Two benchmark rounds (14 models on 30 problems, then gpt-4o-mini vs gpt-4.1-mini
on 102 problems under three prompt versions, hand-graded): gpt-4.1-mini scored
95-96/102 against 85-90 for gpt-4o-mini, at 0.12 vs 0.04 cents per answer.
The default now lives in settings so the deploy needs no .env edit.
The context note "in the book / is a decimal point, not a fraction" was written
for the upper-grade books but went to every grade, so gpt-4.1-mini computed
1/7 + 1/8 as 3.5. For primary grades the note now says / can be either, and a
reading rule sits next to the question itself (the same rule at the end of
the system prompt had no effect). Slash problems went from 11 to 14 of 17;
three are still wrong.
generate_answer now reports the provider's exact per-call cost, reasoning
tokens and whether the raw output broke the plain-text rule. The benchmark
fixes primary grades being sent with no book context, caches retrieval so
runs compare on identical context, and retries Qdrant timeouts.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Kavenegar is being switched on, so every OTP request now costs credit:
- phone numbers are normalised to 09XXXXXXXXX everywhere (login, OTP,
family invite, TEST_LOGIN_PHONES keys) and existing rows are migrated;
non-Iranian and landline numbers are rejected before any SMS
- cooldown and a daily per-phone cap are counted in the database, so the
three gunicorn workers no longer triple them
- a global daily OTP SMS cap (default 300) stops SMS pumping
- per-IP rates widened for CGNAT / school Wi-Fi (env-overridable)
- provider message id is logged; SMS text warns not to share the code
Second audit round: an offer no longer shortens a longer paid plan,
Zarinpal error bodies no longer 500, island XP reaches the parent report,
a non-numeric questionId no longer 500s after the answer is generated.
596 tests green.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Tutor (prompt tutor-v3-stepwise-plain): plain text instead of LaTeX/markdown,
with rag/services/mathtext.py converting whatever still slips through; full
step-by-step solutions with a check before the final answer; three tones by
grade; the last 6 messages of the conversation go to the model and follow-ups
are no longer served from another user's cache; book solutions the checker
disputes are kept out of the context; a questionId gives the tutor the
practice question and the student's wrong answer. /api/health reports when
the AI credit runs out. rag_model_benchmark compares chat models on verified
book problems (run on the server; credit ran out mid-run).
Map: only lessons that have questions count toward finishing an island,
lessonIds[0] / nextLessonId is always the next lesson to play, and a finished
island stays finished. The Seyar characters (sigma/delta/pi) are seeded.
Audit fixes, each reproduced before fixing:
- the plan is stored on the order, so paying a monthly order after starting
a yearly checkout no longer grants a year
- opening checkout no longer demotes an active subscription; renewals extend
from the current expiry; expired subscriptions are not reported active
- one discount code per order and only before the gateway; a 100% code
completes the purchase; lost Zarinpal confirmations are re-verified
- the unused /api/payment/webhook "mark paid" endpoint is removed
- XP counts only answers recorded on the server
- 6-digit OTP, each code dies after 5 wrong guesses; POST /api/auth/logout
- a guest who signs up keeps their account and progress (test phones excluded)
- affiliate commission on the first real payment; guests excluded
- parents with several children no longer get a 500
- SQLite runs transactions IMMEDIATE, since it ignores select_for_update
- admin login is rate-limited; display names drop phone numbers and links;
userQuestion is capped at 2000 characters
- server-side heart enforcement exists behind HEARTS_ENFORCED (off until the
frontend handles 403 no_hearts)
Not done on purpose: rotating the server's secret key and moving to Postgres.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Each heart used to take 24 hours, so a student who lost all five waited up to
five days. Now one heart returns every 5 hours, and 24 hours after the first
heart was lost they all come back at once (the owner's call). /api/user/hearts
reports both times (nextRefillAt, fullRefillAt); an existing timer longer than
5 hours is shortened the first time it is read.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Found in a deeper pass over what the frontend's flow actually touches:
- Nothing in the app ever wrote StreakRecord: "days in a row" was 0 forever
for every real user. Answers and lesson/island completions now record the
day (Tehran time); a broken chain shows 0. A streak error never fails the
answer itself.
- /api/leaderboard only changed when someone ran rebuild_leaderboard by
hand. It is now computed live (60s cache); weekly counts island XP too.
- gunicorn ran 3 sync workers with a 30s timeout, so every "ask Pi" stream
pinned a whole worker (~10s, GapGPT buffers the answer) and three at once
queued the entire API. gunicorn.conf.py (read automatically from the
working directory) switches to gthread, 8 threads, 120s timeout.
- Every /api/ response now says Cache-Control: private, no-store, so turning
on caching in the ArvanCloud panel can never serve one student another's data.
- /api/user/summary named no active plan ever ("subscription app not
implemented yet" had long stopped being true).
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Production is ArvanCloud -> nginx -> gunicorn, but NUM_PROXIES was 1, so DRF
took ArvanCloud's edge IP as the client: every guest and every OTP request
behind one edge shared a single throttle bucket (20 guest sessions an hour for
everyone). Default is now 2, and /api/health reports clientIp so the proxy
count can be checked from outside.
PATCH /api/notifications/read-all replaces the frontend's one-PATCH-per-item
loop, which spent the shared "read" budget 75 requests at a time.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
The frontend plays node quizzes, but a node only completed once every one of its
8-13 lessons was completed separately, so students were stuck after the first
island of each unit. POST /api/nodes/{id}/quiz/complete now completes the node
(any score; score only sets stars/xp) and returns nextNodeId.
Also closes the other backend gaps found while auditing the frontend:
- /api/ai/ask without lessonId now picks the book from the user's grade instead
of skipping retrieval, so the "ask Pi" tab is grounded in the textbook.
- guest sessions return a refreshToken; they used to go silently 401 after 1h.
- lesson_complete throttle 10/hour -> 120/hour (a lesson here is 1-2 questions).
- progressPercent is per grade, not over all 2,617 lessons of every grade.
- a one-year plan (299,000 toman) is created by migration when no plan exists.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Grade ids were the order the books were imported in (ninth=1, eighth=5), so
gradeId: 5 meant eighth grade and the admin, the question filter and the API
all listed grades out of order. Grade.number (1-12) is now read from the title,
new grades take it as their id, and migration 0008 moves existing ids plus every
reference to them: Unit, the loose grade_id in accounts/ai_tutor/rag, and the
grade target inside campaign JSON. Unnumbered demo grades move above 100 and the
id sequence is raised past 12 so they never collide with a real grade.
The frontend needs no change: it always reads gradeId from the server.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
The README had grown into a 295-line mixture of onboarding, an ops runbook, a
content-authoring workflow, bulk question generation and a Docker log stack. A
reader arriving at the repo could not tell in ten seconds what this service is,
whether it is live, or where to start, and five of its claims no longer matched
the code:
- it said to export .env values by hand; settings.py has loaded .env through
python-dotenv for a while now
- it listed six variables as "everything the app actually reads"; .env.example
has carried many more than that for some time
- it called DJANGO_SECRET_KEY, DJANGO_ALLOWED_HOSTS and CACHE_URL required in
production; all three now have working defaults, and the app boots without
them on purpose so a partial .env cannot take the service down
- it claimed there is no insecure SECRET_KEY fallback; there is one, under DEBUG
- it required Python 3.12 while the project runs on 3.11 (Docker uses 3.12)
The README now states what the service is, where it runs, how healthy it is and
how to get it running in six commands, then links onward. Procedures moved to
docs/operations.md, docs/content-authoring.md, docs/architecture.md and
docs/docker.md, which is where someone follows a procedure rather than skims it.
Nothing was dropped; the deploy one-liner now includes the separate sudo restart
that deploy.sh cannot perform itself, and backup/restore is written down for the
first time.
Every number in the README was measured rather than quoted: content counts from
the live /api/health and content/seed/curriculum.json, 55 endpoints from the
generated OpenAPI schema, 481 tests from a full run.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
