Add SRS-driven noun and adjective flashcards modeled on the existing verb
flashcard flow:
- SharedModels/Lexeme — catalog of non-verb vocab, frequency-ranked, with
gender for nouns and optional example sentences. Seeded from a bundled
vocab_lexemes.json built by Scripts/vocab/build_lexemes.py, which joins
frequency.csv + es-en.data from a pinned doozan/spanish_data commit
(CC-BY-SA: hermitdave/FrequencyWords + Wiktionary). 1,449 nouns and 600
adjectives, each with Wiktionary-sourced gender and (where available)
an example sentence with English translation.
- LexemeReviewCard + LexemeReviewStore — cloud-synced SM-2 SRS, keyed by
partOfSpeech + lexemeId + drillMode so future drill modes can coexist.
- LexemeSessionQueue + LexemePool — parallel to VocabSessionQueue; fresh
cards sort by frequency rank.
- LexemeStudyGroup — cloud-synced resumable session per
(partOfSpeech, drillMode).
- NounFlashcardPracticeView + AdjectiveFlashcardPracticeView — same flow
as VocabFlashcardPracticeView: English prompt → tap to reveal Spanish
→ Again/Hard/Good/Easy. Nouns reveal with their article (la taza, el
problema) so gender is taught alongside meaning, not as a separate
quiz. Example sentence shown when present.
CEFR-style level toggles:
- LexemeLevel enum (A1/A2/B1/B2/C1+) derived from frequencyRank with
standard Spanish-frequency-dictionary cutoffs (250/500/1000/2000).
- UserProgress.selectedLexemeLevels — cloud-synced multi-select, defaults
to A1+A2 on first launch.
- SettingsView gains a "Vocabulary Levels" section with five toggles; the
existing "Levels" section is renamed "Verb Levels" for clarity.
- Due SRS cards always surface regardless of toggles. Disabling a level
only stops new cards from that band entering the pool.
PracticeView gets "Nouns" and "Adjectives" rows under "Books".
DataLoader: new lexemeDataVersion gate that re-seeds the Lexeme table
from vocab_lexemes.json independent of book seeding. project.yml lists
the new JSON resource and the existing book_olly-vol2.json (which the
previous build was silently excluding because xcodegen rewrote the
project from project.yml).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The book reader's word lookup used DictionaryService, a verb-conjugation
index plus ~200 hand-typed words: ordinary nouns like "taza" returned
nothing, and homographs always lost (tapping "como" in "como siempre"
gave the verb "comer" because the verb index is checked first).
Add a glossary phase to the books pipeline (build_glossary.py): every
distinct Spanish word is translated once, in its sentence context, by
the same Claude-Code-subagent LLM step the pipeline already uses for
chapter translation. English front matter is excluded by an ES==EN
paragraph-ratio heuristic. The glossary is bundled into book_<slug>.json
and is now part of the pipeline for every book.
In the app, Book carries the decoded glossary and BookReaderView resolves
each tap automatically through cache -> glossary -> DictionaryService ->
on-device LLM, citing which source answered so a curated glossary hit
reads differently from a best-effort AI guess.
book_olly-vol2.json regenerated with a 3,658-word glossary.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Trey T