@TraceApps@lemmy.world

NoteTrace is a self-hosted alternative to Google Keep, Evernote and Apple Notes: notes, checklists and reminders in a card grid, on your own server. AGPL-3.0, a single Docker container, a web app that works offline, a native Android app, and a Wear OS app. No telemetry, no cloud. This is the first stable release.

Part of the TraceApps family: NutriTrace (nutrition), CookTrace (recipes / pantry / shopping), LiftTrace (strength / lifting).

What it does

• Notes and checklists. Pins, colors, nested labels, archive, trash, version history, and full-text search that also finds words in voice transcripts and in photos.
• Reminders and Tasks. Repeating reminders that keep their local time, exact alarms on Android, and one view of everything that’s due.
• Offline everywhere. The installed web app keeps editing with no connection and syncs later; Android and the watch work offline too.
• Wear OS. Tick off lists, read notes, see what’s due, and speak a note (“call the plumber tomorrow at nine” sets the reminder), with a tile and a watch face complication.
• Voice notes and drawings. Record with the screen off and get a transcript you can tap to jump to.
• Bring your notes with you. Import from Google Keep, Evernote, Memos, Blinko and Markdown vaults; export everything as Markdown with images.
• Optional AI. Tidy up, summarise, or turn a note into a checklist, with the provider of your choice. Off unless you set it up.

Links

• Repo: github.com/TraceApps/notetrace
• Docs: traceapps.github.io/docs/notetrace/
• Release notes + signed APKs (phone and watch): github.com/TraceApps/notetrace/releases/…/v1.0.0
• Docker: ghcr.io/traceapps/notetrace:latest (mirror: traceapps/notetrace:latest)

AI Disclosure

Per Rule 7 / [AIP] disclosure requirements AI was used during development as a coding assistant. Level per category:

• Design (architecture, system design): Hint: I make the architectural calls; AI suggests trade-offs and edge cases I might have missed.
• Implementation (production code): Pair: roughly 50/50. AI drafts, I review, adjust, test on real hardware, and only commit what I’ve verified. Every commit is manually reviewed before it goes to my dev repo.
• Testing (writing tests, test plans, QA): Assisted: real-device testing is manual (I test on my own PC and mobile devices before every release). AI helps draft test plans and think through edge cases.
• Documentation (docs, comments, README, CHANGELOG): Pair: release notes and changelog entries are drafted with AI then edited for tone; comments and code docs are mostly Pair as well.
• Review (code review, PR feedback): Assisted: I’m the reviewer; AI helps with security sweeps, audit passes on complex changes, and consistency checks.
• Deployment (CI/CD config): Hint: Docker/GitHub Actions/release pipeline is largely conventional; AI-suggested improvements only.

CookTrace is a self-hosted alternative to Mealie / Tandoor / Paprika: recipes, pantry inventory, shopping lists, and a cook diary in one app. AGPL-3.0, single Docker container, native Android app.

Part of the TraceApps family: NutriTrace (nutrition), CookTrace (recipes / pantry / shopping), LiftTrace (strength / lifting).

What v1.2.0 adds

• Ingredient links on recipe steps. Link specific ingredients to the step that uses them, and Cook Mode shows each step’s linked ingredients inline with their quantities, no more scrolling back up to check how much flour a step needs. Tapping one checks it off the main list too, and finishing a step checks off everything linked to it. Tandoor imports carry this linkage over automatically.
• Wide-screen desktop layouts across six main pages plus Cookbooks. Settings, Manage, Shopping, Diary, Pantry, and Recipes all get real desktop treatments instead of a stretched-out phone layout: masonry shopping lists, a two-pane Settings shell, denser pantry and diary grids, and wider content caps on ultrawide monitors.
• Cookbooks get search, drag-and-drop reorder, and a cover image. Pick a recipe card up from anywhere on it to reorder, not just a tiny handle. Cookbook cards now show the same info as the main Recipes grid (category, rating, tags, pantry match).
• Kitchen auto-share was silently dropping recipes created on the Android app. Recipes made on your phone weren’t fanning out to other Kitchen members. Fixed, and toggling auto-share off then back on backfills anything missed.
• Mobile ingredient-name suggestions no longer cover the keyboard. The field used the browser’s native suggestion picker, which some mobile WebViews render as a full-screen overlay fighting the keyboard for space. Replaced with an in-app dropdown that sizes itself to whatever room is actually free.
• A batch of smaller fixes: CSRF errors on file/URL import dialogs, email links rendering as http:// behind a reverse proxy, single-user-mode data getting stranded on upgrade, pantry items disappearing when sorted A-Z with an orphaned category, and more in the full changelog.

Community contributions this release: @clifmo (email-link proxy fix), @xiaojwus (pantry sort bug report).

Security

fast-uri, browserslist, @xmldom/xmldom, and qs bumped, closing 8 advisories (4 high, 4 moderate: host confusion / SSRF via URL normalization, unbounded memory growth, XML fragment injection, denial of service). No app behavior changes.

Links

• Repo: github.com/TraceApps/cooktrace
• Docs: traceapps.github.io/docs/
• Full release notes + signed APK: github.com/TraceApps/cooktrace/releases/…/v1.2.0
• Docker image (multi-arch, amd64 + arm64, Pi 4/5 works out of the box). Published to two registries with identical tag sets:
  • GHCR (primary): ghcr.io/traceapps/cooktrace:latest
  • Docker Hub (mirror): traceapps/cooktrace:latest

docker compose pull && docker compose up -d

AI Disclosure

Per Rule 7 / [AIP] disclosure requirements AI was used during development as a coding assistant. Level per category:

• Design (architecture, system design): Hint, I make the architectural calls; AI suggests trade-offs and edge cases I might have missed.
• Implementation (production code): Pair, roughly 50/50. AI drafts, I review, adjust, test on real hardware, and only commit what I’ve verified. Every commit is manually reviewed before it goes to my dev repo.
• Testing (writing tests, test plans, QA): Assisted, real-device testing is manual (I test on my own PC and mobile devices before every release). AI helps draft test plans and think through edge cases.
• Documentation (docs, comments, README, CHANGELOG): Pair, release notes and changelog entries are drafted with AI then edited for tone; comments and code docs are mostly Pair as well.
• Review (code review, PR feedback): Assisted, I’m the reviewer; AI helps with security sweeps, audit passes on complex changes, and consistency checks.
• Deployment (CI/CD config): Hint, Docker/GitHub Actions/release pipeline is largely conventional; AI-suggested improvements only.

Fathom is an all-in-one client for Jellyfin, on Linux, Windows, and Android (with experimental Android TV). It puts movies, shows, music, and Live TV in one window, with most of Jellyfin’s server-side management built in, plus optional Seerr requests and a full YouTube client. Everything plays through mpv (via media_kit), so you get direct play, hardware decoding, and real subtitle and audio track control. Free and open source (AGPL-3.0), built by one person. This is my first update post since the v0.11.0 rundown, so here’s what’s new across v0.11.1 and v0.12.0.

Feedback is very welcome: bug reports and feature requests on GitHub Issues, questions in Discussions.

Downloads

Downloads is now a full offline library instead of a flat list: separate Movies, TV Shows, Recordings, and Music sections, with the same poster covers and rating badges as the regular library.

A downloaded title opens the same detail page as its library page (backdrop, cast, ratings, overview), scoped to what’s downloaded: only the episodes you have, with local-only play, mark watched, and remove that never touch the server.

Download a whole series or season in one go, picking a scope, plus a download option on every episode’s own menu.

Download music too, a single track or a whole album or artist, and it plays in the music player with the familiar album view, fully offline.

Live TV recordings can be downloaded as well, and can be found in their own Recordings section.

YouTube

Fixed playback being blocked entirely by YouTube’s “confirm you’re not a bot” gate.

Fixed multi-language videos defaulting to a dubbed audio track instead of the original.

Shuffle and repeat for background audio, plus skip back to the previous track.

Live streams start in a couple of seconds instead of tens of seconds.

Account and updates

Change your own password from the Profile screen (current, new, confirm). Leaving the new password blank removes it, the same option the official Jellyfin clients offer.

Update checks now have a frequency setting: on or off, plus Every Launch, Daily, or Weekly.

A new build is announced with a floating banner and a native system notification on Linux and Android.

Also since v0.11.0

Tapping an episode row opens its page; the thumbnail or play icon plays it directly.

Background audio no longer freezes on an unplayable track, and recovers from brief network drops.

Saved radio stations are no longer left out of settings backups.

Importing YouTube subscriptions on Android no longer greys out cloud-storage files.

Settings and your Jellyfin login now persist on minimal Linux desktops where the system keyring starts cold, such as Hyprland.

In-app updates on Android work again; a build-numbering issue was rejecting newer builds as a downgrade.

A Nix flake for Linux, so you can build and run Fathom with nix build / nix run.

Platforms: Linux and Windows (self-contained downloads) and Android (APK; Android TV experimental). macOS and iOS still need Mac hardware I don’t have yet.

Links

Repo: github.com/Fathom-Media/fathom

Latest release: github.com/Fathom-Media/fathom/releases/latest

Bugs and feature requests: github.com/Fathom-Media/fathom/issues

Docs: fathom-media.github.io/fathom

AI Disclosure

Per Rule 7 / [AIP] disclosure requirements, AI was used during development as a coding assistant. Level per category:

• Design (architecture, system design): Hint — I make the architectural calls; AI suggests trade-offs and edge cases I might have missed.
• Implementation (production code): Pair — roughly 50/50. AI drafts, I review, adjust, test on real hardware, and only commit what I’ve verified. Every commit is manually reviewed before it goes to my dev repo.
• Testing (writing tests, test plans, QA): Assisted — real-device testing is manual (I test on my own PC and mobile devices before every release). AI helps draft test plans and think through edge cases.
• Documentation (docs, comments, README, CHANGELOG): Pair — release notes and changelog entries are drafted with AI then edited for tone; comments and code docs are mostly Pair as well.
• Review (code review, PR feedback): Assisted — I’m the reviewer; AI helps with security sweeps, audit passes on complex changes, and consistency checks.
• Deployment (CI/CD, release pipeline): Hint — GitHub Actions and the release pipeline are largely conventional; AI-suggested improvements only.

Fathom is an all-in-one client for Jellyfin, on Linux, Windows, and now Android. It brings movies, shows, music, and Live TV into one window, with most of Jellyfin’s server-side management built in, plus optional Seerr requests and a full YouTube client. Everything plays through mpv (via media_kit), so you get direct play, hardware decoding, and real subtitle and audio track control. Free and open source (AGPL-3.0).

Feedback is very welcome. Bug reports and feature requests both belong on GitHub Issues, and questions are fine in Discussions. Fair warning: the new Android TV build is still rough around the edges, so testers and reports there especially would help a lot.

This is my first update post since the 0.9.0 launch, so here’s everything added since then.

New platforms

• Android phones and tablets, from a single universal APK.
• Android TV, experimental for now: D-pad navigation and a 10-foot interface, still being refined.
• Android Auto (audio-only): browse Jellyfin music, internet radio, and YouTube, search by voice, and control playback from the car.
• ARM64 (aarch64) Linux builds alongside x86_64.

Player

• Up Next over the credits (a poster card or a compact Netflix-style pill) that rolls into the next episode, with configurable timing and autoplay.
• Skip Intro, Skip Credits, and Skip Recap.
• Audio passthrough: bitstream Atmos, Dolby Digital, and DTS to a receiver on the desktop player.
• Playback Info overlay: play method, codecs, resolution, the live hardware-decode path, and dropped frames.
• Display Sync for smoother playback on high-refresh displays.
• Chromecast casting from Android.

Library and management

• A per-item menu on posters, episode rows, and the detail page: Play or Resume, mark watched, favorite, add to a playlist, refresh metadata, and delete.
• Delete media from the app (with the right server permission): a whole series, a season, a single episode, or a movie.
• In-app plugin configuration as a real form with toggles and fields, instead of a raw JSON blob.
• Backup and Restore your settings to a portable file, by group.

Beyond Jellyfin

• Internet radio: add stations by URL or from the radio-browser.info directory, organize them into groups and favorites, with live time-shift to pause and rewind a live station.
• OS media controls: system media keys and on-screen controls on Linux (MPRIS) and Windows (SMTC), covering video, Live TV, YouTube, and radio.
• The built-in YouTube client gains a Shorts viewer, background audio, a playlist queue, and much faster browsing, on top of the existing SponsorBlock, DeArrow, and downloads.

Quality of life

• Unified search, drag-to-reorder lists, and a customizable Home and navigation.
• Diagnostics screen with exportable logs, internal/external server address auto-switching, and a documentation site.
• Reliable HTTPS on Windows, and in-app updates that verify the download’s size and architecture before installing.

Platforms: Linux and Windows (self-contained downloads) and Android (APK; Android TV experimental). macOS and iOS need Mac hardware I don’t have yet.

• Code and releases: github.com/Fathom-Media/fathom
• Latest release: github.com/Fathom-Media/fathom/releases/latest
• Docs: fathom-media.github.io/fathom

AI Disclosure

Per Rule 7 / [AIP] disclosure requirements AI was used during development as a coding assistant. Level per category:

• Design (architecture, system design): Hint — I make the architectural calls; AI suggests trade-offs and edge cases I might have missed.
• Implementation (production code): Pair — roughly 50/50. AI drafts, I review, adjust, test on real hardware, and only commit what I’ve verified. Every commit is manually reviewed before it goes to my dev repo.
• Testing (writing tests, test plans, QA): Assisted — real-device testing is manual (I test on my own PC and mobile devices before every release). AI helps draft test plans and think through edge cases.
• Documentation (docs, comments, README, CHANGELOG): Pair — release notes and changelog entries are drafted with AI then edited for tone; comments and code docs are mostly Pair as well.
• Review (code review, PR feedback): Assisted — I’m the reviewer; AI helps with security sweeps, audit passes on complex changes, and consistency checks.
• Deployment (CI/CD config): Hint — the GitHub Actions build and release pipeline (Linux AppImage, Windows, Android APK) is largely conventional; AI-suggested improvements only.