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Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
 prosolis
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8f2ad34a10 |
Four ways the two scripts weren't the same app, and a smaller cat
A review of the pair work found the seams — every one of them a place where
the Chinese half was written and the older Latin half was left standing.
The right-click menu still asked the Latin tokenizer whether there was a word
under the pointer, so right-clicking a hanzi opened the browser's own menu
instead of the card. Hover, long-press and Ctrl+D had all moved to the shared
resolver; this one hadn't, and it is the surface the segmenter's own header
names first.
isHan is a property escape precisely so the extension blocks are covered, and
then every call site handed it one UTF-16 code unit — half a surrogate pair
for anything above the BMP, which \p{Script=Han} rightly says is not Han. The
run split in two around the character and the words either side stopped being
looked up. The walk, the scan and wordAt now step by code point, the regex is
anchored, and the test that passed by accident (unanchored, so it searched a
two-unit string rather than testing one character) is joined by one that
would have failed.
The pair picker sent the pair alone. The server validates pair and direction
as one decision and refuses a learner direction for a pair it has no word
list for — so an English speaker learning Chinese could not move to French at
all: every button failed with the generic message. It now names both, keeps
her direction where the target pack has a learner side, and returns her to
learning_en where it does not. Routed through useSession rather than the
picker's own api call, so me.direction — which decides whether the word list
stays loaded — moves with it.
UpdateMe answered every error from Get with 401. A SQLite fault on a PATCH
would have tripped the client's session interceptor and thrown a writer into
the signed-out overlay while her session was fine. Only a missing row means
not signed in, which is the distinction SetPair already made below it.
emitCommittedRef was assigned during render and called later from
compositionend; a render React discards must not leave its closure behind for
a DOM event.
And the kitten is 10% smaller — one clamp, three terms, everything else
calc()s off it.
vitest 297/297, tsc, go build/vet/test clean.
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prosolis
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77f284f65c |
The zh pair's other direction, and a rule pack that mostly says no
`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. |
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prosolis
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9224c44fff |
The es pair, and a dictionary that was quietly Spain's
Phase 25. Spanish was never built — the groundwork was all [x] (DreamDict data, the prompt language, the L1 rule gating, TTS env-discovery), which is why the plan read as though it had shipped. shippedPairs was the honest answer: the server had been refusing es on purpose. The langpack is neutral Latin American, chosen with the user: tú, ustedes, no vosotros, and the pan-American half of every vocabulary split. A vitest greps for the peninsular twins the way fr is greped for québécismes — including coger, which is not merely regional but obscene through most of Latin America. The dictionary is the story. Debian's hunspell-es symlinks twenty country codes to one file, which reads as pan-Hispanic; RLA publishes twenty-four builds per release, one per country plus a generic es that is the union, and Debian ships peninsular es_ES. The 58,622-form gap is essentially voseo, so the first version of this commit underlined vení and tenés as misspellings and called it a considered gap. The MUST_ACCEPT list was written to catch exactly that and structurally could not: it asserted the pan-Hispanic vocabulary, and every RLA variant carries the full pan-Hispanic vocabulary — only the paradigms are localised. The REP table cited as the second witness is shared by all builds too. Two independent-looking proofs, neither able to distinguish anything, agreeing with each other. The profile now demands what discriminates, each verified against the build it targets: voseo rejects es_ES and Debian, vosotros rejects es_MX, and arepa/chévere/bacán reject es_AR, which has both paradigms and would otherwise pass. 717,640 forms, 1.74 MB gzipped, 762 ms / 97 MB in a real nspell. fr and pt-PT rebuild byte-identical from their own upstream debs, so the shared script still means what it meant. Shipping the union is fr's call arrived at from the other side: coût and cout are both correct French, tienes and tenés are both correct Spanish. The dictionary holds every variety because underlining is all it can do; the copy picks a register because speaking requires one. Reviewed by four models at the usual >=2-of-4 threshold, 5 of 27 findings applied — one catching the bedtime proverb as fr's Qui dort dîne calqued into Spanish, gloss and all, which is the rule the fr header states. One below-threshold finding (a missing ¡, seen by 1 of 4 because an absent opening mark has no closing ! to look wrong against) was applied and turned into an assertion instead: the suite now rejects any native line that closes ? or ! without opening one. piper-es on es_MX-ald-medium, not the es_ES-davefx-medium the plan named — six of Piper's nine Spanish voices are peninsular, so the obvious pick was the pt-PT trap through a different door. go build/vet/test, tsc, vite, vitest 251/251. Not deployed, not seen in a browser, not read by a native speaker, and no es account exists. |
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prosolis
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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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prosolis
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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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prosolis
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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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prosolis
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10e8aef86c |
Stop regenerating the world on every check
A card vanishing and coming back seconds later, with different words, was never about latency: every pass deleted its whole family and re-inserted it, so each round minted new row ids. The rail keys on suggestion.id, so a full remount was guaranteed — new id, new created_at (hence the re-fired chime), and a fresh explanation from a model that re-reasons every time it is asked. One unchanged mistake carried three different explanations in a single sitting. Passes now reconcile instead of replace. A re-proposed edit keeps its row: its id, its created_at, and the wording she has already read. And the grammar checkpoint stops asking about sentences nobody touched — the document is split into hashed sentences, checked_chunks records which ones a family has read, and only the difference is sent. When nothing changed it doesn't call the model at all, and doesn't spend its rate-limit slot on having done nothing. The tone is part of a sentence's identity: cached advice was written for the old register, so switching doc type re-reads every line. replaceMechanics reconciles too, which mattered more than expected — the rule pack fires 250 ms after a keystroke, so it was re-minting every local card's id several times a sentence. Only the grammar checkpoint is chunked. Voice is a property of the whole document, and the collocation coach is a button she pressed asking for a fresh read. No client change was needed; stable ids were the whole of it. Claude-Session: https://claude.ai/code/session_016y6gyuHkQXPiEuW8RGQyua |
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prosolis
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69bf3ffde1 |
Close the door the edge gate used to hold
A security review of the whole repo. The queries were already scoped, the
OIDC flow already did state and nonce and PKCE, the session tokens were
already stored as hashes. What it found was mostly the seam between the
code and the deployment — and one place where the deployment quietly
undid the code.
The one that matters: with any AUTHENTIK_* variable missing, Petal fell
back to resolving every request to the single `local` user. That is right
on a laptop and a catastrophe on a public host, and Phase 16 removed the
Traefik basic-auth gate that used to stand behind the mistake. A typo in
the client secret would have served her journals to the open internet and
said so only in a log line nobody reads. It now refuses to start, guarded
by default for any BASE_URL that isn't loopback.
Then the one that would have been fixed and wasn't: stored images now
serve under `default-src 'none'; sandbox`, so an SVG pasted into a
document can't run as a page on Petal's own origin. Traefik's
customresponseheaders *overwrites*, so the CSP declared in the compose
labels would have silently replaced that per-route policy in production.
The whole header block moved into the binary, where a route can tighten
its own and a test can prove it; only HSTS stays at the edge, where TLS
actually terminates.
The rest, smaller:
- PETAL_ALLOWED_SUBS empty means everyone authentik authenticates, and
authentik here fronts half a dozen applications. Still legal, now
said out loud every boot, and set in both env examples.
- LLM failures relayed err.Error() to the browser, which carries the
address of the inference box on the far side of the VPN. Logged
instead; the client only ever rendered "the helper is resting".
- Exports scheme-check their links. Escaping makes a URL safe to sit
in an attribute and says nothing about following it, and an export
is the one artifact here meant to leave. Writing the test found the
markdown image src, which I'd missed reading it.
- The draft rescue is namespaced per account and cleared on sign-out.
Everything else in localStorage is a preference; this is her unsaved
writing, sitting in a profile two people share.
- /auth/logout is POST-only. With SameSite=Lax a GET route lets any
page on the internet sign her out mid-draft.
- Image uploads get a per-account allowance and the TTS cache a size
cap. Both share the encrypted volume the database is on, and a full
disk is SQLite failing to write, not a feature degrading.
- The session cookie takes the __Host- prefix over https, so nothing
else under parodia.dev can plant one. Old cookies still resolve;
nobody is signed out to get there.
- npm audit: linkify-it and postcss.
Verified: go build, go vet, the full Go suite, tsc, 195 frontend tests,
npm audit clean. The startup guard and both CSPs checked against a
running server rather than only asserted.
Claude-Session: https://claude.ai/code/session_016y6gyuHkQXPiEuW8RGQyua
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prosolis
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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 |
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prosolis
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1f4ca4775a |
Let her choose her own pair
Raised by the user, not by the plan: there was no way to change language in the mobile UI. There was no way anywhere. `users.pair_lang` has been readable since Phase 19 and writable by nobody — /api/me was GET-only and Upsert deliberately skips the column — which is also why "no pt-PT account exists yet" has stood through two phases. Nothing could create one. PATCH /api/me answers with the whole user rather than 204, so the client re-reads the pair from the server instead of trusting its own request. One write reaches everything: langpack, Hunspell dictionary, Piper voice, lexicon provider and prompt language all read the column at use time. The server refuses a pair it has no copy for, and auth.shippedPairs is deliberately not internal/llm's list. That one names pairs the prompts can talk about (fr and es, since Phase 19); this one names pairs Petal can render itself in, which needs a langpack. Storing fr today would strand her on Chinese with no way back except a lucky guess at a button she cannot read. The picker sits in the sidebar footer because the sidebar is the mobile drawer — always one tap away. The status bar exists only while a document is open, which is the wrong moment to find the app speaking a language you can't read. Each language names itself, 中文 and Português: the one place bilingual copy would get in the way. Claude-Session: https://claude.ai/code/session_016y6gyuHkQXPiEuW8RGQyua |
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prosolis
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1bbc8fc8d3 |
Finish Phase 22: the half of Petal that works with the tunnel down
Grammar lite, the false-friend list, the daily invitation and the offline miscollocations — the four remaining §5–§6 items, all client-side and all alive on a box that cannot reach the model. The offline collocations forced a schema change. `type` had been doubling as the answer to "which engine found this" — `mechanics` meant offline — and that stops being true the moment an offline rule proposes a collocation. Migration 0013 adds `source` (llm | local) and every pass now scopes its DELETE by engine; without it the coach silently wiped every offline chunk on the page. Existing rows backfill by type, so a pre-0013 collocation row is claimed as the coach's, which it was: the offline list did not exist yet. The rule pack is hand-curated rather than mined, and the entries left out are the point — `married with` is wrong until "married with children", `arrive to` wants at or in depending on the noun. A pack running on every keystroke must not correct correct writing. Claude-Session: https://claude.ai/code/session_016y6gyuHkQXPiEuW8RGQyua |
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prosolis
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e9b8595456 |
Let the garden keep what she was given, not only what she sought
Two halves of the same idea, both read out of work Petal already records. Planting: an accepted collocation is a learnable chunk, so it becomes a phrase card. The scheduler didn't need to know — a three-word chunk climbs the ladder exactly like a looked-up word. What needed care was deciding what *isn't* a chunk (single words are word choice; a six-word-plus "collocation" is a rewritten sentence, and sentences make miserable flashcards), and that the example must be the *corrected* sentence — the stored draft still holds the phrasing she just left behind. Re-accepting the same chunk leaves the existing card alone rather than resetting a schedule it has been climbing. The whole thing is best-effort: accepting an edit must never fail because a flashcard couldn't be made. The growth journal: kept this month beside kept the month before, the phrasing that stuck, the patterns that faded. The queries were the easy part; the honesty is the feature. "Stuck" needs the phrase in a *second* document, because one document is just the edit where she left it. "Faded" says nothing at all unless she has been writing lately — otherwise a month away from Petal comes back to her as progress, which is the one way this could lie. And a suggestion had to start recording when she *decided* it, not when the model proposed it, so 0012 adds resolved_at and backfills the old rows to their created_at. It lives as a second tab in the garden, and it feeds the kitten: after an accept she now sometimes hears something true of her alone, once per line, half the time, never waited for. Claude-Session: https://claude.ai/code/session_016y6gyuHkQXPiEuW8RGQyua |
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prosolis
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24c3533e18 |
Give read-aloud a Portuguese voice, and a slower one
Phase 21's infra half. Two things the pt-PT pair needs from TTS, and one thing every learner has wanted since Phase 11. **A language is no longer a code change.** The handler knew exactly two languages, named in the Config struct: English on TTS_ENDPOINT and Chinese on TTS_ENDPOINT_ZH. Petal now discovers its Piper instances from the environment — English keeps the unsuffixed pair it has always had, and every other language is a TTS_ENDPOINT_<LANG>/TTS_VOICE_<LANG> pair — so fr and es cost a compose service and two lines of .env. <LANG> is the base tag, because an environment variable name cannot hold pt-PT's hyphen and only one Portuguese model is loaded either way. A language configured by halves is dropped rather than routed: half a configuration should reach the client as "no voice here, use Web Speech", not as an instance that errors on every tap. The startup line now names the voices it actually resolved rather than the English endpoint it was handed — the same lesson the dictionary line learned last week. **pt_PT-tugão-medium is the only European voice Piper ships.** The other five pt models in the catalogue are Brazilian, so the default anyone reaches for is the wrong country — the same trap as `dictionary-pt` packaging VERO, arriving through the catalogue rather than through the model. Named explicitly in compose, with the query that checks it in the deploy README. **The slow replay** (SUGGESTIONS §5e) is `slow: true` on /api/tts, raising Piper's length_scale to ~4/3. Piper stretches durations rather than resampling, so it stays a voice instead of a groan. The pace is part of the cache key — without it the slow replay of a word already heard at normal speed would be served back at normal speed, which is the one request where the difference is the whole point. 🐢 sits beside 🔊 on the word card, the selection bubble and the garden flashcard; the Web Speech fallback slows too, so the button means the same thing when Piper is down. **And the other reading gets her own voice.** The `alsoIn` block — the Portuguese sense of a word that is also English — now speaks in the pair's locale, which the pack names (`locale`) rather than anything inferring it from the letters. "comum" is spelled identically in both halves; a detector would have to guess, and this is the same reason the gloss shows both directions instead of picking one. Tests: config discovery (both existing deployment shapes, half-configured languages dropped, the pre-map voice defaults preserved), the slow scale and its separate cache entry, pt routing on the base tag with pt-BR landing on the European instance, and speech.ts's request body. The i18n shape suite now asserts every pack names a speakable locale in its own language — and that pt-PT's is not pt-BR. Verified: go build/vet/test, tsc, vitest 125/125, vite build. Live smoke against two fake Piper servers: en/pt × normal/slow all reached the right instance at the right length_scale with four distinct cache entries, and an unconfigured language still 404s. |
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prosolis
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ccb43e5a4d |
Phase 21: Petal learns to be an English+Portuguese pair
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 |
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prosolis
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74bf600593 |
Make the dictionary startup line report rows, not capabilities
It logged dictionary.Langs(), which is a compile-time constant of the languages DreamDict *supports*. The database deployed until today supported Spanish and contained none of it, so the line printed a confident "[en fr pt-PT es zh]" over a file where every Spanish lookup came back empty — the exact failure the line exists to catch, reported as success. Contents() counts rows per language instead. For a file somebody has to copy onto the box by hand, "what is in it" is the only question worth asking, and the answer is now en=136615 es=102971 fr=56096 pt-PT=136300 zh=120883. Claude-Session: https://claude.ai/code/session_016y6gyuHkQXPiEuW8RGQyua |
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prosolis
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97e9c269ec |
Phase 20: the dictionary stops being English and Chinese only
Word lookups now come from DreamDict's dict.db for every pair but Chinese — opened read-only beside petal.db, no service, nothing over the VPN, because a hover gloss has to answer in milliseconds. `Provider` is the two questions the popover and the tooltip already asked, so the embedded *Lexicon satisfies it with no changes at all; Set.For(lang) is the single place the choice between them is made. The prerequisite in the dreamdict repo turned out to be two things, not one: the module path was unfetchable *and* the query layer sat in internal/, which no other module may import whatever the module is called. Both fixed upstream. The plan's central assumption did not survive the data. It mapped Gloss ← Translate(word, "en", L1) one-to-one; against the real 452 MB database that table answers for 17% of the 2,000 commonest English words into pt-PT. Wiktionary's translation sections are thin in that direction — "ephemeral", "think" and "quickly" have no en→pt-PT row at all. Shared WordNet synsets answer for 61%, so DreamDict gained Equivalents() and Petal glosses through it. Ordering those was wrong in an instructive way too: sorting by frequency glosses "think" as lembrar, "remember", because lembrar is the commoner Portuguese word even though pensar shares six of think's synsets to lembrar's one. Counting sense agreement first asks the right question. The same measurement is why zh stays on ECDICT: DreamDict reaches a Chinese gloss for 53% of those words, ECDICT for nearly all of them. The plan said converge only if quality holds. It didn't, so nothing converged. Two decisions about failure worth keeping. A missing dict.db is not an error — a laptop checkout has never had one — but a present-and-never-imported one is, because that is a half-finished deploy. And a pt-PT writer with no dictionary falls back to the embedded datasets with the gloss suppressed, keeping definitions, synonyms and phonetics rather than blanking the popover: an empty field reads as "not found", the wrong language reads as broken. The new fields surface as an etymology line and a three-band chip. Three, not five: the difficulty score separates "everyday" from "you'll have to explain this" but cannot rank obfuscate against serendipity, and a finer scale would be a confident-looking lie. An unscored word gets no chip. Writing the tests found two bugs first — trimEtymology sliced by byte, which would have emitted invalid UTF-8 for exactly the Greek and Latin etymologies the feature exists for, and its ellipsis path overran its own cap. go build/vet/test, tsc, vite, vitest 96/96 clean; live smoke against the real dict.db with one instance flipped from zh to pt-PT mid-run. Not deployed: go.mod still replaces github.com/prosolis/dreamdict with ../dreamdict, so the Docker build needs the two upstream commits pushed and the replace dropped. The deployed dict.db also predates DreamDict's Spanish data. Claude-Session: https://claude.ai/code/session_016y6gyuHkQXPiEuW8RGQyua |
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prosolis
|
336cae93e0 |
Phase 19: the copy stops being hardcoded Mandarin
Every `中文 · English` string moves out of ~29 components into web/src/i18n: one Pack type, a verbatim zh pack, and two ways to read it — usePack() for components, pack() for the modules that build a line when something happens rather than when something renders. Anything with a value in it is a function on the pack rather than a template at the call site, English pluralisation included: word order isn't universal, and a pack author has to be able to move the number. The roster constants (tones, rewrite styles, export formats, companions) keep only value + emoji, so a label can't drift from its key. On the server, internal/llm/lang.go replaces "Simplified Chinese" in the three prompts that actually name her language. pt-PT is spelled "European Portuguese (pt-PT, never Brazilian Portuguese)" in the prompt itself, and each Lang carries her word for "why" so the tutor prompt still recognises the question when she asks it her way. pair_lang reaches the model through the row-scoped query each handler already ran — the one that proves she owns the document — rather than a second lookup that could disagree with it. Also records Phase 18's deploy: migration 0011 rehearsed against a copy of the live VPS database, then applied for real. |
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prosolis
|
30d5e691c9 |
Phase 18: settings that belong to the writer, not the browser
The mute toggle, the falling-petals toggle and the chosen companion lived in localStorage, which is a property of the machine. Now that two people can sign in to one Petal, sharing a laptop would have meant sharing a mascot and one person's silence muting the other. Each key is namespaced by user id. The awkward part is timing: sounds.ts and petals.ts read their value the moment they are imported, long before /api/me can have answered. Rather than block startup on the network for a mute flag, a read before the answer arrives sees the old un-namespaced key -- on a single-writer browser, exactly the right value -- and setPrefsScope then adopts it into that account's namespace and tells every reader to look again. Adoption moves rather than copies, so the first account inherits what was set before accounts existed and the second starts from Petal's defaults. The personal spelling dictionary moves further than that: onto the server. It is built from her own writing, so it should not be readable by whoever sits down at the same browser next -- but merely namespacing it would have split the list she already has between her laptop and her tablet, which is worse than where we started. A table keyed (user_id, lang, word) follows her instead. The lang is the dictionary's, not hers: an English exception must not silence a pt-PT flag once the second pair ships. Adding a word takes effect in the editor immediately and persists in the background, so the underline goes away the instant she asks. A browser still holding the old list hands it over on first load, and only lets go once the server has taken it. Claude-Session: https://claude.ai/code/session_016y6gyuHkQXPiEuW8RGQyua |
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prosolis
|
151df4565b |
Phase 17: a script to move the local user's writing onto a real account
The destination is an OIDC subject id, which the app cannot know — it belongs to the identity provider — so this runs deliberately, with Petal stopped and a backup taken, rather than as a startup migration. documents, tags, vocab_words and images carry user_id directly; versions, suggestions and tag assignments hang off their parents and follow, which is why it has to be one transaction with foreign keys off. Sessions for the old identity are deleted rather than moved: a session is proof someone signed in, and nobody ever signed in as 'local'. Dry run by default, VACUUM INTO backup first, and it verifies every row it expected to move actually moved — and that the source is left owning nothing — before committing. The 'is the app stopped?' guard took two attempts. BEGIN EXCLUSIVE, the obvious check, sails past a running-but-idle Petal because in WAL mode it only conflicts with another writer, which is precisely the case worth catching. PRAGMA locking_mode = EXCLUSIVE conflicts with any connection at all, since it locks the shared-memory index every WAL reader maps. Sequencing this also turned up a crash waiting to happen: the image backfill claims unowned files for 'local', which no longer exists after a migration, and the resulting foreign-key error is fatal inside images.New. Petal would have crash-looped the first time it started on a migrated database. It now skips a missing owner, which costs nothing — the migration moves the image rows itself. Claude-Session: https://claude.ai/code/session_016y6gyuHkQXPiEuW8RGQyua |
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prosolis
|
6d71276513 |
Auth: pass the OIDC issuer through untouched, trailing slash and all
Deploying against the real Authentik turned this up immediately: its issuer ends in a slash, OIDC requires the discovered issuer to match the configured one byte-for-byte, and trimming it made discovery fail every time. The stub in the tests happened to advertise a slashless issuer, so the whole suite passed while the only provider Petal actually talks to could not be reached. The stub now takes its issuer as a knob, and a regression test runs the flow against one that ends in a slash. Claude-Session: https://claude.ai/code/session_016y6gyuHkQXPiEuW8RGQyua |
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prosolis
|
1cf207d73f |
Phase 16: Petal authenticates for itself
Petal is now an OIDC client in its own right rather than trusting a header from the proxy. The Phase-0 Resolver seam was the only integration point: main.go picks the session store when Authentik is configured and the static local user otherwise, and no handler or query moved for either. internal/auth gains three pieces. session.go issues an opaque cookie token and stores only its SHA-256, so a database copy yields nothing usable; the 30-day expiry slides on every request, throttled to one write an hour, and logout deletes the row rather than just the cookie. oidc.go runs the authorization-code flow with state, nonce and PKCE, and discovers the provider lazily and on retry — an Authentik outage should block new logins without stopping Petal booting or invalidating live sessions. users.go provisions accounts from the token's claims and gates them on an allowlist that matches emails as well as subject ids, since a subject is an opaque uuid that doesn't exist until someone has already logged in once. Migration 0010 lands sessions, images and users.pair_lang together. The images table closes the capability-URL hole the Phase-0 audit flagged: a hash was previously enough to fetch anyone's picture. Rows are keyed (name, user_id) so one file can have several owners and deduplication survives; a stranger gets 404 rather than 403, the cache header drops to private, and files already on disk are claimed at startup or every image already pasted into a document would 404. On the frontend a single 401 interceptor feeds a warm bilingual sign-in overlay, drawn over a still-visible editor because nothing has been taken away. Behind it is the part that matters: a save that comes back 401 stashes its body to localStorage before anything else and stops the auto-save loop, and reopening that document after signing in merges the draft back and saves it. An expired session must not cost writing. Writing the round-trip test against a stub identity provider turned up a real bug: the one-shot state/nonce/PKCE cookies were cleared in a defer, which runs after the redirect has written the response header, so the clearing Set-Cookie was silently dropped and they lingered for their full ten minutes. Also swaps the emoji favicon for a drawn sakura, which renders as Petal's own rose palette everywhere instead of whatever each platform's font decides, and doubles as the app tile in Authentik. Migration 0010 verified against a VACUUM INTO copy of the live millenia database: counts intact, FTS still matching, the one existing image claimed. Claude-Session: https://claude.ai/code/session_016y6gyuHkQXPiEuW8RGQyua |
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prosolis
|
2363ef2d37 |
Make Piper's synthesis path configurable (TTS_PATH)
piper-tts 1.6.0 moved synthesis from POST / to POST /synthesize, with an identical request body; the VPS sidecars run 1.6.0 and returned 405 to every read-aloud request, while millenia's older server still expects /. Rather than pinning both deployments to one Piper release, the path is configuration -- default "/" keeps millenia working untouched, and the compose stack sets /synthesize. The container healthcheck moves with it, since it was probing the old route too. |
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prosolis
|
8410b6315b |
Phase 15: containerize Petal for the parodia.dev VPS
Deploy plumbing so Petal can run on the public VPS behind the Traefik already on that box, with vLLM reached over headscale. - Dockerfile: node build -> go build -> alpine runtime. CGO stays off (modernc SQLite is pure Go), so the runtime layer exists only for ffmpeg (read-aloud transcodes Piper's WAV) and tzdata (the companion's bedtime nag and night mode read the local clock). Runs as uid 10001 with /data as the single writable mount. - docker-compose.yml: Traefik labels following this host's convention (external `traefik` network, `web-secure` entrypoint, `default` cert resolver). Petal publishes no host port. ./data is a bind mount, not a named volume, so the nightly backup and a restore are reachable from the host. - Piper runs as two sibling containers rather than host systemd units. The plan assumed Piper was already installed on the VPS; it is not, the host has no lingering user session to keep user units alive, and containers keep the TTS ports on an internal network unreachable from anywhere but Petal. One image, voice chosen per service, model cached in a shared volume -- so the pt-PT voice is a new service, not a new image. - db.Backup + a `-backup` flag: VACUUM INTO, not a file copy. Petal runs in WAL mode, so the newest committed pages may live in petal.db-wal; copying the three files separately can capture a torn mid-checkpoint state. VACUUM INTO reads one coherent snapshot without taking a write lock, and emits a single file with no -wal/-shm companions. Refuses an existing destination so a failed run can't destroy the last good backup. - deploy/backup-petal.sh: nightly snapshot, compress, push to millenia over headscale with a post-transfer size check, prune both sides. - deploy/petal.env.example: LLM_TIMEOUT raised 30s -> 90s for the WAN+VPN round trip, since the voice and collocation passes send a whole document and the timeout is a hard deadline on Complete. |
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prosolis
|
6901cdbbe4 |
Multi-user groundwork: request-scoped user identity
Petal ran as a single hardcoded user, with db.LocalUserID named directly
at ~35 query sites. That made the caller's identity a compile-time
constant scattered across every package — nothing a real login could
replace without touching all of them.
New internal/auth moves it into the request context:
- Middleware(Resolver) resolves the caller once per API request
- handlers read auth.UserID(r.Context()) instead of naming a user
- Resolver is the seam an Authentik session check drops into
- StaticResolver(db.LocalUserID) keeps Petal single-user today
Behavior is unchanged. UserID returns "" rather than panicking when the
middleware is absent, so a mis-wired route fails closed: every query is
WHERE user_id = ?, which then matches nothing.
main.go splits /api into a public group (/health, /version) and an
authenticated group for everything else — a monitoring probe must not
need a session.
Two pre-existing access-control gaps fixed while threading, both
harmless with one user and not with two:
- setStatus (accept/dismiss) updated a suggestion by bare id with no
ownership check at all
- listForDoc/fetchPending read a document's suggestions by doc_id
alone; a suggestion quotes the sentence it corrects, so that leaked
the source prose
Both now scope through documents.user_id.
Tests: internal/auth covers the context round-trip, the absent-context
case, and both 401 paths. Two-user isolation suites in docs and
suggestions mount the same routers twice behind two resolvers over one
database and assert a stranger gets 404 on every id-taking path, sees
nothing in list/search, and leaves the owner's data untouched.
Those suites earned their keep immediately: docs.fetch gained a userID
parameter but kept binding db.LocalUserID in the query. Unused
parameters are legal Go, so it compiled clean, vet was silent, and every
existing test passed while the lookup stayed unscoped.
Still global, out of scope and flagged in BUILD_PLAN.md: the image store
has no per-user association, and frontend localStorage keys are
per-browser rather than per-account.
|
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prosolis
|
61b3c6cd62 |
Disable thinking on the vLLM backend
Qwen3-family models reason by default and prepend a plain-text preamble
ahead of the answer — not a <think> block, so it cannot be stripped
after the fact. Every Petal pass parses a JSON object out of the
completion, so an unsuppressed preamble fails the parse outright.
Send chat_template_kwargs {"enable_thinking": false} on every request,
matching the unconditional think:false the Ollama backend already sends.
|
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prosolis
|
78ed1dd281 |
Writing passport: evidence of process instead of an AI score
She's submitting work that gets run through an AI detector and wants to pre-check she won't be wrongly flagged. Petal should not answer that with a detector of its own: they misfire badly on non-native English (Stanford 2023 found >50% of TOEFL essays flagged as AI vs. near-zero for native writers), so a percentage aimed at an ESL writer is worse than nothing — it either scares her off her own voice or gives false comfort. So the artifact is provenance, not a verdict. Petal already snapshots every ~3 minutes; this turns that history into a standalone printable report: session breakdown, word-count growth, span, active time. No score is emitted anywhere. Two schema additions back it. preserve_history opts a document out of the 40-snapshot prune cap — right for recovery, wrong for provenance, where you want the whole span including the oldest rows. content_hash/prev_hash chain each snapshot to the one before it, so a history edited or thinned after the fact fails verification. Pruning legitimately severs links, so a link break reports as "gaps" unless preserve_history is on; only a hash that fails against its own contents is unconditionally "broken". The chart's x axis is snapshot order, not wall-clock, and that is the load -bearing decision. On a linear time axis an essay written in three sittings across three days renders as three vertical cliffs separated by empty space — visually identical to text pasted in three chunks, i.e. the report would have argued the opposite of the truth. Breaks are compressed into explicitly labelled gutters instead. TestChartGivesWidthToWriting pins it. The report volunteers its largest single word-count jump and states its own limits: it cannot show who was at the keyboard, or whether typed text was composed or copied in. Overclaiming would be self-defeating — a reader who catches it overstating discounts all of it. HTML rather than server-rendered PDF, as with the other exports: a CJK-safe PDF needs an embedded Unicode font or a headless browser. Print styles are there so the browser's Save as PDF is the handoff path. Claude-Session: https://claude.ai/code/session_016Yr6jELuRc7hyzYLccQKZd |
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prosolis
|
9d2501a625 |
Suppress fickle re-edits of sentences the user already settled
Suppression keyed on the exact original->replacement pair, which the
model routinely sidestepped: it reverses an accepted edit (reverse
pair), re-polishes its own accepted output (new original == accepted
replacement), and the editor's smart-quote churn ("..." -> '...')
defeated even a byte-exact match. Result: a few sentences got nudged
back and forth pass after pass.
Replace the exact-pair actionedKeys with a suppressor that compares
under a normalization folding all quote variants and collapsing
whitespace, and drops a fresh suggestion when it re-touches an
already-settled span: same edit re-proposed, an original the user
already accepted/dismissed, the model re-touching its own accepted
output, or a multi-word sub-clause contained in an accepted span.
Tradeoff: once a sentence is accepted/dismissed it won't be re-flagged
until its text changes — stability over marginal improvement, the right
call for the calm ESL persona.
Claude-Session: https://claude.ai/code/session_016Yr6jELuRc7hyzYLccQKZd
|
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prosolis
|
08b801e752 |
Drop no-op suggestions where replacement equals original
The checkpoint model sometimes "flags" a correct sentence and echoes it verbatim as the replacement, producing a card whose before/after are identical and whose explanation says it's already fine — a suggestion that suggests nothing. ParseCheckpoint already dropped empty-original items; also drop these no-ops. Awareness-only families (voice) carry an empty replacement, so the guard only fires on the edit families. Claude-Session: https://claude.ai/code/session_016Yr6jELuRc7hyzYLccQKZd |
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prosolis
|
96f68a91ee |
Add deterministic mechanics suggestion family (rule-based, no LLM)
Reuse the companion's prose.ts rules engine as the single source of
deterministic detection instead of duplicating it. Applyable rules now
also emit exact-span fixes (original -> replacement) that surface as
suggestion cards; awareness-only rules (run-ons, splices, ...) stay
companion bubbles. The companion hides fix-bearing hints so a span is
never both a bubble and a card.
Spans are widened to a distinctive phrase ("a old" -> "an old",
"She have" -> "She has") so they re-anchor by string in the editor; a
lone lowercase "i" stays awareness-only since a single char can't anchor.
Backend: detection lives client-side, so the new persist-only
POST /docs/{id}/mechanics endpoint receives findings and stores them as
the 'mechanics' family with their exact offsets. It honours
actioned-suppression, leaves the LLM families untouched, and a checkpoint
no longer wipes it. fetchPending dedupes spans with mechanics winning any
collision against an LLM card (its span is exact). Migration 0008 adds the
'mechanics' suggestion type.
Client renders the mechanics fixes immediately (no LLM wait) and the cards
use a calm sage "Tidy-up" accent.
Verified end-to-end in a real browser on millenia: detect -> persist ->
render -> accept applies the fix.
Claude-Session: https://claude.ai/code/session_016Yr6jELuRc7hyzYLccQKZd
|
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prosolis
|
8c6bc1604b |
Code-review follow-ups: httputil, validation caps, a11y
Backend: - Extract shared internal/httputil (WriteJSON/ErrorJSON/BadRequest/ ServerError); drop the triple-duplicated helpers in docs, suggestions, vocab. ServerError now logs the real error and returns a generic 500 so raw DB/internal errors never reach the client. - vocab capture: validate doc_id ownership (blank -> none, unknown -> 400 instead of a leaked FK 500); rune-safe clamp word/gloss/definition/ phonetic/example. - vocab review(): wrap the read-modify-write in a transaction (TOCTOU). - /api request-size cap via MaxBytesReader middleware (2 MiB), exempting /api/images (own 10 MiB limit). Frontend: - StatusBar: drive the checking/voicing/collocating indicators from one array; llmDown uses !anyBusy. - Slide-overs: new useFocusTrap hook (focus-in, Tab trap, focus-restore) on GardenPanel + HistoryPanel, both role=dialog/aria-modal/aria-label. - speech.ts: export stopSpeech(); GardenPanel cancels audio on unmount. Tests: add doc_id-validation and field-clamp coverage; full suite green. Claude-Session: https://claude.ai/code/session_016Yr6jELuRc7hyzYLccQKZd |
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prosolis
|
4161830da6 |
Code-review fixes for collocation coach + vocab garden
Correctness: - useCheckpoint: clear the busy flag unconditionally so overlapping explicit passes don't strand each other's spinner; explicit actions now also supersede a queued auto-check and clear the stranded "checking" dot. Deduped runVoice/runCollocation into runExplicitPass. - EditorCore: token-guard the auto-capture so a late capture can't resurrect a removed word; move toggleSaveWord side effects out of the setWordInfo updater (StrictMode double-fire); fix sentenceAround offset desync via shared exampleAt (textBetween + parentOffset, single resolve); optimistic saved state so the heart doesn't flash unsaved. - vocab capture: normalize word to lower+trim (matches lexicon) so "Apple"/"apple" don't make duplicate cards; check rows.Err() in queryList. - GardenPanel: Promise.allSettled so a /due failure doesn't blank the whole garden; scrim click during review ends the review (mirrors Esc); gate footer on !error; O(1) due lookup via a Set. Features requested in review: - Definition-only review card: add vocab_words.definition (migration 0007) as an English fallback meaning, threaded through capture and used by review/garden when there's no Chinese gloss. - Scheduler caps: maxEase 3.0 + maxInterval 365d so "easy" growth can't push a word out of rotation for years. Tests: TestCaptureCaseInsensitive, TestCaptureStoresDefinitionFallback, TestCapsBoundGrowth. go build/vet/test, tsc, vitest 51/51, vite build clean. Claude-Session: https://claude.ai/code/session_016Yr6jELuRc7hyzYLccQKZd |
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prosolis
|
8aa437ec82 |
Phase 12 + 13: collocation coach + vocabulary garden
Phase 12 — collocation coach: a third suggestion family for gentle
"natives usually say…" hints on non-native word pairings, reusing the
existing runPass/pendingScope/rail machinery.
- llm/collocation.go (RunCollocation, 25s floor, reuses ParseCheckpoint)
+ collocationSystemPrompt/CollocationMessages (warm, Mandarin gloss,
defers grammar/spelling to the grammar family)
- migration 0005 rebuilds the suggestions table to extend the type CHECK
(SQLite can't ALTER a CHECK)
- collocationScope + CollocationLimit + POST /{id}/collocation
- fix: grammarScope was `type != 'voice'` and would wipe the new
collocation flags; now `type NOT IN ('voice','collocation')`
- frontend: --color-blossom, "Make it sound natural 🌸" pill,
collocating/runCollocation in useCheckpoint, StatusBar dot
Phase 13 — vocabulary garden: capture looked-up words and surface them
for gentle spaced repetition.
- new internal/vocab package: migration 0006 (vocab_words, SM-2-lite
columns, doc_id ON DELETE SET NULL, UNIQUE(user_id,word)),
scheduler.go (Leitner ladder 1/3/7/16/35 then geometric; gentle
"again", no streak-shaming), handlers (capture-upsert/list/due/
review/delete, owner-scoped, SQLite-side datetime math)
- auto-capture on word lookup (dictionary-known words only, captures
the surrounding sentence + doc_id) + 🤍/💚 toggle on WordCard
- GardenPanel: blossom grid (bloom by reps), flashcard review (sentence
blanked, flip, again/good/easy, recognition↔production), sleepy-kitten
footer; opened from a global 🌷 header button
Tests: TestCollocationPassCoexists, vocab scheduler + handlers, db CHECK
extended. go build/vet/test + tsc + vite + vitest (51/51) clean;
migration verified against a copy of the live DB; live backend smoke
walked the full vocab lifecycle + the warm-502 collocation path.
Claude-Session: https://claude.ai/code/session_016Yr6jELuRc7hyzYLccQKZd
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prosolis
|
8bd2509bc2 |
Checkpoint: raise output cap to 4096 + salvage truncated JSON
The grammar checkpoint capped num_predict at 1024, but qwen3.5:9b ignores
the prompt's "up to 5 issues" and emits ~17-20 suggestions (~2000 tokens)
on a 300+ word doc. The output hit the cap mid-array (done_reason=length),
the JSON never closed, and ParseCheckpoint found no parseable object -> a
502 in ~20s on every long doc (1024 tok @ ~50 tok/s, not a network
timeout). The repeated failures made the writing-assist helper look
permanently asleep.
Fix:
- Raise the cap to checkpointMaxTokens=4096. It is a ceiling, not a
target -- the model stops at its JSON close, so shorter docs are
unaffected; only genuinely long outputs use the headroom.
- Make ParseCheckpoint salvage the completed {...} suggestion objects
from a truncated array (refactor extractJSONObject onto a shared
firstBalancedObject scanner), so an over-long doc degrades to partial
feedback instead of a hard 502.
Verified live on millenia: 'The Missing Key' (382 words) now returns 200
with 17 suggestions in ~38s, previously 502 every time.
Claude-Session: https://claude.ai/code/session_016Yr6jELuRc7hyzYLccQKZd
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prosolis
|
46db0a3e16 |
Checkpoint: auto-retry after a failed pass; release rate-limit slot on failure
A paste fires exactly one grammar checkpoint, and a failed one never retried until the next keystroke — stranding the writer on "Petal's helper is resting" after a paste. Long docs make it worse: their 15-25s checks have a wide window to catch a transient 502 from the shared Ollama (co-tenant apps load other models and evict the 9B). A failed pass also burned the per-document rate-limit slot, so a retry within 30s hit the throttle path and got an empty set back. - llm.RateLimiter.Release rolls back a slot when its pass fails; Allow now returns the recorded timestamp so Release only frees its own slot. - suggestions.runPass releases the slot on LLM failure before returning 502. - useCheckpoint auto-retries a failed checkpoint with backoff (3/12/35s), keeping the breathing dot up and only flagging "resting" once retries exhaust. Claude-Session: https://claude.ai/code/session_016Yr6jELuRc7hyzYLccQKZd |
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prosolis
|
82e2bcc777 |
Suggestions: right-margin comment rail + Mandarin explanations
Surface every outstanding suggestion as a card in the right-hand
whitespace, vertically aligned to the text it flags — so the writer sees
the whole queue at once instead of hovering each highlight. Cards stack
with collision avoidance, link both ways with their highlight (hover/click
↔ soft text wash, driven through the decoration plugin so it survives
edit repaints), and carry the same Accept / Dismiss / Ask Petal actions.
The rail is a progressive enhancement: it mounts only when there's room
beside the editor, otherwise the existing inline hover card is unchanged.
Stacked cards that reach the bottom-right corner tuck behind the
companion mascot (z-order).
When a card is expanded, the Ask Petal bubble now opens with the
Simplified-Chinese translation of the explanation (the English stays in
the card body) instead of repeating the same text twice — a new
POST /api/suggestions/{id}/translate one-shot LLM endpoint, loaded
lazily on open with an English fallback.
Verified live against the local LLM via the uitest harness: rail
stacking, hover↔text wash, expand/Ask Petal, accept-from-rail, narrow
fallback, and the Mandarin bubble.
Claude-Session: https://claude.ai/code/session_016Yr6jELuRc7hyzYLccQKZd
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prosolis
|
5120b1e5a2 |
Read-aloud: natural neural voice via local Piper TTS
Replace the browser's robotic Web Speech API (espeak on Chromium) as the
primary read-aloud path with server-side Piper neural TTS, served by petal
and kept fully offline on millenia next to Ollama.
- internal/tts: proxy short passages to Piper, transcode WAV -> mp3/opus via
ffmpeg, content-addressed disk cache (instant re-taps). Each Piper instance
loads one voice, so language routes to its own endpoint:{voice}. Unknown
language -> 404 so the client falls back to Web Speech. UTF-8-safe truncation
for multibyte (Chinese) text.
- config: TTS_ENDPOINT / TTS_ENDPOINT_ZH / TTS_VOICE_EN / TTS_VOICE_ZH /
TTS_CACHE_DIR / TTS_TIMEOUT / TTS_AUDIO_FORMAT. Route mounts only when
TTS_ENDPOINT is set; otherwise unchanged behavior.
- web/audio/speech.ts: speak() hits /api/tts first, falls back to Web Speech on
any failure; rapid-tap-safe via a request token. Call sites unchanged.
- deploy/: Piper user systemd units (EN :5005, ZH :5006), setup script, README.
English (en_US-amy-medium) and Chinese (zh_CN-huayan-medium) are both live.
Claude-Session: https://claude.ai/code/session_016Yr6jELuRc7hyzYLccQKZd
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prosolis
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6783ce7a51 |
Suggestions: stop re-nagging resolved edits + fix typographic anchoring
Two fixes for the "accept Petal's change, then it nags about the same sentence moments later" report: - replacePending now suppresses any freshly-generated suggestion whose original->replacement matches one the user already accepted or dismissed for that doc. The model has no memory between passes, so without this it re-proposes the identical edit on the next checkpoint. - findRange anchored suggestions by exact string match, which missed whenever the model echoed an `original` with plain ASCII (straight quotes, --, ...) while the document held the Typography-converted glyphs (curly quotes, em-dash, single-char ellipsis). The miss meant no highlight AND a silent no-op on accept, which then fed the re-nag above. foldTypography canonicalizes those variants (with a source index map for length changes) so matching survives the mismatch. Covered by a server-side regression test (accept+dismiss then re-check returns nothing) and frontend unit tests for the fold and anchoring. Claude-Session: https://claude.ai/code/session_016Yr6jELuRc7hyzYLccQKZd |
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prosolis
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db737fa612 |
Editor: Find & Replace, read-aloud, backup, typography, phonetic, org niceties
Writer power-ups (Phase 11), plus the selection-bubble vs copy/paste fix. - Find & Replace (Ctrl/Cmd+F): SearchHighlight decoration extension + FindReplace bar (match-case, replace-all back-to-front, scroll without popping the selection bubble). - Read-aloud (Web Speech, offline) on the word card and selection bubble. - Keyboard/touch access to the ESL helpers: Ctrl/Cmd+D look up word at caret, Ctrl/Cmd+J rewrite selection, touch long-press lookup. Refactored the right-click handler into a shared openWordLookup(pos). - Whole-corpus backup: GET /api/docs/export-all zips every doc (md/docx), de-dupes filenames, dated name; sidebar download links. TestExportAll. - Smart typography input rules (curly quotes/em-dash/ellipsis), ASCII-only so CJK is untouched. - Duplicate doc, sidebar sort (Recent/Title/Longest), toolbar outline popover. - English phonetic (chosen over pinyin for an English learner): ECDICT-built phonetic.json.gz (46,579 words) + Result.Phonetic + WordCard IPA line; scripts/build_phonetic.py (full build + --seed fallback). - Selection bubble no longer blocks copy/paste: deferred to pointer-up and made click-through except on its buttons. Claude-Session: https://claude.ai/code/session_016Yr6jELuRc7hyzYLccQKZd |
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prosolis
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6e6e4edce7 |
Editor: font-size presets + image insert/export support
Two editor features that were in flight alongside the sound work: - FontSize TipTap extension (rides on textStyle) with Small/Normal/Large/ Title presets in the toolbar; StatusBar + CSS support - Image handling: internal/images handler, upload route + config, client API, EditorCore wiring, and md/html/docx export support for images Claude-Session: https://claude.ai/code/session_016Yr6jELuRc7hyzYLccQKZd |
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prosolis
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9e141e4169 |
Phase 10: organization & polish — cross-doc search, tags, touch, warm failures
Cross-document FTS5 search (trigram tokenizer for EN + space-free CJK, kept in sync by triggers, back-filled from existing docs). GET /api/search uses the FTS index for queries >=3 runes and a LIKE fallback for 1-2 (so 2-char Chinese words resolve); snippets are built in Go with rune-aware boundaries and sentinel highlights. Tags: user-scoped tags + document_tags join (both cascade), idempotent create/assign, per-tag doc counts. Doc list and search carry each doc's tags (one tagsByDoc query). Frontend: useTags, TagChip/TagPicker/SearchBox, rewritten DocList with chips + filter bar + search. Tablet/touch: responsive sidebar drawer (hamburger + scrim <768px), coarse- pointer tap targets, tap-to-open + outside-pointerdown-close for suggestion cards. Warm LLM-down state: useCheckpoint llmDown flag drives a gentle bilingual StatusBar note (writing still saves locally). Migration 0004 (tags + FTS). Tests: tags lifecycle, search EN/CJK/LIKE/update- reindex. go build/vet/test, tsc, vite all clean; verified live on deployment host. Claude-Session: https://claude.ai/code/session_016Yr6jELuRc7hyzYLccQKZd |
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prosolis
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60eba25fee |
Phase 9: ESL superpowers — Chinese gloss + tone-rewrite
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
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prosolis
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8e1111d768 |
Phase 8: version history + export (trust foundation)
Version history: new document_versions table (migration 0003) holding full-body snapshots that cascade with the doc. Throttled auto-snapshots on save (>=3min apart, max 40/doc, pruned), explicit manual restore points, and a pre_restore safety copy taken before each restore so restoring is itself undoable. Endpoints under /api/docs/:id/versions, all owner-scoped. Empties and bare renames never snapshot. Export: pure-Go Tiptap-JSON -> Markdown / HTML / plain-text / docx (no cgo/pandoc, single-binary intact), CJK-safe with RFC 5987 filenames. docx is a hand-built OOXML zip. PDF is handled client-side via the browser print dialog + an @media print stylesheet so CJK renders with the reader's own fonts. Frontend: ExportMenu (downloads + Print/PDF) and HistoryPanel (snapshot list, preview, restore) wired into the title row; bilingual zh-first to match chrome. Restore remounts the editor via editorEpoch. Stop saving empty docs: blank Untitled drafts now reuse-on-create and self-discard when navigated away from (refs avoid stale closures). Tests: versions_test.go, export_test.go (incl. valid-zip docx). go build/vet/test, tsc, vite build all clean; live end-to-end smoke verified snapshot/throttle/restore/export. Claude-Session: https://claude.ai/code/session_016Yr6jELuRc7hyzYLccQKZd |
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prosolis
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4c288834c0 |
Editor: document tone, right-click word lookup, expanded stats
Four enhancements to make the editor fit real school usage:
- Per-document tone (academic/professional/casual/humorous/creative/
persuasive/general): new documents.tone column (migration 0002), threaded
through the docs API, a bilingual ToneSelect dropdown on the title row, and
injected into the grammar-checkpoint LLM prompt so advice fits the register.
The voice pass stays tone-agnostic.
- Right-click word lookup: a new offline `lexicon` package serves definitions
(Wordset, modern ESL-friendly glosses) and synonyms (WordNet synsets first,
then frequency+stopword-ranked Moby for breadth) from gzipped embedded data,
behind /api/word/{word} with light morphology. The WordCard popover shows the
definition and tappable synonym pills that swap the word in place.
- Expanded writing stats: clicking the word count opens a StatsPanel with page
count, sentences, paragraphs, reading time, average word length, word variety,
and Flesch-Kincaid reading level — all computed client-side.
Claude-Session: https://claude.ai/code/session_016Yr6jELuRc7hyzYLccQKZd
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prosolis
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0fa70979a0 |
Phase 5: voice consistency pass
Tier-1 voice-consistency pass: whole-document LLM review surfacing passages that read tonally out of place (formal/over-polished/paraphrased-too-closely), as honey-decorated `voice` flags with no correction (awareness-only). - internal/llm/voice.go: RunVoice sends the whole document (no TruncateDoc), MaxTokens 2048, 20s per-doc floor (VoiceInterval). Standalone voice prompt in prompts.go (not bundled with the grammar checkpoint, per spec). - internal/suggestions: POST /api/docs/:id/voice. replacePending is now family-scoped (pendingScope) so grammar and voice never clobber each other's pending flags; both passes return the unified pending set. check/voice share one runPass helper. TestVoicePassCoexists covers both directions. - Frontend: api.voiceDoc, useCheckpoint voicing/runVoice, honey "Check my voice" toolbar pill, breathing honey dot in StatusBar. Claude-Session: https://claude.ai/code/session_016Yr6jELuRc7hyzYLccQKZd |
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prosolis
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3c5f3ecb96 |
Phase 4: Ask Petal SSE chat
Conversational follow-up on a suggestion, streamed token-by-token. Backend (interface-only; handlers never touch a concrete LLM client): - internal/llm/chat.go: StreamAskPetal with conversational sampling (max_tokens 512, temp 0.7, rep 1.15, top_p 0.92, stop "\n\n\n"), reusing AskPetalSystemPrompt + TrimHistory. - internal/suggestions/chat.go: POST /api/suggestions/:id/chat. One user-scoped join loads the suggestion + parent content_text; surroundingParagraph extracts the \n\n-bounded paragraph at from_pos (whole-doc fallback when unlocated) and injects it server-side. Streams event: token / event: done SSE frames with JSON-encoded data so token newlines can't break framing; real http.Flusher per chunk. LLM-unreachable -> 502 before SSE headers; unknown suggestion -> 404. Frontend: - streamSuggestionChat: fetch + ReadableStream SSE parser (not EventSource, needs POST), abortable. - AskPetal.tsx: whole conversation in component state (no persistence, cleared on close), Petal's first bubble pre-seeded with the explanation, rose/lavender bubbles, CJK font stack on the bubbles only (Note #17), streaming caret. - SuggestionCard "Ask Petal" pill pins the card open while chatting (hover-close suppressed, click-away closes) and widens it to 340px. Tests: chat_test.go covers streamed-text concat + done event, server-side context injection on the system message, sampling params, 404, and surroundingParagraph. go build/vet/test clean, tsc clean, vite build OK. Live SSE smoke-tested against a fake streaming vLLM: tokens flushed individually through the chi middleware stack, done terminator, 502 on LLM-down, 404 on unknown suggestion. Claude-Session: https://claude.ai/code/session_016Yr6jELuRc7hyzYLccQKZd |
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prosolis
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3f7e705028 |
llm/ollama: disable thinking so reasoning models return content
Qwen 3.5 — the spec's recommended model — is a reasoning model. With thinking on, Ollama streams its chain-of-thought into a separate `thinking` field and hits num_predict before emitting any answer into `content`, so Complete() got an empty string and the checkpoint failed with "no JSON object in model output". Sending `"think": false` on every /api/chat request fixes it; non-thinking models (qwen2.5) ignore the flag. Validated end-to-end on deployment hardware (Ollama, qwen3.5:9b): the grammar checkpoint now caught all five ESL errors in a 3-sentence sample with correct JSON and string-anchoring, ~8.5s warm. Claude-Session: https://claude.ai/code/session_016Yr6jELuRc7hyzYLccQKZd |
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prosolis
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a4069d5755 |
Phase 3: LLM grammar checkpoint
Backend (internal/llm): backend-agnostic LLMClient interface + factory
with vLLM (OpenAI-compat) and Ollama (native) clients, each Complete +
Stream. prompts.go holds the checkpoint and Ask Petal templates;
checkpoint.go salvages JSON from model output (brace-matched), enforces a
per-doc 30s RateLimiter, and truncates the doc to a latency cap.
internal/suggestions: POST /api/docs/:id/check runs a checkpoint and
replaces the doc's pending suggestions in one tx (accepted/rejected kept
as history); GET /api/docs/:id/suggestions lists pending;
POST /api/suggestions/:id/{accept,dismiss} resolves one. Throttled checks
return the current set rather than erroring.
Frontend: useCheckpoint (4s debounce, loads existing on open, stale-guard
tokens); SuggestionHighlight renders ProseMirror decorations re-anchored
by the `original` string on every doc change (not stored marks), with
precise textblock-offset→PM-position mapping; SuggestionCard shows the
type tag + diff + explanation and applies the replacement in-editor on
accept; breathing rose checkpoint dot in the StatusBar; fade-float +
breathe animations.
Tests: llm parse/rate-limit/truncate; suggestions full flow + rate-limit
over httptest with a stub client. Smoke-tested end-to-end against a fake
vLLM endpoint (anchoring verified) and the LLM-unreachable 502 path.
Claude-Session: https://claude.ai/code/session_016Yr6jELuRc7hyzYLccQKZd
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prosolis
|
5e00cdce88 |
Phase 2: document CRUD + auto-save
Backend internal/docs: chi sub-router (list/create/get/update/delete) mounted at /api/docs, scoped to the local user. Create uses RETURNING; update is a COALESCE partial-update so rename and full editor save share one PUT. JSON 404/400 errors; handlers_test.go walks the lifecycle. Frontend: api/client.ts, useAutoSave (1.5s debounce + saveNow flush before doc switch), EditorCore (Tiptap StarterKit/Underline/TextAlign/ Placeholder/CharacterCount) + Toolbar, DocList/DocListItem, StatusBar, and an App.tsx that orchestrates load/select/create/delete with optimistic sidebar patching. content + content_text + word_count are emitted together on every edit. .petal-prose styling (Lora body, Nunito headings). Verified: tsc clean, vite build, go build, full CRUD smoke test incl. CJK title round-trip and SPA serve. Claude-Session: https://claude.ai/code/session_016Yr6jELuRc7hyzYLccQKZd |
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prosolis
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9c98e97030 | Phase 1: data layer (SQLite, migrations, models, seed) | ||
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prosolis
|
e72d48d64e |
Phase 0: project scaffold
- Go module + chi server with embedded SPA serving and /api/health - internal/config env loader (local-dev defaults; auth/copyleaks deferred) - React 19 + Vite 6 + Tailwind v4 frontend with full Petal design tokens - Frontend embedded into the binary via web/embed.go (go:embed all:dist) - README dev workflow, .env.example, BUILD_PLAN progress tracker - Verified end-to-end: binary serves health, embedded SPA, and SPA fallback |