AIPLA — AI in Physics Learning and Assessment
Execution repo for AIPLA, a technical-infrastructure contract for the
University of Copenhagen Center for Digital Education: AI physics tutors,
interactive sims, and teacher/researcher tooling for upper-secondary physics.
Repo: sunholo-data/cphu-aipla-app · Default & working branch: dev.
Built on the open-source AI Protocol Platform template (Skills + AG-UI +
A2UI + MCP Apps + A2A on Google ADK). Some inherited files still say "Aitana
Platform v6" — the AIPLA reality is authoritative. See CLAUDE.md.
Run it locally (no GCP credentials)
cp .env.example backend/.env # then set LOCAL_MODE=1
cd backend && make install && cd ..
make dev # frontend :3456 · backend :1956
Open http://localhost:3456 — you get a yellow LOCAL_MODE banner and working
demo skills, with Firestore/Firebase/Vertex all stubbed in-memory. Full walkthrough
and the cloud tiers: WORKSHOP.md.
Where things are
| |
|---|
frontend/ | Next.js 15 + React 19 + Tailwind (chat, teacher, researcher surfaces) |
backend/ | FastAPI + Google ADK (skills, agents, protocols, auth, analytics) |
cli/ | the aiplatform CLI (make cli-install) |
infrastructure/ | mcp-sandbox (sim iframes) + Terraform |
docs/design/ | design docs — start at docs/design/README.md |
Where the design lives
- Execution design (file paths, wire shapes, acceptance) → this repo,
docs/design/aipla/SEQUENCE.md.
- Public project information → the app's native
/project pages, authored
as reviewed English Markdown in frontend/content/project/. Each page has a
named owner, status, and next-review date; npm run check:project-content
checks those fields and internal links before deployment.
- Historical product and pedagogical scoping material → the separate AIPLA
Quarto repository. It remains an archive and redirect source during cutover,
not the maintained public source of truth.
- Working with this repo as an AI agent → CLAUDE.md is the
authoritative context (identity, gotchas, footguns, ports).
Common commands
make dev # local dev servers (:3456 / :1956)
make seed ENV=dev # push SKILL.md templates to Firestore (manual, post-deploy)
cd frontend && npm run quality:check # CI parity: lint + typecheck + tests + build
cd backend && make lint && make test-fast
See the Makefile (make help) for the full target list and
CLAUDE.md for the development workflow.
