的 refs_style（如 Frontiers 两种制式并存待核实）：
+        # 绝不猜测改写用户样式——保持原样 + warning 提示（拍板 2026-10-10）
+        return [_warning_change(
+            doc_idx + 1, orig[doc_idx],
+            "该刊引用风格未确认，未改动 \\bibliographystyle；"
+            "建议人工核实期刊投稿指南后再调整",
+            "bib_style",
+        )]
+
+    m = next((mm for line in lines if (mm := _BIBSTYLE_RE.search(line))), None)
+    if m is not None:
+        i = next(idx for idx, line in enumerate(lines) if _BIBSTYLE_RE.search(line))
+        cur = m.group(1).strip()
+        if style not in REFS_BST_MAP:
+            return [_warning_change(
+                i + 1, orig[i],
+                f"目标参考文献样式 {style} 无对应标准 .bst，未替换"
+                f"（当前 \\bibliographystyle{{{cur}}}），请按目标期刊模板手动选择样式",
+                "bib_style",
+            )]
+        target = REFS_BST_MAP[style]
+        if cur.casefold() == target.casefold():
+            return []
+        new_line = lines[i][:m.start(1)] + target + lines[i][m.end(1):]
+        lines[i] = new_line
+        hint = "（需 gbt7714 宏包）" if target == "gb7714" else ""
+        return [_change(
+            i + 1, orig[i], new_line,
+            f"参考文献样式要求 {style}：\\bibliographystyle{{{cur}}} → {{{target}}}{hint}",
+            "bib_style", "modified",
+        )]
+
+    has_biblatex = any(_BIBLATEX_RE.search(line) for line in lines)
+    if has_biblatex:
+        suggest = BIBLATEX_STYLE_MAP.get(style, style)
+        return [_warning_change(
+            doc_idx + 1, orig[doc_idx],
+            f"检测到 biblatex 工作流（未找到 \\bibliographystyle），"
+            f"请在 \\printbibliography 选项中手动配置：style={suggest}（对应 {style}）",
+            "bib_style",
+        )]
+
+    if style in REFS_BST_MAP:
+        target = REFS_BST_MAP[style]
+        return [_warning_change(
+            doc_idx + 1, orig[doc_idx],
+            f"未检测到 \\bibliographystyle，建议手动添加：\\bibliographystyle{{{target}}}"
+            f"（对应 {style}）",
+            "bib_style",
+        )]
+    return [_warning_change(
+        doc_idx + 1, orig[doc_idx],
+        f"未检测到 \\bibliographystyle，目标样式 {style} 无标准 .bst 映射，"
+        f"请按期刊模板手动配置",
+        "bib_style",
+    )]
+
+
+# ================================================================ 入口
+
+def reformat_tex(source: str, rules: dict[str, Any]) -> dict[str, Any]:
+    """源码 + 规则 → {modified_tex, changes[], warnings[]}。
+
+    结构守卫：0 处 \\documentclass → ReformatError(PARSER_FAILED)；
+    >1 处 → 只处理第一处 + warnings 补 MULTI_DOCUMENTCLASS。
+    """
+    lines = source.splitlines(keepends=True)
+    doc_idxs = [i for i, line in enumerate(lines) if _DOCCLASS_RE.search(line)]
+    if not doc_idxs:
+        raise ReformatError(
+            "PARSER_FAILED",
+            "未找到 \\documentclass{...}：无法确定主文档"
+            "（P1 不支持由 \\input 拆分的多文件工程，请上传完整单文件源码）",
+        )
+    warnings: list[dict[str, str]] = []
+    if len(doc_idxs) > 1:
+        warnings.append({
+            "code": "MULTI_DOCUMENTCLASS",
+            "message": f"检测到 {len(doc_idxs)} 处 \\documentclass，"
+                       f"仅处理第一处（第 {doc_idxs[0] + 1} 行）",
+        })
+    doc_idx = doc_idxs[0]
+    orig = list(lines)  # 纯净快照：所有 change.original 取自这里
+
+    changes: list[dict[str, Any]] = []
+    changes += _transform_font(lines, orig, rules, doc_idx)
+    changes += _transform_margin(lines, orig, rules, doc_idx)
+    changes += _transform_spacing(lines, orig, rules, doc_idx)
+    changes += _transform_bib(lines, orig, rules, doc_idx)
+    changes.sort(key=lambda c: c["line"])
+
+    return {"modified_tex": "".join(lines), "changes": changes, "warnings": warnings}
@@ -0,0 +1,223 @@
+"""services/self_review.py —— 植物基因组学专属自审稿（System Prompt + 报告模型）。
+
+六大领域维度检查清单硬编码在 SYSTEM_PROMPT（发给 DeepSeek）：
+1. 基因组组装质量（N50/L50/BUSCO 完整格式/Hi-C 挂载率；硬性缺项打 hard_rule 标签）
+2. 基因注释可靠性（MAKER/AUGUSTUS 流程、RNA-seq 证据、基因数与已知范围一致性）
+3. 比较基因组学与进化（Bootstrap/后验概率、OrthoFinder 等直系同源策略）
+4. 数据可用性合规（SRA/BioProject + 组装/GFF3 Accession，缺失即硬性 major）
+5. 统计与实验设计（GWAS/QTL 样本量·多重校正·群体结构；转录组生物学重复）
+6. 伦理与合规·植物特异性（凭证标本 voucher、ABS 惠益分享声明——均为硬性 major）
+
+2026-10-12 判定链重构：LLM 不再输出 recommendation（旧配额制 "major 3-8 条" 导致
+accept/minor 几乎不可达，见 recommend_engine.py 模块 docstring）；只如实列 weakness
+并打 hard_rule/fatal 标签，recommendation 由规则引擎计算。Major/Minor 每条必须给
+Evidence（论文章节位置或具体指标数值），由 coerce 宽容归一化（缺失补空串，不丢条目）。
+"""
+from __future__ import annotations
+
+from typing import Any
+
+from pydantic import BaseModel, Field
+
+from .recommend_engine import HARD_RULE_TAGS
+
+SYSTEM_PROMPT = """你是一位植物基因组学领域资深审稿人，长期为 Plant Cell、Nature Plants、
+Genome Biology、Molecular Plant、Plant Journal 等期刊审稿。请对用户提供的论文正文做
+投稿前自审（pre-submission self review），严格按以下六个植物基因组学专属维度逐项检查，
+输出结构化审稿意见。所有条目使用中文撰写（专业术语、指标名、工具名保留英文）。
+
+【维度一：基因组组装质量】必查指标：
+- contig N50 / scaffold N50 / L50（报了哪个要写明哪个）
+- BUSCO 完整度：必须按完整格式报告——例如
+  "Complete 95.3% [S:93.1%, D:2.2%], Missing 4.7%, n=1614 (embryophyta_odb10)"
+  （含 Complete/Single-copy/Duplicated/Missing 四项与数据集版本、n 值）
+- Hi-C 挂载率（anchoring rate，chromosome-level 比例）及挂载到染色体的 scaffold 比例
+BUSCO 完整度三级判定：
+- 完全未提 BUSCO → Major Weakness，hard_rule="busco_missing"
+- 提了 BUSCO 但只有总百分比（如 98.57%），缺 Single-copy/Duplicated/Missing
+  分项或数据集版本（如 n=1614, embryophyta_odb10）→ 列 Minor（不打 hard_rule）
+- 完整格式（如 Complete 95.3% [S:93.1%, D:2.2%], Missing 4.7%, n=1614）→ 通过，不列
+Hi-C/挂载率报告识别（命中任一且给出数值即视为已报告，不得判缺）：
+anchoring rate / anchored to chromosome(s) / % of sequences anchored /
+pseudo-chromosome(s) / chromosome-level 挂载比例。
+判定规则：若组装类论文只报 N50 而未报 BUSCO 且未报 Hi-C 挂载率，列为
+Major Weakness 并打对应 hard_rule 标签（BUSCO 缺失→"busco_missing"；宣称
+chromosome-level/Hi-C 挂载但未报挂载率→"hic_missing"）。同时检查组装是否为
+pseudo-chromosome 级别、污染评估（如 k-mer/coverage 检查）与 gap 比例。
+
+【维度二：基因注释可靠性】检查：
+- 是否使用标准注释流程（MAKER、AUGUSTUS、BRAKER、GeMoMa、EVidenceModeler 等），参数与版本是否交代
+- 是否有转录组证据支持：RNA-seq（组织/时期/物种内或近缘种）比对支撑比例，或蛋白同源证据
+- 基因数量是否与该物种已知基因数范围一致（如水稻 ~37-40k、拟南芥 ~27k、玉米 ~39-45k、
+  小麦 ~107k、大豆 ~46k；近缘种偏差过大须说明）；有无转座元件基因误注释的排查
+- 注释质量评估：BRAKER/AED 分值、BUSCO 在蛋白集上的复核
+
+【维度三：比较基因组学与进化】检查：
+- 系统发育树：每个节点建议标注 Bootstrap 支持率（建议 ≥1000 次重复）或贝叶斯后验概率。
+  分诊：
+  * 完全未做节点支持率分析（方法与正文均无任何声明）且支撑核心进化结论 → Major
+  * 方法/正文声明已做 bootstrap 或后验概率，仅图中未标注数值 → presentation_format
+    （图注补标即可，不需重跑分析）
+  * 附带性质的树无支持率 → Minor
+- 直系同源基因鉴定策略是否说明清楚：OrthoFinder/OrthoMCL/RBX 等工具、版本、参数、
+  聚类阈值（inflation/coverage）、single-copy 标记基因的筛选方式
+- 分子进化分析是否规范：dN/dS 检验方法与多重校正、共线性（synteny）分析参数、
+  分化时间估算是否校准（化石/二次校准点）
+
+【维度四：数据可用性合规——极其重要】必查（在 Data Availability 节或
+Methods 数据声明处核对，不因正文引用他人数据的 accession 而误判）：
+- 原始测序数据是否上传公共数据库并给出 Accession 号。前缀清单：
+  PRJNA/PRJEB（NCBI/ENA BioProject）、PRJCA/CRA（中国 NGDC/GSA）、
+  SRP/ERP/DRP（SRA 项目）、SRR/ERR/DRR（run 级号）——命中任一即视为已有
+  原始数据 accession
+- 基因组组装是否有 GenBank/ENA accession（GCA_/GCF_），GFF3 注释文件、
+  蛋白/CDS 文件是否有可公开获取的位置（仓库 accession 或补充数据链接）
+- 转录组数据是否同样有 SRA accession
+判定规则：组装/注释类论文若缺失上述任何一环（含 "will be deposited" 等未给号的
+承诺式表述），列为 Major Weakness 并打 hard_rule 标签 "accession_missing"。
+
+【维度五：统计与实验设计】检查：
+- GWAS/QTL 定位：样本量/群体大小是否充分；多重检验校正是否明确（Bonferroni/FDR/
+  permutation 阈值/PCA 显著性水平）；群体结构控制（PCA、亲缘关系矩阵 K、分层分析）
+  是否交代；表型测量描述是否充分
+- 转录组分析：生物学重复数量（≥3 为底线）、差异分析工具（DESeq2/edgeR 等）与
+  校正方法、批次效应处理、|log2FC| 与 padj 阈值
+- 其他统计：t 检验/ANOVA 是否满足前提、重复类型（生物学 vs 技术重复）写明与否
+
+【维度六：伦理与合规（植物特异性）】检查：
+- 野生植物材料：是否提供凭证标本（voucher specimen）信息——标本馆编号、存放机构、
+  采集地点（GPS）与采集许可；无凭证标本的野生资源取样 → Major Weakness 并打
+  hard_rule 标签 "voucher_missing"
+- 遗传资源获取与惠益分享（ABS）合规性：是否声明符合《名古屋议定书》/本国遗传资源
+  获取条例（如中国《生物安全法》/《种子法》相关条款）、是否说明材料来源与授权；
+  涉及遗传资源但缺 ABS/名古屋合规声明 → Major Weakness 并打 hard_rule 标签
+  "abs_missing"
+- 农业转基因/基因编辑材料的合规声明（若涉及）
+- fatal 标签：仅当你发现明确的数据造假或伦理违规证据时，将该条 "fatal" 置 true
+  （数据内部矛盾、明显编造迹象等；无明确证据绝不可打标——该标签会触发拒稿建议）。
+
+输出要求（必须输出单个 JSON 对象，不要输出其他任何内容；不要输出 recommendation
+字段——推荐结论由程序规则引擎根据你列出的问题与标签计算）：
+{
+  "summary": "总体评价（3-5 句，须点明论文类型与所适用的维度）",
+  "major_weaknesses": [{"title": "...", "detail": "...", "evidence": "...", "suggestion": "...",
+                        "hard_rule": "busco_missing|hic_missing|accession_missing|voucher_missing|abs_missing|null",
+                        "fatal": false}],
+  "minor_weaknesses": [{"title": "...", "detail": "...", "evidence": "...", "suggestion": "..."}],
+  "presentation_format": [{"title": "...", "detail": "...", "evidence": "...", "suggestion": "..."}],
+  "questions_for_authors": ["..."]
+}
+
+【严重程度分级——据此分类，不设条数配额】
+- major_weaknesses：问题的解决需要补充实验/补充数据/补充分析流程/大幅改写论证结构，
+  或影响论文核心结论的可信度与数据合规性。列在这里意味着"不解决就不能发表"。
+- minor_weaknesses：在现有数据与实验范围内即可解决（补一段说明、补一个基于已有数据的
+  统计、澄清方法描述、局部重写）。列在这里意味着"改了更好，不改也能审"。
+- presentation_format：仅呈现层面的问题（图表样式、图注格式、参考文献体例、语法）。
+  严禁把呈现问题升格为 major。
+
+【负向清单——以下情况严禁列为 major_weaknesses，按对应类别归档】
+- 图表未标注统计量（bootstrap 数值/误差棒/显著性标记/P 值），但方法或正文已声明
+  做过该分析 → presentation_format 或 minor_weaknesses
+- 方法描述不够详细，但所用方法是领域标准做法且论证逻辑完整 → minor_weaknesses
+- 阈值/参数未给出具体数值，但逻辑完整且结论不依赖精确数值 → minor_weaknesses
+- 引用格式/排版/图注体例/语法 → presentation_format
+- 标准流程的合理省略（如 IQ-TREE/DESeq2 等工具默认参数未逐一列出）→ 不列
+总纲：只有"需要补做实验/补数据/重跑分析/改核心论证"的问题才允许列为 major；
+      其余一律 minor 或 presentation。与上文各维度冲突时以本节为准。
+
+分级与条数规则：
+1. major_weaknesses、minor_weaknesses、presentation_format 均【不设下限，可以为 0 条】。
+   论文确实完善时输出空数组是正确答案；严禁为凑数而降低分级标准或制造问题。
+2. **每条 major_weaknesses 的 evidence 字段必填**：必须引用论文的具体章节位置
+   （如 "Methods 2.1"、"Table 2"、"Results 第 3 段"、"Data Availability 一句话未见"）
+   或具体指标数值（如 "仅报 scaffold N50=42.6 Mb，未提供 BUSCO 与 Hi-C 挂载率"）。
+   evidence 严禁编造：引用不到具体位置时，写明"正文未见相关报告"。只列有 evidence
+   的问题：列不出具体章节位置或指标数值的问题，不要列。
+3. minor_weaknesses/presentation_format 的 evidence 尽量给出，无法定位时可留空字符串。
+4. 论文不涉及的维度（如纯 RNA-seq 论文不谈组装）在 summary 中说明并跳过，不硬凑条目。
+5. 宁可把拿不准严重程度的问题放 minor_weaknesses（由作者判断），不要放 major。
+
+硬性规则（命中必须列 major 并打 hard_rule 标签，不论其他方面多完善；规则不可协商）：
+A. 组装类论文缺 BUSCO 完整格式报告 → hard_rule="busco_missing"
+B. 宣称 chromosome-level/Hi-C 挂载但未报挂载率 → hard_rule="hic_missing"
+C. 缺数据 Accession（SRA/GenBank/组装/GFF3；"will be deposited" 等承诺式表述视为缺）
+   → hard_rule="accession_missing"
+D. 野生植物材料缺凭证标本（voucher）→ hard_rule="voucher_missing"
+E. 涉及遗传资源但缺 ABS/名古屋合规声明 → hard_rule="abs_missing"
+（核心进化结论所依赖的系统发育树若**完全未做**节点支持率分析 → 列 major（非硬性，
+  不打标签）；若方法/正文已声明分析但图中未标数值 → presentation/minor；附带性质
+  的树无支持率 → minor。GWAS 缺多重校正等统计问题按同样原则判级：阈值/方法完全
+  缺失且影响结论 → major；已声明校正逻辑仅缺细节 → minor。）
+
+presentation_format 覆盖：图表规范（图注含单位/误差棒说明）、参考文献格式、
+字数与结构、英文语法（若投英文刊）。
+"""
+
+
+class WeaknessItem(BaseModel):
+    title: str
+    detail: str = ""
+    evidence: str = ""
+    suggestion: str = ""
+    hard_rule: str | None = None   # 仅 major 可带；白名单外置 None（见 coerce）
+    fatal: bool = False            # 明确造假/伦理证据才可 true（触发 R0 拒稿）
+    # 扫描器冲突降级标记（程序层置位，LLM 输出不读/coerce 不透传 → 不可伪造）：
+    # True 表示该条原为 major，因关键词扫描器证伪其 hard_rule 缺项声明被降级至 minor
+    scanner_downgraded: bool = False
+
+
+class SelfReviewReport(BaseModel):
+    summary: str = ""
+    major_weaknesses: list[WeaknessItem] = Field(default_factory=list)
+    minor_weaknesses: list[WeaknessItem] = Field(default_factory=list)
+    presentation_format: list[WeaknessItem] = Field(default_factory=list)
+    questions_for_authors: list[str] = Field(default_factory=list)
+    # recommendation 由 recommend_engine 计算后写入；LLM 输出的同名字段一律忽略
+    recommendation: str = ""
+    recommendation_rationale: dict[str, Any] = Field(default_factory=dict)
+
+
+def build_user_prompt(text: str, target_journal: str) -> str:
+    header = f"目标期刊：{target_journal}\n\n" if target_journal else ""
+    return f"{header}论文正文：\n\n{text}"
+
+
+def _coerce_items(raw: object) -> list[WeaknessItem]:
+    items: list[WeaknessItem] = []
+    if not isinstance(raw, list):
+        return items
+    for entry in raw:
+        if isinstance(entry, str) and entry.strip():
+            items.append(WeaknessItem(title=entry.strip()))
+        elif isinstance(entry, dict):
+            title = str(entry.get("title") or "").strip()
+            detail = str(entry.get("detail") or "").strip()
+            if not title and not detail:
+                continue
+            hard_rule = str(entry.get("hard_rule") or "").strip() or None
+            if hard_rule not in HARD_RULE_TAGS:
+                hard_rule = None  # 白名单外的标签丢弃（防 LLM 编造标签操纵引擎）
+            items.append(WeaknessItem(
+                title=title or "（未命名）",
+                detail=detail,
+                evidence=str(entry.get("evidence") or "").strip(),
+                suggestion=str(entry.get("suggestion") or "").strip(),
+                hard_rule=hard_rule,
+                fatal=bool(entry.get("fatal")),
+            ))
+    return items
+
+
+def coerce_report(payload: dict) -> SelfReviewReport:
+    """宽容归一化 LLM 输出。不读 recommendation 字段（引擎唯一来源，防注入操纵）。"""
+    questions = payload.get("questions_for_authors") or []
+    if not isinstance(questions, list):
+        questions = []
+    return SelfReviewReport(
+        summary=str(payload.get("summary") or "").strip(),
+        major_weaknesses=_coerce_items(payload.get("major_weaknesses")),
+        minor_weaknesses=_coerce_items(payload.get("minor_weaknesses")),
+        presentation_format=_coerce_items(payload.get("presentation_format")),
+        questions_for_authors=[str(q).strip() for q in questions if str(q).strip()],
+    )
@@ -0,0 +1,288 @@
+r"""services/zip_safety.py —— LaTeX 项目 zip 安全校验与解压（P4，纯函数模块）。
+
+安全清单（每条攻击 → 防御位置，对应设计 §2）：
+  #1  路径穿越 ../../etc/passwd   → sanitize_entry_name：拒绝 .. 段/绝对路径/盘符/空段
+                                    （\ 已先归一为 /，Windows 反斜杠变体同规则）
+  #2  反斜杠变体 ..\\..\\x         → 同上（name.replace("\\\\", "/") 后再校验）
+  #3  符号链接条目                 → _is_symlink：external_attr 的 S_IFMT == S_IFLNK → 整包拒绝
+  #4  可执行扩展名 .exe/.sh/.so    → classify_entry：DENY_EXT → 整包拒绝（点名条目）
+  #5  Unix 可执行位 0o111          → _has_exec_bit：普通文件带 x 位 → 整包拒绝（目录 0o755 例外）
+  #6  无害非白名单 .docx/.log/.zip → classify_entry：skip（记 skipped[]；.zip 跳过=天然防嵌套递归）
+  #7  zip bomb 压缩比              → 预扫 file_size/compress_size > max_zip_ratio → ZIP_BOMB
+  #8  zip bomb 总量                → 预扫声明累计 > max_extract_bytes → ZIP_BOMB；
+                                    流式写盘按**实际字节**再计数（不信头部声明）超限即中止
+  #9  zip bomb 单条目              → 预扫 file_size > max_entry_bytes → ZIP_BOMB；实写计数兜底
+  #10 zip bomb 条目数              → 预扫 len(infolist) > max_zip_entries → ZIP_BOMB（先于一切写盘）
+  #11 深嵌套/超长路径              → 路径深度 > max_path_depth 或总长 > max_path_len → ZIP_UNSAFE
+  #12 损坏/加密 zip                → zipfile.BadZipFile / RuntimeError → ZIP_INVALID
+  #13 头部谎报小文件               → 实写计数兜底（#8）；CRC 错 → ZIP_INVALID
+  #14 恶意 .tex shell escape       → 不在本模块范围（tectonic --untrusted 防护，P3a 已实证）
+  #15 解压阻塞事件循环             → 调用方 asyncio.to_thread 包裹；本模块上限 200MB/2000 条封顶
+
+设计要点：
+  - 两段式：①纯预扫（所有结构性检查，全部通过才开始写）→ ②流式写盘（8KB 块 + 实字节计数）。
+    任何异常 → 调用方 rmtree(dest)，磁盘零残留。
+  - 绝不 extractall；绝不保留可执行位（写盘一律 0o644）。
+  - 目录条目只建不校验扩展名；SKIP_DIRS 整目录跳过（补充 4 提示对应）。
+
+纯函数：输入 bytes/路径/Settings，输出 ExtractResult 或抛 ZipSafetyError，无 FastAPI/asyncio 依赖。
+"""
+from __future__ import annotations
+
+import io
+import re
+import stat
+import zipfile
+from dataclasses import dataclass, field
+from pathlib import Path, PurePosixPath
+from typing import Literal
+
+# 危险类型（deny → 整包拒绝）
+DENY_EXT = {
+    ".exe", ".com", ".bat", ".cmd", ".sh", ".bash", ".ps1", ".vbs",
+    ".dll", ".so", ".dylib", ".msi", ".jar", ".py", ".rb", ".pl", ".php", ".js",
+}
+# LaTeX 项目白名单（allow → 解压）
+ALLOW_EXT = {
+    ".tex", ".cls", ".sty", ".bst", ".bib", ".bbl", ".blg", ".def", ".clo",
+    ".fd", ".cfg", ".ist", ".dtx", ".ins",
+    ".png", ".jpg", ".jpeg", ".pdf", ".eps", ".svg",
+    ".txt", ".md", ".csv", ".dat", ".ttf", ".otf",
+}
+# 无扩展名白名单
+ALLOW_BARE = {"README", "LICENSE", "Makefile", ".gitignore"}
+# 整目录跳过（不进 skipped 计数之外的拒绝路径，直接 skip）
+SKIP_DIRS = {".git", "node_modules", "__MACOSX"}
+
+
+class ZipSafetyError(Exception):
+    """zip 不安全/超限/损坏。code ∈ {ZIP_UNSAFE, ZIP_BOMB, ZIP_INVALID}。"""
+
+    def __init__(self, code: str, message: str, entry: str = "") -> None:
+        super().__init__(message)
+        self.code = code
+        self.message = message
+        self.entry = entry
+
+
+@dataclass
+class SkippedEntry:
+    name: str
+    reason: str
+
+
+@dataclass
+class ExtractResult:
+    files: int = 0
+    tex: int = 0
+    images: int = 0
+    cls: int = 0
+    bib: int = 0
+    other: int = 0
+    bytes: int = 0
+    skipped: list[SkippedEntry] = field(default_factory=list)
+    skipped_count: int = 0
+
+
+_IMG_EXT = {".png", ".jpg", ".jpeg", ".eps", ".svg"}
+_BARE_RE = re.compile(r"^[A-Za-z]:")   # 盘符
+_CTRL_RE = re.compile(r"[\x00-\x1f]")  # 控制字符
+
+
+def sanitize_entry_name(raw: str) -> str:
+    """归一 + 校验条目名，返回 posix 相对路径；不安全 → ZIP_UNSAFE。
+
+    拒绝：绝对路径（/ 或 \\ 开头）、盘符（C:）、任一段 `..`、空段、NUL/控制字符。
+    """
+    name = raw.replace("\\", "/")
+    if not name or name in ("/", "."):
+        raise ZipSafetyError("ZIP_UNSAFE", f"zip 含空条目名：{raw!r}", raw)
+    if name.startswith("/") or _BARE_RE.match(name):
+        raise ZipSafetyError("ZIP_UNSAFE", f"zip 含绝对路径条目：{raw}", raw)
+    if _CTRL_RE.search(name):
+        raise ZipSafetyError("ZIP_UNSAFE", f"zip 条目名含控制字符：{raw!r}", raw)
+    segs = name.split("/")
+    if any(s == ".." for s in segs):
+        raise ZipSafetyError("ZIP_UNSAFE", f"zip 含路径穿越条目：{raw}", raw)
+    # 空段（//）拒绝；尾段为 ""（目录 / 结尾）在除末位外的段上已由 split 覆盖
+    if any(s == "" for s in segs[:-1]) or (segs and segs[0] == ""):
+        raise ZipSafetyError("ZIP_UNSAFE", f"zip 含非法路径条目：{raw}", raw)
+    depth = len([s for s in segs if s])
+    if depth > 16:
+        raise ZipSafetyError("ZIP_UNSAFE", f"zip 条目路径过深（{depth} 层）：{raw}", raw)
+    if len(name) > 200:
+        raise ZipSafetyError("ZIP_UNSAFE", f"zip 条目路径过长（{len(name)} 字符）：{raw}", raw)
+    return "/".join(s for s in segs if s)
+
+
+def classify_entry(name: str, is_dir: bool) -> Literal["allow", "skip", "deny"]:
+    """条目分类：目录 → allow（只建）；DENY_EXT → deny（整包拒绝）；白名单 → allow；其余 → skip。"""
+    if is_dir:
+        return "allow"
+    segs = name.replace("\\", "/").split("/")
+    # 中间目录段命中 SKIP_DIRS → skip（.git/node_modules 整树跳过）
+    if any(seg in SKIP_DIRS for seg in segs[:-1]):
+        return "skip"
+    p = PurePosixPath(name)
+    ext = p.suffix.lower()
+    # 多重扩展如 .synctex.gz：取最后一段即可（gz 不在白名单 → skip）
+    if ext in DENY_EXT:
+        return "deny"
+    if ext in ALLOW_EXT:
+        return "allow"
+    if p.name.upper() in {b.upper() for b in ALLOW_BARE}:
+        return "allow"
+    return "skip"
+
+
+def _is_symlink(info: zipfile.ZipInfo) -> bool:
+    """external_attr 高 16 位为 Unix mode；S_IFMT == S_IFLNK(0xA000) → 符号链接。"""
+    mode = (info.external_attr >> 16) & 0xFFFF
+    return stat.S_IFMT(mode) == stat.S_IFLNK
+
+
+def _has_exec_bit(info: zipfile.ZipInfo) -> bool:
+    mode = (info.external_attr >> 16) & 0xFFFF
+    # Windows 造的 zip（external_attr 无 Unix mode）mode 可能为 0 → 无 x 位
+    return bool(mode & 0o111)
+
+
+def _prescan(zf: zipfile.ZipFile, settings) -> list[tuple[zipfile.ZipInfo, str]]:
+    """预扫中央目录：条目数 → 路径 → 符号链接/可执行位 → 分类 → 声明大小/压缩比。
+
+    全部通过才允许写盘（两段式第一段）。
+    """
+    infos = zf.infolist()
+    if len(infos) > settings.max_zip_entries:
+        raise ZipSafetyError(
+            "ZIP_BOMB", f"zip 条目数超限（{len(infos)} > {settings.max_zip_entries}）")
+
+    plan: list[tuple[zipfile.ZipInfo, str]] = []
+    declared_total = 0
+    for info in infos:
+        is_dir = info.is_dir()
+        name = sanitize_entry_name(info.filename)
+        if is_dir:
+            continue
+        # #3 符号链接 → 整包拒绝
+        if _is_symlink(info):
+            raise ZipSafetyError("ZIP_UNSAFE", f"zip 含符号链接条目：{info.filename}", info.filename)
+        # #4/#6 分类
+        kind = classify_entry(name, is_dir=False)
+        if kind == "deny":
+            raise ZipSafetyError("ZIP_UNSAFE", f"zip 含危险条目：{info.filename}", info.filename)
+        if kind == "skip":
+            continue
+        # #5 可执行位 → 整包拒绝（仅普通文件；目录已 continue）
+        if _has_exec_bit(info):
+            raise ZipSafetyError(
+                "ZIP_UNSAFE", f"zip 含可执行权限条目：{info.filename}", info.filename)
+        # #9 单条目声明大小
+        if info.file_size > settings.max_zip_entry_bytes:
+            raise ZipSafetyError(
+                "ZIP_BOMB",
+                f"zip 条目过大：{info.filename}（{info.file_size} 字节）", info.filename)
+        # #7 压缩比（compress_size=0 且 file_size>0 视为异常）
+        if info.file_size > 0:
+            cs = info.compress_size
+            if cs == 0 or info.file_size / cs > settings.max_zip_ratio:
+                raise ZipSafetyError(
+                    "ZIP_BOMB",
+                    f"zip 条目压缩比异常（疑似 zip bomb）：{info.filename}", info.filename)
+        declared_total += info.file_size
+        # #8 声明累计
+        if declared_total > settings.max_extract_bytes:
+            raise ZipSafetyError(
+                "ZIP_BOMB",
+                f"zip 解压总大小超限（声明 {declared_total} > "
+                f"{settings.max_extract_bytes} 字节）")
+        plan.append((info, name))
+    return plan
+
+
+def safe_extract(zip_bytes: bytes, dest: Path, settings) -> ExtractResult:
+    """安全解压 zip_bytes → dest（新建目录）。
+
+    两段式：①预扫（结构性检查全过）②流式写盘（8KB 块 + 实字节计数）。
+    任何 ZipSafetyError → 调用方负责 rmtree(dest) 清残留。
+    """
+    try:
+        zf = zipfile.ZipFile(io.BytesIO(zip_bytes))
+    except zipfile.BadZipFile as exc:
+        raise ZipSafetyError("ZIP_INVALID", f"zip 文件损坏或不是有效 zip：{exc}") from exc
+
+    result = ExtractResult()
+    with zf:
+        # ---- 第一段：纯预扫 ----
+        plan = _prescan(zf, settings)
+
+        # ---- 第二段：流式写盘 ----
+        dest.mkdir(parents=True, exist_ok=True)
+        written_total = 0
+        for info, rel in plan:
+            target = dest / rel
+            # #1 双保险：resolve 后必须仍在 dest 内
+            resolved_parent = target.parent.resolve()
+            if not str(resolved_parent).startswith(str(dest.resolve())):
+                raise ZipSafetyError(
+                    "ZIP_UNSAFE", f"zip 条目逃逸目标目录：{info.filename}", info.filename)
+            target.parent.mkdir(parents=True, exist_ok=True)
+            try:
+                src = zf.open(info)
+            except RuntimeError as exc:  # 加密条目
+                raise ZipSafetyError("ZIP_INVALID", f"zip 条目受密码保护：{info.filename}") from exc
+            try:
+                with src, open(target, "wb") as out:
+                    while True:
+                        chunk = src.read(8192)
+                        if not chunk:
+                            break
+                        # #8/#13 实写字节计数（不信头部声明）
+                        written_total += len(chunk)
+                        if written_total > settings.max_extract_bytes:
+                            raise ZipSafetyError(
+                                "ZIP_BOMB",
+                                f"zip 实际解压超限（> {settings.max_extract_bytes} 字节），已中止")
+                        out.write(chunk)
+            except zipfile.BadZipFile as exc:  # CRC 校验失败（#12/#13）
+                raise ZipSafetyError(
+                    "ZIP_INVALID", f"zip 条目损坏（CRC 校验失败）：{info.filename}",
+                    info.filename) from exc
+            # #5 绝不保留可执行位
+            target.chmod(0o644)
+            result.files += 1
+            _tally(result, rel)
+        result.bytes = written_total  # 实写累计（#8 计数器终值）
+
+        # 跳过统计（限 20 条 + 总数）
+        skipped: list[SkippedEntry] = []
+        skipped_count = 0
+        for info in zf.infolist():
+            if info.is_dir():
+                continue
+            try:
+                name = sanitize_entry_name(info.filename)
+            except ZipSafetyError:
+                continue  # 预扫已拒绝，不会到这里
+            if classify_entry(name, is_dir=False) == "skip":
+                skipped_count += 1
+                if len(skipped) < 20:
+                    skipped.append(SkippedEntry(name=name, reason="unsupported"))
+        result.skipped = skipped
+        result.skipped_count = skipped_count
+
+    return result
+
+
+def _tally(result: ExtractResult, rel: str) -> None:
+    ext = PurePosixPath(rel).suffix.lower()
+    if ext == ".tex":
+        result.tex += 1
+    elif ext in _IMG_EXT or ext == ".png":
+        result.images += 1
+    elif ext == ".cls":
+        result.cls += 1
+    elif ext == ".bib":
+        result.bib += 1
+    else:
+        result.other += 1
@@ -0,0 +1,493 @@
+{
+  "version": 2,
+  "updated": "2026-10-10",
+  "notes": "会议种子数据 v2。deadline_source=placeholder 表示日期为首版占位数据（按各会议公开周期窗口/历年规律填写，未经官方渠道逐条核验），接入官方数据源前须人工核验；严禁以 AI 推测日期替代核验。deadline_confidence 标注日期置信度：high=官方已公布或历年极稳定；medium=按历年规律区间推算；low=新一届尚未公告或历届波动大，待核验。ccf_rank 按 CCF 推荐目录（第七版，2026-03 发布）标注，非目录内会议为 null（含全部生物信息/植物类会议）。timezone_note 默认 AoE (UTC-12)。首版不做自动同步。",
+  "conferences": [
+    {
+      "id": "naacl-2027",
+      "name": "NAACL 2027",
+      "full_name": "North American Chapter of the Association for Computational Linguistics",
+      "domain_tags": ["AI/ML", "自然语言处理"],
+      "application_tags": ["交叉学科"],
+      "ccf_rank": "B",
+      "deadline_abstract": null,
+      "deadline_full_paper": "2026-10-12T23:59:59+00:00",
+      "notification_date": null,
+      "conference_date": "2027-06-01 ~ 2027-06-05",
+      "location": "San Francisco, California, USA",
+      "official_url": "https://www.naacl.org/",
+      "timezone_note": "AoE (UTC-12)",
+      "deadline_source": "placeholder",
+      "last_verified": "2026-10-10",
+      "deadline_confidence": "high"
+    },
+    {
+      "id": "coling-2027",
+      "name": "COLING 2027",
+      "full_name": "International Conference on Computational Linguistics",
+      "domain_tags": ["AI/ML", "自然语言处理"],
+      "application_tags": ["交叉学科"],
+      "ccf_rank": "B",
+      "deadline_abstract": null,
+      "deadline_full_paper": "2026-10-12T23:59:59+00:00",
+      "notification_date": null,
+      "conference_date": "2027-05-09 ~ 2027-05-14",
+      "location": "Macau SAR, China",
+      "official_url": null,
+      "timezone_note": "AoE (UTC-12)",
+      "deadline_source": "placeholder",
+      "last_verified": "2026-10-10",
+      "deadline_confidence": "medium"
+    },
+    {
+      "id": "www-2027",
+      "name": "WWW 2027",
+      "full_name": "The Web Conference (ACM WWW)",
+      "domain_tags": ["AI/ML", "数据挖掘"],
+      "application_tags": ["交叉学科"],
+      "ccf_rank": "A",
+      "deadline_abstract": "2026-10-18T23:59:59+00:00",
+      "deadline_full_paper": "2026-10-25T23:59:59+00:00",
+      "notification_date": "2027-01-04",
+      "conference_date": "2027-05-10 ~ 2027-05-14",
+      "location": "Dublin, Ireland",
+      "official_url": "https://www2027.thewebconf.org/",
+      "timezone_note": "AoE (UTC-12)",
+      "deadline_source": "placeholder",
+      "last_verified": "2026-10-10",
+      "deadline_confidence": "high"
+    },
+    {
+      "id": "recomb-2027",
+      "name": "RECOMB 2027",
+      "full_name": "International Conference on Research in Computational Molecular Biology",
+      "domain_tags": ["生物信息学"],
+      "application_tags": ["交叉学科"],
+      "ccf_rank": null,
+      "deadline_abstract": "2026-11-06T23:59:59+00:00",
+      "deadline_full_paper": "2026-11-13T23:59:59+00:00",
+      "notification_date": "2027-02-01",
+      "conference_date": "2027-04-25 ~ 2027-04-28",
+      "location": "TBD（待官方公布）",
+      "official_url": "https://recomb.org/",
+      "timezone_note": "AoE (UTC-12)",
+      "deadline_source": "placeholder",
+      "last_verified": "2026-10-10",
+      "deadline_confidence": "medium"
+    },
+    {
+      "id": "cvpr-2027",
+      "name": "CVPR 2027",
+      "full_name": "IEEE/CVF Conference on Computer Vision and Pattern Recognition",
+      "domain_tags": ["AI/ML", "计算机视觉"],
+      "application_tags": ["交叉学科"],
+      "ccf_rank": "A",
+      "deadline_abstract": "2026-11-10T23:59:59+00:00",
+      "deadline_full_paper": "2026-11-16T23:59:59+00:00",
+      "notification_date": "2027-02-25",
+      "conference_date": "2027-06-20 ~ 2027-06-25",
+      "location": "Seattle, USA",
+      "official_url": "https://cvpr.thecvf.com/",
+      "timezone_note": "AoE (UTC-12)",
+      "deadline_source": "placeholder",
+      "last_verified": "2026-10-10",
+      "deadline_confidence": "high"
+    },
+    {
+      "id": "wsdm-2027",
+      "name": "WSDM 2027",
+      "full_name": "International Conference on Web Search and Data Mining",
+      "domain_tags": ["AI/ML", "数据挖掘"],
+      "application_tags": ["交叉学科"],
+      "ccf_rank": "B",
+      "deadline_abstract": null,
+      "deadline_full_paper": "2026-11-17T23:59:59+00:00",
+      "notification_date": null,
+      "conference_date": "2027-02-15 ~ 2027-02-19",
+      "location": "Hong Kong SAR, China",
+      "official_url": "https://www.wsdm-conference.org/",
+      "timezone_note": "AoE (UTC-12)",
+      "deadline_source": "placeholder",
+      "last_verified": "2026-10-10",
+      "deadline_confidence": "high"
+    },
+    {
+      "id": "pag-2027",
+      "name": "PAG 2027",
+      "full_name": "Plant & Animal Genome Conference",
+      "domain_tags": ["植物/农学", "基因组学"],
+      "application_tags": ["种业", "分子育种"],
+      "ccf_rank": null,
+      "deadline_abstract": "2026-11-30T23:59:59+00:00",
+      "deadline_full_paper": "2026-12-15T23:59:59+00:00",
+      "notification_date": "2027-01-05",
+      "conference_date": "2027-01-08 ~ 2027-01-12",
+      "location": "San Diego, USA",
+      "official_url": "https://www.intlpag.org/",
+      "timezone_note": "AoE (UTC-12)",
+      "deadline_source": "placeholder",
+      "last_verified": "2026-10-10",
+      "deadline_confidence": "medium"
+    },
+    {
+      "id": "acl-2027",
+      "name": "ACL 2027",
+      "full_name": "Annual Meeting of the Association for Computational Linguistics",
+      "domain_tags": ["AI/ML", "自然语言处理"],
+      "application_tags": ["交叉学科"],
+      "ccf_rank": "A",
+      "deadline_abstract": null,
+      "deadline_full_paper": "2027-01-04T23:59:59+00:00",
+      "notification_date": null,
+      "conference_date": "2027-08-20 ~ 2027-08-22",
+      "location": "Kyoto, Japan",
+      "official_url": "https://2027.aclweb.org/",
+      "timezone_note": "AoE (UTC-12)",
+      "deadline_source": "placeholder",
+      "last_verified": "2026-10-10",
+      "deadline_confidence": "high"
+    },
+    {
+      "id": "plantbio-2027",
+      "name": "Plant Biology 2027",
+      "full_name": "ASPB Annual Meeting — Plant Biology",
+      "domain_tags": ["植物/农学", "分子生物学"],
+      "application_tags": ["分子育种"],
+      "ccf_rank": null,
+      "deadline_abstract": "2027-01-08T23:59:59+00:00",
+      "deadline_full_paper": "2027-01-08T23:59:59+00:00",
+      "notification_date": null,
+      "conference_date": "2027-07（待官方公布）",
+      "location": "Albuquerque, New Mexico, USA",
+      "official_url": "https://plantbiology.aspb.org/",
+      "timezone_note": "AoE (UTC-12)",
+      "deadline_source": "placeholder",
+      "last_verified": "2026-10-10",
+      "deadline_confidence": "high"
+    },
+    {
+      "id": "ijcai-2027",
+      "name": "IJCAI 2027",
+      "full_name": "International Joint Conference on Artificial Intelligence",
+      "domain_tags": ["AI/ML"],
+      "application_tags": ["交叉学科"],
+      "ccf_rank": "B",
+      "deadline_abstract": "2027-01-11T23:59:59+00:00",
+      "deadline_full_paper": "2027-01-18T23:59:59+00:00",
+      "notification_date": null,
+      "conference_date": "2027-08-07 ~ 2027-08-17",
+      "location": "Kyoto, Japan / Hengqin, China",
+      "official_url": "https://www.ijcai.org/",
+      "timezone_note": "AoE (UTC-12)",
+      "deadline_source": "placeholder",
+      "last_verified": "2026-10-10",
+      "deadline_confidence": "medium"
+    },
+    {
+      "id": "sigir-2027",
+      "name": "SIGIR 2027",
+      "full_name": "ACM SIGIR Conference on Research and Development in Information Retrieval",
+      "domain_tags": ["AI/ML", "信息检索"],
+      "application_tags": ["交叉学科"],
+      "ccf_rank": "A",
+      "deadline_abstract": "2027-01-14T23:59:59+00:00",
+      "deadline_full_paper": "2027-01-21T23:59:59+00:00",
+      "notification_date": "2027-04-05",
+      "conference_date": "2027-07-20 ~ 2027-07-24",
+      "location": "San Jose, California, USA",
+      "official_url": "https://sigir2027.org/",
+      "timezone_note": "AoE (UTC-12)",
+      "deadline_source": "placeholder",
+      "last_verified": "2026-10-10",
+      "deadline_confidence": "high"
+    },
+    {
+      "id": "icml-2027",
+      "name": "ICML 2027",
+      "full_name": "International Conference on Machine Learning",
+      "domain_tags": ["AI/ML", "深度学习"],
+      "application_tags": ["交叉学科"],
+      "ccf_rank": "A",
+      "deadline_abstract": "2027-01-15T23:59:59+00:00",
+      "deadline_full_paper": "2027-01-22T23:59:59+00:00",
+      "notification_date": "2027-05-01",
+      "conference_date": "2027-07-19 ~ 2027-07-25",
+      "location": "TBD（待官方公布）",
+      "official_url": "https://icml.cc/",
+      "timezone_note": "AoE (UTC-12)",
+      "deadline_source": "placeholder",
+      "last_verified": "2026-10-10",
+      "deadline_confidence": "medium"
+    },
+    {
+      "id": "chil-2027",
+      "name": "CHIL 2027",
+      "full_name": "ACM Conference on Health, Inference, and Learning",
+      "domain_tags": ["AI/ML", "健康医疗"],
+      "application_tags": ["交叉学科"],
+      "ccf_rank": null,
+      "deadline_abstract": "2027-01-15T23:59:59+00:00",
+      "deadline_full_paper": "2027-01-29T23:59:59+00:00",
+      "notification_date": null,
+      "conference_date": "2027-06（待官方公布）",
+      "location": "TBD（待官方公布）",
+      "official_url": "https://dl.acm.org/conference/chil",
+      "timezone_note": "AoE (UTC-12)",
+      "deadline_source": "placeholder",
+      "last_verified": "2026-10-10",
+      "deadline_confidence": "low"
+    },
+    {
+      "id": "kdd-2027",
+      "name": "KDD 2027 (Cycle 2)",
+      "full_name": "ACM SIGKDD Conference on Knowledge Discovery and Data Mining",
+      "domain_tags": ["AI/ML", "数据挖掘"],
+      "application_tags": ["交叉学科"],
+      "ccf_rank": "A",
+      "deadline_abstract": "2027-01-31T23:59:59+00:00",
+      "deadline_full_paper": "2027-02-07T23:59:59+00:00",
+      "notification_date": null,
+      "conference_date": "2027-08-01 ~ 2027-08-05",
+      "location": "San Jose, California, USA",
+      "official_url": "https://kdd2027.kdd.org/",
+      "timezone_note": "AoE (UTC-12)",
+      "deadline_source": "placeholder",
+      "last_verified": "2026-10-10",
+      "deadline_confidence": "medium"
+    },
+    {
+      "id": "ismb-eccb-2027",
+      "name": "ISMB/ECCB 2027",
+      "full_name": "Intelligent Systems for Molecular Biology / European Conference on Computational Biology",
+      "domain_tags": ["生物信息学"],
+      "application_tags": ["交叉学科"],
+      "ccf_rank": null,
+      "deadline_abstract": "2027-02-12T23:59:59+00:00",
+      "deadline_full_paper": "2027-02-19T23:59:59+00:00",
+      "notification_date": null,
+      "conference_date": "2027-07-18 ~ 2027-07-22",
+      "location": "Copenhagen, Denmark",
+      "official_url": "https://www.iscb.org/ismbeccb2027/home",
+      "timezone_note": "AoE (UTC-12)",
+      "deadline_source": "placeholder",
+      "last_verified": "2026-10-10",
+      "deadline_confidence": "medium"
+    },
+    {
+      "id": "ipmbc-2027",
+      "name": "IPMB 2027",
+      "full_name": "International Congress on Plant Molecular Biology (14th)",
+      "domain_tags": ["植物/农学", "分子生物学"],
+      "application_tags": ["分子育种"],
+      "ccf_rank": null,
+      "deadline_abstract": "2027-02-15T23:59:59+00:00",
+      "deadline_full_paper": "2027-02-22T23:59:59+00:00",
+      "notification_date": null,
+      "conference_date": "2027-07（待官方公布）",
+      "location": "Wuhan, China",
+      "official_url": "https://www.ipmb2027.org/",
+      "timezone_note": "AoE (UTC-12)",
+      "deadline_source": "placeholder",
+      "last_verified": "2026-10-10",
+      "deadline_confidence": "low"
+    },
+    {
+      "id": "uai-2027",
+      "name": "UAI 2027",
+      "full_name": "Conference on Uncertainty in Artificial Intelligence",
+      "domain_tags": ["AI/ML"],
+      "application_tags": ["交叉学科"],
+      "ccf_rank": "B",
+      "deadline_abstract": null,
+      "deadline_full_paper": "2027-02-24T23:59:59+00:00",
+      "notification_date": null,
+      "conference_date": "2027-08-16 ~ 2027-08-20",
+      "location": "TBD（待官方公布）",
+      "official_url": "https://www.auai.org/",
+      "timezone_note": "AoE (UTC-12)",
+      "deadline_source": "placeholder",
+      "last_verified": "2026-10-10",
+      "deadline_confidence": "medium"
+    },
+    {
+      "id": "miccai-2027",
+      "name": "MICCAI 2027",
+      "full_name": "International Conference on Medical Image Computing and Computer-Assisted Intervention",
+      "domain_tags": ["AI/ML", "医学影像"],
+      "application_tags": ["交叉学科"],
+      "ccf_rank": null,
+      "deadline_abstract": "2027-02-11T23:59:59+00:00",
+      "deadline_full_paper": "2027-02-25T23:59:59+00:00",
+      "notification_date": null,
+      "conference_date": "2027-09-26 ~ 2027-10-01",
+      "location": "Auckland, New Zealand",
+      "official_url": "https://miccai.org/",
+      "timezone_note": "AoE (UTC-12)",
+      "deadline_source": "placeholder",
+      "last_verified": "2026-10-10",
+      "deadline_confidence": "medium"
+    },
+    {
+      "id": "iccv-2027",
+      "name": "ICCV 2027",
+      "full_name": "IEEE/CVF International Conference on Computer Vision",
+      "domain_tags": ["AI/ML", "计算机视觉"],
+      "application_tags": ["交叉学科"],
+      "ccf_rank": "A",
+      "deadline_abstract": "2027-02-26T23:59:59+00:00",
+      "deadline_full_paper": "2027-03-05T23:59:59+00:00",
+      "notification_date": null,
+      "conference_date": "2027-10-02 ~ 2027-10-08",
+      "location": "Hong Kong SAR, China",
+      "official_url": null,
+      "timezone_note": "AoE (UTC-12)",
+      "deadline_source": "placeholder",
+      "last_verified": "2026-10-10",
+      "deadline_confidence": "medium"
+    },
+    {
+      "id": "bosc-2027",
+      "name": "BOSC 2027",
+      "full_name": "Bioinformatics Open Source Conference",
+      "domain_tags": ["生物信息学"],
+      "application_tags": ["交叉学科"],
+      "ccf_rank": null,
+      "deadline_abstract": null,
+      "deadline_full_paper": "2027-03-26T23:59:59+00:00",
+      "notification_date": null,
+      "conference_date": "2027-07-18 ~ 2027-07-22",
+      "location": "Copenhagen, Denmark",
+      "official_url": "https://openbioinformatics.org/",
+      "timezone_note": "AoE (UTC-12)",
+      "deadline_source": "placeholder",
+      "last_verified": "2026-10-10",
+      "deadline_confidence": "low"
+    },
+    {
+      "id": "acm-bcb-2027",
+      "name": "ACM-BCB 2027",
+      "full_name": "ACM Conference on Bioinformatics, Computational Biology and Health Informatics",
+      "domain_tags": ["生物信息学", "AI/ML"],
+      "application_tags": ["交叉学科"],
+      "ccf_rank": null,
+      "deadline_abstract": "2027-04-16T23:59:59+00:00",
+      "deadline_full_paper": "2027-04-23T23:59:59+00:00",
+      "notification_date": null,
+      "conference_date": "2027-08（待官方公布）",
+      "location": "TBD（待官方公布）",
+      "official_url": "https://acm-bcb.org/",
+      "timezone_note": "AoE (UTC-12)",
+      "deadline_source": "placeholder",
+      "last_verified": "2026-10-10",
+      "deadline_confidence": "medium"
+    },
+    {
+      "id": "ieee-bibm-2027",
+      "name": "IEEE BIBM 2027",
+      "full_name": "IEEE International Conference on Bioinformatics and Bioengineering",
+      "domain_tags": ["生物信息学"],
+      "application_tags": ["交叉学科"],
+      "ccf_rank": null,
+      "deadline_abstract": "2027-05-07T23:59:59+00:00",
+      "deadline_full_paper": "2027-05-14T23:59:59+00:00",
+      "notification_date": null,
+      "conference_date": "2027-11（待官方公布）",
+      "location": "TBD（待官方公布）",
+      "official_url": null,
+      "timezone_note": "AoE (UTC-12)",
+      "deadline_source": "placeholder",
+      "last_verified": "2026-10-10",
+      "deadline_confidence": "low"
+    },
+    {
+      "id": "emnlp-2027",
+      "name": "EMNLP 2027",
+      "full_name": "Conference on Empirical Methods in Natural Language Processing",
+      "domain_tags": ["AI/ML", "自然语言处理"],
+      "application_tags": ["交叉学科"],
+      "ccf_rank": "B",
+      "deadline_abstract": "2027-05-14T23:59:59+00:00",
+      "deadline_full_paper": "2027-05-21T23:59:59+00:00",
+      "notification_date": null,
+      "conference_date": "2027-11（待官方公布）",
+      "location": "TBD（待官方公布）",
+      "official_url": null,
+      "timezone_note": "AoE (UTC-12)",
+      "deadline_source": "placeholder",
+      "last_verified": "2026-10-10",
+      "deadline_confidence": "low"
+    },
+    {
+      "id": "neurips-2027",
+      "name": "NeurIPS 2027",
+      "full_name": "Conference on Neural Information Processing Systems",
+      "domain_tags": ["AI/ML", "深度学习"],
+      "application_tags": ["交叉学科"],
+      "ccf_rank": "A",
+      "deadline_abstract": "2027-05-14T23:59:59+00:00",
+      "deadline_full_paper": "2027-05-21T23:59:59+00:00",
+      "notification_date": null,
+      "conference_date": "2027-12（待官方公布）",
+      "location": "TBD（待官方公布）",
+      "official_url": "https://neurips.cc/",
+      "timezone_note": "AoE (UTC-12)",
+      "deadline_source": "placeholder",
+      "last_verified": "2026-10-10",
+      "deadline_confidence": "medium"
+    },
+    {
+      "id": "psb-2028",
+      "name": "PSB 2028",
+      "full_name": "Pacific Symposium on Biocomputing",
+      "domain_tags": ["生物信息学"],
+      "application_tags": ["交叉学科"],
+      "ccf_rank": null,
+      "deadline_abstract": null,
+      "deadline_full_paper": "2027-07-01T23:59:59+00:00",
+      "notification_date": null,
+      "conference_date": "2028-01（待官方公布）",
+      "location": "TBD（待官方公布）",
+      "official_url": "https://psb.stanford.edu/",
+      "timezone_note": "AoE (UTC-12)",
+      "deadline_source": "placeholder",
+      "last_verified": "2026-10-10",
+      "deadline_confidence": "low"
+    },
+    {
+      "id": "pag-europe-2027",
+      "name": "PAG Europe 2027",
+      "full_name": "Plant & Animal Genome Conference Europe",
+      "domain_tags": ["植物/农学", "基因组学"],
+      "application_tags": ["种业", "分子育种"],
+      "ccf_rank": null,
+      "deadline_abstract": null,
+      "deadline_full_paper": "2027-07-09T23:59:59+00:00",
+      "notification_date": null,
+      "conference_date": "2027-10（待官方公布）",
+      "location": "TBD（待官方公布）",
+      "official_url": null,
+      "timezone_note": "AoE (UTC-12)",
+      "deadline_source": "placeholder",
+      "last_verified": "2026-10-10",
+      "deadline_confidence": "low"
+    },
+    {
+      "id": "aaai-2028",
+      "name": "AAAI 2028",
+      "full_name": "AAAI Conference on Artificial Intelligence",
+      "domain_tags": ["AI/ML"],
+      "application_tags": ["交叉学科"],
+      "ccf_rank": "A",
+      "deadline_abstract": "2027-07-20T23:59:59+00:00",
+      "deadline_full_paper": "2027-07-27T23:59:59+00:00",
+      "notification_date": null,
+      "conference_date": "2028-02（待官方公布）",
+      "location": "TBD（待官方公布）",
+      "official_url": "https://aaai.org/",
+      "timezone_note": "AoE (UTC-12)",
+      "deadline_source": "placeholder",
+      "last_verified": "2026-10-10",
+      "deadline_confidence": "medium"
+    }
+  ]
+}
@@ -0,0 +1,61 @@
+journals directory 导入对账报告
+生成时间: 2026-10-10T15:37:11
+源文件: /home/xzq/5090/teamWorkspace/wjq/PlantAI-RAG-new-latest/PlantAI-rag-new/review_service/data/journals/source_v4.xlsx（193386 bytes）
+阶段: 完成
+
+=== 计数 ===
+读取有效行: 国际 779 / 中文 277 / 合计 1056
+成功: 1056   跳过(名称空): 0   失败: 0
+写入后 count(*): en=779 zh=277 total=1056
+期望: en=779 zh=277 total=1056 → ✓ 相符
+
+=== 分区分布（国际）===
+1区 233 / 2区 214 / 3区 181 / 4区 134 / 空白 17
+分区空白(→null 无note): 17
+分区未检得(→null + note): 0
+
+=== JIF 缺失 13 条（jif=null + note=核对状态）===
+  - eLife  [2025 JIF未检得/未给值]
+  - Heliyon  [2025 JIF未检得/未给值]
+  - Australian Journal of Crop Science  [2025 JIF未检得/未给值]
+  - International Journal of Agriculture and Biology  [2025 JIF未检得/未给值]
+  - Journal of Agriculture and Rural Development in the Tropics and Subtropics  [2025 JIF未检得/未给值]
+  - Fruits  [2025 JIF未检得/未给值]
+  - RANGELAND JOURNAL  [2025 JIF未检得/未给值]
+  - Science of The Total Environment  [2025 JIF未检得/未给值]
+  - Chemosphere  [2025 JIF未检得/未给值]
+  - Environmental Science and Pollution Research  [2025 JIF未检得/未给值]
+  - Bioengineered  [2025 JIF未检得/未给值]
+  - Cell Biomaterials  [2025 JIF未检得/未给值]
+  - National Science Open  [2025 JIF未检得/未给值]
+
+=== 中文复合IF 缺失 0 条 ===
+
+=== 分区未检得 期刊名 ===
+  （无——源表以空白表示未检得，见上方'分区空白'）
+
+=== 重复 id 冲突（应为空）===
+  （无）
+
+=== id 策略 ===
+ISSN 型: 692 条   slug 型: 364 条
+
+=== 来源超链接 ===
+国际 JIF来源: 779/779   分区来源: 762/779   中文数据来源: 277/277
+
+=== 结构迁移（ALTER TABLE，幂等）===
+  本次加列: official_check_status, jcr_release_year
+  已存在跳过: official_url
+
+=== 官网映射（决策：official_source 不入库）===
+  识别列: 官网网址
+  official_url 填充: 1053/1056   official_check_status 填充: 1056/1056
+  jcr_release_year 填充: 779（仅国际=2026；中文表无此列→null）
+  官网缺失 3 条（official_url=null，前端显示「—」不生成链接）:
+    - [zh] 中国食用菌
+    - [zh] 水土保持应用技术
+    - [zh] 粮食与饲料工业
+
+=== 幂等性验证 ===
+  第二次 upsert 后 count 不变: ✓ 通过
+
@@ -0,0 +1,177 @@
+{
+  "version": 1,
+  "updated": "2026-10-10",
+  "notes": "植物基因组学领域种子期刊。acceptance_rate 无公开权威数据一律为 null（不编造）；impact_factor / review_time_weeks 为公开 JCR/期刊官网常识近似值，以 last_updated 标注刷新时间，接入真实数据源前需人工核验。scope_desc 为英文范围描述，供 vstore 向量匹配使用。 format_rules_default 为通用默认规则（rules_source=default）；精选 5 本 format_rules 已于 2026-10-10 按各刊官网投稿指南人工核验填入（rules_source=official，附 source_url / last_verified / notes），官网未规定的字段一律 null 不猜测。 新增标签字段（不进 SQLite，接口按 id 从本文件合并）：scope_tags / application_tags / cross_domain 按 scope_desc 归类的标签；cas_partition / jcr_quartile 为占位（partition_source=placeholder），核实不确定的一律 null、不猜测，接入真实分区数据前需人工核验。 精选列表已更换为本环境可访问官网的 5 本（Genome Biology / BMC Plant Biology / Molecular Plant / Frontiers in Plant Science / Rice）；原 OUP/Wiley/Springer 4 本（The Plant Cell / The Plant Journal / Theoretical and Applied Genetics / The Plant Genome）移出精选，仍保留在 journal_directory 1056 条全量目录中。 [2026-10-12] 5 本精选期刊新增 review_tier（1=顶刊/2=主流，供 presubmit recommendation 分档判定；匹配失败默认 tier 2）。",
+  "format_rules_default": {
+    "rules_source": "default",
+    "max_pages": 10,
+    "min_font_pt": 9,
+    "min_margin_mm": 15,
+    "min_line_spacing": 1.15,
+    "min_figures": 1,
+    "max_fonts": 6,
+    "refs_style": "apa"
+  },
+  "journals": [
+    {
+      "id": "genome-biology",
+      "name": "Genome Biology",
+      "scope_desc": "High-impact open-access journal for genome-scale research across all organisms, including genome assembly and annotation, comparative and evolutionary genomics, computational methods, single-cell and multi-omics studies, and reproducible bioinformatics.",
+      "impact_factor": 10.1,
+      "review_time_weeks": 4.0,
+      "acceptance_rate": null,
+      "submission_deadline": null,
+      "official_url": "https://genomebiology.biomedcentral.com",
+      "last_updated": "2026-10-09",
+      "scope_tags": ["基因组学", "生物信息学", "多组学", "计算生物学"],
+      "application_tags": ["基础研究", "算法与方法"],
+      "cas_partition": "1区",
+      "jcr_quartile": "Q1",
+      "review_tier": 1,
+      "partition_source": "placeholder",
+      "cross_domain": ["进化生物学", "单细胞组学"],
+      "format_rules": {
+        "max_pages": null,
+        "min_font_pt": null,
+        "min_margin_mm": null,
+        "min_line_spacing": 2.0,
+        "max_fonts": null,
+        "min_figures": null,
+        "refs_style": "vancouver",
+        "anonymous": false,
+        "rules_source": "official",
+        "source_url": "https://genomebiology.biomedcentral.com/submission-guidelines",
+        "last_verified": "2026-10-10",
+        "notes": "官网要求双倍行距（'Use double-line spacing'）、行页码编号；参考文献 'Journal abbreviations follow Index Medicus/MEDLINE'（顺序编号制→vancouver）；BMC 出版社 policy 页明确 single-anonymous（审稿人知道作者身份，作者无需匿名）；字号/边距/页数上限该页未规定。BMC editorial policy 辅助来源：https://www.biomedcentral.com/getpublished/editorial-policies"
+      }
+    },
+    {
+      "id": "bmc-plant-biology",
+      "name": "BMC Plant Biology",
+      "scope_desc": "Open-access journal covering all aspects of plant biology, from molecular and cellular studies to the physiology and ecology of whole plants and communities, including plant-microbe interactions, biotechnology and applied plant science.",
+      "impact_factor": null,
+      "review_time_weeks": null,
+      "acceptance_rate": null,
+      "submission_deadline": null,
+      "official_url": "https://bmcplantbiol.biomedcentral.com",
+      "last_updated": "2026-10-10",
+      "scope_tags": ["植物生物学", "分子生物学", "逆境生物学", "植物-微生物互作"],
+      "application_tags": ["基础研究"],
+      "cas_partition": null,
+      "jcr_quartile": null,
+      "review_tier": 2,
+      "partition_source": "placeholder",
+      "cross_domain": ["植物生物技术"],
+      "format_rules": {
+        "max_pages": null,
+        "min_font_pt": null,
+        "min_margin_mm": null,
+        "min_line_spacing": 2.0,
+        "max_fonts": null,
+        "min_figures": null,
+        "refs_style": "vancouver",
+        "anonymous": false,
+        "rules_source": "official",
+        "source_url": "https://bmcplantbiol.biomedcentral.com/submission-guidelines",
+        "last_verified": "2026-10-10",
+        "notes": "同 BMC 系列模板页：双倍行距+行页码编号；参考文献 MEDLINE 缩写（→vancouver）；BMC 系列 editorial policy 为 single-anonymous（作者无需匿名）；字号/边距/页数上限该页未规定。"
+      }
+    },
+    {
+      "id": "molecular-plant",
+      "name": "Molecular Plant",
+      "scope_desc": "High-impact journal for fundamental and translational plant science at the molecular level, covering genomics, cell and developmental biology, signal transduction, stress and metabolic responses, and plant biotechnology.",
+      "impact_factor": null,
+      "review_time_weeks": null,
+      "acceptance_rate": null,
+      "submission_deadline": null,
+      "official_url": "https://www.cell.com/molecular-plant",
+      "last_updated": "2026-10-10",
+      "scope_tags": ["分子生物学", "基因组学", "多组学"],
+      "application_tags": ["基础研究", "分子育种"],
+      "cas_partition": null,
+      "jcr_quartile": null,
+      "review_tier": 1,
+      "partition_source": "placeholder",
+      "cross_domain": ["植物生物技术"],
+      "format_rules": {
+        "max_pages": null,
+        "min_font_pt": 12,
+        "min_margin_mm": null,
+        "min_line_spacing": 1.5,
+        "max_fonts": null,
+        "min_figures": null,
+        "refs_style": "author_year",
+        "anonymous": null,
+        "rules_source": "official",
+        "source_url": "https://www.cell.com/molecular-plant/authors",
+        "last_verified": "2026-10-10",
+        "notes": "官网作者指南（本环境 cell.com 403，依据作者浏览器核对摘录）：正文 12 point 字号、1.5 行距，参考文献 'cited in the text by name and year in parentheses'（作者-年份制→author_year）；页数上限/边距/图表下限/匿名审稿政策该摘录未覆盖→null"
+      }
+    },
+    {
+      "id": "frontiers-in-plant-science",
+      "name": "Frontiers in Plant Science",
+      "scope_desc": "Open-access journal spanning fundamental and applied plant sciences: molecular and cellular mechanisms, physiology, ecology, evolution, and applications in agriculture and biotechnology.",
+      "impact_factor": null,
+      "review_time_weeks": null,
+      "acceptance_rate": null,
+      "submission_deadline": null,
+      "official_url": "https://www.frontiersin.org/journals/plant-science",
+      "last_updated": "2026-10-10",
+      "scope_tags": ["植物生物学", "分子生物学", "生理学", "生态学"],
+      "application_tags": ["基础研究"],
+      "cas_partition": null,
+      "jcr_quartile": null,
+      "review_tier": 2,
+      "partition_source": "placeholder",
+      "cross_domain": ["农业科学"],
+      "format_rules": {
+        "max_pages": null,
+        "min_font_pt": null,
+        "min_margin_mm": null,
+        "min_line_spacing": 1.0,
+        "max_fonts": null,
+        "min_figures": null,
+        "refs_style": null,
+        "anonymous": null,
+        "rules_source": "official",
+        "source_url": "https://www.frontiersin.org/journals/plant-science/for-authors/author-guidelines",
+        "last_verified": "2026-10-10",
+        "notes": "官网 author-guidelines：'The entire document should be single-spaced and must contain page and line numbers'（单倍行距→1.0）；页数按 Article types 页 word count 而非数字页限→max_pages=null；字号/边距/图表下限该页未规定。Frontiers 为 open peer review；官网未明文规定作者是否匿名，建议人工核实 review-guidelines 页。Frontiers 官网明确两种制式并存：Harvard (author-date) 或 Vancouver (numbered)，具体到 Plant Science 需查 help center（当前抓取失败），建议人工核实 https://www.frontiersin.org/help/"
+      }
+    },
+    {
+      "id": "rice",
+      "name": "Rice",
+      "scope_desc": "Open-access journal publishing research on all aspects of rice science, from molecular biology and genetics to breeding, physiology, ecology and production systems, with relevance to cereal crop improvement.",
+      "impact_factor": null,
+      "review_time_weeks": null,
+      "acceptance_rate": null,
+      "submission_deadline": null,
+      "official_url": "https://thericejournal.springeropen.com",
+      "last_updated": "2026-10-10",
+      "scope_tags": ["水稻", "作物基因组学", "遗传育种"],
+      "application_tags": ["基础研究", "分子育种", "种业"],
+      "cas_partition": null,
+      "jcr_quartile": null,
+      "review_tier": 2,
+      "partition_source": "placeholder",
+      "cross_domain": ["作物科学"],
+      "format_rules": {
+        "max_pages": null,
+        "min_font_pt": null,
+        "min_margin_mm": null,
+        "min_line_spacing": 2.0,
+        "max_fonts": null,
+        "min_figures": null,
+        "refs_style": "vancouver",
+        "anonymous": false,
+        "rules_source": "official",
+        "source_url": "https://thericejournal.springeropen.com/submission-guidelines",
+        "last_verified": "2026-10-10",
+        "notes": "SpringerOpen 系列模板页：'Use double-line spacing'（双倍行距→2.0）、行页码编号；参考文献 'Journal abbreviations follow Index Medicus/MEDLINE'（→vancouver）；审稿明文 single-anonymous（审稿人知道作者身份，作者无需匿名）；字号/边距/页数上限/图表下限该页未规定。"
+      }
+    }
+  ]
+}
@@ -0,0 +1,815 @@
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+      "research_direction": "综合与交叉",
+      "cas_partition": "3区",
+      "cas_partition_note": null,
+      "cas_partition_year": 2025,
+      "jif": 3.8,
+      "jif_year": 2024,
+      "jif_note": null,
+      "jif_check_status": "已匹配公开汇编",
+      "composite_impact_factor": null,
+      "comprehensive_impact_factor": null,
+      "metric_year": null,
+      "metric_report_year": null,
+      "metric_caliber": null,
+      "annual_report_page": null,
+      "top_flag": "否",
+      "publisher_series": "其他",
+      "journal_mark": "领域期刊/新兴刊",
+      "article_type": "研究/方法/综合",
+      "issn": null,
+      "eissn": "2752-6542",
+      "jcr_disciplines": [
+        "MULTIDISCIPLINARY SCIENCES(ESCI)",
+        "SOCIAL SCIENCES, INTERDISCIPLINARY(ESCI)"
+      ],
+      "supplement_note": null,
+      "evidence_note": null,
+      "official_url": null,
+      "partition_source": "official",
+      "jif_source": "official",
+      "jif_source_url": "https://github.com/yongqianxiao/share_repo/blob/master/JCR/2024JCR%E5%AE%8C%E6%95%B4%E7%89%88%EF%BC%882025.6.18%E5%8F%91%E5%B8%83%EF%BC%89.xlsx",
+      "partition_source_url": "https://huaxue.hebtu.edu.cn/a/2025/09/23/A5A5BBD96F6B4410B87B6D4C43BDFD63.html",
+      "data_source_label": "JIF来源",
+      "data_source_url": null
+    },
+    {
+      "id": "en:heliyon",
+      "lang": "en",
+      "name": "Heliyon",
+      "research_direction": "综合与交叉",
+      "cas_partition": "4区",
+      "cas_partition_note": null,
+      "cas_partition_year": 2025,
+      "jif": 3.6,
+      "jif_year": 2024,
+      "jif_note": null,
+      "jif_check_status": "已匹配公开汇编",
+      "composite_impact_factor": null,
+      "comprehensive_impact_factor": null,
+      "metric_year": null,
+      "metric_report_year": null,
+      "metric_caliber": null,
+      "annual_report_page": null,
+      "top_flag": "否",
+      "publisher_series": "其他",
+      "journal_mark": "领域期刊/新兴刊",
+      "article_type": "研究/方法/综合",
+      "issn": null,
+      "eissn": "2405-8440",
+      "jcr_disciplines": [
+        "MULTIDISCIPLINARY SCIENCES(SCIE)"
+      ],
+      "supplement_note": null,
+      "evidence_note": null,
+      "official_url": null,
+      "partition_source": "official",
+      "jif_source": "official",
+      "jif_source_url": "https://github.com/yongqianxiao/share_repo/blob/master/JCR/2024JCR%E5%AE%8C%E6%95%B4%E7%89%88%EF%BC%882025.6.18%E5%8F%91%E5%B8%83%EF%BC%89.xlsx",
+      "partition_source_url": "https://huaxue.hebtu.edu.cn/a/2025/09/23/A5A5BBD96F6B4410B87B6D4C43BDFD63.html",
+      "data_source_label": "JIF来源",
+      "data_source_url": null
+    },
+    {
+      "id": "en:2054-5703",
+      "lang": "en",
+      "name": "Royal Society Open Science",
+      "research_direction": "综合与交叉",
+      "cas_partition": "3区",
+      "cas_partition_note": null,
+      "cas_partition_year": 2025,
+      "jif": 2.9,
+      "jif_year": 2024,
+      "jif_note": null,
+      "jif_check_status": "已匹配公开汇编",
+      "composite_impact_factor": null,
+      "comprehensive_impact_factor": null,
+      "metric_year": null,
+      "metric_report_year": null,
+      "metric_caliber": null,
+      "annual_report_page": null,
+      "top_flag": "否",
+      "publisher_series": "其他",
+      "journal_mark": "领域期刊/新兴刊",
+      "article_type": "研究/方法/综合",
+      "issn": "2054-5703",
+      "eissn": "2054-5703",
+      "jcr_disciplines": [
+        "MULTIDISCIPLINARY SCIENCES(SCIE)"
+      ],
+      "supplement_note": null,
+      "evidence_note": null,
+      "official_url": null,
+      "partition_source": "official",
+      "jif_source": "official",
+      "jif_source_url": "https://github.com/yongqianxiao/share_repo/blob/master/JCR/2024JCR%E5%AE%8C%E6%95%B4%E7%89%88%EF%BC%882025.6.18%E5%8F%91%E5%B8%83%EF%BC%89.xlsx",
+      "partition_source_url": "https://huaxue.hebtu.edu.cn/a/2025/09/23/A5A5BBD96F6B4410B87B6D4C43BDFD63.html",
+      "data_source_label": "JIF来源",
+      "data_source_url": null
+    },
+    {
+      "id": "en:1932-6203",
+      "lang": "en",
+      "name": "PLoS One",
+      "research_direction": "综合与交叉",
+      "cas_partition": "3区",
+      "cas_partition_note": null,
+      "cas_partition_year": 2025,
+      "jif": 2.6,
+      "jif_year": 2024,
+      "jif_note": null,
+      "jif_check_status": "已匹配公开汇编",
+      "composite_impact_factor": null,
+      "comprehensive_impact_factor": null,
+      "metric_year": null,
+      "metric_report_year": null,
+      "metric_caliber": null,
+      "annual_report_page": null,
+      "top_flag": "否",
+      "publisher_series": "其他",
+      "journal_mark": "领域期刊/新兴刊",
+      "article_type": "研究/方法/综合",
+      "issn": "1932-6203",
+      "eissn": "1932-6203",
+      "jcr_disciplines": [
+        "MULTIDISCIPLINARY SCIENCES(SCIE)"
+      ],
+      "supplement_note": null,
+      "evidence_note": null,
+      "official_url": null,
+      "partition_source": "official",
+      "jif_source": "official",
+      "jif_source_url": "https://github.com/yongqianxiao/share_repo/blob/master/JCR/2024JCR%E5%AE%8C%E6%95%B4%E7%89%88%EF%BC%882025.6.18%E5%8F%91%E5%B8%83%EF%BC%89.xlsx",
+      "partition_source_url": "https://huaxue.hebtu.edu.cn/a/2025/09/23/A5A5BBD96F6B4410B87B6D4C43BDFD63.html",
+      "data_source_label": "JIF来源",
+      "data_source_url": null
+    },
+    {
+      "id": "en:2167-8359",
+      "lang": "en",
+      "name": "PeerJ",
+      "research_direction": "综合与交叉",
+      "cas_partition": "3区",
+      "cas_partition_note": null,
+      "cas_partition_year": 2025,
+      "jif": 2.4,
+      "jif_year": 2024,
+      "jif_note": null,
+      "jif_check_status": "已匹配公开汇编",
+      "composite_impact_factor": null,
+      "comprehensive_impact_factor": null,
+      "metric_year": null,
+      "metric_report_year": null,
+      "metric_caliber": null,
+      "annual_report_page": null,
+      "top_flag": "否",
+      "publisher_series": "其他",
+      "journal_mark": "领域期刊/新兴刊",
+      "article_type": "研究/方法/综合",
+      "issn": "2167-8359",
+      "eissn": "2167-8359",
+      "jcr_disciplines": [
+        "MULTIDISCIPLINARY SCIENCES(SCIE)"
+      ],
+      "supplement_note": null,
+      "evidence_note": null,
+      "official_url": null,
+      "partition_source": "official",
+      "jif_source": "official",
+      "jif_source_url": "https://github.com/yongqianxiao/share_repo/blob/master/JCR/2024JCR%E5%AE%8C%E6%95%B4%E7%89%88%EF%BC%882025.6.18%E5%8F%91%E5%B8%83%EF%BC%89.xlsx",
+      "partition_source_url": "https://huaxue.hebtu.edu.cn/a/2025/09/23/A5A5BBD96F6B4410B87B6D4C43BDFD63.html",
+      "data_source_label": "JIF来源",
+      "data_source_url": null
+    },
+    {
+      "id": "en:2050-084X",
+      "lang": "en",
+      "name": "eLife",
+      "research_direction": "综合与交叉",
+      "cas_partition": "1区",
+      "cas_partition_note": null,
+      "cas_partition_year": 2025,
+      "jif": null,
+      "jif_year": 2024,
+      "jif_note": "未被2024 JCR收录",
+      "jif_check_status": "源表标N/A",
+      "composite_impact_factor": null,
+      "comprehensive_impact_factor": null,
+      "metric_year": null,
+      "metric_report_year": null,
+      "metric_caliber": null,
+      "annual_report_page": null,
+      "top_flag": "是",
+      "publisher_series": "其他",
+      "journal_mark": "领域期刊/新兴刊",
+      "article_type": "研究/方法/综合",
+      "issn": "2050-084X",
+      "eissn": "2050-084X",
+      "jcr_disciplines": [
+        "BIOLOGY(ESCI)"
+      ],
+      "supplement_note": "源表2024 JIF为N/A；不可用历史IF代填。",
+      "evidence_note": null,
+      "official_url": null,
+      "partition_source": "official",
+      "jif_source": null,
+      "jif_source_url": null,
+      "partition_source_url": "https://huaxue.hebtu.edu.cn/a/2025/09/23/A5A5BBD96F6B4410B87B6D4C43BDFD63.html",
+      "data_source_label": "JIF来源",
+      "data_source_url": null
+    }
+  ],
+  "meta": {
+    "total": 21,
+    "page": 1,
+    "size": 50,
+    "lang": "en",
+    "domain": "综合与交叉",
+    "cas_partition": "",
+    "q": "",
+    "domains": [
+      "细胞分子发育与生理",
+      "生态环境与保护",
+      "微生物真菌与生物技术",
+      "农学作物与种质",
+      "遗传组学与计算生物",
+      "植物科学与分子育种",
+      "水产渔业与海洋生物",
+      "食品营养与安全",
+      "植物保护与昆虫",
+      "畜牧动物营养与繁殖",
+      "土壤肥料与地球生物化学",
+      "林业木材与草业",
+      "兽医与寄生虫",
+      "综合与交叉",
+      "园艺果树与采后"
+    ],
+    "data_source_note": "分区：2025年中科院公开表（official）；JIF：2024 JCR，由2025版JCR发布（official）；整理日期2026-10-10。空白=来源未给值≠0；研究方向/期刊标记/文章类型为导航标签，非官方评级。",
+    "data_imported": true
+  },
+  "error": null
+}
@@ -0,0 +1,10 @@
+{
+  "ok": false,
+  "items": [],
+  "meta": null,
+  "error": {
+    "code": "VALIDATION",
+    "message": "size 必须在 1-200，收到 500",
+    "degraded": false
+  }
+}
@@ -0,0 +1,10 @@
+{
+  "ok": false,
+  "items": [],
+  "meta": null,
+  "error": {
+    "code": "VALIDATION",
+    "message": "不支持的 lang='xx'，可选：en / zh",
+    "degraded": false
+  }
+}
@@ -0,0 +1,31 @@
+{
+  "id": "academic-blue",
+  "display_name": "学术蓝",
+  "label": "学术蓝",
+  "description": "经典蓝白 · 答辩常用",
+  "palette": {
+    "bg": "#FFFFFF",
+    "cover_bg": "#EFF6FF",
+    "section_bg": "#DBEAFE",
+    "section_text": "#FFFFFF",
+    "primary": "#1D4ED8",
+    "accent": "#3B82F6",
+    "text": "#0F172A",
+    "muted": "#64748B",
+    "cover_text": "#1E3A8A",
+    "box_line": "#93C5FD"
+  },
+  "fonts": {
+    "title": "Microsoft YaHei, Source Han Sans SC, Noto Sans CJK SC, sans-serif",
+    "body": "Microsoft YaHei, Source Han Sans SC, Noto Sans CJK SC, sans-serif"
+  },
+  "sizes": {
+    "cover_title_pt": 40,
+    "title_pt": 30,
+    "bullet_pt": 18,
+    "reference_pt": 14,
+    "figure_pt": 13
+  },
+  "cover_style": { "title_align": "left", "accent_bar": true },
+  "content_style": { "figure_split_pct": 60 }
+}
@@ -0,0 +1,31 @@
+{
+  "id": "academic-minimal",
+  "display_name": "学术极简",
+  "label": "学术极简",
+  "description": "白底蓝黑 · 投屏通用",
+  "palette": {
+    "bg": "#FFFFFF",
+    "cover_bg": "#FFFFFF",
+    "section_bg": "#F3F4F6",
+    "section_text": "#FFFFFF",
+    "primary": "#111827",
+    "accent": "#2563EB",
+    "text": "#1F2937",
+    "muted": "#6B7280",
+    "cover_text": "#111827",
+    "box_line": "#9CA3AF"
+  },
+  "fonts": {
+    "title": "Microsoft YaHei, Source Han Sans SC, Noto Sans CJK SC, sans-serif",
+    "body": "Microsoft YaHei, Source Han Sans SC, Noto Sans CJK SC, sans-serif"
+  },
+  "sizes": {
+    "cover_title_pt": 40,
+    "title_pt": 30,
+    "bullet_pt": 18,
+    "reference_pt": 14,
+    "figure_pt": 13
+  },
+  "cover_style": { "title_align": "left", "accent_bar": false },
+  "content_style": { "figure_split_pct": 60 }
+}
@@ -0,0 +1,31 @@
+{
+  "id": "botanic-forest",
+  "display_name": "植研绿林",
+  "label": "植研绿林",
+  "description": "植物绿系 · 所内汇报",
+  "palette": {
+    "bg": "#F4FAF6",
+    "cover_bg": "#14532D",
+    "section_bg": "#DCFCE7",
+    "section_text": "#FFFFFF",
+    "primary": "#14532D",
+    "accent": "#16A34A",
+    "text": "#1A2E1A",
+    "muted": "#4D7C57",
+    "cover_text": "#FFFFFF",
+    "box_line": "#86C79A"
+  },
+  "fonts": {
+    "title": "Microsoft YaHei, Source Han Sans SC, Noto Sans CJK SC, sans-serif",
+    "body": "Microsoft YaHei, Source Han Sans SC, Noto Sans CJK SC, sans-serif"
+  },
+  "sizes": {
+    "cover_title_pt": 40,
+    "title_pt": 30,
+    "bullet_pt": 18,
+    "reference_pt": 14,
+    "figure_pt": 13
+  },
+  "cover_style": { "title_align": "left", "accent_bar": false },
+  "content_style": { "figure_split_pct": 60 }
+}
@@ -0,0 +1,31 @@
+{
+  "id": "classic-defense",
+  "display_name": "经典答辩",
+  "label": "经典答辩",
+  "description": "深蓝衬线 · 正式答辩",
+  "palette": {
+    "bg": "#FFFFFF",
+    "cover_bg": "#1A365D",
+    "section_bg": "#EEF2F7",
+    "section_text": "#FFFFFF",
+    "primary": "#1A365D",
+    "accent": "#B7791F",
+    "text": "#1F2937",
+    "muted": "#64748B",
+    "cover_text": "#FFFFFF",
+    "box_line": "#94A3B8"
+  },
+  "fonts": {
+    "title": "Times New Roman, Georgia, Noto Serif CJK SC, SimSun, serif",
+    "body": "Times New Roman, Georgia, Noto Serif CJK SC, SimSun, serif"
+  },
+  "sizes": {
+    "cover_title_pt": 40,
+    "title_pt": 30,
+    "bullet_pt": 18,
+    "reference_pt": 14,
+    "figure_pt": 13
+  },
+  "cover_style": { "title_align": "left", "accent_bar": false },
+  "content_style": { "figure_split_pct": 60 }
+}
@@ -0,0 +1,36 @@
+{
+  "id": "domestic",
+  "display_name": "国内组会",
+  "label": "国内组会",
+  "description": "深蓝红强调 · 国内组会 / 学术报告",
+  "palette": {
+    "bg": "#FFFFFF",
+    "cover_bg": "#FFFFFF",
+    "section_bg": "#1F4E79",
+    "section_text": "#FFFFFF",
+    "primary": "#1F4E79",
+    "accent": "#C00000",
+    "text": "#1A1A1A",
+    "muted": "#6B6B6B",
+    "cover_text": "#1F4E79",
+    "box_line": "#F2F2F2"
+  },
+  "fonts": {
+    "title": "Microsoft YaHei, PingFang SC, Source Han Sans SC, Noto Sans CJK SC, Arial, sans-serif",
+    "body": "Microsoft YaHei, PingFang SC, Source Han Sans SC, Noto Sans CJK SC, Arial, sans-serif"
+  },
+  "sizes": {
+    "cover_title_pt": 36,
+    "title_pt": 28,
+    "bullet_pt": 20,
+    "reference_pt": 16,
+    "figure_pt": 13
+  },
+  "cover_style": {
+    "title_align": "left",
+    "accent_bar": true
+  },
+  "content_style": {
+    "figure_split_pct": 60
+  }
+}
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
admin	9b746db452	Merge feature/admin-console: 管理后台 + 用户端鉴权(登录/授权/数据隔离/日志)	2026-10-16 16:01:13 +08:00
admin	d9abd0b86a	feat(auth): 用户端鉴权(登录/授权清单/逐次校验/功能门禁 + owner 数据隔离)	2026-10-16 14:42:23 +08:00
admin	282415fcb1	feat(admin): 行为日志记录 hub_id(便于区分不同中枢)	2026-10-15 23:56:42 +08:00
admin	1ca2241a97	feat(admin): 增加中枢设置(自定义 ID 与名称,右上角设置入口)	2026-10-15 23:52:17 +08:00
admin	8b5095f70f	Merge pull request 'feat(review): P5 科研汇报助手（论文 → PPT 大纲 → PPTX）' (#5 ) from wjq/PlantAI-rag-new:feature/p5-ppt-assistant into main Reviewed-on: http://8.163.92.8:3000/admin/PlantAI-rag-new/pulls/5	2026-10-15 20:19:30 +08:00
potaser	f5a951f47a	docs: add P5 PR report	2026-10-15 19:35:51 +08:00
potaser	7ced30fa96	feat(review): P5 科研汇报助手 + 14 风格 + 真图嵌入	2026-10-15 18:51:59 +08:00
admin	c78df3a6a6	feat(admin): 新增管理后台(登录/用户管理/日志查看) + 行为日志文件采集(请求中间件 + log_event)	2026-10-15 18:43:19 +08:00
admin	69e3f35a43	Merge pull request 'feat(review): P3b+P4 论文重排版支持编译 PDF（含 zip 项目）' (#4 ) from wjq/PlantAI-rag-new:feature/p3b-compile-ui into main Reviewed-on: http://8.163.92.8:3000/admin/PlantAI-rag-new/pulls/4	2026-10-15 18:30:14 +08:00
potaser	de0b9f92be	fix(review): EPS batch conversion in zip compile (v2) - v1 fell through because it required pre-converted PDF in zip - v2: convert all .eps files post-extract via gs -dSAFER - 15s timeout per file; fail per-file, not blocking - Size guards: 20MB per file warning, 100MB total abort - Conversion log written to output.log - Verified on real MDPI official zip → 7-page PDF v1 lesson: test sample had pre-converted PDF but real zip does not	2026-10-14 09:47:49 +08:00
potaser	2797145104	feat(review): P4 two-phase zip compile + XDV→PDF diagnostics + EPS fallback - inspect/upload zip then compile project (main-file detection, zip safety, single-slot queue, failed-envelope carries compile_id + log_url) - keep failed project/ scene 24h (failed_project_ttl_s; KEEP_FAILED_PROJECTS=1 forever), success deletes immediately; two-tier compile_jobs sweep - add tectonic --print and persist full engine chatter to output.log so XDV→PDF (xdvipdfmx) errors are visible (MDPI: logo EPS inclusion failure) - EPS fallback: swap X.eps refs for *-eps-converted-to.pdf when present and materialize X.pdf for extension-less graphicx lookup; friendly error when no converted PDF exists - frontend: ReformatPanel zip upload/inspect/run flow; one-off scripts/debug_compile.py (gitignored) - tests: backend 169 passed (22 zip_safety + 34 compile_zip + P3a regression), frontend edu vitest 43 passed	2026-10-13 18:42:04 +08:00
potaser	4e19350115	docs: add P3b PR report	2026-10-13 11:23:01 +08:00
potaser	e036301e1a	feat(review): show format rules summary per target journal - New summary row: shows the journal's rules (even if no diff applies) - Fixes user confusion when switching journals yields same diff - When all rules are null: 'no explicit format requirements' - Vitest: add case for summary rendering	2026-10-13 11:22:52 +08:00
potaser	da84dff9bb	fix(review): persist uploaded .tex file in reformat panel - File now stored in edu.js store (reformatFile) - Switching target journal no longer requires re-upload - Explicit reset button clears file - Vitest: 4 cases	2026-10-13 11:20:33 +08:00
potaser	3a72d3a861	feat(review): P3b enable compile PDF in reformat panel - ReformatPanel: compile tab state machine (idle/loading/success/error) - Blob URL for PDF preview; backend path hidden - First-compile 1-3min hint banner (dismissible) - QUEUE_FULL 429 with fixed message - Store: compileStatus/compileResult/compileError + actions - prewarm_tectonic.sh: minimal .tex compilation to pre-cache TeX bundles - Vitest: 6 new cases (guide / button / loading / success / error / queue-full)	2026-10-13 10:24:55 +08:00
admin	ac07cb2008	Merge pull request 'feat(review): AI 预审稿修复 + 审稿回复助手 Phase 1' (#3 ) from wjq/PlantAI-rag-new:feature/presubmit-explainable-engine into main Reviewed-on: http://192.168.0.175:3000/admin/PlantAI-rag-new/pulls/3	2026-10-13 09:34:41 +08:00
potaser	d077a5b930	test(docs): rebuttal + tracker tests + PR reports	2026-10-12 16:38:28 +08:00
potaser	c4dc344a31	feat(edu): presubmit UI + rebuttal assistant + tracker removal - PresubmitPanel: rationale / conflict chips / file persistence - RebuttalPanel: Phase 1 UI (3-column, 5-type form, stance pre-check) - ReformatPanel / ReportPanel: hide internal fields (job id / version) - EduSideNav: SVG icon, remove tracker menu item - EduWorkspace: unmount tracker - edu.js: rebuttal state + presubmitFile + SECTIONS (drop tracker)	2026-10-12 16:38:28 +08:00
potaser	cf5ccb3a37	feat(review): presubmit 4-bug fix + rebuttal Phase 1 backend - 4 bugs: truncation window / keyword scanner / tier heuristic / vocab - Scanner conflict demotion now truly affects recommendation (major → minor) - Rebuttal Phase 1: store / parse / draft / 10 endpoints - max_text_chars 150K + token guard + 400/413 retry - Journals tier override (13 journals) + jif heuristic (exclude reviews)	2026-10-12 16:38:28 +08:00
potaser	d99d5ef74a	fix(review): replace presubmit recommendation quota with explainable rule engine - Remove '3-8 major' quota that made accept/minor_revision unreachable - Add recommend_engine.py: rule-based R0-R5 + tier-parameterized judgment - Journal tier (1/2/3) from journals.json review_tier field - LLM no longer outputs recommendation; engine is single source of truth - Rationale exposed in API and rendered in PresubmitPanel - Weak draft still major_revision (R1); strong draft now minor_revision (R5)	2026-10-12 09:55:07 +08:00
admin	4add9f176b	Merge pull request 'feat(review): journal_directory 启动自动 seed（部署即运行）' (#2 ) from wjq/PlantAI-rag-new:feature/journal-seed-autoload into main Reviewed-on: http://8.163.92.8:3000/admin/PlantAI-rag-new/pulls/2	2026-10-11 21:12:56 +08:00
potaser	1319328b85	feat(review): auto-seed journal_directory on startup when empty	2026-10-11 20:55:36 +08:00
admin	2d0e3a4858	fix(build): compile_sdk 白名单加入 review_proxy.py（科研审稿反代断流高危点）	2026-10-11 16:40:24 +08:00
admin	ea0f2b3fad	Merge pull request 'feat(review): 教育科研工作台 + 论文自动重排版 + journals v4 数据集' (#1 ) from wjq/PlantAI-rag-new:feature/academic-review-assistant into main Reviewed-on: http://8.163.92.8:3000/admin/PlantAI-rag-new/pulls/1 Reviewed-by: admin <jerryhaozhang@gmail.com>	2026-10-11 13:49:12 +08:00
admin	19fa12eb39	merge main: 解决 .gitignore 冲突（合并部署文档忽略规则）	2026-10-11 13:47:47 +08:00
admin	11337a788f	更新 .gitignore 解决冲突 Signed-off-by: admin <jerryhaozhang@gmail.com>	2026-10-11 13:29:35 +08:00
potaser	55410b663a	feat(review): journal format-rule fetch scripts (offline CLI) - fetch_format_rules.py CLI: robots.txt-aware fetcher (httpx + bs4, >=2s per-host throttle) + DeepSeek quote-backed rule extractor - Status: OUP/Wiley/Cell return 403 from this environment; the five featured journals' format_rules in journals.json were manually verified against official sites instead. Tooling kept for future re-runs; data/format_cache/ is runtime output and gitignored - Service code never imports this toolchain (standalone CLI only)	2026-10-11 12:19:18 +08:00
potaser	dddb70ff6f	fix(review): directory partition source shown as constant note Stop sending partition_source_url; respond with a fixed explanatory note instead. DB values untouched (dropped after SELECT).	2026-10-11 12:19:18 +08:00
potaser	649e66f41d	feat(review): tectonic PDF compile API (P3a) + rename journals panel - POST/GET /api/review/compile[/{id}[/pdf\|/log]]: isolated workdir, --untrusted, 60s timeout with process-group kill, single-slot queue (429 QUEUE_FULL), 7-day retention sweep - tools/install_tectonic.sh: pinned tectonic 0.17.0 (sha256) + README - Rename menu/panel title to 学术期刊情报 - Compile UI stays a placeholder per product decision (P3 deferred)	2026-10-11 12:19:18 +08:00
potaser	42aeb8fa4c	feat(review): paper auto-reformat P1 (.tex rule engine + diff panel) - Rule engine: font/margin/line-spacing/bib-style transformers, tighten-only + structural guard + idempotency - POST/GET /api/review/reformat with 200-envelope errors and job store - ReformatPanel: journal dropdown (featured + directory search), source/diff tabs; compile tab is a dev placeholder for now - journals.json format_rules_default kept as generic fallback	2026-10-11 12:19:17 +08:00
potaser	c747ebd77a	feat(review): official format rules for 5 featured journals - Replace featured list with accessible journals: Genome Biology, BMC Plant Biology, Molecular Plant, Frontiers in Plant Science, Rice - Per-journal format_rules verified against official author guidelines (rules_source=official, source_url, last_verified=2026-10-10) - Update recommend tests to the new seed set	2026-10-11 12:19:17 +08:00
admin	60375b04d7	chore: .gitignore 忽略含凭据的部署方案文档 DEPLOY_PAPER_176.md	2026-10-10 18:53:25 +08:00
admin	1bd4aea5fd	fix(build): render_active_library_env 输出 GENE_FAMILY_ROOT 而非未定义的 QA_ROOT active_library.env 里 $QA_ROOT 从未定义，QA start.sh 在 set -u 下 source 时报 unbound variable 导致 8091 起不来。改用 prod.env 中已定义的 GENE_FAMILY_ROOT。	2026-10-10 18:52:15 +08:00
admin	51532a30bc	fix(ui): 工作台「提取任务」tab 与离线提示改为「上传文献」	2026-10-10 18:27:06 +08:00
potaser	5a71e29cf7	feat(edu): complete 7-panel academic assistant + journals v4 dataset Backend: - review_service: presubmit / recommend / journals / journals/directory / format-check / conferences endpoints - journals.json 5 精选种子 + journal_directory 1056 条全量（v4 数据） - v4 数据集：2025 JIF（2026 JCR 发布）+ 2025 中科院分区 + 1053 条官网 URL - format_check 行距 bug 修复（基线 y + 物理过滤 + docx EMU） BFF: - review_proxy 反代（修复 httpx build_request await bug） - REVIEW_ENABLED 开关（默认关闭，零痕部署） Frontend: - 教育科研工作台（7 面板 + 菜单 + 状态管理） - TopBar 教育科研入口（v-show 覆盖层语义，RAG 会话不丢） - 期刊情报：Tab 切换 / 搜索 / 筛选 / 分页 / 官网列 / 展开凭证 - 智能推荐 / AI预审稿 / 专业报告 / 投稿台账 / 排版规范 / 会议日历	2026-10-10 16:05:08 +08:00
potaser	d43d30ee3f	feat: add review_service with plant genomics presubmit, journals endpoint, and BFF proxy	2026-10-09 16:54:03 +08:00
admin	d37e0d9c3a	fix(paper): 确认大纲后即时 seed 进度卡并逐节刷新 - 后端写稿循环不再落空 paper_progress 块（重载后出现空卡），改落开始撰写文本 - 前端 confirmPaper 时用大纲节标题本地 seed 进度卡，2s 轮询 patch 逐节状态 - 当前节按 current_section_id 标 writing（…动画）	2026-10-08 17:10:50 +08:00
admin	c923419d2d	fix(paper): 大纲阶段修改意见路由回 sendPaper + 用原始 brief 重新生成大纲	2026-10-08 16:23:28 +08:00
admin	43a7c6c132	feat(paper): UI 优化(卡片文字颜色/去模式按钮) + 模板下拉加论文选项并接线渲染	2026-10-08 15:17:44 +08:00
admin	8b228923bd	fix(paper): 取消路径(cancel_paper) + 引用元数据清洗(丢弃杜撰 DOI/PMID)	2026-10-08 14:59:16 +08:00
admin	2e5372cf90	fix(paper): 论文产物渲染为 HTML + 文末追加参考文献列表/disclaimer	2026-10-08 14:54:00 +08:00
admin	91f6a1c242	feat: 新增论文撰写功能 paper-writer（独立 MCP 服务 + BFF 大脑 + 前端三卡） - paper_writer_service(8097)：FastAPI + MCP streamable-http 单端点，9 工具（propose_paper_outline/write_paper_section/get_paper_progress/search_refs/ revise_paper_section/revise_paper/get_paper/complete_paper/cancel_paper）， SQLite 三表（papers/paper_sections/citations，WAL），GB/T 7714 引用协议 - BFF：services/paper/{mcp_client,agent}.py（裸 JSON-RPC 客户端 + 规则状态机）、 routers/paper.py、schemas.py 4 个 Paper*Block + ArtifactBlock 加 paper_id/citation_count、 config.py 开关、main.py 条件注册、docgen.py 抽 insert_artifact 公共 helper - 前端：intent.js paperIntent 纯函数、Composer docgen 分支 sub-route、sendPaper/轮询、 PaperBriefCard/PaperOutlineCard/PaperProgressCard、DocPane cite-chip - deploy/paper_restart.sh + toggle_paper.sh；compile_sdk.sh 白名单追加 paper 文件 - tests/paper 26 条（工具逻辑 + MCP 协议 + BFF 状态机 + 块 schema + 前端 intent 单测）	2026-09-30 22:29:22 +08:00
				`@@ -0,0 +1 @@`
				`"""paper_writer_service —— 论文撰写独立 MCP 服务（8097）。"""`