Tavotto
AI drew your research figure. Tavotto makes it publication-ready: edit matplotlib figures on a canvas, lay out in mm, check journal rules. Free, open source.
翻譯準備中
尚未偵測到更新。GitHub 發布版本後會顯示在這裡。
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一分鐘完成驗證正在載入完整 README。 以下為已儲存的摘錄。
A browser-based lighting calculation workspace for room sizing, luminaire counts, 2D illuminance heatmaps, 3D room preview, design checks, and printable reports.檢視完整 README ↗A browser-based lighting calculation workspace for room sizing, luminaire counts, 2D illuminance heatmaps, 3D room preview, design checks, and printable reports.
node server.js
Open http://localhost:8787.
Copy .env.example to .env and provide AI_API_KEY and AI_MODEL. The server exposes POST /api/ai as an OpenAI-compatible proxy. The frontend never receives the secret key.
The endpoint is guarded: per-IP rate limit, small request body cap, message length cap, only user/assistant roles accepted, and a server-side system prompt that keeps answers on lighting topics (override with AI_SYSTEM_PROMPT).
On Vercel, api/ai.js is deployed as a serverless function. Add AI_API_KEY, AI_MODEL, and optionally AI_API_URL under Project Settings → Environment Variables, then redeploy. Keep the variables enabled for the Production environment. (Rate limiting on Vercel is in-memory per function instance — best effort.)
The app remains fully usable without AI configuration.
Results are design estimates based on the entered assumptions and simplified photometry. The heatmap treats each luminaire as a Lambertian source; validate final designs against the applicable project standard and real photometric data.