Tapping a letter of the Greek alphabet among the dictionary's results
opened the character sheet, which could only say that there's no stroke
order for it. A letter of an alphabet has no strokes drawn, so the
dictionary now offers the tap only for characters of a script whose
strokes are drawn (Han characters, kana, Hangul), as a studied
character's answer does.
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 clause ending in a separable particle joined each word before it to the
particle and offered whatever the dictionary found, so "Er holt mich ab."
offered aber, "Er schläft ein." einer and "Er hört dem Lehrer zu." zudem.
Now only an entry that is a verb is offered, and a capitalised word after
the clause's first is taken for a noun and never joined.
The particles of fernsehen, hochheben, durchlesen, unterbringen,
übersetzen and bereitstellen were missing, as were the spoken rein, raus
and runter, so "Ich sehe heute Abend fern." now finds fernsehen.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
"Ich rufe dich morgen an": where a clause ends in a separable particle,
each word before it is also asked for with the particle joined on, as a
subordinate clause writes the verb (anrufe), which Wiktionary lists among
anrufen's forms. The verb is offered beside its stem and its particle,
as the longer words running over a Japanese word are.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
Parity with Japanese's kanji and kana:
- The characters' tab is named by its language (Hanzi, Hangul & Hanja,
Alphabet), its groups too: HSK levels and the characters in common use
(Hong Kong's grades for traditional ones); Hangul and the Hanja taught
in schools; Greek's letters. Radicals for Chinese and Korean in their
own forms (讠 for 言 in simplified Chinese), none for Greek.
- A character's readings are named as its language names them: On and
Kun, Pinyin, Eum and Hun (음, 훈); a letter means its sound and name.
- How characters are written comes by language: Chinese from Make Me a
Hanzi (its medians in KanjiVG's square, Arphic Public License, a data
file beside the app, never in cards), the Hangul letters drawn by the
curator; a Korean word is written letter by letter (닭: ㄷ ㅏ ㄺ). Words
of alphabets (German, Greek) aren't written by hand.
- A Chinese word's pinyin is typed in a session, tone numbers turning
into marks (ni3 → nǐ); KRDict's levels (초급, 중급, 고급) tag Korean
words; a Korean word's pronunciation shows in brackets ([가치]).
- Smaller: Look up in the composer keeps a noun's article; the Watch
filter names its level list; hints and placeholders by language.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
As a Japanese word's says its JLPT level: HSK 1 … HSK 6, HSK 7–9. The
levels' scheme (`WordLevels`, `levelOf`) moves from the Watch screen's
filter into the dictionary's model, which both name levels with.
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 studyset in German, Greek, English, Chinese or Korean finds its
dictionary as one in Japanese does (ADR 0008), and its subtitles are cut
into words by its language (`WordCutting`): Chinese by its longest
words as they stand, the longer words over each cut offered as for
Japanese; Korean at its spaces, a word the dictionary lacks as it stands
taken without the particle it ends with (집에서 is 집, 아이 stays a
child); every other language at its spaces, a word written exactly so
first (the noun Essen before the verb essen). A studyset finds the
dictionary of its language tag, else of its language alone (zh for
zh-Hans).
A Wiktionary word shows its genders, principal forms, IPA, romanisation
and Hanja; a German or Greek noun of one gender goes onto its card with
its article (das Haus, το σπίτι); its tag is its word class, named in
full (Noun, Adjective, Preposition), as Wiktionary's adj and adv would
read as JMdict's codes. Articles, pronouns, prepositions and
conjunctions are left out of a video's words. Chinese words show their
pinyin over each character on the Watch screen, carry their HSK level
as a tag (HSK-1 … HSK-7-9), and the dictionary adds a level whole; the
Watch screen filters by HSK levels for Chinese, JLPT's for Japanese, and
by none for a language without. A reading is typed in a session only
when it is kana, so pinyin isn't. Words are looked up on the web on
Jisho in Japanese, on Wiktionary at the language's section otherwise,
and a search's hint speaks of kana and romaji only in Japanese.
`DICTIONARY_LANGUAGES` in deploy/.env names the languages an instance
keeps (unset: de,el,en,ko,zh; empty: none).
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
The cut takes the longest word and knows no grammar, so 今日は reads as
こんにちは where it is 今日 and は. Any stretch of a line's characters can
now be chosen by hand: dragged across with a mouse, Shift+clicked from
the word or stretch chosen, or on a touch screen held on a character and
dragged on. It is looked up as one word, as it stands or as a form of
one, in one small request (the instance has the line's text already);
while it is chosen the line reads it as that word (きょう over 今日), and
what the dictionary lacks as one word is offered as a search on Jisho.
The line's words move into line_words.dart, out of the Watch screen.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
Cutting a line into words, kana that is no common word gave way to a
shorter common one whatever its length, so もうろく (耄碌, senility) was
taken as もう and ろく. The rule now holds only for kana of up to three
characters (が and まだ still win over がま, a cattail, and だ); a longer
kana word stands even when uncommon, as ichi.moe's segmenter weighs long
kana words by their length. And as no cut is always right, each word now
knows the longer words running over it into its neighbours, worked out
from the same lookup, which the Watch screen's panel offers beneath its
entries ("Longer words here"), each to add with the line.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
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>
The foot of the dictionary named each source with its makers and
licence, three lines of small print. It now names the sources alone in
a line ("Words from JMdict, JLPT vocabulary lists, Tatoeba"); tapping
it or its ⓘ shows who made each, under which licence, with its link,
which is still where the entries show, as the licences ask.
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>
Beside Words and Kanji & kana, a Radicals tab lists the 214 Kangxi
radicals by their strokes, with the forms Japanese writes them as inside
kanji (亻, 氵, 艹, …). One chosen lists the kanji KANJIDIC2 files under
it, in the dictionary's order, to add or to see how one is written; the
tab shares the characters' bloc, so a kanji added there shows as held in
a search too.
The curator labels each kanji with its classical radical (`radical:N`),
so the server's existing label queries serve the tab unchanged. Its
files now say which conversion made them (`.conversion`): an instance
running a curator that converts differently converts again at once,
rather than at its weekly update, so the radicals appear right after a
deploy.
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>
Explore says how many people learn a published studyset on this instance
(ADR 0005, rule 8): shown, never ranked, counted daily by the server from
the people with an identity who chose to be counted (Settings, Privacy;
settings schema 8) and studied a copy on 3 or more days of the last 30,
rounded down from 5 on, so that nobody can be told apart. Only a number
the instance computes itself counts; votes count for nothing. The author
sees the same rounded number in the Publish sheet.
A copy of a published studyset is published within the original's
licence: never under "no derivatives", under a licence that keeps
adaptations under it only under that one, in every studyset of the copy.
Its releases say what they are based on, and Explore shows it.
ADR 0005 gets an addendum with stage 3's decisions.
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>
Every dictionary entry now has a version: 16 hex digits of the SHA-256 of
what cards take of it (headword, reading, entry), made by the loader and
carried on every hit. A card keeps the version it took (card schema 8).
DictionaryEndpoint.changed returns, of the entries named with the
versions cards keep (1,000 at most a call; the app asks 500 at a time),
those whose version is another now.
The card browser says how many cards are behind their dictionary and takes
the corrections at a tap (decided 2026-10-09: by offer, never by
themselves). Taking one writes the entry as it is now over the revision
in which the card last took it, beside whatever came after, so the
revisions merge per side as two devices' edits do (ADR 0003): a side only
the dictionary changed takes the correction, a side the person changed
too is a conflict settled in the composer, whose words now name that
case. Cards made before versions are never offered one.
The server rereads its dictionary folder hourly now, not daily: the
dictionaries service fills its volume after an instance's first start,
and an hour with nothing changed costs a hash of each file.
Migration 20261009145434785-dictionary-entry-version: adds
dictionary_entry.version, text NOT NULL DEFAULT '' (rows loaded before
have none and are never reported as corrected), and by hand empties
dictionary_source."fileHash", so every source loads once more and its
entries get their versions; the schema stays as definition.sql says. The
old server goes on working until the switch.
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>
About lists the data the app comes with beside the instance's
dictionaries: KanjiVG's strokes, by Ulrich Apel under CC BY-SA 3.0, with
the link its licence asks for. The server's README names the dictionary
of kanji and kana beside JMdict.
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>
KanjiVG's strokes come with the app (assets/kanjivg/, CC BY-SA 3.0, its
notice in the licence list): 94 gzipped files, one per 256 code points,
2.7 MB in all, a file read the first time a character of it is asked for
(StrokeRepository, app-wide beside the maps). The strokes are SVG path
data, read with path_parsing (the Flutter team's, pure Dart, already in
the build through flutter_svg), so the model can flatten them into points
without dart:ui, as checking handwriting will.
A character's sheet traces its strokes in order over those to come, with
its stroke count, meanings, readings, level and the components KanjiVG
splits it into, each a tap away. It opens from a studied character's
answer (Stroke order) and from a character found in the dictionary.
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>
Where the instance holds the characters of a studyset's language, the
dictionary screen has a tab for them, Kanji & kana: search by character,
reading (kana or romaji) or meaning, and whole levels to add, under their
names: the kana (hiragana, katakana), the JLPT levels and the school
grades. A character becomes a character card, its meanings (a kana's
romaji) and readings, tagged with its level (JLPT-N5), school grade
(Grade 1 … Grade 6, Secondary school) and script (Hiragana, Katakana). A
character card's Look up searches the characters, and an entry looked up
again on a card swaps the tags the one before brought, as words do.
A dictionary's entries are now words or characters (DictionaryItem), as
its kind says.
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 dictionary source now says what it holds (`kind`: `words`, the default
for files from before, or `characters`), a string so that an app older
than a new kind leaves it out. Search, countLabelled and labelled take the
dictionary by its source and meaning language, as the unique index names
it, rather than by the language: with KANJIDIC2 beside JMdict, a search
for words would otherwise bring kanji, and JLPT N5 would hold both. The
search reads the language for its query variants from the source's row;
a dictionary the instance doesn't hold finds nothing. The rank index goes
by source too.
Migration: drops and recreates dictionary_entry_rank_idx on (source,
glossLanguage, rank), and adds dictionary_source.kind, text NOT NULL
DEFAULT 'words', so a JMdict loaded before is a dictionary of words. Both
tables are reference data, never synced; the old server keeps working
until the switch (its queries by language just lose the index).
In the app, a studyset's dictionary is one of words unless a kind is
asked for.
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>
The curator reads JMdict's examples edition (jmdict-simplified), which
ties Tatoeba's sentences to the meanings they show, and keeps them on
each sense of an entry (the form the word takes, the sentence, its
English, its Tatoeba id), crediting Tatoeba (CC BY 2.0 FR). A card made
from a word takes its first three as hints: the sentence with the word in
bold, the English below; Look up gives them to a card without hints of
its own. 98% of N5 and N4 words have one, 82% of N1. No new card format:
hints exist since card schema 5.
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 word tapped twice, or added while a level is being added, makes one
card: adds run one at a time, and the word counts as in the studyset
at once. The adder reads the studyset's cards once rather than for
every word.
- Adding that fails says so, and a level shows "Making the cards…" once
its words have come.
- Finding a studyset's dictionary tells finding, none and unreachable
apart: the dictionary screen says there is none or offers Retry, and
an instance unreachable at start is asked again once a sync goes
through (Look up and From the dictionary appear then).
- Look up's tags wait on the card by name and are made when it is saved:
leaving the card at once no longer saves it untagged, a word replaced
leaves no tag behind, and a new word replaces any level or word class
on the card, pinned ones too. Look up marks words already made into
cards of the studyset.
- The tag picker's Create keeps the case typed.
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 vocabulary card filled through Look up in the composer got the word but
none of its tags, while the dictionary screen tags every word with its
JLPT level and word class. Both now take the tags from the word itself
(DictionaryWord.tagNames). Looking another word up on the same card swaps
the tags the word before brought; tags the person gave the card stay.
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 tag is still its name, but no longer in lowercase: the name keeps the
case it was written in, and names that differ only in case are one tag
(ADR 0004, rule 2, amended). Two such tags from two devices fold into the
one with the smaller id, its case with it. Tags stored before stay
lowercase until renamed.
Words from the dictionary are tagged JLPT-N5 to JLPT-N1 and with their
word class (Noun, Verb, i-Adjective, na-Adjective, ...). Anki tags and
PDF chapter tags arrive as written.
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 studyset's dictionary follows from its language, as decided: the
instance's dictionary of its front's language, with meanings in its
back's (else English). Nothing to attach or detach; nothing of it shows
where there is none.
- Add material › From the dictionary: search a word (kanji, kana,
romaji, meaning) and add it as a flashcard, or add a whole level
(JLPT N5…N1, common words) at once, asked first above 500 words, its
progress shown. Words already in the studyset show as such and are
left out. Each card is a vocabulary card (headword, reading, senses
with their codes), tagged `jlpt-n5` and with its word class, and
marked as imported from the dictionary.
- Look up beside a vocabulary card's front fills the card with the word
chosen, keeping its hints, explanation and tags.
- A card keeps the dictionary entry it was made from (card schema 6:
`dictionary` {source, id}), to be found again and not added twice.
- The dictionary's credits show at its foot and in About, as its licence
asks.
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>
