Animelon's way of learning from video, from the person's own Jellyfin server: connected per device (Settings, or a studyset's Add material › Watch from Jellyfin) with a name and password or a Quick Connect code, over HTTPS only (plain HTTP only to a server on the same machine); the token stays in the system's keyring. Shows, films and videos tied to a studyset follow the person in their settings as the server's and the item's ids alone (settings schema 9), named by the server when shown. The Watch screen plays the video (video_player on Android, media_kit's libmpv on Linux and Windows) with the line in the studyset's front language cut into the dictionary's words with furigana, and the back language's line beneath; a word tapped pauses the video and becomes a card with the line and its translation as its first hint, tagged with the show. The video's words are listed, most frequent first. The sound is the track in the studyset's language, whichever the file marks default, and the menu switches it; the subtitles read are a whole track, never a forced one (which only covers what the sound doesn't say), and captions for the hard of hearing only without plain ones. The line and its translation take the video's width in a box of a fixed height, so the video keeps its size; in the dark theme the video's colours glow around it, as YouTube's ambient mode, and the words' panel takes the colour of the episode's picture under the pointer. A line is cut into words with one request: DictionaryEndpoint.withKeys looks up every stretch of it that may be a word, as it stands and as every word it may be a conjugation of, in the new dictionary_key table (one row per key, indexed; migration dictionary-keys adds the table and its index, nothing else), which the loader fills beside the entries. The instance gets the text of each line looked up and keeps none of it, as the Watch screen says. Linux builds need libmpv-dev, and the app links libmpv: the snap stages Ubuntu's libmpv2, makes the update-alternatives links for BLAS and LAPACK that ffmpeg's speech recognition needs (staging never runs install scripts), and removes what the GNOME runtime and core24 already hold, as older copies of cairo, pango and librsvg hid the runtime's from its GTK. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
158 lines
8.8 KiB
Markdown
158 lines
8.8 KiB
Markdown
# Halkyon Learn
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Halkyon Learn is for creating, sharing and collaborating on study material. It schedules
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flashcards with [FSRS](https://github.com/open-spaced-repetition) to strengthen
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retention, and organises study material together with the external references it draws
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on. It is offline-first: everything works on the device, without a connection. And the
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whole stack is transparent: the app, the server and everything needed to host an
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instance are published, so anyone can see how an instance works and run their own.
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- **Offline first.** Each device keeps its own database and syncs in the background
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(`serverpod_offline_sync`). Edits made on two devices while offline are never lost:
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card content is stored as append-only revisions, and a side changed differently on two
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devices is shown as a conflict until the person picks a version
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([ADR 0001](docs/adr/0001-offline-sync.md), [ADR 0003](docs/adr/0003-card-revisions.md)).
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- **No sign-up needed.** The app starts with an anonymous account; signing in with GitHub
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later keeps everything. A GitHub sign-in stores only the numeric GitHub ID.
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- **No end-to-end encryption.** Content is readable by the operator of the instance, as on
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Mastodon; whoever trusts no operator can run their own
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([ADR 0002](docs/adr/0002-no-end-to-end-encryption.md)).
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Targets: Linux, Windows, macOS, Android and iOS. There is no web build.
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## Packages
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| Package | What it is | Licence |
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|---|---|---|
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| `halkyon_learn_server` | The [Serverpod](https://serverpod.dev) server: endpoints, models, migrations | SSPL-1.0 |
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| `halkyon_learn_client` | The client, generated from the server's models | AGPL-3.0-or-later |
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| `halkyon_learn_flutter` | The app (`app.halkyon.learn`) | AGPL-3.0-or-later |
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## Setting up
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- **Flutter v3.47.5**, the version CI uses (`FLUTTER_VERSION` in
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`.forgejo/workflows/ci.yaml`). Set up each platform you build for with Flutter's own
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guides: [Linux](https://docs.flutter.dev/platform-integration/linux/setup),
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[Windows](https://docs.flutter.dev/platform-integration/windows/setup),
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[Android](https://docs.flutter.dev/platform-integration/android/setup),
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[macOS](https://docs.flutter.dev/platform-integration/macos/setup),
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[iOS](https://docs.flutter.dev/platform-integration/ios/setup).
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- **The Serverpod CLI v4.0.4**: `dart install serverpod_cli@4.0.4`. Pass `--no-analytics`
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to every call; otherwise it reports the commands run to Serverpod.
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- **Linux**, on top of Flutter's packages, the libraries of four plugins: WebKitGTK
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(pulled in by the sign-in package), libsecret (keeps the session), GStreamer (plays
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sounds) and libmpv (plays videos from Jellyfin; the app doesn't start without it).
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On Debian or Ubuntu, Flutter's and these together:
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```sh
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sudo apt-get install clang cmake ninja-build pkg-config libgtk-3-dev libstdc++-12-dev \
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libwebkit2gtk-4.1-dev libsecret-1-dev libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev \
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libmpv-dev
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```
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- **Windows** needs Developer Mode (Settings › System › For developers): building makes
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symbolic links, as Flutter links each plugin's native code into the build and the PDF
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engine's build does too, and Windows lets ordinary users make them only in Developer
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Mode.
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- **No Docker** for development: `serverpod start` and the server's tests run an embedded
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PostgreSQL. Docker Compose is only for running an instance (below).
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- **For the scripts in `tool/`**: Python 3 (`tool/app_icons.py` also needs Pillow,
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`python3-pil`), and for releases what [Releases](#releases) lists.
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The rich-text editor comes from our fork of AppFlowy Editor
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([project-halkyon/appflowy-editor](https://code.halkyon.app/project-halkyon/appflowy-editor)),
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which `flutter pub get` fetches by itself.
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## Running it locally
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The server's secrets live in `halkyon_learn_server/config/passwords.yaml`, which is never
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committed. In a fresh clone, create it with a `development` and a `test` section, each
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holding `database`, `serverSideSessionKeyHashPepper` and `serviceSecret` (for example from
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`openssl rand -base64 32`). GitHub sign-in is optional: add `githubClientId` and
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`githubClientSecret` of your own GitHub OAuth app to `development`, registered with the
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callback URLs `app.halkyon.learn://github-callback` and `http://127.0.0.1/github-callback`.
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Then start the server, its embedded database and the app:
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```sh
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cd halkyon_learn_server
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serverpod --no-analytics start
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```
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`serverpod start` applies pending migrations and reloads on changes. The app talks to the
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server named by `--dart-define=SERVER_URL=…`, or else to the one in
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`halkyon_learn_flutter/assets/config.json` (`http://localhost:8080`). Without
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`--no-analytics`, the Serverpod CLI reports usage to Serverpod.
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## Tests
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```sh
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tool/check.sh
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```
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runs the format check, the analyzer with the strict lints of `leancode_lint`, the server's
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tests (against an embedded PostgreSQL, no Docker needed) and the app's tests. To run it
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before every push: `ln -s ../../tool/check.sh .git/hooks/pre-push`. CI runs it on every
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push too (`.forgejo/workflows/ci.yaml`).
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The sync tests need a running server (`serverpod start`); run them in
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`halkyon_learn_flutter` with `flutter test -t requires-server`.
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## Running an instance
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`deploy/` holds a Docker Compose setup: Caddy (HTTPS), the server and PostgreSQL. Copy
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`deploy/.env.example` to `deploy/.env` and fill it in; it explains every value. The
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licences require offering the source of what the instance runs to the people who use it.
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Assistants such as Claude read people's studysets through the instance's MCP connector at
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`/mcp` ([ADR 0006](docs/adr/0006-assistant-connector.md)): `webServer` in
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`halkyon_learn_server/config/production.yaml` names its public address, as `apiServer`
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does for the app.
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learn.halkyon.eu itself deploys from `main` once CI is green: `deploy/redeploy.sh`, run by
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the CI runner described in `deploy/runner/`, deploys only commits signed by a key in
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`deploy/allowed-signers`. It backs up its database every hour, off-site and encrypted;
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[`deploy/backups.md`](deploy/backups.md) says how to set that up and how to restore.
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## Releases
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Releases are published on [code.halkyon.app](https://code.halkyon.app/project-halkyon/halkyon_learn/releases),
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with the APK and the snap, and the APK also in the project's F-Droid repository
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(`https://halkyon.app/fdroid/repo?fingerprint=E8082788756F6B7E682AA22FCEAD24B53E2A8B0912AD66D65E8C2D4F07BB94B0`,
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added in the F-Droid app as a repository). The Snap Store (`halkyon-learn`) follows.
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Their builds offer learn.halkyon.eu, the project's instance, at first start; people
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may choose another there, and keep accounts on several.
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- **Checking a download:** `SHA256SUMS` lists the checksum of every file, signed with the
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maintainer's GPG key (`SHA256SUMS.asc`). The APK is signed with the app's key, whose
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certificate has the SHA-256
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`27:E2:43:FC:BD:C8:26:FF:98:AB:7D:BB:10:43:6C:98:C3:BE:A2:4B:2A:01:5E:94:E4:CF:C7:D1:FC:2A:00:6C`
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(`apksigner verify --print-certs` shows it).
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- **Versions** follow [semantic versioning](https://semver.org): `version` in
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`halkyon_learn_flutter/pubspec.yaml`, `<major>.<minor>.<patch>+<build>`. Since the last
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release, a commit typed `feat` raises the minor number, `fix` or `perf` the patch
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number, and a breaking one (`feat!:` or a `BREAKING CHANGE:` line) the major number from
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1.0 on, the minor one before; other commits release nothing by themselves. Every
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release raises the build number: Android only installs a higher one over an older, and
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the server tells apps below the build it supports to update.
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- **Making one** is for maintainers, on their own machine and never in CI:
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`tool/release.sh`, or `tool/release.sh minor` (or `major`, `patch`) to choose. It needs
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`main` clean, pushed and green in CI, the app's key, the F-Droid repository's key and
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a Forgejo token; its header says more. It shows the version and its commits and asks
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first, then writes the version into the pubspec in a signed release commit with a
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signed tag, builds the APK and the snap (`snap/snapcraft.yaml`, built in LXD; its icon
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comes from `tool/app_icons.py`), checks both, signs the checksums, pushes, and
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publishes on code.halkyon.app and in the F-Droid repository; the Snap Store once it is
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switched on in the script. Besides Flutter and the Android SDK, it uses snapcraft with
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LXD, a JDK (keytool), GnuPG, curl, jq, unzip, squashfs-tools, rsync and fdroidserver.
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Release builds made without the app's key are signed with the debug key and can't
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update a released app.
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- **The F-Droid repository** is kept by `tool/fdroid_repo.sh` (fdroidserver v2.4.5,
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e.g. `pipx install fdroidserver==2.4.5`); its settings and the app's listing are in
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`tool/release/fdroid/`.
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## More
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- [`AGENTS.md`](AGENTS.md): how the code is organised and the rules it follows.
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- [`docs/adr/`](docs/adr/): the architecture decisions and their reasons.
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- [`CONTRIBUTING.md`](CONTRIBUTING.md): licences of contributions and the sign-off.
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- [`LICENSE.md`](LICENSE.md): which licence covers what.
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