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
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
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
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
- 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
