Single sign-on wrote a random string nobody would ever know. That reads as
"has a password" to everything that asks — so Settings demanded a current
password before it would let those accounts set their first, and the only way
through was to click "forgot password" for a password they never had. The same
trap was waiting for anybody who only ever signs in with a code.
Null says the true thing. Signing in refuses an account with no password the
way it refuses a wrong one, because which accounts have one is not a question
that endpoint answers. Setting a first password asks for no current one;
changing an existing password still does. `/auth/me` reports whether there is
one at all and nothing about it, because Settings has to choose between "Set a
password" and "Change password" and cannot tell from the outside.
The random strings already written are left alone. They are unguessable, so
nothing can sign in with them, and clearing them would mean deciding from
outside which accounts were meant to have one.
Identity is the email address throughout, so the three ways in are three ways
into the same account: single sign-on, a code, or a password — and a person may
acquire or drop the third at any point without losing the other two.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01TqXevQJhxFrM7jJg82cgZN
The voice picker was a dropdown in the quiz player, beside the question — the
one control on that screen with nothing to do with answering it, and one a
learner sets once and never touches. It is a setting now, on the user rather
than in a Redis blob, with a play button beside each voice because a voice is
worth hearing before it is chosen. Choosing nothing stays a real choice: it
means whatever an administrator marked default, so a site that changes its
default reaches everybody without a row being edited.
The tutor reads figures from `question_media` rather than the two legacy path
columns. Those agree exactly today, so nothing was being lost — the first
question given a second figure in the editor would have been the one that
broke it, silently and only for the tutor. The legacy columns remain as a
fallback for anything not projected into that table yet.
And the retrieval thresholds are written down in docs/retrieval-thresholds.md:
the three answers, the sixteen queries they were measured against, why they are
deliberately not the retrieval floor, and how to re-measure when the corpus
grows. Worth keeping the headline in mind — "discuss love" scores 0.491,
alongside "tell me a joke". A number in the 0.4s is noise, not a weak signal.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01TqXevQJhxFrM7jJg82cgZN
Deleting a user failed with a not-null violation from quiz_attempts.
Every foreign key to users is already CASCADE or SET NULL in Postgres,
but the ORM relationships had no passive_deletes, so SQLAlchemy insisted
on emptying each one itself by writing NULL into columns that refuse it.
passive_deletes leaves it to the database, which knows. The two tables
that genuinely cannot forget a user — question_categories and
quiz_categories are NOT NULL and NO ACTION — hand their rows to the
administrator doing the deleting: the taxonomy is the site's, not the
author's.
/tags counted through question_tag_links, which is now empty, so every
organ system read zero and an active exam hid them entirely. It counts
through the topics that carry them instead: 2,919 of 2,924 questions, all
sixteen systems with real numbers. The session builder's Disciplines and
Symptoms pickers were over the retired vocabularies and are gone —
Topics is the same axis said once and said better, 673 against 203.
The end-block dialog offered one button. A confirmation with one button
is not a confirmation: it now leads with the way back into the block,
says how many are unanswered as a sentence rather than a grid to count
by eye, and the unanswered are numbers you can press to go there.
Registration asks for the password twice, on both forms — a password you
cannot see is one you can mistype into an account you then cannot open.
The public pages had no footer, so signing in meant losing the way to
About, Contact and the clinical disclaimer. They sit in a plain layout
that keeps it.
Draft batches can be filed from the workbench: the topic they file into
is a picker at the top, and nothing crosses over until it is set.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01TqXevQJhxFrM7jJg82cgZN
The linking was the gap
The marker system was built weeks ago — resolves by id, survives a rename, shows
a preview on hover — and not one of 333 articles used it. Every article was
written in isolation, so a piece on croup named stridor and epiglottitis and
offered no way to reach either. `scripts/link_articles.py` reads what is written
and links it: 3,718 cross-references across 307 articles, by id, so a later
rename cannot break them.
Conservative on purpose, because a wrong link is worse than a missing one: only
the first mention in a section, whole words, longest title first so "Otitis media
with effusion" beats "Otitis media", never inside an existing link, marker,
heading, code span or table, and never an article to itself.
That exposed a second thing: the reading view had its own Markdown pipeline with
its own cross-reference regex, and it only understood the old slug form. It would
have printed every one of those 3,718 links as literal brackets. Article prose
now goes through the same renderer as the rest of the site.
Short and Clinical looked empty
Both are usually a single section, and everything starts collapsed, so the tab
showed one heading over blank space. A view of one section is not a contents
page; it opens.
Removed
Quiz reminders — emailed nudges to retake anything under 75%, with a scheduler
that existed solely to send them: the model, the service, the scheduler, the
email, the table. Article comments. The dashboard's in-progress list and its
stat cards, both of which the analysis page now answers better.
One mistake worth recording: the first pass at removing the reminder cleanup used
a regex that took 109 lines with it, including an unrelated endpoint. The test
suite caught it (`/attempts/quiz/{id}/in-progress` returning 404 instead of 403),
and the file was restored and edited by exact match instead.
208 backend, 249 frontend green.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01TqXevQJhxFrM7jJg82cgZN
Exams (migration v4b5c6d7e8f9)
"Pediatrics Boards" was a hardcoded checkbox that filtered nothing. Exams are now
rows: Pediatrics Boards and USMLE Step 2 CK ship seeded, and everything already
in the bank is linked to the boards. Membership is a link table, not a column,
because one paediatric cardiology question can count towards several exams.
The learner's choice lives on `users.active_exam_id`, so it follows them between
devices instead of sitting in one browser's storage. Choosing an exam scopes the
bank; a question with no exam links stays visible, since unlinked content is
unclassified rather than excluded. A switcher sits in the navbar.
AI mode — matching, never generating
Both entry points build a test from the educator-reviewed questions that already
exist, ranked against the request. Nothing is invented:
- POST /questions/builder/describe turns "what I want to study" into a test.
- POST /questions/builder/from-upload matches a document against the bank. The
file is read in memory and never stored — it is a search query, not a source
of questions, so there is nothing to retain or expire. 10 MB cap, 30 questions.
Handing a whole document to `websearch_to_tsquery` builds one enormous
conjunction that matches nothing, so text over 300 characters is reduced to its
most distinctive terms, OR-joined, before it reaches the lexical ranker.
Continue your study (migration w5c6d7e8f9a0)
A dashboard panel with the sessions in flight and the articles most recently
opened. `article_views` records one row per learner and article, written best
effort so a reading page never fails because a bookkeeping write did.
Tests: 5 new exam tests (active exams and counts, choice persisted and cleared,
unknown/inactive refused, bank scoping including unlinked questions, moderator-only
creation) and 7 for AI-mode matching (no questions created, invisible questions
excluded, no-match reported rather than an empty test, upload limits enforced).
Full suites green: 113 backend, 136 frontend, build clean.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01PpfzbZ1QTLMeVYxM2kyq8m
- Add reminders_disabled boolean column to users (DB source of truth).
- Scheduler reads the DB column directly; Redis no longer used for
opt-out checks.
- Scheduler now deactivates reminders when a user has no completed
attempts left for a quiz (e.g., after deleting their attempts).
- Settings API: GET returns DB value for reminders_disabled; PUT
persists that key to DB and keeps the rest of the blob in Redis.
Rollback point for Alembic wiring.
Embedding:
- Embedding model now configurable via Admin UI (More tab) or LITELLM_EMBEDDING_MODEL env
- Calls LiteLLM proxy directly via httpx (bypasses LiteLLM library param validation)
- Passes dimensions=1024 to proxy; Redis setting overrides env var
- Default model: ge-gemini-embedding-001 (Gemini AI Studio, 1024-dim)
- Test button in admin UI to verify model works
- Fixed vector_service to use httpx + Redis model (was broken with non-prefixed model names)
Polly:
- Global enable/disable toggle in Admin → More settings (stored in Redis)
- /tts/voices filters out polly/* when disabled
- /tts/speak rejects polly requests when disabled
Job cancellation:
- POST /quizzes/job/{job_id}/cancel endpoint
- Cancel button on JobsPage for running jobs
- Celery task checks Redis status at each chunk boundary and exits cleanly
- Fixes DB lock on restart caused by cancelled jobs leaving open transactions
Admin UI:
- Settings tab renamed to "More" (heading: More Settings)
- Model row overflow fixed (minWidth: 0 + ellipsis on model_id)
- Embedding model search shows all proxy models (no auto-filter by "embed")
- Navbar correctly excludes cancelled/failed jobs from "extracting" count
README:
- Added Rebuild & Restart section with commands
- Updated embedding model reference
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- FastAPI backend with JWT auth, roles (admin/moderator/user)
- PDF upload (up to 500MB) with streaming, PyMuPDF text extraction
- ChromaDB vectorization per page with metadata
- LiteLLM AI question extraction from PDF (not generation)
- Image extraction from PDF pages, graceful fallback
- Quiz modes: timed (countdown timer) + learning (answers shown inline)
- Page-by-page question navigation with dot navigator
- TTS endpoint using LiteLLM (Google Vertex / OpenAI voices)
- Admin dashboard: AI model management per task, user role management
- Moderator role: upload PDFs, create sections, generate quizzes
- Spaced repetition reminders via SMTP email (SM-2 intervals)
- APScheduler daily reminder jobs
- Celery + Redis for background PDF processing
- React frontend with all pages
- Docker Compose deployment (nginx + backend + celery + redis)
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
