halkyon/halkyon_learn_server
Repository files (latest commit first)
Filename Latest commit message Latest commit date
Tizian 「ティツィアーン」 9f1716f16d
fix(assistant): single use under racing requests, a cap on registering, Caddy reloaded
A connect code, an authorization code and a refresh token are each
consumed by deleting their row and going on only if that deleted it, so
of two requests racing with the same one only one succeeds (as OAuth
requires); tests race them. Registration, open to anyone, takes at most
200 clients an hour (429 after), so a flood can't fill the table before
pruning. The deploy reloads Caddy in place when deploy/Caddyfile changed,
as `docker compose up` doesn't restart it for a file it mounts: without
it the connector's paths wouldn't reach the web server.

Also formats the app's fake assistant gateway, new and so unchecked by
the last commit's check (tool/check.sh formats tracked files only).

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-10 15:11:18 +02:00
..
bin chore: scaffold the Serverpod 4 build 2026-09-24 15:32:29 +02:00
config feat(assistant): Claude reads studysets through a connector on the instance 2026-10-10 15:11:17 +02:00
dictionaries feat(server): dictionaries, loaded from files and searched 2026-10-09 18:09:25 +02:00
lib fix(assistant): single use under racing requests, a cap on registering, Caddy reloaded 2026-10-10 15:11:18 +02:00
migrations feat(assistant): Claude reads studysets through a connector on the instance 2026-10-10 15:11:17 +02:00
test fix(assistant): single use under racing requests, a cap on registering, Caddy reloaded 2026-10-10 15:11:18 +02:00
.gitignore feat(dictionary): the radicals, each listing the kanji written with it 2026-10-10 09:46:46 +02:00
analysis_options.yaml build: Serverpod v4.0.3 2026-09-30 20:38:15 +02:00
CHANGELOG.md chore: scaffold the Serverpod 4 build 2026-09-24 15:32:29 +02:00
dart_test.yaml chore: scaffold the Serverpod 4 build 2026-09-24 15:32:29 +02:00
Dockerfile feat(publish): releases in git (public tier, stage 2) 2026-10-10 09:46:38 +02:00
LICENSE docs: licences and how to contribute 2026-09-30 20:38:16 +02:00
pubspec.yaml fix: Serverpod v4.0.4 and serverpod_offline_sync v0.0.10 2026-10-09 18:09:27 +02:00
README.md feat: a dictionary's corrections reach the cards made from it, by offer 2026-10-09 18:09:37 +02:00

halkyon_learn_server

This is the starting point for your Serverpod server.

Start your server by running:

cd halkyon_learn
serverpod start

When you are finished, you can shut down the running server with Q.

Dictionaries

The dictionaries people look words up in (JMdict, …) are reference data the server holds for everyone. They come as dictionary files, which halkyon_learn_curator makes from the sources' downloads (its README says how). At every start, and every hour at seven past, the server loads the files in its dictionaries folder that changed since they were last loaded (by their SHA-256): in the background, a source at a time, and all at once, so searches meanwhile still find the old entries. A file it can't read is logged and left out. DICTIONARIES_DIR names another folder.

EDRDG's licence asks a server showing its dictionaries to update them at least once a month:

  • An instance keeps them current by itself: the dictionaries service in deploy/compose.yaml (the curator, in a container of its own) downloads EDRDG's files of the day once its files are a week old, converts them, and replaces them in a volume the server reads (curate update, the curator's README); the server takes them up within the hour. To supply files yourself instead, remove the service and mount deploy/dictionaries/ into the server (compose.yaml says how), and update them monthly.
  • Development: dart run halkyon_learn_curator:curate update --into ../halkyon_learn_server/dictionaries in the curator's folder (about a minute); the server takes them up within the hour.

JMdict in English, with the JLPT levels and Tatoeba's example sentences, is about 20 MB gzipped and takes the server half a minute to load (219,000 entries). KANJIDIC2 in English, with the JLPT levels of the kanji and the kana, is a dictionary of characters beside it (kanjidic-en.jsonl.gz, 0.7 MB, 12,800 entries): the app's Kanji & kana tab. Their licences (CC BY-SA 4.0; CC BY 2.0 FR for the sentences; CC BY for the JLPT lists) ask for attribution: the app lists the credits each file carries.

Licence

Copyright (C) 2026 The Halkyon Learn contributors

Licensed under the Server Side Public License, version 1 (SSPL-1.0); the full text is in LICENSE.