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Tizian 「ティツィアーン」
da51ef73cb
Animelon's way of learning from video, from the person's own Jellyfin server: connected per device (Settings, or a studyset's Add material › Watch from Jellyfin) with a name and password or a Quick Connect code, over HTTPS only (plain HTTP only to a server on the same machine); the token stays in the system's keyring. Shows, films and videos tied to a studyset follow the person in their settings as the server's and the item's ids alone (settings schema 9), named by the server when shown. The Watch screen plays the video (video_player on Android, media_kit's libmpv on Linux and Windows) with the line in the studyset's front language cut into the dictionary's words with furigana, and the back language's line beneath; a word tapped pauses the video and becomes a card with the line and its translation as its first hint, tagged with the show. The video's words are listed, most frequent first. The sound is the track in the studyset's language, whichever the file marks default, and the menu switches it; the subtitles read are a whole track, never a forced one (which only covers what the sound doesn't say), and captions for the hard of hearing only without plain ones. The line and its translation take the video's width in a box of a fixed height, so the video keeps its size; in the dark theme the video's colours glow around it, as YouTube's ambient mode, and the words' panel takes the colour of the episode's picture under the pointer. A line is cut into words with one request: DictionaryEndpoint.withKeys looks up every stretch of it that may be a word, as it stands and as every word it may be a conjugation of, in the new dictionary_key table (one row per key, indexed; migration dictionary-keys adds the table and its index, nothing else), which the loader fills beside the entries. The instance gets the text of each line looked up and keeps none of it, as the Watch screen says. Linux builds need libmpv-dev, and the app links libmpv: the snap stages Ubuntu's libmpv2, makes the update-alternatives links for BLAS and LAPACK that ffmpeg's speech recognition needs (staging never runs install scripts), and removes what the GNOME runtime and core24 already hold, as older copies of cairo, pango and librsvg hid the runtime's from its GTK. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me> |
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| .. | ||
| bin | ||
| config | ||
| dictionaries | ||
| lib | ||
| migrations | ||
| test | ||
| .gitignore | ||
| analysis_options.yaml | ||
| CHANGELOG.md | ||
| dart_test.yaml | ||
| Dockerfile | ||
| LICENSE | ||
| pubspec.yaml | ||
| README.md | ||
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
dictionariesservice indeploy/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 mountdeploy/dictionaries/into the server (compose.yamlsays how), and update them monthly. - Development:
dart run halkyon_learn_curator:curate update --into ../halkyon_learn_server/dictionariesin 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.