8f2ad34a101b4465923aa88702e0648ac4e34d7a
4
Commits
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b2d50e9136 |
A dismissed card stays dismissed, even offline
The server already suppressed every span she had accepted or dismissed, on
both the LLM reconcile and the mechanics pass, with tests either side. What
had no memory was the half that never asks it: item 3b's rule pack renders
250 ms after a keystroke with no network, and its record of "she already
answered this" was a set cleared on every document switch and added to only
for cards dismissed while still provisional.
So dismissing a persisted rule-pack card recorded nothing client-side and the
next keystroke put it straight back until the server's reply removed it again;
and after a reload the client knew nothing at all — permanently so with the
server unreachable, which is the case the rule pack exists for.
GET /docs/{id}/settled hands over the normalized originals of the document's
actioned rows, scoped through documents because an original quotes her
sentence. The client seeds a SettledSpans from it on open and adds to it for
every card that leaves, keyed on the original alone the way the server keys
it. The load adds rather than assigns, so a dismissal made while it is in
flight survives it.
normalizeForDedup now exists in both languages, compared across a network
boundary, so the same nine cases are asserted on both sides and each test
names the other.
Also: the status-bar count — "🌸 5片花瓣待打磨 · 5 petals to polish" beside the
word count, from the packs, hidden at zero. An empty rail already says nothing
is waiting; a badge announcing it after every check is a verdict, which the
review's non-goals rule out.
Verified in Chrome at 1517x810 with the server killed: a new violation was
detected, underlined and counted with no network, while the dismissed span
stayed gone.
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978cb80642 |
Ask Petal answers in both languages, with room to read
The tutor prompt said "never mix languages in a single response" and mirrored the language of the question, so asking in English — which she does, because she is practising — returned the one explanation surface that gives nothing in her own language. It now answers in both, pair language first, halves separated by a blank line. Which half is the safety net and which is the lesson depends on who is writing: the pair is (English + X) and Petal is used from both ends, so the prompt asks for both and says it doesn't know which way round. The split is a rendering nicety, never a parse the reply depends on: a half-streamed reply is all one half, a model that ignores the instruction renders as one block, and nothing is ever dropped. For the height, the first attempt clamped the box to the room left below the anchored card so it could never overhang — measured, that gave 176px against a 442px answer, worse than the 220px it replaced. The card's own chrome spends ~290px of an 810px window, so "fits below the word" and "room to read" are not both available. The ceiling is now a flat 50vh and the overhang is made navigable instead, per item 4: the card reports its reach like the rail already does, the column grows, and the page can scroll to the actions below it. |
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25e415daa2 |
When she writes in Chinese, say Translate — not Clarity
She reaches for her own language mid-sentence when English won't come, and Petal already handled it: it found the span and rendered it into English. It just filed the result as a Clarity fix, so the pair model's flagship moment read as tidying up her Chinese. The type is now derived from the span rather than asked of the model. A type is structural, and a model that re-reasons every pass would drift between labels for a sentence nobody had touched — the instability the last session spent itself removing. The label the model volunteers is still ignored. Only the grammar checkpoint can be promoted. A pass with a forced type owns its family: voice reads paragraphs for tone and its rows carry no replacement, so a "translation" there would be a card offering nothing to accept. zh is a different script and counting Han runes is close to certain. The Latin pairs share an alphabet with English and get none of that, so they fall back to function words and need two before Petal claims anything — with every word that is also English left out, even the common ones. The heuristic is justified by how cheap being wrong is: it changes a coloured pill, and nothing else. The pill is the one bilingual type name in the rail. Every other type stays English because those are the terms she is learning; this card's whole subject is her own language. And it stops truncating its two lines — elsewhere the diff is a word and the explanation is what she reads, but here the two sentences are the card. Two things only the running page could report. The inline underline was invisible: the decoration carries a per-type class and the base rule is a transparent border, so a type with no colour rule gets no mark at all. And at 1517×810 with the document list open there is no rail — the margin is 258 where railEnabled wants 348 — so what she gets is the inline hover card. Item 7 is written the other way round. Migration 0015 rebuilds the suggestions table for the CHECK, which makes it the first one here that could quietly drop her rows; there is a test that carries every column, both timestamps and both indexes across it. Claude-Session: https://claude.ai/code/session_016y6gyuHkQXPiEuW8RGQyua |
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071ea7b835 |
Petal learns French, and the pack that shipped was misspelling itself
Phase 24, the fr half: langpack, Hunspell dictionary, Piper voice, and the lexicon coverage that turned out to have been measured already (63.1%, better than pt-PT's 62.1%). No migration; not deployed. The plan recorded that build_ptpt_dictionary.py "generalizes" to French. It did not. It handled single-character flags and plain PFX/SFX and stopped on everything else, and fr.aff uses four of the things it stopped on. FLAG long is the dangerous one: French flags are two characters, so the old reader's set(flagstr) yields a bag of unrelated letters and expands every entry through the wrong paradigm without ever erroring. Plus continuation flags (French really does affix an affixed form), NEEDAFFIX on 68,075 of 84,140 stems, and FULLSTRIP. Renamed build_hunspell_dictionary.py with a per-language profile, asserting that CIRCUMFIX and FORBIDDENWORD are still unused rather than assuming it — and it rebuilds pt-PT byte-identical to the shipped asset, which is the only thing that makes "generalized" a claim rather than a hope. Elision was decided by building both halves and measuring. Keeping l'arbre and its thirty-three siblings: 3,159,832 forms, 8.25 MB gzipped. Dropping them: 473,326 and 1.19 MB. They are not new words, but the tokenizer keeps internal apostrophes, so they genuinely would have been underlined — so they moved out of the dictionary into withElision, which splits at a known clitic and still requires the remainder to be a word (l'zzzz stays flagged). Real nspell: 369 ms and 74 MB, against pt-PT's 842 ms and 139 MB, on the larger language. Where the regional trap lives is the mirror image of Portuguese's: every fr_* Piper voice is fr_FR and Debian's fr_FR/fr_CA/fr_BE dictionaries are one shared word list, so nothing can be quietly wrong about the country and the whole decision sits in the copy. What French has instead is the 1990 reform, packaged three ways; comprehensive ships, because Petal never corrects her French and coût and cout are both correct. Then the interim review pass, at the user's suggestion and explicitly "for now": four models read each Latin pack independently, and only findings at least two of them reached on their own were applied — five per pack. It earned its keep on the pack that was already live. pt-PT was carrying pre-Acordo spellings (adjectivos, actualmente) in a file whose own header commits to post-Acordo, plus Brazilian decepção, because the Phase 21 greps checked for Brazilian vocabulary and never checked the pack against its own spelling policy. That grep now exists and was confirmed to fail on the old text before being kept. Where reviewers agreed a line was wrong but split on the fix, the wording is mine and the reasoning is in BUILD_PLAN rather than averaged away. Still owed, and both packs now say so precisely: a quorum of models agreeing is agreement, not authority. No native speaker has read either pack, and none of this has been seen in a browser. go build/vet/test clean, tsc, vite build, vitest 190/190. Claude-Session: https://claude.ai/code/session_016y6gyuHkQXPiEuW8RGQyua |