尚未偵測到更新。GitHub 發布版本後會顯示在這裡。
個人 GitHub 帳號下公開儲存庫的擁有者可以登入並驗證所有權,自行管理介紹,無需管理員核准。
登入並產生驗證檔案,在 30 分鐘內將其提交至此儲存庫的預設分支。其他分支或分叉儲存庫中的檔案無效。然後在下方檢查檔案,即可無需管理員核准直接管理專案。請保留檔案以維持管理權限。
如需登入,將前往登入頁面。登入後請回到此處,再次點擊所選的驗證按鈕。
在專案資料夾中執行 /nomorevibe verify,即可驗證所有權並自行管理介紹。
一分鐘完成驗證Spring It at Night Shift London (Mubit hackathon). Voice-to-handover AI for residential property teams that learns from manager corrections.
翻譯準備中
取自儲存庫 README
正在載入完整 README。
檢視完整 README ↗Spring It turns a night concierge's radio calls into a clean handover, and learns each building's rules from the manager's corrections.
Built at Night Shift London (Mubit hackathon), 24–25 Oct 2026.
This comes straight from the Spring It product, and from six years of front-desk experience in London residential buildings. A night shift lives on the radio, and every building has its own rules that nobody writes down: which door is a fire door, which gate is locked this week, what the day manager wants to decide personally. Today that knowledge sits in people's heads and in binders, and it walks out at every shift change.
Night teams in residential buildings report problems over the radio: a door propped open, a leak, a resident locked out. Those reports end up as scribbled notes, and nothing teaches the system that, in this building, the bin store door is a fire door on the escape route. Spring It logs each report as a structured open item. When a manager corrects an item, the correction becomes building memory, so the next report is handled correctly. Every model call goes through Mubit, which uses those right answers to train this building's own model.
radio call ──► transcript ──► POST /api/report ──► one model call via Mubit
(frozen prompt + tools,
building facts in the message)
│
spoken reply back to staff ◄────────┤
▼
open item on the manager's desk
│
manager corrects it ──────┤ (before/after saved)
▼
building fact ──► included in every later call
│
▼
right answers kept by Mubit ──► adapter trained for
this building
/radio listens on the USB sound card, transcribes the call and sends the text to POST /api/report.src/lib/agent/fingerprint.ts), so every call lands in one Mubit task ("Spring It 3"). Mubit keeps the correct answers as training examples. Training starts once a task has 25 kept examples, and each new adapter version appears in the Mubit console.Mubit lets us deliver a model per building. Beyond the hackathon, the hierarchy is Org > Estate > Building. Each customer unit gets its own model, trained on its own procedures and its own managers' corrections. See docs/vision.md.
The same story npm run demo checks end to end against real Mubit:
npm run demo passes on the iMac with every call on mubit/anthropic/claude-haiku-4-5).step_outcome call returned 404 for our key, so it is off by default (MUBIT_CONTROL=on enables it). The learning loop doesn't depend on it.Needs Node 20+ (tested on 24), a Mubit key with a Claude provider key saved in the Mubit console, and optionally a Neon Postgres URL.
npm install
vercel env pull .env.local # or: cp .env.example .env.local and fill in MUBIT_API_KEY, DATABASE_URL
npm run dev # desk at http://localhost:3000, radio at /radio
npm run demo # second terminal: the story above, with PASS/FAIL checks
npm run demo -- --keep-facts # same, but keeps standalone facts already loaded
Without MUBIT_API_KEY the app uses an offline stand-in model, only for testing the wiring, and the demo prints which model ran. Without DATABASE_URL it uses an embedded Postgres in .data/.