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
