perf: 首屏 JS 减少 2/3、随机评分查询提速，WebSocket 防刷和登录限流

- prettier 点“整理”时才加载，编辑器页面按路由懒加载：首屏 JS 2345 KB → 766 KB
- 随机评分先随机抽 64 个 rowid 挑选，抽不中再退回全表随机：6 万条提交时 50ms → 1ms
- WebSocket 消息最大 64 KB；AI 回复中再发来的消息直接拒绝，不再排队
- 同一用户名 10 分钟失败 10 次、同一 IP 失败 100 次后暂停登录（返回 429，登录框显示提示）
- 作品展的 iframe 加 loading="lazy"
- 新增 ws.test.ts（正常生成、回复中再发消息、中途断开、握手失败）和随机评分、登录限流的测试

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

CLAUDE.md

@@ -17,7 +17,7 @@ The backend was rewritten from Django in 2026-10 to cut memory use (~25 MB vs. 1
   - `src/auth.ts` — Django-compatible password hashing; JWT login, no cookies: `POST /account/login` returns a 15-min HS256 `access_token` (sent as `Authorization: Bearer`, signed with `JWT_SECRET`, random per process if unset) and a 14-day opaque `refresh_token` (only its sha256 is stored, in `auth_refresh_token`; `POST /account/refresh` trades it for a new access token, logout / password change / deactivation delete it). An invalid or expired Bearer token is a 401 even on public endpoints so the client knows to refresh. `requireUser/requireAdmin/requireSuper` (401 / 403)
   - `src/routes/` — `account`, `tasks` (tutorial / challenge / creation), `files` (task assets + image upload), `submission`, `showcase` (mounted under `/submission/showcase`), `prompt`
   - `src/services/` — `score.ts` (rating weights super×0.5, admin×0.3, normal×0.2, then Bayesian smoothing with C=3 and zones), `gradebook.ts`, `llm.ts` (OpenAI-compatible streaming via fetch; DeepSeek default, ARK for doubao models), `classifier.ts` (Bloom-level L1–L6 prompt tagging, runs in background), `cascade.ts` (Django's CASCADE deletes, done by hand), `pyround.ts` (`pyRound`/`pySum` reproduce Python's `round()` and `sum()` so scores match the old system bit-for-bit)
-  - `src/ws.ts` — `/ws/prompt/<task_id>/?token=<access_token>` (code generation chat) and `/ws/guidance/<task_id>/?token=...` (prompt coaching); messages per connection are processed serially; on disconnect the pending user message is deleted and the LLM request aborted
+  - `src/ws.ts` — `/ws/prompt/<task_id>/?token=<access_token>` (code generation chat) and `/ws/guidance/<task_id>/?token=...` (prompt coaching); one message per connection at a time (a message sent while the AI is still replying gets an error, payloads capped at 64 KB); on disconnect the pending user message is deleted and the LLM request aborted
   - `scripts/` — one-off CLIs: `create-superuser.ts`, `classify-prompts.ts`, `recalculate-scores.ts`
   - Roles: `super`, `admin`, `normal`. Task model is multi-table: `task_task` + one of `task_tutorial` / `task_challenge` / `task_creation` (`task_ptr_id`)