A worker that answers /v1/models has not necessarily loaded its weights, so the app
was offering an AI control that could only fail after the upload. Readiness now
passes only once the pinned model is loaded, and the not-loaded state reaches manual
Bristol entry in one tap. Verified against the real pinned llama.cpp build: it serves
503 while loading and the gate reports the distinct not-loaded state.
Adds the reproducible container recipe (digest-pinned bases, pinned llama.cpp commit,
hash-verified read-only weights, unprivileged, loopback-only publish), one shared
post-load readiness gate used by the host bootstrap and the image healthcheck, and a
target-GPU benchmark that refuses to write a receipt it did not measure.
Refs #15
Logging must never depend on AI availability, and an unsaved entry must not
disappear when the user navigates away mid-log.
- add src/vision-readiness.js so the photo flow consumes one readiness contract
- when the worker is offline/disabled/unknown, offer no AI action and no
analysis-consent prompt, and keep manual Bristol entry one action away
- add src/draft.js and make the draft own the photo so a chosen photo and
entered context survive a recoverable close or navigation, with a visible
kept-draft summary and an explicit start over
- drafts stay in session memory only: a photo awaiting consent is never
persisted, and reload starts clean
- service worker now refuses to cache image bodies in addition to analysis
requests and no-store responses
- tests: 2 new unit files, 3 service-worker privacy assertions (1 hold-out),
1 browser acceptance file, release-demo and CI/package assertions
- release demo now visibly replays the vision-offline pass and the retained
draft with synthetic data and an in-script assertion