Entry points (no sixth tab): Ask in the Library header (desktop button,
phone icon), Ask about this deck in the deck menu, Ask a question on
study/homework results (compact result travels as context), and a Chat
row in the desktop sidebar. Phones get a full-screen route with back +
New chat; the tab bar steps aside.
- Client-side retrieval: chunk scoped decks (~800 tokens), BM25 against
the question + recent turns, top chunks under ~7k tokens, each
labelled with deck + section. Notes come from the deck's stored
sourceText (already kept for Regenerate); decks without it fall back
to generated content and the UI says so.
- Stateless server: /api/chat validates against the CHAT_MODELS
allowlist, trims the history to ~6k tokens, caps context at ~9k and
streams token/thinking/done/error NDJSON. /api/chat/extract reduces
attachments to text through the existing vision step.
- UI: user bubbles + full-width assistant text, streaming with stop,
auto-scroll that pauses with a jump-to-bottom button, safe markdown
(React nodes, no HTML injection; KaTeX dynamically imported only when
a message has math), Thinking row for reasoning, copy/regenerate/
edit-and-resend, model + context pickers (last model remembered),
composer with visualViewport keyboard handling, safe-area, 16px
textarea, Enter-to-send on desktop.
- Usage-limit failures keep the draft and show the shared message with
Settings/Ollama actions; stopping maps the reader abort to a clean
stopped state; offline disables sending with a reason.
- Settings: Keep notes text for chat toggle; deck menu: Delete notes
text. RATE_LIMIT_CHAT + CHAT_MODELS in .env.example and README.
- Tests: chat suite (63 checks, stub Ollama) wired into run-all.
Full set: 12/12 suites, 487 checks. SW -> freezmo-v32.
Also: tests/model-compare.mjs (diagnostic) benchmarks two models on the
same notes (latency, repair rounds, activity types) so the gpt-oss vs
gemma default can be decided on numbers; defaults unchanged.
Martin Dvorak
756a6257a2