English stays the default; Czech is a full translation. Only the app chrome
is translated - notes and generated decks keep their own language, which is a
core feature, not a setting.
i18n
- lib/i18n-dict.ts: flat en/cs dictionaries (441 keys each), translate() and
translatePlural() with real Czech plural rules (1 sada / 2-4 sady / 5+ sad).
English is the default and the fallback for a missing key.
- lib/i18n.ts: browser store (freezmo.locale.v1), useI18n() hook, and the
x-freezmo-locale header. The hook's t/plural are bound to the locale React
is rendering with, so the first client render matches the server HTML and
then re-renders in the stored language; module-level t is only for event
handlers and non-React helpers.
- <html lang> follows the choice (inline script + setLocale).
UI
- Settings -> Language segmented control (English / Cestina), plus an EN/CS
button on the key gate for first run.
- Every screen translated: sidebar, header, tab bar, library, deck cards,
folder bar, create flow, all seven activities, study chrome, results,
settings + health panel, API-key gate and help, install sheet, offline and
the deck-not-found page.
- Plural-aware counts everywhere (decks, folders, activities, runs, photos,
documents, pages, words, wrong attempts).
Server
- API routes and guards (generate, grade, health, http-guard, rate-limit,
ollama error mapping) answer in the request's language, so error cards and
the health panel never fall back to English mid-sentence.
Fixes
- A hydration mismatch when a non-default locale was stored silently dropped
the .dark class after hydration; render-time t() is now bound to the
hook's locale (UploadScreen.describeExtraction, ResultsScreen.answerFor,
DeckCard's folder fallback).
- Bumped the service worker cache to freezmo-v4 for this deploy.
Tests: i18n 27/27 (gate toggle, persistence, html lang, Czech plurals,
settings switch) and a rebuilt regression suite 72/72 (English default,
library, create, all 7 activity types, results, settings, install sheet,
offline, PWA, security, Czech smoke).
Next.js 15 app that turns photos, PDFs, DOCX/PPTX and text into a swipeable
feed of AI-generated activities (flashcards, multiple choice, true/false,
fill-in-the-blank, matching, ordering, short answer) using the user's own
Ollama models.
Highlights:
- All AI calls run in server route handlers; the browser never talks to Ollama.
- Bring-your-own-key mode (default): the key lives only in the browser and is
sent per-request; server, local-daemon and shared-key modes also supported.
- Client-side document extraction (pdf.js, mammoth, jszip) with scanned-PDF
page rendering for the vision model; notes stay in their original language.
- ChatGPT-style shell: collapsible sidebar / mobile drawer, neutral token-based
light + dark themes, folder organisation, PWA (manifest, SW, offline page).
- Strict JSON validation with zod + auto-repair, rate limiting, and request
guards (cross-origin, body-size, API-key sanitising).
- setup.sh bootstraps deps, .env.local and a production build.
Gitignore excludes .env*, the generated pdf.js worker and local scratch files.
