Its server, client, app and curator, and the tools that write its
assets (maps, Anki fixtures, icons), as they are; paths are fixed in
the commits that follow.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
Once the person agrees, the device holds MeCab's IPADIC and the
instance's JMdict and cuts lines as Jisho.org does, so their text never
leaves it (ADR 0012). MeCab comes through mecab_for_dart, whose build
hook compiles it; its tokens are grouped by Ve's rules, written anew in
Dart, with に kept a word of its own. Each word is found as it stands or
as a form of a word, else by its dictionary form, else as the longest
words it holds from token to token; longer words over token boundaries
are offered as before.
The curator packs Ubuntu's compiled IPADIC beside the dictionary files
(curate ipadic, and every update run). The server exports its JMdict
from its tables, so the device finds the same keys and keeps the same
versions, and serves both at /device-dictionaries/, named in
dictionary.deviceFiles('ja') with their hashes; Caddy forwards the path.
The app checks each file against its hash, unpacks IPADIC, builds a
SQLite database from the export on an isolate, and asks the instance
for newer files every 30 days, downloading only what changed. The Watch
screen offers the download once per device with its size (34 MB, some
150 MB once set up); Settings downloads and removes them. Without them,
or should cutting on the device fail, lines go to the instance as
before. MeCab's, IPADIC's and Ve's licences join the licence list.
Every build now needs a C++ compiler; mecab_for_dart holds code_assets
at 1.x.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
JMdict brings Tatoeba's sentences for Japanese; the other languages'
dictionaries had none (CC-CEDICT) or Wiktionary's own, often
quotations. Each file now takes Tatoeba's sentences of the week (its
per-language exports, CC BY 2.0 FR) as its entries' first examples,
which become a card's hints: each sentence with a translation into the
dictionary's meaning language goes to the entries its words find, cut
as the app cuts a line of subtitles (at spaces, Korean's particles off,
Chinese by its longest words), up to three for each, those using the
word as its headword writes it first (Haus rather than zu Hause; 学习
rather than 學習 in the simplified dictionary), then those nearest seven
words long. German's common words nearly all get some (8,849 of
9,292), in ten seconds and under 300 MB; a dictionary whose sentences
can't be had keeps its words. `curate tatoeba` does the same for a file
made by hand.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
A dictionary file now says whether it holds words or characters (`kind`).
The kanjidic adapter turns KANJIDIC2 into one entry per kanji that has a
Japanese reading or an English meaning (12,633), with its readings,
meanings, school grade, strokes, frequency and JLPT level (Jonathan
Waller's, through kanji-data's kanji.json), labelled `jlpt:nX`,
`grade:N`/`grade:secondary`, followed by the 71 hiragana and katakana of
the kana table with their romaji. A kun reading is found whole; its kanji
part only as a loose key, so typing "ta" brings た before every kanji read
so.
`curate kanjivg` writes KanjiVG's strokes and components as the app's
stroke files, one gzipped JSON file per 256 code points, keyed by the code
point in each entry's id (KanjiVG's 橅 names itself 機).
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>
A package of its own in the workspace, without Serverpod (AGPL, like the
tooling): an adapter per source writes one format for all, documented in
its README, which the server will load. The format is JSON Lines: a
header (source, version, languages, licence, credits), then entries with
a headword and reading, labels (`common`, `jlpt:n5`), a rank, the keys a
search matches, and the entry as cards take it. Everything specific to a
language happens in its adapter (Japanese: forms, readings in kana and
Hepburn romaji, long vowels typed once, meanings without "to" and
articles), so the server's search knows no language.
JMdict comes as jmdict-simplified's JSON, read one entry at a time: all
218,863 entries in some 20 seconds and 300 MB, 16.8 MB gzipped. The JLPT
lists (yomitan-jlpt-vocab, CC BY-SA 4.0, from Waller's CC BY lists) add
levels by JMdict entry, the easiest when a word is on several, and give
the headword its common spelling. Words rank N5 to N1, then the other
common words, then the rest.
The server's image leaves the package out, as it does the client's.
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>
