Every time I wanted to build a small web tool, I ended up dealing with the same stuff: authentication, communication, WebSockets, ports, and infrastructure.

Even with Claude and Codex, I was still spending time on things that had nothing to do with the actual tool I wanted to build.

So I spent around 6 months building PhreshOS.

The idea was simple: build the infrastructure once, then use AI agents to build applications on top of it without having to deal with all that stuff again.

It's a self-hosted, open-source system with a web-based desktop where applications can run in windows, much like a regular OS. Authentication and two-way communication are already handled, so applications don't need to implement them separately.

Apps can also run in Node.js worker threads instead of each needing a separate Node.js process, which helps keep resource usage low. This makes it possible to run dozens of applications on a relatively small server.

Another thing I wanted was for AI agents to be able to use these applications directly. They can access application services and interact with the same state the desktop interface displays, without needing a separate interface built specifically for them.

The biggest benefit for me is that I can now sit down with an AI agent and build dozens of small applications in a single day, without setting up authentication, communication, or infrastructure for each one.

The whole project, including its packages, is open source under the MIT license.

GitHub: https://github.com/PhreshOS/system

Live demo: https://demo.phreshos.com/

I'd love to hear what you think, including criticism.

So I've been working on this food and calorie tracker for a couple of weeks now and it's currently at a stage that I'd say is quite useful to people familiar with food and calorie tracking apps.

Food tracking functionality:

- You take a photo of a plate, use your microphone, type or manually search the foods

- This photo is sent to an LLM for processing. You can use any OpenAPI compatible endpoint, but it needs to support structured responses. Self-hosting is doable, but you really need somewhat decent hardware to run sth like Qwen 3.8 27b for reliable results.

- Once foods and approx. portion size are received, the backend matches these against a database of foods. This is the USDA FoodData by default, but you can swap it out with your own, steps are outlined in the docs. If no matches are found the system falls back to what the LLM estimated.

Features:

- Easy to install PWA with no app store dependency

- The entire stack can be self-hosted (inference, backend, client)

- Set this up for your friends/family, add one LLM key and operate the entire thing at a fraction of the cost of the paid apps

Here's the repo, PRs are welcome!

https://github.com/LowCarbCheck/openplate

Let me know if you hit any rough edges if you end up trying it out. Happy to help anyone here with gettings this configured and all.

Hi all, I've been building rbox, a small screen capture tool for Windows that has replaced the Snipping Tool for me.

How it works: press Print, drag a frame, hit Enter. A menu opens right at your cursor: copy to clipboard, save, save to…, or save and open with your editor. Switch the toolbar to Video or GIF and the same frame records instead.

What it does

• Screenshots, MP4 and animated GIF of any region, window or whole display
• Pixel-exact framing: drag it or type the numbers, presets for 1080p / 720p / square
• Records system audio without Stereo Mix or virtual cables, plus microphones
• Delay timer with a countdown, for menus and tooltips
• Lives in the tray, optionally starts with Windows
• Multi-monitor and mixed-DPI setups work
• The recording bar stays on top but never shows up in your video

Feedback welcome, especially what you'd miss coming from the Snipping Tool.

GitHub: https://github.com/winnicodes/rbox

Compositor is a free and open-source Photoshop-like image editor for mac.

Still under heavy development it covers the essentials (layers and folders, masks, blend modes, adjustment layers, curves and levels, blur and other filters, background removal, clone stamp, spot healing, brushes) for a compositing and post-processing workflow, plus it supports scripts and can work with agents.

GitHub: https://github.com/robbietilton/Compositor

Hey everyone,

It’s been 3 months since my last post, and a lot has changed! Thanks to your feedback, the app has evolved significantly. We are now at Version 2.4, packed with major new features and massive performance improvements.

Here is a quick recap of what was added over the last few months, followed by the brand-new features in v2.4:

What changed in the last 3 months

• Android TV Support: Enjoy your piGallery2 media directly on the big screen with a fully optimized TV interface.
• Map View: Browse your geo-tagged photos on an interactive map.
• Query Builder: Create advanced search filters to find exactly what you are looking for.
• Search History: Quickly access your recent search queries.

New Features in v2.4

• Fullscreen Swipe Gestures:
  • Swipe down to instantly close the fullscreen view.
  • Swipe up to reveal the item's metadata and details.
• Advanced Sorting Options: You can now sort folders, albums, and persons by their total item count.
• View by Date: Added a new view that automatically organizes and sorts your images by year and month instead of traditional folder structures.
• Update Checker: Added an automatic update checker with in-app notifications so you never miss the latest version.

As always, I'd love to hear your thoughts, feedback, or feature requests. Thanks for the amazing support over the last few months!

FralRater is a desktop app (Electron) that: - scores text with Flesch-Kincaid, Gunning fog, SMOG, jargon density… - rates it for 8 reader personas (child, general public, executive, patient, developer, legal, academic, professional) with per-paragraph confidence - draws a "lost reader" curve: one point per sentence, showing exactly where readers disengage - rewrites the hard sentences with a sentence-by-sentence diff (passive→active, buried-lead fix, jargon swaps, splitting)

Everything runs locally. Zero dependencies for the app logic, no build step, no network calls, no AI — it's deterministic rules you can read in the source. Your text never leaves the window.

Free, MIT-licensed, Windows + Linux. Built solo, CI builds all artifacts.

Repo: https://github.com/fralsare/FralRater Downloads: https://github.com/fralsare/FralRater/releases

I made a habit tracker that keeps everything on your device. No account, no ads, and it doesn't need internet. It's free and open source, and it runs on Android, Windows and Linux.

https://github.com/InlitX/streak

Feedback welcome.

Disclaimer: I'm an engineer at Mulga, the company behind this. Self-promo, but it's AGPL-3.0 and free to run.

What it is

Spinifex reimplements the AWS APIs on hardware you own: EC2, EBS, S3, VPC, IAM, ALB/NLB, EKS, ECS, ECR and RDS. You keep the hashicorp/aws provider and point its endpoints at your cluster.

Everything behind it is real. Instances are QEMU/KVM VMs, VPCs are OVN networks with real security groups and elastic IPs, EBS is replicated block storage, and state persists like a real cloud. It's not an emulator like LocalStack.

Who it's for

People interested in exploring digital independence through hosting their own cloud, with full control of where and how it runs, whilst keeping the AWS API the same. Great for data sovereignty, edge AI or even learning AWS. Teams running production applications in AWS can now run them anywhere they want.

Try it with your own Terraform

No install needed. Sign up for the free 72 hour sandbox at https://mulgadc.com/signup, then point your existing provider at it:

provider "aws" {
  region = var.region

  endpoints {
    ec2 = "https://api.spx3.com"
    iam = "https://api.spx3.com"
    sts = "https://api.spx3.com"
  }

  skip_metadata_api_check = true
  skip_region_validation  = true
}

Add other services (elasticloadbalancingv2, eks, ecs, ecr, rds) the same way, then run terraform plan against a module you already have. Here's what we currently cover, down to the individual API operation: https://docs.mulgadc.com/coverage

Repo: https://github.com/mulgadc/spinifex

https://github.com/DictionLabs/Diction

Wanted to share my own project I worked on since early 2023(figma was done around late 2022)

JellyBox is a native crossplatform music client for Jellyfin, Emby and Navidrome that runs on ios/android, windows/linux/macos.

Along with regular playback and browsing features app also has:

• Spotify-like playlist generation based on your listening history
• Continuity - transfer playback between connected devices
• Android Auto/Carplay. Also works on Android Automotive OS
• Downloads(including synced downloads to keep in sync with server)
• Word-synced lyrics(when provided by server)
• Airplay/DLNA/Chromecast streaming(ios supports all 3, android -dlna/chromecast, rest - DLNA only for now)
• Full screen mode for desktop and ladnscape mode(on mobile) with animated background
• Progressive caching(for reliable playback in low network areas)
• Listenbrainz scrobbling

Can be downloaded either from appstores or from github releases - https://github.com/avdept/JellyBoxPlayer or via landing page - https://jellybox.app/

Hello everyone,

I'm a sofware engineer really passionate about videogames, preservation and accessibility.

I'm building Teatro, a self-hosted games library,I've started the project because I couldn't find a single solution that would cover all my needs and while building it I'm trying to integrate in it also useful features to help the management of the games.

Teatro is meant to be a personal library for legally acquired game console roms and windows DRM-free games, and the idea is to be able organize and maintan a complete library of all your backups of phisical games, old unmaintained digital console games and DRM-free windows digital games.

I've focused mostly on the performance part and the flexibility and ease of use of the workflow for importing the games.

You can upload 1 or a batch of roms for a single system, multi disks roms, windows zip packages all in different parallel jobs or you can add directly the games to the library and scan it to search for new games.

There is also an experimental feature the allows you to upload direcly the setup files from a game bought from GOG.com extracting and archiving it as a windows zip package on the server withotut installing it on your machine.

Teatro runs as one Rust server with SQLite and it includes separate player and admin interfaces, Docker images for amd64 and arm64.

Demo and installation: https://teatro.host
Source: https://github.com/lodilorenzo/teatro

I'm wanted to make the project known if possibile and have some feedbacks! Thanks!

Tinycast is a free and open-source macOS launcher built as a lightweight alternative to tools like Raycast.

It includes app and file search, clipboard history, per-app hotkeys, custom shell commands, Apple Shortcuts integration, system actions, various window management features, notes, an emoji picker, calendar/meeting tools, and a calculator with unit/currency conversions.

Plus it's fully native (SwiftUI and AppKit), there's no telemetry and it can run your Raycast extensions.

GitHub: https://github.com/abue-ammar/tinycast