`pair_lang` had always been answering a second question nobody asked: it
says which two languages, and every surface built on it assumed English
was the one being learned. That is why hanzi is never tokenized, never
spell-checked, never glossed — correct for a Mandarin native practising
English, backwards for an English native practising Mandarin.
`users.direction` (migration 0016) separates the two questions; a
`zh-learner` pair code would have been cheaper and would have made two
directions of one pair look like two unrelated languages to every query.
Segmentation is what replaces `wordAt` where there are no spaces: a
shortest-path walk over log-probabilities, 232 ms and 14 MB for 188,522
words. The browser gets the word list because segmentation runs on hover;
the server keeps the whole dictionary. Their coverage gates come out
opposite on purpose — the client list is frequency-gated because the
segmentation is measurably identical without the tail, and the dictionary
is gated by nothing, because its only power is to explain and the word a
learner stops on is the rare one.
The 错别字 pack is 24 confusable pairs behind two mechanical gates. One
admits a pair only if the wrong form is not a dictionary word and the
right form is, which is why it refuses 自已 for 自己 — a real error whose
wrong form is a headword. The other asks the segmenter whether the two
characters already belong to two different words, without which 自己经常,
睡觉的时候 and 不知到底 would all be corrupted silently into text still
made of real characters.
Not deployed (this carries a migration), not seen in a browser, and no
account has ever been in the learner direction. The IME composition
guards were in scope and are not done — see BUILD_PLAN Phase 26.
The plan said "Hunspell pt-PT vendored like en-US". Measuring that first is
what saved it: nspell expands affixes eagerly on construction, and European
Portuguese's 1,340 rules over 44,257 stems want over a gigabyte of browser
heap — ~340 MB for the first 12,000 entries, and no return at all after three
minutes on the whole file. So the expansion runs once at build time instead:
1,039,058 forms, 2.66 MB gzipped, read by the same nspell in 842 ms.
The obvious npm package would also have shipped the wrong language. Both
dictionary-pt and dictionary-pt-br carry VERO, the Brazilian word list, so
vendoring by name puts pt-BR spellings behind a pt-PT label — the drift
SUGGESTIONS §3 warns about, arriving through the packaging where no reviewer
can see it. The source is Projecto Natura's, and the build script now asserts
the fault lines (receção in, recepção out) before writing anything.
Spellcheck consults both dictionaries and flags only what both reject, which
is the no-detector answer to a pair with no script boundary. The word card
does the same in the other direction: "data" is a word in both languages, so
Petal shows both readings rather than guessing which she meant.
Writing the tests caught the one real bug — extendedAlphabet was a snapshot
while correct/suggest read live, and her dictionary arrives after English, so
every lookup would have resolved "cora" while the underlines were already
right.
Not done, and not claimed: the pack has not been read by a pt-PT speaker, and
the Piper voice is deferred with the deploy.
Claude-Session: https://claude.ai/code/session_016y6gyuHkQXPiEuW8RGQyua
Inline Chinese gloss (offline) and a "say it more naturally" / tone-rewrite,
the two ESL features for the Mandarin-speaking writer.
Gloss: embedded English→Chinese dictionary (gloss.json.gz, 57k common words
built from ECDICT via scripts/build_gloss.py). lexicon gains Gloss()/Result.Gloss
and a lightweight GET /api/gloss/{word}; the right-click WordCard leads with the
中文; GlossTip shows it on a 350ms hover (reuses wordAt, so CJK is never glossed).
Offline + instant, works with the LLM down.
Rewrite: selecting text pops a SelectionBubble (✨更自然 + the tone vocabulary);
picking a style calls POST /api/docs/:id/rewrite (llm.RunRewrite, stateless,
owner-scoped) and shows a RewritePreview (original→rewrite, accept/cancel/retry).
Accept applies it in-editor.
Tests added in lexicon and suggestions. go build/vet/test, tsc, vite all clean;
live smoke vs a fake vLLM verified gloss + rewrite + 400/404/502 paths.
Claude-Session: https://claude.ai/code/session_016Yr6jELuRc7hyzYLccQKZd
prosolis