25e415daa24a77c4c8a80b11029abeb76f584a45
24
Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
 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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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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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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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
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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
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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
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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
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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
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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
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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
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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
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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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95123e8c49 |
Grow the companion, fix idle fallback, add update banner
Companion: bump the corner mascot ~12% (128→144) and make animation resolution robust — fall back to the idle clip when a mood has no clip of its own, and pin the always-asleep cat to one pose so its Lottie never reloads. This stops a bare emoji from replacing the cute companion on idle. Update notifications: serve a build id at /api/version (a hash of the embedded dist/index.html, which changes on every frontend deploy). The client records its load-time id, polls every 90s (and on tab focus), and floats a Mandarin-first "new version available" banner offering a refresh when the id changes. 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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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
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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 |