Mirobody
인간 건강의 표준 레지스트리, 약 2천 개 임상·생활 지표를 하나의 언어로 정리
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README 전체를 불러오는 중입니다.
README 전문 보기 ↗Opacity is a web-based platform that screens for early signs of dyslexia through interactive browser games. Designed for children, parents, and teachers, it uses evidence-based cognitive assessments delivered through engaging gameplay.
Status: All five game API/UI implementations are present. The dashboard's main UI is a placeholder. The Rello Random Forest now has an optional website research demo at /research/rello, backed by ml/service/. Actual Opacity gameplay classification and child report generation are not implemented.
Opacity screens for dyslexia risk through five short, game-like cognitive assessments. The platform supports:
The output is a risk band (low/moderate/elevated), never a diagnostic label. This is a screening tool, not a diagnostic tool.
skill_states stored per childBrowser (React 19, Next.js 16, App Router)
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├─ Supabase browser client (anon key, RLS-scoped)
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Next.js Route Handlers (frontend/app/api/**/route.ts)
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├─ Supabase server client (cookie-bound, anon key)
├─ Supabase admin client (service role key, server-only)
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Supabase (Postgres + Auth + RLS)
Route handlers provide the game and account backend. A standalone FastAPI research service under ml/service/ serves the frozen Rello benchmark to /api/research/rello. Setup instructions cover model installation and the optional demo flag. Product ML scoring and Whisper transcription remain planned; Rello features cannot be substituted with gameplay scores.
auth.users row with a real JWT. No separate guest code path.frontend/lib/supabase/admin.ts, used only in server-only code (route handlers).| Layer | Technology |
|---|---|
| Frontend | React 19, Next.js 16, TypeScript, Tailwind CSS, shadcn/ui |
| UI State | Zustand, TanStack React Query |
| Database | Supabase (Postgres + Auth + RLS) |
| API | Next.js route handlers, REST |
| Validation | Zod |
| Animations | Motion, Cuelume (haptics), tw-animate-css |
| Auth | Supabase Auth (email/password + anonymous) |
| ML | Python research baseline and FastAPI demo under ml/; product scoring, XGBoost/SHAP and Whisper remain planned |
여기까지가 README 앞부분입니다. 나머지는 원문에서 읽을 수 있습니다. README 전문 보기 ↗