A 2,000px radiograph written into an article rendered at whatever width it
happened to be — a wall of greyscale in the middle of a sentence, four
megabytes to draw it, and no way to look at it properly. Every image in prose
is now a 256px thumbnail with the author's label under it, and a click gives it
the screen.
The viewer puts what is known about the figure beside it: its title, what it
shows, and where it came from. `media_assets` gains `source` and `source_url`
for that — a citation belongs to the file, because the same figure used in
three articles is cited the same way in all three, and a licence that turns out
to be wrong is one row to fix rather than three paragraphs to find. Asked for
when the figure is opened, not when the page is drawn.
And `overlay`: the regions an educator has marked, as vector shapes in
normalised coordinates on the unit square, so one drawing is correct in a
thumbnail, in the viewer and on a projector. Off until the learner turns it on
— marks shown before they have looked answer the question for them. Vectors
rather than a second burnt-in picture, for four reasons written down in
docs/image-overlays.md. The tool that draws them is next; this is the storage,
the contract and the reader's half.
On a narrow screen the description stacks above the image rather than beside
it, where it can be read before scrolling to the picture.
Also here: `classify_question_difficulty`, which labelled all 2,924 questions
in batches of twenty-five against a written rubric — 622 easy, 1,634 medium,
668 hard, no failed batches. The column had been NULL on every row since it
existed. Migration l2c3d4e5f6a7.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01TqXevQJhxFrM7jJg82cgZN
Storage
Media now goes through `storage_service`, which has two backends: the container
volume, and S3/MinIO. A volume can only be mounted by one host, has no presigned
URLs and no lifecycle rules, none of which suits ~860 MB of media. Reads fall
back to the volume when an object is missing, so the existing uploads keep
working and files can migrate gradually rather than in one risky pass.
A row stores the object key, never a URL: a URL embeds the backend, so a row
holding `http://minio:9000/...` breaks the moment the backend changes.
MinIO publishes no host ports — the backend reaches it over the compose network,
and 9000/9001 are already taken on this host by other stacks.
Image libraries (migration d2e3f4a5b6c7)
An image belongs to a library, and a person is granted a library the way they are
granted a category, so access can be given to some images without giving away all
of them. Tags reuse the shared `question_tags` vocabulary rather than inventing a
media-only one. Uploads are type- and size-checked, stored through the service,
and embedded so an image can be found by what it shows.
Classification finished
The 316 questions the chooser had declined are now filed with `--force`, which
takes the nearest candidate from the same shortlist the chooser saw. 306 were
forced, 10 the chooser accepted on this pass. No question sits on a bare system
any more:
system only 2,730 -> 0
condition/subsystem 214 -> 1,782
full depth 4 -> 1,166
A forced match is a weaker signal than a chosen one, so expect more errors among
those 306 — but the original system stays as a cross-link, so nothing is lost and
they can be corrected by hand.
Tests: 8 new backend covering library scoping, edit confinement, shared-vocabulary
tags, storage indirection on upload, and type/size limits. 131 backend green.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01WgRcMaScVEL7TBLpnAoSV9
Images were findable only by the filename someone typed. `media_assets` gives
them a title, caption, alt text, a category on the shared tree and tags, with a
weighted tsvector so they are searchable now (migration y7e8f9a0b1c2).
The embedding column is filled from the caption today. A vision-capable model can
fill it from the image itself later without another migration — and because
`embedding_model` stamps every vector, a text-embedded caption and a
vision-embedded image stay distinguishable instead of being silently mixed in one
index. Adding "media" to the embeddable kinds is all the retry task, the full
regeneration and the health report needed.
`media_tag_links.tag_id` carries no ORM-level foreign key: `question_tags` is
created by raw DDL rather than a model, so the constraint lives in the migration
where the table actually exists.
Tests: 113 backend green.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01PpfzbZ1QTLMeVYxM2kyq8m
