1. Bugs fixed:
- Backup schema now accepts theme: "aero" so backups exported under
Frutiger Aero pass parseBackup on import, and applyImport in "replace"
mode replaces SRS schedules, answer history, and chats instead of
merging into existing SRS or skipping empty arrays.
- Typed FillBlank cards bind the input value to chosen ?? value instead
of chosen ?? "", and normalise() preserves Unicode letters (\p{L}\p{N})
when grading non-ASCII answers.
- OpenAI-compatible vision calls (contentFor in lib/openai-compat.ts)
prefix data:image/jpeg;base64, when routes pass stripped base64.
- Streaming calls (ollamaChatStream, providerChatStream) keep their
AbortController active across the entire body stream and API routes
forward request.signal so stopping a chat or cancelling a run aborts
the upstream request immediately.
- HomeworkCard uses homeworkModeLabelKey so "check" records display the
Checked label instead of Step-by-step guide.
- Desktop dropzones on /create and /homework accept dropped documents as
well as images.
- LibraryScreen filters reported questions out of its due and mistake
counts to match ReviewClient.
- Clearing a provider key resets generation if it pointed at that
provider; chat conversations persist and restore provider; ModelPicker
keys items by provider:name.
- RouteTransition no longer mutates module-level lastPath during render.
- Service worker asset handler falls back to Response.error() when an
uncached asset fetch fails offline.
- Confetti and .ice-orb / .ice-bubble respect the in-app reduce-motion
toggle.
2. Performance & cleanup:
- Deduplicate window storage listeners across all six localStorage
stores (one listener while subscribed instead of N^2 notifications).
- Use todayAnswerCount in LibraryScreen and pass sorted folders to
DeckCard.
- Memoize MessageRow with stable callbacks in ChatScreen and compute
last message IDs in a single pass.
- Close ImageBitmap after drawing in lib/image.ts and destroy pdf.js
documents in finally in lib/documents.ts.
- Avoid re-parsing serialized sync payloads in POST /api/sync.
- Deduplicate copyText (lib/share.ts -> lib/clipboard.ts), chatMessageId,
describeExtraction, ALL_FOLDERS, useIsPhone, and remove unused helpers
and boilerplate public/*.svg files.
Version 0.5.8, SW -> freezmo-v80.
Settings -> Providers takes keys for OpenAI, Anthropic (their official
OpenAI-compatibility layer), DeepSeek, Groq, OpenRouter and any custom
OpenAI-compatible endpoint. One adapter (lib/openai-compat) covers
listing, streaming chat, JSON generation and vision, and every model
flow can run on a provider: the chat picker lists each enabled
provider's models (labelled, remembered), and a "Study generation"
choice moves decks, homework, grading and attachment transcription onto
a provider model.
Keys stay in this browser exactly like the Ollama one
(freezmo.providers.v1): never stored server-side, never in a backup or
the sync payload, forwarded only with the request that needs them. The
provider test asserts the key reaches the provider while the routing
header stays on the app side.
New suite tests/providers-test.mjs (13 checks) stubs both protocols:
model listing, chat streaming, study generation and the Settings flow.
Privacy policy updated (en+cs). Contrast 0 findings, axe clean, mobile
126/126, chat 102/102, wizard 95/95, bubbles 34/34, regression 44/44,
i18n 13/13, native 33/33. Version 0.4.7, SW -> freezmo-v72.
- Aero: blue gradients back on the active segment and every primary
(Review due, the card's Study button, the composer's send button); a
frosted backing behind the page heading and the All decks label; a
bottom-weighted rail tint; chat header/composer/welcome panels; calmer
orbs; stronger card veil + a stronger blur bake.
- Dark/Light: a dedicated --track token makes progress bars read (the
first attempt shifted --surface-sunken and the pixel scan caught the
sheet-contrast regression); brighter dark secondary text; darker light
segmented labels and difficulty tints; stronger light card border and
shadow.
- Chat UI: friendly model chip ("Gemma 4 31B") with the raw name in a
tooltip, larger chips, plain centered disclaimer, vertically centered
welcome panel, distinct chat-plus icon for new chat.
- Chat models: every chat-capable model from the server's /api/tags is
selectable (favourites first, search field when long, live-list
validation in the route); default CHAT_MODEL_DEFAULT or gemma4:31b.
- Reduce motion: Settings toggle (default off) that parks the scene,
collapses CSS animations and drives framer-motion's calm mode.
- Folders hint, "New" badge on fresh decks.
Contrast: 0 findings, axe clean, mobile 126/126, chat 102/102, wizard
95/95, regression 44/44, i18n 13/13, native 33/33.
Version 0.4.6, SW -> freezmo-v71.
Audit pass with the threats that actually apply to a self-hosted, account-less
app: getting the Ollama key throttled or banned, and someone grinding the app
down. Per-route windows already existed; these are the missing layers.
- lib/model-guard.ts: every route that spends a model call now takes a slot —
60 calls per window across all clients (RATE_LIMIT_MODEL_TOTAL), 3 in flight
per IP, 6 in total — and the slot is released when the call finishes, on
errors and on client disconnects. Over the concurrency cap answers 429
kind=busy, not a punishment. Slots are taken after every cheap rejection so
a malformed request cannot hold one (found by the new suite: early 400s
were leaking slots).
- Images must be base64 data URLs (dataUrlSchema in lib/schemas): a plain URL
in an images field made Ollama fetch an arbitrary address on our behalf.
- Push endpoints must be a real push service (PUSH_ALLOWED_HOSTS, defaulting
to FCM/Mozilla/Apple/WNS): the server POSTs to whatever is stored.
- The rate-limit identity is the LAST x-forwarded-for hop. Reading the first
let a client spoof its own IP and dodge every per-IP limit.
- Disk guards: reports.jsonl stops at REPORTS_MAX_BYTES (8 MB), reminder
devices cap at PUSH_MAX_SUBSCRIPTIONS (50).
- Security headers: frame-ancestors 'none' + X-Frame-Options DENY, nosniff, a
referrer policy and a Permissions-Policy without camera/mic/geo/payment.
New tests/security-test.mjs (13 checks, registered in run-all) proves each
guard against a slow stub Ollama with deliberately tiny limits. README:
security notes + rate-limit tables updated. Version 0.1.3, SW -> v51.
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.
