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.
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.
Resolve the misspelled word from the click/right-click position and the
checker rather than from the .petal-misspelling DOM span: clicking a word
moves the caret into it, which fires the decoration rebuild that
deliberately un-underlines the caret word, so the span is already gone by
the time the handler runs. Factored into openMisspellAt(pos), which only
opens when the checker actually flags the word, and is gated to clicks
inside .petal-prose so a click on a floating card doesn't resolve a word
hidden behind it.
Right-click now offers spelling corrections first on a misspelled word
(the familiar "did you mean" gesture), falling back to word lookup
otherwise.
AskPetal: focus the input with preventScroll so opening the card doesn't
jump the document to the top.
Claude-Session: https://claude.ai/code/session_016Yr6jELuRc7hyzYLccQKZd
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
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
prosolis