# ❄️ Freezmo

**Turn photos of your study notes into a swipeable feed of mini study games.**

Freezmo is a TikTok/Gizmo-style study app. You paste or upload photos of your notes, an AI reads
them and builds a deck of 8–15 interactive activities — flashcards, quizzes, matching games and
more — that you swipe through vertically like a feed. Every answer gives instant feedback, XP and
streaks, and the deck is saved in your browser so you can retry it later.

All AI runs through **your own Ollama setup** (a local daemon or the Ollama cloud API). No accounts,
no database, no data leaving your machine except the requests you send to Ollama.

---

## Table of contents

- [Features](#features)
- [Quick start](#quick-start)
- [Supported input formats](#supported-input-formats)
- [Ollama setup](#ollama-setup)
- [Rate limits](#rate-limits)
  - [Mode 1 — local daemon (recommended)](#mode-1--local-daemon-proxying-cloud-models-recommended)
  - [Mode 2 — direct Ollama cloud API](#mode-2--direct-ollama-cloud-api-api-key)
  - [Changing models](#changing-models)
  - [Checking the connection](#checking-the-connection)
- [Running on your network / from your phone](#running-on-your-network--from-your-phone)
  - [Keep it running as a service](#keep-it-running-as-a-service-systemd-user-service)
- [Folders](#folders)
- [Install as an app (PWA)](#install-as-an-app-pwa)
- [Security notes](#security-notes)
- [How it works](#how-it-works)
- [Project structure](#project-structure)
- [API routes](#api-routes)
- [Scripts](#scripts)
- [Data, storage and privacy](#data-storage-and-privacy)
- [Troubleshooting](#troubleshooting)
- [Decisions and notes](#decisions-and-notes)

---

## Features

**Capture & generate**

- Drag & drop, file picker, **mobile camera capture** and **clipboard paste** (Ctrl/⌘+V)
- **Phones get a 3-step flow** — notes → options → summary — with a thin progress bar and
  “1 / 3”. Step 1 leads with the step name as the headline, a formats/limits hint, one big
  *Add photos or files* area plus *Camera* and *Paste text instead*, and a “nothing added
  yet” placeholder that becomes the thumbnail/chip list. Next stays disabled until something
  is added. Step 2 keeps folder, difficulty and count at their defaults with a helper under
  each group and tucks the topic hint and pasted notes behind one collapsed row. Step 3 is a
  real summary — thumbnails/chips, files, difficulty, activities and folder, each with an
  *Edit* link back to its step. A flat Back/Cancel + Next/Freeze bar sits at the bottom above
  the safe area (the tab bar hides inside the wizard), and it is portalled to `<body>` so the
  screen entrance animation can never displace it. The desktop page is unchanged.
- **Native-feel touches (phones)**: the Android Back gesture closes the topmost layer first
  (sheet, drawer, actions panel, then one wizard step); deleting a deck shows an *Undo*
  toast instead of a confirm; the deck menu can share a deck as JSON through the system share
  sheet (clipboard fallback); content shared from other apps opens a chooser and lands
  pre-filled in either wizard; haptics (Settings → Haptics, on by default) tick on tab
  switches, toggles, correct/wrong answers and completion; the screen stays awake during
  study sessions and homework guides; wizard drafts survive a reload or an OS kill; re-tapping
  the active tab scrolls to the top; an offline pill appears and generation is disabled with
  a reason until the connection is back.
- **Learning engine**: every answer is recorded (deck, activity, topic, correct/wrong, time) in an
  IndexedDB log, and each activity gets a light **SM-2 schedule** — correct answers come back after
  1 day, then 3, then interval × ease; wrong ones after ten minutes. The Library shows a **Smart
  review** card with the due count, a **Mistakes** count (activities whose latest answer was wrong —
  they clear themselves once answered correctly) and today's **daily goal** progress. A **Progress**
  screen (drawer) has the day streak, a five-week calendar, accuracy per subject and per deck and
  the weakest topics. **Exam mode** (drawer) takes one or more decks, a question count and an
  optional timer, hides hints and shows a per-deck/per-topic breakdown at the end. **Daily
  reminders** appear in Settings only when the server has VAPID keys configured; subscriptions are
  stored as endpoint + keys only, and `node scripts/send-reminders.mjs` (cron/systemd timer) does
  the sending.
- **Backup, sync and limits**: *Settings → Data & backup* exports **everything** (decks, folders,
  homework, progress, safe settings — never the API key) to one JSON file and imports a backup with
  a preview and a merge/replace choice; a gentle, dismissible nudge appears after 5 new decks or 14
  days without a backup, and the storage-persistence state (`navigator.storage.persist()`) is shown.
  *Settings → Sync* is **off by default** and opt-in: the data is encrypted in the browser
  (PBKDF2-SHA256 → AES-GCM, key kept as a non-extractable `CryptoKey`) before it is uploaded, the
  server stores only an opaque blob under a random 128-bit sync ID, and conflicts are surfaced with
  an explicit *keep this device / use synced copy* choice. When Ollama's **free monthly usage** runs
  out, every flow that calls the model shows the same clear message with **Open Settings** (jumps to
  the key field) and **Open Ollama** — never a silent fallback to another model.
- **Photos and documents**: JPG/PNG/WEBP/HEIC images plus **PDF, DOCX, PPTX, ODT/ODP/ODS, TXT, MD, CSV**
- Documents are read **in the browser**: PDF text layers are extracted, scanned PDF pages are rendered
  as images for the vision model, DOCX/PPTX text, speaker notes and embedded images are pulled out.
  The raw file never leaves your device.
- Up to 8 photos + 6 documents per deck (max 12 images reach the model); photos are resized to max
  1600 px and re-encoded as JPEG before upload
- Optional extra text (pasted notes) and a topic hint
- Easy / Medium / Hard difficulty and 8 / 10 / 12 / 15 activities per deck
- Fun staged loading state (`Reading your notes… → Finding the key ideas… → Building your activities…`)
- Friendly error cards with a **Retry** button that point at Settings when a key is needed

**Language**

- The notes' language is detected and **preserved end to end**: transcription, deck title, questions,
  options, explanations, short-answer grading and later *regenerate* / *add more* all stay in that
  language. Czech notes produce a Czech deck; the app never translates them to English.
- **Language guard:** after the vision step, the transcription is checked (script + language markers).
  If it clearly came back in another language, `TEXT_MODEL` (which is much stronger multilingually)
  restores it before any activities are written — the UI shows *“Restoring the notes' language…”*.
  On good transcriptions the guard stays silent and costs nothing.
- The deck stores its language, so short answers are graded and feedback written in the same language.
- The **Freezmo interface** has its own language switch: **English (default)** and a full **Czech**
  translation, picked in **Settings → Language** or from the `EN`/`CS` button on the key gate. The
  chosen locale is remembered per browser and also decides the language of server messages (API
  errors, health notes), so nothing falls back to English mid-sentence.

**Study feed**

- Full-screen vertical scroll-snap feed, one activity per screen
- Arrow-key / PageUp / PageDown / Home / End navigation, plus swipe on touch devices
- Progress bar, activity counter, XP counter and answer streak in the chrome
- Instant feedback with a short explanation for every activity, confetti when you finish
- Results screen: **Retry missed ones** (fresh, answerable items), **Study the whole deck again**,
  and **Regenerate deck** — rebuilds the activities from the stored notes so you can keep drilling
  until you're ready

**Make my homework**

- Same intake as a deck — paste the assignment, photograph it, or add a PDF/DOCX/PPTX/ODT/text
  file; photos go through the same vision model and language guard that notes do
- Two modes: **Just make it** returns the finished homework (the answer only, ready to copy), and
  **Explain how to make this homework** turns it into a guided walkthrough
- On phones this is a **2-step flow**: the assignment first (same simplified input as the
  deck flow, with its own step headline, formats hint, big add area and empty placeholder),
  then the two mode cards under a short preview — tapping a card starts it immediately, so
  there is no separate button. Step 1 starts with *Cancel* and the flat action bar matches
  the deck wizard. Desktop keeps the select-then-confirm layout.
- The guide is one step per screen in the same snap-feed feel as the study feed: what to do and
  why, **three progressive hints** per step (nudge → hint → the full answer), and a **checkpoint**
  built from the normal activity components and graded through `/api/grade`
- The last screen assembles the solution from the step answers, with a copy button
- Results live in `freezmo.homework.v1` — the homework screen's history and the library's
  **Homework** tab — where you can reopen or delete them; **Make it again** re-runs from the
  stored assignment text, and original files are never saved
- The answer and the guide are always written in the **language of the assignment**, never
  translated into the interface language

**Activity types** (each one is its own React component, rendered from JSON by a `type` field)

| Type | Interaction |
| --- | --- |
| `flashcard` | Tap to flip, then self-assess *I knew it / Not yet* |
| `multiple_choice` | 4 options, keys 1–4, correct answer + explanation |
| `true_false` | Tap the buttons **or** swipe the card right/left |
| `fill_blank` | Inline input (one typo forgiven) or a word bank |
| `matching` | Tap a term, then its definition; perfect match for full XP |
| `ordering` | Drag with the mouse/finger, or use ▲▼ buttons, then check |
| `short_answer` | Typed answer graded by the AI via `/api/grade`, with a self-check fallback |

**First run**

- A full-screen **API-key gate** replaces the app until a key is saved (in `user-key` mode): one
  masked input with a show/hide toggle, a single **Continue**, and a "?" sheet with the four steps
  to a free key. The key is validated with a real 1-token probe before it is accepted — invalid
  keys and network trouble get different inline messages. Removing the key in Settings brings the
  gate back; `server` and `local` installs skip it entirely.

**Library & folders**

- **Two pools, never mixed**: a **Study Decks** tab (the folder + card library) and a **Homework**
  tab with saved solutions and step-by-step guides — each with its own empty state and call to
  action, and the active tab lives in the URL (`/?tab=homework`)
- **Phone library, decluttered**: no stats line, the folder row and “Unorganized” heading only
  appear once folders exist (the drawer has *New folder*), and Import is a small icon button in
  the tab row. Deck cards shrink to title + one meta line (activities · difficulty · best
  score) + a one-line description that expands on tap, with the whole card tappable and a small
  **Study** pill; homework cards match.
- Decks saved locally with title, subject, folder, activity count, date, play count and best score
- **Folders**: create named groups ("History", "Biology", …) from the sidebar or the create screen.
  New decks freeze straight into the selected folder; anything unfiled lives in **Unorganized**.
  Rename, delete (decks survive — they return to Unorganized) and move decks between folders
- Rename, delete (with confirm), regenerate (from the library or the results screen), and
  **add more activities** to an existing deck
- Export a deck as JSON and import it back — the folder name travels with the file and is recreated
  on import

**Design**

- **ChatGPT-style shell**: a persistent left **sidebar** (brand, a quiet "New deck" row, a *Folders*
  list with per-folder counts, Settings/Dark mode pinned to the bottom). It **collapses** to a 68px
  icon rail (remembered in `localStorage`) and becomes a slide-in **drawer** behind a hamburger on
  phones; mobile also keeps the frosted header + iOS tab bar
- **Frosted ice glass, both themes**: light page `#eef5fd` (pale ice) with white glass panels;
  dark page `#0a1120` with `rgba(255,255,255,.06)` glass. Every large surface shares one recipe —
  translucent tint, 24px `backdrop-blur` (16px on phones), a bright 1px rim, an inner top highlight
  and a blue-tinted shadow — over a fixed ice scene (navy/pale base, drifting glacier blobs, glossy
  ice orbs and a whisper of grain).
  Text tiers are documented AA ratios (see below), and the cards fill the row with
  `repeat(auto-fill, minmax(280px, 1fr))` — no stranded cards, no dead space
- Deck cards: title → muted metadata → neutral tags (difficulty carries the only colour:
  green/amber/red) → summary → a single **Study** button, with everything else in the `⋯` menu
- **Frosted UI**: the sticky header, tab bar, sheets and panels use real `backdrop-filter` blur over
  the fixed ice scene (drifting glacier blobs, glossy orbs, a whisper of grain) — depth without noise
- **Pill language**: primary CTAs are near-black in light mode and white in dark mode; secondaries
  are outlined or ghost. Colour is reserved for meaning — activity tints (sky/lilac/mint/peach/rose),
  correct/wrong feedback, key status
- Micro-interactions: 160–200ms colour/transform transitions, `active:scale-[0.985]`, skeleton
  shimmer, hairline hover washes on every row and card
- **Motion (phones)**: one shared language (`lib/motion.ts`) — every button, card, chip, tab and
  drawer row scales to 0.96 on press with a spring release; the tab bar, segmented controls and
  difficulty/size pickers glide their highlight with a shared `layoutId`; wizard steps slide
  forward and backward and page content enters direction-aware; the Settings sheet and drawer
  follow the finger and settle on release velocity; library cards fade up in a capped stagger and
  animate out on delete; score and XP count up; correct answers pulse, wrong ones shake;
  `prefers-reduced-motion` collapses everything to short fades. Only transform and opacity
  animate — never blur.
- **iOS-flavoured PWA**: standalone mode, safe-area insets, bottom tab bar, sheet-style dialogs with
  a grabber, inset grouped lists, segmented controls, "Add to Home Screen" hint — see
  [Install as an app](#install-as-an-app-pwa)
- Mobile-first, dark mode, keyboard accessible, focus rings, ARIA labels, `prefers-reduced-motion` support

---

## Quick start

Requirements: Node.js 20+ (tested on 24) and npm.

```bash
cd freezmo
./setup.sh                     # install + .env.local + production build
npm start                      # http://0.0.0.0:3207
```

Or do it by hand (and use the dev server):

```bash
cd freezmo
npm install
cp .env.example .env.local     # first time only
npm run dev                    # http://0.0.0.0:3207
```

`setup.sh` flags: `--dev` installs and prepares `.env.local` without building, `--no-build` skips the
build too.

Open <http://localhost:3207>. The app runs without any Ollama configuration — you'll just need a
key (or a signed-in daemon) before it can generate a deck. Complete one of the Ollama setups below,
then paste the key on the gate (or later in **Settings**).

`npm run dev` and `npm run build` also copy the pdf.js worker into `public/` automatically (see
`scripts/copy-pdf-worker.mjs`), which is what lets the browser parse PDFs.

Production:

```bash
npm run build
npm start                      # http://0.0.0.0:3207
```

Production is also where the PWA comes alive: the service worker registers, the app can be installed
to the home screen and the `/offline` fallback works. In `npm run dev` none of that runs, so you
won't fight a stale cache while developing.

---

## Ollama setup

Freezmo talks to **`POST /api/chat`** and **`GET /api/tags`** of whatever URL is in
`OLLAMA_BASE_URL`. All calls happen in Next.js route handlers on the server — the browser never
talks to Ollama directly.

Who provides the API key is controlled by **`OLLAMA_AUTH`**:

| `OLLAMA_AUTH` | Key comes from | Use it when |
| --- | --- | --- |
| **`user-key`** (default) | each browser, pasted on the key gate (or in Settings) | several people/devices share the app, or you don't want a key on the server |
| `server` | `OLLAMA_API_KEY` in `.env.local` | a single-user install |
| `local` | nothing — a daemon signed in with `ollama signin` | you run Ollama locally |

### Mode 1 (default) — bring your own key

```bash
OLLAMA_AUTH=user-key
OLLAMA_BASE_URL=https://ollama.com
VISION_MODEL=gemma4:31b-cloud
TEXT_MODEL=gpt-oss:120b-cloud
```

1. Open the app — the **key gate** asks for a key on first visit.
2. Create one at <https://ollama.com/settings/keys>, paste it in and press **Continue**.
3. The gate validates it with a real 1-token request, then drops you into the icebox.
   **Settings → Test connection** re-checks any time and shows the model list.

Where the key lives:

- **In the browser only.** It is stored in this browser's `localStorage` under `freezmo.settings.v1`
  and sent with each API call in the `x-ollama-key` header.
- **Never on the server:** the route handlers read the header, use it for that one request and drop
  it. It is not written to `.env.local`, a database, a cookie, a log line or a JS bundle. Restarting
  the server does not remember any key, and every browser/device needs its own (or the same) key.
- You can remove it any time with **Remove key from this browser**.
- Because the browser hands the key to your own server, use HTTPS if the LAN is not trusted — on a
  plain-HTTP LAN somebody sniffing traffic could read it. The key never goes to any third party.

Keys are verified with a real (tiny, 1-token, 5-minute-cached) chat request, because model listing
on `ollama.com` is public and would happily accept a bogus key.

### Mode 2 — local daemon (no key at all)

Runs cloud models through your local Ollama daemon, signed in once with `ollama signin`.

```bash
ollama                              # start the app/daemon
ollama signin                       # approve the printed link in any browser
ollama pull gemma4:31b-cloud        # vision model, reads the photos of your notes
ollama pull gpt-oss:120b-cloud      # text model, builds the activities and grades
```

`.env.local`:

```bash
OLLAMA_AUTH=local
OLLAMA_BASE_URL=http://localhost:11434
VISION_MODEL=gemma4:31b-cloud
TEXT_MODEL=gpt-oss:120b-cloud
```

Restart `npm run dev` after editing `.env.local`. Verify with the **⚙️ settings dialog** in the
app or `curl localhost:3207/api/health`.

**Free tier.** `gemma4:31b-cloud` and `gpt-oss:120b-cloud` are included in the Ollama **Free** plan
(verified October 2026). Other free models: `gpt-oss:20b-cloud`, `nemotron-3-super:cloud`,
`nemotron-3-nano:30b-cloud`. Models such as `glm-5.3-flash:cloud`, `deepseek-v4.1-flash`,
`minimax-m2.7` and `mistral-large-3` reply with *"this model is not included in your free
usage…"* — Freezmo detects that (HTTP 402) and says so instead of pretending the key is broken.

### Mode 3 — one key for the whole server

```bash
OLLAMA_AUTH=server
OLLAMA_BASE_URL=https://ollama.com
OLLAMA_API_KEY=your_key_here
```

The key stays in `.env.local` (gitignored) and is never sent to the browser. Requests from any
device use it.

#### Installing without root (user-space)

The official installer needs root. If there is no `sudo` on the machine (like the box Freezmo was
built on), Ollama can be installed entirely under your home directory:

```bash
cd ~ && mkdir -p .local/ollama && cd .local/ollama
# grab the tarball for your arch from https://github.com/ollama/ollama/releases/latest
# (ollama-linux-amd64.tar.zst) and extract it here, so you end up with
#   ~/.local/ollama/bin/ollama  and  ~/.local/ollama/lib/ollama/
# No zstd CLI on Debian? Stream it with Python's zstandard module instead of tar --zstd.

export PATH="$HOME/.local/ollama/bin:$PATH"   # add to ~/.profile too
ollama serve &                                 # daemon on 127.0.0.1:11434
ollama signin
ollama pull gemma4:31b-cloud && ollama pull gpt-oss:120b-cloud
```

On the development machine the daemon runs as a **systemd user service**
(`~/.config/systemd/user/ollama.service`):

```bash
systemctl --user status ollama      # is it up?
systemctl --user restart ollama     # restart it
journalctl --user -u ollama -f      # logs
```

If the user has lingering enabled (`loginctl show-user $USER | grep Linger`) the service also
starts at boot with nobody logged in; otherwise it starts when you log in. Use the system-wide
installer if you want a boot service without a login session.

### Changing models

Any model that your Ollama instance exposes works. Edit `.env.local`:

```bash
VISION_MODEL=<model used to transcribe the photos>
TEXT_MODEL=<model used to build activities and grade short answers>
```

Current cloud models that work well (verified against the Ollama cloud in October 2026):

| Purpose | Model | Free tier? | Notes |
| --- | --- | --- | --- |
| Vision (default) | `gemma4:31b-cloud` | ✅ | Native multimodal, 256K context, current generation |
| Text (default) | `gpt-oss:120b-cloud` | ✅ | OpenAI open-weights, excellent at strict JSON, quick |
| Text, light | `gpt-oss:20b-cloud` | ✅ | Smaller/faster, slightly weaker |
| Text, cheap | `nemotron-3-super:cloud` | ✅ | 120B MoE with 12B active, very inexpensive |
| Text, smallest | `nemotron-3-nano:30b-cloud` | ✅ | Lowest cost option |
| Text, faster | `glm-5.3-flash:cloud` | 💳 credits | 18B active, 1M context, very fast |
| Text, best quality | `kimi-k3:cloud` | 💳 credits | Strongest open-weight model, slowest/most expensive |
| Vision, larger | `mistral-large-3:675b`, `deepseek-v4.1-flash` | 💳 credits | Multimodal alternatives |

> The previously suggested `qwen3-vl:235b-cloud` has been retired. The current defaults —
> `gemma4:31b-cloud` (vision) and `gpt-oss:120b-cloud` (text) — are both free-tier friendly and
> were verified end-to-end on a real photo of notes. The full list is one click away in the
> settings dialog or at <https://ollama.com/search?c=cloud>.

If your vision model is also good at generation you can point both variables at the same model —
the two pipeline steps stay separate either way.

### Checking the connection

- **In the app:** click the ⚙️ button — it shows mode, base URL, API key status, latency and
  whether each configured model is available, with a hint for what to fix. On phones the sheet
  is simplified: a **Connection** card with one status row (dot + “Connected · 2 models ready”)
  and the key field, the raw health details live behind a **Details** expander, and the key can
  be removed from a small danger button at the very bottom.
- **From the shell:** `curl http://localhost:3207/api/health`
- **Directly against Ollama:** `curl http://localhost:11434/api/tags`

---

## Rate limits

Generation is expensive (one to two model calls per request), so the API routes are limited per
client IP with a sliding window. Everything is configurable in `.env.local`:

| Route | Default | Env var |
| --- | --- | --- |
| `POST /api/generate` | 12 per 5 minutes | `RATE_LIMIT_GENERATE` |
| `POST /api/homework` | 12 per 5 minutes | `RATE_LIMIT_HOMEWORK` |
| `POST /api/grade` | 40 per 5 minutes | `RATE_LIMIT_GRADE` |
| `GET /api/health` | 90 per 5 minutes | `RATE_LIMIT_HEALTH` |
| `POST/GET/DELETE /api/sync` | 60 per 5 minutes | `RATE_LIMIT_SYNC` |
| `GET/POST/DELETE /api/push`, `POST /api/push/test` | 30 per 5 minutes | `RATE_LIMIT_PUSH` |
| window for all of them | 5 minutes | `RATE_LIMIT_WINDOW_MS` |

When a limit is hit the route answers **429** with a `Retry-After` header and a friendly message
(“Too many requests — try again in 42s”); the UI shows that message and keeps the Retry button. The
client IP is taken from `x-forwarded-for` / `x-real-ip` when present (reverse proxy), otherwise all
local clients share one bucket.

Caveats, stated honestly: counters live **in memory**, so they reset on restart and are not shared
between multiple instances or Node workers. That is fine for a self-hosted single-instance app; if
you put Freezmo behind a reverse proxy, keep the proxy's own limits in place too.

Model names are normalised automatically: when the base URL points at `ollama.com`, Freezmo strips
the local routing suffix (`gemma4:31b-cloud` → `gemma4:31b`, `gpt-oss:120b-cloud` → `gpt-oss:120b`)
because the cloud API expects plain library names, while a local daemon wants the `-cloud` form.
The same `.env` therefore works in every mode.

## Running on your network / from your phone

The dev and start scripts already bind to `0.0.0.0` on port **3207**:

```bash
npm run dev     # next dev -H 0.0.0.0 -p 3207
npm start       # next start -H 0.0.0.0 -p 3207
```

1. Find your machine's LAN IP: `hostname -I` (Linux) or `ipconfig getifaddr en0` (macOS).
2. On your phone open `http://<your-lan-ip>:3207`.
3. Allow port 3207 through the firewall if needed
   (e.g. `sudo ufw allow 3207/tcp`, or the equivalent Windows rule).
4. Ollama only needs to be reachable from the Next.js server, not from the phone.

Notes for phones:

- **The camera button works over plain HTTP** because it uses `<input type="file" capture="environment">`,
  not `getUserMedia` (which would require HTTPS). Tapping **Camera** opens the phone's camera app
  and the photo comes back as a file.
- Clipboard paste works best on desktop; on mobile use the camera or photo picker.
- Add the page to your home screen for a full-screen, app-like experience.

### Keep it running as a service (systemd user service)

`deploy/freezmo.service` runs the production build under **systemd (user)**, so Freezmo comes back by
itself after a reboot and restarts if it ever crashes:

```bash
npm run build                                 # the service serves the built app
mkdir -p ~/.config/systemd/user
cp deploy/freezmo.service ~/.config/systemd/user/
systemctl --user daemon-reload
systemctl --user enable --now freezmo.service
loginctl enable-linger "$USER"                # start at boot without logging in
```

| Command | What it does |
| --- | --- |
| `systemctl --user status freezmo` | is it up? |
| `journalctl --user -u freezmo -f` | live logs |
| `systemctl --user restart freezmo` | after a rebuild |
| `systemctl --user stop freezmo` | stop it |

It binds `0.0.0.0:3207` exactly like `npm start` and reads `.env.local` from the project directory.
The unit refuses to start without `.next/BUILD_ID`, so run `npm run build` before enabling it — and
again after pulling changes.

Because the build and the running server share `.next/`, stop the service before a manual rebuild:

```bash
systemctl --user stop freezmo && npm run build && systemctl --user start freezmo
```

---

## Folders

Decks are organised into folders — the same way you'd file paper notes.

- **Unorganized** is where every deck starts. It is virtual: it simply means "no folder yet".
- Create a folder from the library's folder bar (**New folder**) or from the create screen's
  **Freeze into folder** row. Names are unique, case-insensitive, and can be renamed later.
- **Freezing a deck into a folder:** pick the folder before generating (create screen) or with the
  folder row on the create screen; or use a deck's **⋯ menu → Folder** chips afterwards. The library
  shows which folder each deck is in, and groups the list by folder.
- **Filtering:** the folder bar filters the library to one folder; *All decks* shows every folder as
  its own section, Unorganized last, with per-folder counts on each chip.
- **Deleting a folder never deletes decks** — they move back to Unorganized. The confirmation says
  exactly how many decks will be re-homed.
- Folders live beside the decks in `localStorage` (`freezmo.folders.v1`), so they are per-browser
  and need no account. Exporting a deck records its folder name, and importing recreates or reuses
  that folder.

## Install as an app (PWA)

Freezmo ships as an installable Progressive Web App with iOS in mind.

Phones and tablets get an **"Install the app" bottom sheet** about a second after load (never on
desktop, never when already installed, and at most once per 7 days after a dismissal). It is a
native-feeling sheet with the Freezmo card, numbered steps and chips for the exact buttons to tap,
plus an accent confirmation pill. Close it with the X, the backdrop, Escape, or a swipe down — the
site keeps working normally. On iOS the steps adapt to the browser (Safari, Chrome, in-app), and
on Android Chrome a captured `beforeinstallprompt` turns into a real **Install** button. The sheet
can be reopened any time from **Settings → Install app** (mobile only).

It launches full-screen in standalone mode (no browser chrome), respects the notch/home-indicator
safe areas, and has an iOS-style bottom tab bar (Library · New deck · Settings) with sheet-style
dialogs. Android Chrome also offers "Install app" from the ⋮ menu; Freezmo works offline for the
parts that don't need a model.

What's included:

| Piece | Detail |
| --- | --- |
| `app/manifest.ts` | `id`, `display: standalone`, portrait, theme/background colours, `any` + `maskable` + `monochrome` icons, three app shortcuts (New deck, Make my homework, Library) and a **share target** (text/URL via GET, files via POST) |
| Icons | 192/512 px, a maskable 512 px icon, a monochrome SVG and 180/167/152 px `apple-touch-icon`s, all rendered from `assets/app-icon-source.jpeg` |
| iOS meta | `apple-mobile-web-app-capable`, `-title`, `-status-bar-style`, `viewport-fit=cover`, plus **startup images** for the common iPhone sizes so launch has no white flash |
| Service worker | `public/sw.js`, **production only**: cached app shell, stale-while-revalidate for static assets, network-first navigations with an `/offline` fallback. `/api/*` is never cached |
| Offline page | `/offline` — "your decks are still here, reconnect to generate" |
| Safe areas | `pb-safe` / `pt-safe` utilities plus `pb-tabbar` so nothing hides behind the tab bar |
| Share target | `/share` chooser (New deck / Make my homework); POSTed files wait in a short-lived in-memory store, are handed to the wizard through `sessionStorage`, and are never written to disk |

The icons are generated by `scripts/make-icons.mjs` from `assets/app-icon-source.jpeg` (headless
Chromium); it is a one-off tool and is not part of the app's dependencies. It also writes
`app/favicon.ico`, the Next.js file convention for the browser tab.

## Security notes

An honest review of what Freezmo does and does not defend against. It is a single-user,
self-hosted study app with no accounts, no database and no server-side state.

**What is hardened**

- **No secrets on the client.** The API key lives only in the browser's `localStorage` and travels
  in the `x-ollama-key` header per request. Route handlers use it for that one call and discard it —
  no disk, no log, no cookie, no environment write. Verified by grepping the whole project and the
  production `.next` output for a test key, and by restarting the server (which remembers nothing).
- **No server-side injection surface.** The Ollama endpoint and model names come only from the
  server's `.env`; the client cannot point the server at another host. Model output is validated with
  zod and rendered as text — there is no `dangerouslySetInnerHTML` except two static inline scripts
  (the pre-paint theme choice and the `beforeinstallprompt` capture), so a deck cannot inject markup
  or script (React escapes everything).
- **Key-header sanitisation.** Keys from the client are stripped of control characters/whitespace
  and capped at 512 chars before they are used in an outbound header, so a crafted key cannot inject
  headers. Verified with a raw-socket CRLF attempt.
- **Cross-origin requests are refused** on `/api/generate` and `/api/grade` (`Origin` must match the
  host), so a random website in your browser cannot make your Freezmo spend your rate limit or, in
  `server` auth mode, your credits. Origin-less clients (curl) still work.
- **Body-size limits** (32 MB for generation, 64 KB for grading) are rejected with 413 before any
  parsing, on top of the zod limits on image count, text length and field sizes.
- **Rate limiting** per client IP; see [Rate limits](#rate-limits). Auth is checked *before* parsing
  request bodies, so unauthenticated traffic costs almost nothing.
- **No CSRF surface**: no cookies, no sessions, no server-side mutations.
- **Prompt injection is low impact by design.** Your notes could contain text that tries to
  manipulate the model, but the model can only return a JSON deck (validated per activity, dropped if
  invalid) — it has no tools, no file access and no network access beyond the model call.

**Known limitations (by design)**

- The key travels from your browser to your own Freezmo server, so on an untrusted network it needs
  HTTPS to stay private. On a plain-HTTP LAN someone sniffing traffic could read it, along with your
  notes.
- Anything stored in `localStorage` is readable by JavaScript on the same origin. Freezmo has no XSS
  vector today, but that is the standard risk of browser-stored credentials.
- Rate limiting trusts `x-forwarded-for` when present (correct behind a proxy, spoofable when
  exposed directly) and keeps counters in memory: single instance only, reset on restart.
- Ollama cloud usage is billed to whoever's key is used, so treat a shared Freezmo URL as shared key
  access in `server` mode.
- No accounts means no per-user isolation: anyone who can reach the URL can use the app (and, in
  `user-key` mode, only with their own key).

## Supported input formats

Everything is parsed **client-side**, so documents are never uploaded — only the extracted text and
page images are sent to `/api/generate`.

| Format | What Freezmo reads | Sent to the model as |
| --- | --- | --- |
| JPG / PNG / WEBP / HEIC / GIF | the photo itself, resized to 1600 px JPEG | images (vision model) |
| **PDF, text layer** | text of every page (up to 80 pages) | text |
| **PDF, scanned / image-only** | pages with little or no text are rendered to images | images (vision model) |
| **DOCX** | document text + embedded images | text + images |
| **PPTX** | slide text + speaker notes + slide images | text + images |
| **ODT / ODP / ODS** | text from the OpenDocument `content.xml` | text |
| TXT / MD / CSV / TSV / LOG | the file's text | text |

Limits and behaviour worth knowing:

- up to 6 documents and 8 photos per deck, 40 MB per document, 20 MB per photo
- at most 12 images are sent (photos, rendered scanned pages and images embedded in documents)
- each document is capped at 60 000 characters and the merged text at 100 000; longer documents show
  a “truncated” note in the UI
- the activity generator reads up to 48 000 characters of notes per deck — plenty for lecture notes,
  but a whole book will only be sampled
- password-protected or corrupted files report a clear error on their card and can be removed

## How it works

```
 photos + text                                   /api/generate
 ─────────────┐
              ▼
   ┌──────────────────────────┐   step 1 (if images)   ┌───────────────────────────┐
   │ browser: resize/compress │ ─────────────────────► │ VISION_MODEL              │
   │ max 1600px JPEG data URL │                        │ transcribe + extract      │
   └──────────────────────────┘                        │ notes/concepts/formulas   │
              │                                        └────────────┬──────────────┘
              │ NDJSON progress stream                              │ clean structured text
              ▼                                                     ▼
   ┌──────────────────────────┐                        ┌───────────────────────────┐
   │ browser: study feed      │ ◄───────────────────── │ TEXT_MODEL                │
   │ JSON validated by zod    │   deck JSON            │ design 8–15 activities    │
   └──────────────────────────┘                        └───────────────────────────┘
```

- The prompts live in [`lib/prompts.ts`](lib/prompts.ts). They instruct the model to use **only the
  student's notes**, never invent facts, vary the activity types, write a short explanation for each
  activity and answer with JSON only.
- Every response is parsed (markdown ``` fences stripped), validated with **zod**
  ([`lib/schemas.ts`](lib/schemas.ts)) and — if validation fails — automatically retried **once**
  with the validation error fed back to the model (`lib/ai.ts`).
- Individual broken activities are dropped rather than failing the whole deck; if fewer than half
  the requested activities survive, the step is retried too.
- Requests use `stream: false` with per-request timeouts and a hard overall deadline
  (two sequential model calls). Errors surface as friendly messages
  ("Ollama isn't reachable, check your settings") with a retry button.
- `POST /api/generate` answers with newline-delimited JSON (`stage` / `deck` / `error` events) so the
  UI can show real progress between the vision and generation steps.

---

## Project structure

```
app/
  layout.tsx                 root layout, iOS meta tags + theme bootstrap script
  manifest.ts                web app manifest (installable PWA)
  offline/page.tsx           offline fallback served by the service worker
  globals.css                Tailwind v4 theme, frosty palette, animations, reduced-motion
  page.tsx                   library ("Your icebox")
  create/page.tsx            upload screen
  deck/[id]/page.tsx         study feed for a saved deck
  homework/page.tsx          “Make my homework” (assignment in, homework or guide out)
  api/generate/route.ts      images/text in → NDJSON progress → deck JSON out
  api/homework/route.ts      assignment in → NDJSON progress → homework/guide JSON out
  api/grade/route.ts         short-answer grading
  api/health/route.ts        Ollama reachability + model availability
components/
  activities/                one component per activity type + shared shell
    Flashcard.tsx MultipleChoice.tsx TrueFalse.tsx FillBlank.tsx
    Matching.tsx Ordering.tsx ShortAnswer.tsx shared.tsx index.tsx
  homework/                make-my-homework screens (input, result, guide feed, history)
  UploadScreen.tsx StudyFeed.tsx ResultsScreen.tsx DeckCard.tsx ApiKeyGate.tsx
  InstallSheet.tsx TabBar.tsx ServiceWorkerRegistrar.tsx FolderBar.tsx
  LibraryScreen.tsx SettingsDialog.tsx AppHeader.tsx ThemeToggle.tsx icons.tsx ui.tsx
lib/
  ollama.ts        server-only HTTP client (timeouts, auth, error mapping)
  prompts.ts       the vision, generation, grading, homework and repair prompts
  ai.ts            every pipeline step with zod validation + retry
  schemas.ts       zod schemas and shared types
  config.ts        env config, cloud/direct model-name normalisation
  documents.ts     client-side PDF/DOCX/PPTX/ODT/text extraction
  folders.ts       folder library (create/rename/delete) in localStorage
  install.ts       install-prompt platform/browser detection + 7-day dismissal
  settings.ts      browser-side settings (the user's API key) + auth headers
  use-health.ts    client hook for /api/health, re-runs when the key changes
  rate-limit.ts    in-memory sliding-window limiter for the API routes
  http-guard.ts    same-origin check, body-size cap, API-key sanitiser
  language.ts      script/language checks that catch translated transcriptions
  ui-events.ts     tiny event bus (any screen can open the settings dialog)
  storage.ts       localStorage deck library, import/export
  homework.ts      localStorage homework results + solution assembly
  use-notes-intake.ts  shared client-side photo/document intake hook
  clipboard.ts     copy helper with a non-secure-context fallback
  image.ts         client-side validation, resize and compression
  client-api.ts    browser client for the API routes (NDJSON reader)
  xp.ts utils.ts deck-ops.ts confetti.ts
public/
  sw.js                  service worker (production only)
  icons/                 PWA + iOS icons and splash screens
assets/
  app-icon-source.jpeg   master artwork the icons are rendered from
deploy/
  freezmo.service       systemd user unit (auto-start at boot)
scripts/
  copy-pdf-worker.mjs   copies the pdf.js worker to /public (runs on predev/prebuild)
  make-icons.mjs        regenerates the PWA/iOS icons from the master (one-off tool)
```

---

## API routes

| Route | Body | Returns |
| --- | --- | --- |
| `POST /api/generate` | `{ images?: string[], text?, difficulty, count?, focus?, language?, mode?, existing? }` | NDJSON stream: `{type:"stage"}`, `{type:"deck",deck,meta}`, `{type:"error"}` |
| `POST /api/homework` | `{ mode: "make" \| "guide", images?: string[], text?, language? }` | NDJSON stream: `{type:"stage"}`, `{type:"homework",homework,meta}`, `{type:"error"}` |
| `POST /api/grade` | `{ question, referenceAnswer, keyPoints, userAnswer, language? }` | `{ correct, score, feedback, missing }` |
| `GET /api/health` | – | `{ ok, reachable, mode, baseUrl, hasApiKey, vision, text, latencyMs, modelCount, error }` |
| `POST /api/sync` | `{ id, envelope }` (opaque AES-GCM blob) | `{ updatedAt }` — 413 over `SYNC_MAX_BYTES`, 507 over `SYNC_TOTAL_BYTES` |
| `GET /api/sync?id=` | – | `{ updatedAt, envelope }` or 404 |
| `DELETE /api/sync?id=` | – | `{ ok: true }` (revokes the synced copy) |
| `GET /api/push` | – | `{ enabled, publicKey? }` — reminders are hidden when `enabled` is false |
| `POST /api/push` | `{ endpoint, keys }` | `{ ok, count }` (stored server-side, endpoint + keys only) |
| `DELETE /api/push?endpoint=` | – | `{ ok, count }` |
| `POST /api/push/test` | `{ endpoint }` | `{ ok: true }` or 502 when the push service refuses |

All four routes accept an optional **`x-ollama-key`** header (the browser's own key; required in
`user-key` auth mode). Missing keys answer **401** with `kind: "needs_key"`, a rejected key answers
`kind: "auth"` (or `kind: "no_credits"` for HTTP 402), and exceeding a rate limit answers **429**
with `Retry-After`. Keys are used for the single request and discarded.

Images are sent as base64 data URLs; the server strips the prefix before handing them to Ollama.
Uploads are validated for type (photos and the document formats above), count (max 8 photos,
6 documents, 12 images) and size (max ~8 MB per image after compression, 40 MB per document) and the
client compresses aggressively, so a typical upload is 1–3 MB. `language` is optional wherever it
appears: the vision step fills it in automatically, and the UI passes the stored deck language for
grading, regeneration and “add more” (and the assignment language for homework).

---

## Scripts

| Script | What it does |
| --- | --- |
| `npm run dev` | `next dev -H 0.0.0.0 -p 3207` |
| `npm run build` | production build (type-check + lint) |
| `npm start` | `next start -H 0.0.0.0 -p 3207` |
| `npm run lint` | ESLint |
| `node scripts/make-icons.mjs` | regenerate the PWA/iOS icons (needs a Playwright Chromium) |
| `node scripts/copy-pdf-worker.mjs` | copy the pdf.js worker (also runs on predev/prebuild) |

---

## Data, storage and privacy

- Decks live in **`localStorage`** under `freezmo.decks.v1`, folders under `freezmo.folders.v1` (no
  accounts, no server database).
  Stored per deck: title, subject, summary, language, difficulty, the extracted **source text**,
  activities, play count and best score.
- **Original files are never stored or uploaded** — photos and documents are parsed in the browser,
  and only the extracted text (plus page images for the vision model) is sent to your Ollama
  endpoint. That is why *regenerate* and *add more activities* work from the source text rather than
  the original files. Imported decks that contain no source text can't be regenerated; the UI says so.
- Documents are parsed locally by `pdfjs-dist` (PDF), `mammoth` (DOCX), `jszip` (PPTX/OpenDocument)
  and the browser's own `File.text()` — nothing is uploaded for parsing.
- Images and rendered PDF pages are sent to whatever Ollama endpoint you configure. In local-daemon
  mode they go to your machine first; in direct-cloud mode they are processed by Ollama's cloud.
- In the default `user-key` mode your Ollama API key is also kept in `localStorage` (key
  `freezmo.settings.v1`) and sent with each API call so the server can forward it to Ollama. It is
  never written to the server, a log, a cookie or the environment — see
  [Ollama setup](#ollama-setup) for the full story.
- Clearing browser data deletes the library and the saved key. Use **Export all data**
  (Settings → Data & backup) for anything you want to keep; the file never contains the API key.
- **Opt-in sync** (`freezmo.sync.v1` + a non-extractable `CryptoKey` in IndexedDB) uploads an
  AES-GCM envelope to `POST /api/sync`. The server writes one small JSON file per sync ID under
  `SYNC_DIR` (default `.freezmo/sync`), can't decrypt it, and never receives the passphrase or the
  key. Deleting the synced copy is one button in Settings (and works even on a device that can't
  unlock the data).
- **Answer history lives in IndexedDB** (`freezmo-learning`, versioned stores `answers` + `srs`),
  because an event log would eventually fill `localStorage`; the log is capped at 20 000 answers
  (oldest pruned). Backups and sync include it, so progress survives a device move. Push
  subscriptions are the only reminder state on the server (`PUSH_DIR`, endpoint + keys only) and
  are removed when you turn reminders off — or automatically when the push service reports them
  gone.

---

## Troubleshooting

| Symptom | Fix |
| --- | --- |
| “Ollama isn't reachable at http://localhost:11434” | Start the daemon (`ollama serve`, or `systemctl --user start ollama` for a user-space install), or fix `OLLAMA_BASE_URL`. Check `curl http://localhost:11434/api/tags`. |
| A document card is stuck on “Reading page …” | The pdf.js worker may be missing: run `npm run dev`/`npm run build` (they copy it to `public/pdf.worker.min.mjs`) or `node scripts/copy-pdf-worker.mjs` manually. |
| PDF uploaded but no activities about its content | The PDF is probably image-only (a scan). Freezmo renders such pages and sends them to the vision model — check the card note (“N scanned pages were turned into images”); if it says “No readable text”, the scan may be too low quality. |
| Deck came back in English even though the notes are not | Make sure both model calls succeed (a failed vision step falls back to raw text). The prompts force the notes' language; if you still see translation, switch `TEXT_MODEL` to a stronger instruction-follower such as `gpt-oss:120b-cloud`. |
| “You've run out of your free monthly Ollama usage” | The account's free monthly usage is used up — this is not a short-term rate limit. Upgrade the account at `ollama.com/settings`, or create a new account and paste its key in Settings (the button jumps straight to the field). “Ollama is busy” is the short-term variant: just press Retry. |
| Reminders are missing from Settings | They only appear when `VAPID_PUBLIC_KEY` and `VAPID_PRIVATE_KEY` are set in `.env.local` (generate with `npx web-push generate-vapid-keys`). On iPhone, add Freezmo to the Home Screen first — Safari tabs can't receive push. |
| “Add your Ollama API key first” | Bring-your-own-key mode is active. Paste a key from <https://ollama.com/settings/keys> on the key gate (or in the ⚙️ dialog) — it is stored only in your browser. |
| “Ollama rejected this API key” | The key is invalid or revoked. Create a new one and paste it again; the check uses a real 1-token request, so a green tick means it truly works. |
| “this model is not included in your free usage” | The key works, but the model is outside your plan. Use one of the ✅ models in the table above, or add credits at <https://ollama.com/settings>. |
| “Too many requests — try again in Ns” | You hit a rate limit (12 decks / 40 grades per 5 min by default). Wait, or raise `RATE_LIMIT_*` in `.env.local`. |
| “set to OLLAMA_AUTH=local but points at https://ollama.com” | Fix the combination: use `OLLAMA_AUTH=user-key`/`server` for the cloud URL, or point `OLLAMA_BASE_URL` at `http://localhost:11434`. |
| Settings dialog says a model is “not found” | Local daemon: pull it once — `ollama pull gemma4:31b-cloud` (cloud pulls are just manifests). Direct cloud: check the model name and that your key is valid. |
| 401/403 from `https://ollama.com` | Create a key at <https://ollama.com/settings/keys> and put it in `OLLAMA_API_KEY` (no quotes), then restart. |
| Daemon logs / it keeps dying | User-space install: `journalctl --user -u ollama -f`. Manual start: `~/.local/ollama/bin/ollama serve`. |
| Generation times out | Use fewer/smaller photos, choose a faster `TEXT_MODEL` (e.g. `gpt-oss:20b-cloud`), or raise `OLLAMA_TIMEOUT_MS`. |
| Responses are slow | Thinking models spend tokens on reasoning. Set `OLLAMA_THINK=false` to send `think: false`, and/or use a smaller model. |
| “did not match the expected format” | Freezmo retried once automatically. If it still fails, the model is poor at JSON — switch to a stronger `TEXT_MODEL` (e.g. `gpt-oss:120b-cloud`). |
| Blank/boxed icons on Linux | The app chrome uses inline SVG, but activity badges use emoji. Install an emoji font (`fonts-noto-color-emoji`). |
| Port 3207 already in use | `lsof -i :3207` and stop the other process, or change the port in both scripts in `package.json`. |
| Camera button missing on mobile | It's in the *Add your notes* card; some in-app browsers hide file inputs — open the page in Chrome/Safari directly. |
| Hydration warning in dev | Usually a stale dev artifact: hard-reload. Decks load in `useEffect`/`useSyncExternalStore`, so no library content is server-rendered. |

---

## Decisions and notes

Things I chose while building, with the reasoning:

1. **Defaults follow the current Ollama catalogue and the free tier.** The suggested
   `qwen3-vl:235b-cloud` has been retired, so the defaults are `gemma4:31b-cloud` (vision) and
   `gpt-oss:120b-cloud` (text/JSON/grading) — both verified as included in the free plan on a real
   photo of notes. Paid/credit models such as `glm-5.3-flash:cloud` and `kimi-k3:cloud` are
   documented as alternatives.
2. **One `.env` for both modes.** Direct-cloud names differ from daemon names (`gemma4:31b` vs
   `gemma4:31b-cloud`), so `lib/config.ts` strips the `-cloud` / `:cloud` suffix automatically when
   `OLLAMA_BASE_URL` points at `ollama.com`.
3. **Two separable AI steps.** Photos always go through `VISION_MODEL` for transcription/extraction;
   the structured text then goes to `TEXT_MODEL`. Pointing both variables at one model works too.
   Text-only requests skip the vision step entirely.
4. **NDJSON progress stream instead of a single long request.** The two model calls are sequential
   and slow, so `/api/generate` streams `stage` events; the UI shows real stages rather than a fake
   timer. `stream: false` is still used for each Ollama call for simplicity and reliability.
5. **zod + one repair retry, plus per-activity salvage.** A single bad activity shouldn't cost you
   the whole deck: valid activities are kept, and the repair round is only used when too few survive.
6. **Flashcards count as "correct" via self-assessment** (I knew it / Not yet) so that scoring, XP
   and "retry missed ones" apply to every activity type.
7. **Fill-in-the-blank is graded locally** (case/punctuation-insensitive, one typo forgiven,
   `/` alternatives in the answer) — no round trip needed. Only short answers call `/api/grade`.
8. **Matching requires a perfect match for full XP**, otherwise it's marked as missed with an
   explanation of how many wrong attempts you made.
9. **Source text is stored with each deck** so *regenerate* and *add more* work without keeping the
   original photos (storage/privacy win). Imported decks have no source text, so those two actions
   are disabled for them.
10. **XP is assigned server-side** (easy 10 / medium 15 / hard 20, +5 for matching, ordering and
    short answer) so the model can't invent inconsistent rewards.
11. **Documents are parsed in the browser, not on the server.** pdf.js, mammoth and jszip run
    client-side, so the raw file never leaves the device and the API stays a thin text/image pipe.
    Scanned PDF pages are rendered to JPEG for the vision model, while PDFs with a text layer skip
    the vision step entirely (faster and exact).
12. **The notes' language is detected once and then carried everywhere.** The vision step reports a
    `language` field, the deck stores it, and generation, grading, regenerate and add-more all
    receive it explicitly — plus “never translate” rules in every prompt. Verified with Czech
    notes across all three input paths (text PDF, scanned PDF, DOCX + PPTX).
13. **Keys are per browser and never stored server-side.** Freezmo defaults to
    `OLLAMA_AUTH=user-key`: the key is typed into the UI, kept in `localStorage` and sent in the
    `x-ollama-key` header, and the route handlers use it for that request only — nothing is written
    to disk, logs, cookies or the environment (verified by grepping the whole project for a test key
    and by restarting the server). `server` and `local` modes remain available by env var.
14. **Key verification uses a 1-token chat probe, cached for 5 minutes.** Model listing on
    `ollama.com` is public, so a bogus key would look valid; only a real authenticated request can
    tell. HTTP 402 (“not included in your free usage”) is reported as a *plan* problem rather than a
    broken key.
15. **Rate limits are per client IP, in memory, and generous by default** (12 decks / 5 min, 40
    grades / 5 min). They exist to stop runaway loops and accidental abuse, not to be a security
    boundary — the README says so, and the counters are intentionally not persisted.
16. **A misconfiguration is caught early:** `OLLAMA_AUTH=local` combined with `https://ollama.com`
    returns an explanatory error instead of a confusing 401.
17. **Folders are a first-class, non-destructive idea.** `UNORGANIZED_ID` is virtual (decks simply
    have no `folderId`), deleting a folder re-homes its decks instead of deleting them, and folder
    names travel in exports so an imported deck lands where it came from. 13 browser checks cover
    create → freeze → move → rename → delete → reload → import.
18. **The visual language is frosted ice glass.** Glacier cyan to ice blue (`#38bdf8` → `#0ea5e9`)
    is the accent for focus rings, progress bars and selected states; the primary CTA is an icy
    gradient (deep blue in light, white-to-`#bfe3ff` in dark). The background is a fixed ice scene;
    the sidebar, cards, chrome, sheets and gate are translucent glass with a bright rim and a soft
    blue shadow. Colour appears in activity tints and semantic feedback only — pretty, but still
    readable and quiet.
19. **Custom CSS lives in `@layer components`, and glass uses Tailwind's backdrop utilities.**
    Two build-level traps, both found by looking at real screenshots: unlayered rules beat Tailwind
    utilities (which silently broke `fixed` on the feed), and a hand-written `backdrop-filter` gets
    minified down to `-webkit-` only — which painted no blur at all. `@apply backdrop-blur-*`
    emits both properties correctly.
20. **There is no demo/sample deck.** Every activity comes from the user's own notes; the empty
    state points at the create flow and Settings instead of shipping fake content. Browser tests seed
    a fixture deck into `localStorage` rather than relying on app code.
21. **Dark mode is token-driven, and contrast is audited on glass.** Text colours come from
    `--text` / `--text-muted` / `--text-subtle` (never hardcoded), and a `contrast.mjs` audit checks
    every pairing at WCAG AA against the *effective* frosted background — currently **18/18 pairs
    pass** (e.g. dark secondary `#b3c4e0` on glass `#1c2535` = 10:1, white on the light CTA
    mid-gradient `#1a5fd0` = 5.6:1). Difficulty colours were darkened until they cleared 4.5:1 on
    their pills.
    This was a real bug: an earlier edit silently failed, so `.dark` never overrode `--text`, leaving
    near-black text on a dark page.
22. **The dashboard is one inset glass rail plus glass cards.** The sidebar is a single tall
    rounded glass panel inset from the viewport edges, so the ice scene shows around it; deck cards
    are 24px-radius glass panels with a secondary Study CTA and quiet metadata. Headings are
    semibold with tighter tracking. Nested glass (chips, inputs) is more opaque but never adds a
    second blur layer.
23. **One fixed ice scene instead of per-page blobs.** The decorative background used to be
    rendered inside the content column, so on wide screens it was clipped into a visible hard edge.
    It now lives in a single `position: fixed` layer (`.ice-scene`, `z-index: -1`, pointer-events
    none): base gradient, four drifting glacier blobs, five glossy ice orbs and an SVG-noise grain.
    `prefers-reduced-motion` stops the drift.
24. **The UI was deliberately made quieter.** One accent colour (`accent-*`), a desaturated
    `frost-*` scale, hairline borders and flat surfaces replaced the saturated gradients and the
    seven-colour activity badges. Semantic colours (green/amber/red) survive only where they carry
    meaning: correct/wrong feedback, key status, rate limits.
25. **PWA instead of a native wrapper.** A manifest, iOS meta tags, generated icons, a
    production-only service worker, an offline page and a standalone-aware layout give the
    install-to-home-screen experience without adding a runtime dependency — and the app still works
    as a plain website.
26. **The API is defended like a LAN service.** Cross-origin POSTs are refused, bodies are capped
    before parsing, keys are sanitised before they reach a header, and auth is checked before any
    body work. See [Security notes](#security-notes) for the full list and the known limitations.
27. **A language guard repairs accidentally translated transcriptions.** `TEXT_MODEL` (`gpt-oss:120b`)
    is the strongest multilingual model in the free tier, so when the transcription check
    (`lib/language.ts`: expected script vs. actual script, distinctive diacritics, English stopword
    density) flags a mismatch, the text model rewrites the JSON back into the original language
    before generation. Verified both ways: it fires on a synthetic English-but-declared-Czech
    transcription and never fires on real Czech notes (no extra calls, no added latency).
28. **The first screen is the API-key gate.** In `user-key` mode a browser without a key gets a
    full-screen, monochrome gate instead of the dashboard: one masked input, one Continue button,
    and a "?" sheet with the steps to a free key. The gate reuses the cached 1-token probe through
    `/api/health`, so an invalid key and an unreachable Ollama are worded differently. The old
    dashboard banner is gone; key management stays in Settings, and removing the key brings the
    gate back. The gate covers `/`, `/create` and deck study, but never `/offline`.
29. **The install prompt is a teaching sheet, not a nag.** It appears once, phones/tablets only,
    a second after load, and never in standalone mode; dismissing it silences it for 7 days. It
    detects iOS vs Android and Safari vs Chrome vs an in-app browser so step 1 always matches the
    device, uses Chrome's deferred `beforeinstallprompt` for a one-tap install where available, and
    stays reachable from Settings. It is mounted in the root layout, so it can appear over any
    screen — including the key gate — without blocking the page underneath.
30. **Phones use touch-action, not a zoom lock.** The viewport allows pinch-zoom (accessibility),
    and double-tap zoom is disabled by `touch-action: manipulation` on the UI chrome instead. A
    mobile-only rule keeps every input and textarea at 16px so iOS Safari's focus auto-zoom never
    fires (iOS ignores `user-scalable=no` for that anyway). Desktop keeps the designed 12–14px
    field sizes.
31. **The app icon drives the palette.** The navy rounded-square artwork in
    `assets/app-icon-source.jpeg` is the source of truth: `frost-*` is navy-tinted, the accent is
    glacier cyan, the ice scene uses the artwork's blues, the primary CTA is an icy gradient, and
    every icon/splash/favicon is rendered from it by `scripts/make-icons.mjs`. The sidebar, header, key gate, empty state and install sheet all show
    the real artwork instead of the old monochrome snowflake tile.
32. **The ice scene was profiled, and the blur moved off the animated layer.** A mid-range phone
    viewport with 4x CPU throttling showed the drifting blobs were the only expensive part: a
    `filter: blur(100px)` on a huge element that is also being transformed forces a
    re-rasterisation every frame (150ms vs 33ms per frame in a software renderer). The blobs are now
    soft radial gradients with no filter — visually the same, 4-5x cheaper — phones get two blobs
    instead of four and a 16px (instead of 24px) glass blur, and nested glass never blurs. Result:
    60fps idle and ~17ms median frames while scrolling under 4x throttle.
33. **Interface copy lives in two flat dictionaries, not in a framework.** `lib/i18n-dict.ts` holds
    the `en` and `cs` tables plus `translate()` / `translatePlural()`; `lib/i18n.ts` adds the browser
    store (`freezmo.locale.v1`), the `useI18n()` hook and the `x-freezmo-locale` header that API
    routes read to answer in the same language. English is the default and the fallback for any
    missing key. Czech uses the real plural rules (1 sada / 2–4 sady / 5+ sad). Crucially, the hook's
    `t` is *bound to the locale React is rendering with* — the first client render matches the
    server HTML, then re-renders in the stored language; using the module-level `t` during render
    instead caused a hydration mismatch that silently dropped the `dark` class. Module-level `t` is
    only for event handlers and non-React helpers (documents, folders, API errors). The notes' own
    language is untouched by this — decks still come back in the language of your notes.

34. **The mobile pass was a layering *perception* fix plus a real contrast debt.** The ice orbs were
    never above the content — the scene is a fixed `pointer-events:none` layer at `z-index:-1`
    (verified with `elementFromPoint`), but it shines through the translucent page and glass. Phones
    now get a thinner scene (lower blob/orb opacity, orbs tucked to the edges, the bottom-right orb
    moved out from under the tab bar) and the tab bar paints `color-mix(page 84%)` so its labels keep
    their contrast. Helper text moved onto the tokens (`--text-subtle` is #9db1d0 in dark: 8.6:1 on
    the page, 7.2:1 on dark glass) and disabled buttons are a visible muted chip (`.btn-disabled`)
    instead of `opacity-40`. Buttons share one ice gradient in both themes — which also exposed that
    the danger/success variants never showed their colour, because the primary `background-image`
    painted over `!bg-rose-600` (`bg-none` now strips it). Light mode got a cool card rim instead of
    white-on-white. The settings sheet swipes away like the install sheet (drag only while the body
    is scrolled to the top), its body scrolls to the true bottom with a fading scroll cue, and the
    API-key note is split into a short privacy line plus a collapsible local-daemon tip. axe-core
    reports every glass surface as “incomplete”, so contrast is verified by a pixel-sampled script
    (hide the text → screenshot → worst-case background luminance per glyph rect): 0 runs below AA
    across library and settings, both themes, both languages.

35. **“Make my homework” reuses the study pipeline instead of growing its own.** The intake is the
    same client-side parsing as `/create` (lib/documents + lib/image, wrapped in `useNotesIntake`),
    the photos go through the same `extractNotes` vision step and language guard, and the guide's
    checkpoints are ordinary activity JSON rendered by the existing components — just a
    `checkpoint` field on a step. The route streams NDJSON like `/api/generate` and has its own
    rate limit. Two things are deliberately different: the finished answer and the guide are
    written in the *assignment's* language (the interface language never leaks in), and the final
    solution is assembled on the client from the step answers instead of asking the model for a
    second copy. Result records store the assignment text — the vision transcription when photos
    were used — so “Make it again” works without storing a single original file.

36. **The mobile declutter pass reshapes, it doesn't fork.** Phones (≤639px) get a 3-step deck
    flow and a 2-step homework flow that share the exact state and handlers with the desktop
    cards (one `UploadScreen` / one `HomeworkInput`, two layouts switched by `useIsPhone()`);
    desktop markup is untouched. Library cards collapse to title + one meta line + one
    description line (expand on tap) with the whole card tappable and a small Study pill, the
    stats line and folder row only appear once folders exist, and the settings sheet trades the
    health cards for a Connection status row plus a collapsed Details list. Decorative orbs were
    pushed further off the phone edges so they never glow under CTAs or cards.

37. **The animation pass is one shared language, and it stays off the desktop.** `lib/motion.ts`
    owns the spring presets (snappy / gentle / sheet), durations and variants; components import
    them instead of ad-hoc numbers. Press feedback is CSS (a spring-like cubic-bezier on
    transform) scoped to `≤639px / pointer: coarse`, so every control responds without
    per-component wiring. Sliding highlights use one `layoutId` per control. Route content
    animates on entrance only — the App Router unmounts the outgoing page, so exits are left to
    in-page `AnimatePresence` (list items, sheets). Only transform and opacity animate (plus the
    explicit expander heights); `prefers-reduced-motion` collapses motion to short fades.
    LazyMotion was skipped on purpose: the sliding highlights need layout animations (domMax),
    the same feature set the current `motion` import already pulls in. Verified with a
    4x-CPU-throttled mobile trace (no long tasks, CLS 0) and a reduced-motion run.

38. **Wizard chrome lives outside the animated tree.** The step name is the headline, the
    action bar is a flat full-width bar at the bottom (the tab bar hides inside the wizard),
    and the bar is rendered through a React portal to `<body>`. That last part is a real bug
    fix: the screen entrance animation puts a transform on the content wrapper, and a
    transform on an ancestor becomes the containing block for `position: fixed`, so the bar
    used to paint inside the content and jump to the viewport bottom a second later. It now
    only fades in, pinned to the bottom from its first frame — verified by sampling its
    position across the entrance (5 frames, 60–450ms) from the tab bar, the drawer and the
    empty state, at 360/390, both themes, both languages and with reduced motion.

39. **Native feel is layered onto the platform, never around it.** The Back gesture closes the
    topmost layer through a small history-entry stack (`lib/use-back-close.ts`): each layer pushes
    a same-URL entry, only the top of the stack reacts, and a layer closed by a navigation leaves
    its entry for the permanent listener to skip. Haptics are best-effort behind a Settings toggle
    (Vibration API; the hidden `<input switch>` tick on iOS, throttled); the wake lock is requested
    only while a study feed or guide is open and released on leave. Destructive-but-reversible
    actions (delete deck, remove file) became Undo toasts; irreversible ones keep their confirm.
    Wizard drafts and the last URL are per-browser; the share target hands POSTed files to the
    client through a ten-minute in-memory store so nothing touches disk. Verified by the native
    suite (35 checks: manifest/head/viewport, offline banner + disabled generate, share target GET
    and POST, back-gesture closing for drawer/sheet/wizard, undo toast, share fallback, tab
    re-tap, haptics persistence, draft restore) plus the six standing suites.

    **Needs a real device to verify** (emulation can't do these honestly): the iOS hidden-switch
    haptic tick, the Android/iOS **share target** entry in the system share sheet, the actual
    **wake lock** grant, the **startup images** on an installed iPhone, the iOS **edge-swipe**
    back gesture in standalone, and installability/rich-install prompts (Lighthouse covers the
    manifest side). Pull-to-refresh and the app badge were skipped on purpose — the Settings
    refresh icon already re-checks the connection, and there is no meaningful badge number.

40. **Backups are plain, sync is encrypted, and the key never leaves either.** The backup file is
    the same zod-validated shape the sync payload uses (`lib/backup.ts`), which is why the import
    preview can count added/replaced items without touching the key — the key is simply not part of
    the shape. Sync adds PBKDF2-SHA256 (310k iterations) → AES-GCM on top, keeps the derived key as
    a **non-extractable** `CryptoKey` in IndexedDB, and lets the server be a dumb blob store: it
    stamps `updatedAt` (the conflict clock), enforces `SYNC_MAX_BYTES` / `SYNC_TOTAL_BYTES` and
    writes atomically (temp file + rename). A device that lost its stored key can still *unlock*
    (passphrase re-derivation) or *revoke* (DELETE) the synced copy. Monthly-usage exhaustion and
    short-term throttling are told apart by inspecting the real 429 body
    (`classifyOllamaFailure`) and mapped to `usage_limit` / `throttled` kinds — the client renders
    the same localized message in every model flow, with a jump to the key field and a link to
    Ollama, and keeps the user's input so Retry works right after swapping the key. Verified by the
    phase-1 suite (38 checks, including the real route mapping against a stub Ollama returning a
    monthly-limit body, and a two-device sync round-trip).

41. **The learning log is an event log, so it lives in IndexedDB.** Decks and homework stay in
    `localStorage` (small, always loaded), but answers + SRS schedules go to a versioned
    `freezmo-learning` database with an in-memory mirror so React can read them synchronously via
    `useSyncExternalStore`; writes update the mirror first and persist asynchronously, and the log
    is capped at 20 000 answers. The schedule is deliberately simple (1 day → 3 days → interval ×
    ease; wrong = ten minutes, ease −0.2): predictable beats clever, and the mistakes set needs no
    storage at all — it is *the latest answer per activity being wrong*, so it clears itself the
    moment the activity is answered correctly. Review and exam sessions **freeze their item list at
    start** (a bug the phase-2 suite caught: answering a mistake removed it from the live list and
    collapsed the session mid-run). Push reminders are all-or-nothing: no VAPID keys → no UI, no
    endpoints, nothing to misconfigure; `web-push` is the one added server dependency and the daily
    send is an explicit cron/timer script. Verified by the phase-2 suite (42 checks: history and
    SRS shapes, the review/mistakes sessions, stats math, exam with timer and breakdowns, the
    VAPID-less hidden state and the configured subscribe/validate/test/delete path).

14. **`gpt-oss:120b` does all content work — but it cannot read images** (`this model does not
    support image input`), so `VISION_MODEL` has to stay a multimodal model (`gemma4:31b-cloud`).
    Text-only inputs — pasted text, PDFs with a text layer, DOCX/PPTX/ODT — never touch the vision
    model at all, so those decks are produced by `gpt-oss:120b` start to finish.
13. **No auth, no server storage.** Everything personal lives in `localStorage`; the only server
    state is the request in flight.
14. **`canvas-confetti` and `framer-motion` are the only UI dependencies.** Document parsing adds
    `pdfjs-dist`, `mammoth` and `jszip`, all dynamically imported (the `/create` page grew ~3 kB;
    the parsers load only when a document is added). Animations are skipped when
    `prefers-reduced-motion` is set.
15. **Tailwind v4 class-based dark mode** with a pre-paint script so there is no theme flash, and
    `suppressHydrationWarning` on `<html>`.
16. **Testing.** The pipeline was first tested against a mock Ollama HTTP server (including a
    deliberately invalid first response to exercise the repair path) with the UI driven by headless
    Chromium, then re-run against the real Ollama cloud. Current suites: 13/13 document extraction
    (one fixture per format, including a text PDF and a scanned PDF), 15/15 language preservation,
    24/24 activity/scoring/feed checks and 11/11 real-model browser checks.