Easy-to-manage touch screens
무료 오픈소스 터치스크린으로 USB 설정 가이드, 드래그‑드롭 편집기, 로컬 제어를 제공하며 Home Assistant용으로 제작되었습니다
아직 감지된 업데이트가 없습니다. GitHub 릴리스가 나오면 여기에 보입니다.
메이커가 쓴 소개는 위의 한 줄이 전부입니다. 더 자세한 내용은 저장소 README에서 읽을 수 있습니다. 저장소 README ↗
README 전체를 불러오는 중입니다.
README 전문 보기 ↗Browse Amtrak stations and routes, and ask plain-English questions about schedules ("first train from New York to Boston next Thursday?", "Friday out, Sunday back from Philadelphia"). Built on real Amtrak GTFS data. A learning project: SQL, analytics instrumentation and AI-product evals.
Live: https://amtrak-explorer.vercel.app (behind Vercel SSO, so you need to be signed in)
| Layer | What |
|---|---|
| Database | Neon (serverless Postgres) |
| Frontend | Plain HTML/JS/CSS, no framework, no build step |
| Backend | Vercel serverless functions (api/); all database access goes through them |
| AI | Anthropic API, one pinned model, three fixed-SQL tools (the model never writes SQL) |
| Hosting | Vercel, auto-deploys on push to main |
npm install
npm test # unit tests, free, no network
The api/ functions need real credentials, so test them on the deployed site or with
vercel dev. npx serve only serves the static page.
The eval harness runs 40 hand-written questions through the real ask loop and appends a
row to eval/RESULTS.md. It makes real model calls (a few tens of cents), so run it on
demand, never in CI.
vercel env pull .env.local # DATABASE_URL + ANTHROPIC_API_KEY (git-ignored)
npm run eval # add -- --no-record to skip writing a row
npx vercel env pull .env.local --environment=production..env.local.CLAUDE.md: how the project works, the architecture rules, the AI layer,
data gotchas, roadmap and open items. Start here.docs/PRD.md: what this phase set out to build and why.eval/RESULTS.md: the eval run log.