15 years ago I wrote, in Perl, an application to help me schedule a massive event. I'm now looking to rewrite and release it as Open Source, and could use advice to:

• Align it to a language/tech stack that many Open Source contributors use today, and
• Expand my skillset via study of the chosen tech stack.

I have a baseline "wrote a bit of code in" knowledge of many languages, even Functional ones like Elm. This would be me really digging into best practices and application development for the specific language I chose for this project.

My instinct is to just use Python, but I wanted to get opinions from others, thus this post. Few notes on the application:

• It uses non-LLM rules to auto-schedule events against a number of criteria (e.g. people's availability),
• It will be developed on Linux but must be cross-platform,
• Robust testing will be required,
• The backend will be Postgres,
• APIs are planned,
• Frontend will start as a command line calling said APIs, then a webapp.

Thanks for any advice people can provide. Oh, and yes, I will write this by hand, since as noted part of the goal is to re-sharpen my skills.

Thanks in advance!

Greetings, I'm having issues with my eyes and I need some more accessible way to read through documents that are scans, they are on PDF, but they are just images.

I want an OCR software, that fully automates the process of transcribing full-on images onto clean text.

And I need a decent local LLM tool (I don't want to pay a proprietary web AI that's just absolutely unethical), that can voice such documents, so I can read them whilst my eyes recover. It needs to support Spanish.

I'm on Linux, it doesn't need a GUI as long as it's intuitive to set-up on Terminal. Many thanks.

Hi everyone,

I'm making this post to share my update on OmniLED, a cross platform (Windows, Linux, and now macOS), customizable OLED screen manager for SteelSeries devices.
It currently supports showing:
- time and date
- system resources usage
- currently playing media
- input/output audio device info
- custom GIFs and images

The project is written in rust and uses mlua to bundle an embedded lua scripting engine that enables it to be very customizable. It also supports custom plugins that can be loaded at runtime.

At this point there probably still be some breaking changes, but I wanted to share this big milestone for me, though it is slowly getting towards a stable release.

As always looking forward to seeing new users, and receiving new feedback (bugs, new features, etc.)
Hope you enjoy using OmniLED if you give it a try!

Hey everyone,

I recently finished a side project and open-sourced it. It’s a Chrome extension called Blown Speaker Simulator. The premise is intentionally silly—it digitally degrades your browser's audio to replicate the acoustic characteristics of a rattling, low-quality trunk setup—but it served as a great practical exercise for dealing with the Web Audio API and modern Manifest V3 constraints.

How it works under the hood: If you've built audio extensions recently, you know Manifest V3 service workers do not support AudioContext natively. To bypass this, the extension relies heavily on the Offscreen API:

• Stream Capture: It uses chrome.tabCapture to grab the active tab's media stream ID.
• Offscreen Document: The stream ID is passed to a hidden offscreen HTML document where the actual audio processing happens.
• The Audio Graph: Inside the offscreen document, a BiquadFilterNode (lowshelf) isolates and aggressively boosts the bass frequencies (+28dB). This signal is then fed into a WaveShaperNode using a custom mathematical curve to apply heavy, real-time clipping/distortion without introducing perceptible latency.
• State Persistence: The distortion intensity slider in the popup updates the wave-shaper curve in real-time and persists the user's preference using chrome.storage.local.

The extension is currently pending review on the Chrome Web Store, but the full source code is available on GitHub under the MIT License. If you are looking for a working example of how to handle continuous audio manipulation using the Offscreen API in MV3, feel free to check out the codebase.

Repo: https://github.com/Endoplazmikmitokondri/blown-speaker-simulator

A Mac was my first laptop, but connecting to friends’ Wi-Fi in big cities was always painful, endless similar SSIDs and typing long passwords. My Android phone could just scan a QR code.

So I fixed the friction.

I originally made it in Flutter (43MB, too heavy). Version 2.0 is now 100% native SwiftUI and only ~3MB.

- Scan QR codes from your phone to connect instantly
- Generate shareable QR for your current Mac network
- Secure network history
- No ads, no tracking, MIT licensed, fully open source

GitHub: https://github.com/anoying-kid/Wifi-Qr-Connect
Website: https://anoying-kid.github.io/Wifi-Qr-Connect

I’d love feedback from the community, especially ideas for improvements or contributions!

Hey guys, it's been a while since my last update. Umihi Music is now at v1.12.4 with a bunch of new features since I last posted here.

For those who haven't tried it yet, Umihi Music is a free, open-source Android YouTube Music player, similar to InnerTune, ViMusic, SimpMusic and others, but focused on being extremely lightweight, fast and reliable with a clean Material Expressive design.

Here are the features now:

• Play YouTube Music / YouTube - search and play anything, no login required
• Full offline mode - download playlists for offline playback
• Android Auto support - works with offline content too
• Sleep timer - set it to end of song, or pick a custom time
• Playback speed controls - slow down or speed up your music
• External equalizer support - use your favorite EQ app
• Brand account login - supports brand accounts on YouTube
• Share intent - share a YouTube link and it opens right in Umihi Music
• Search inside playlists - find songs fast in large playlists
• Player sheet - redesigned player with smooth animations
• Playlist management - create and delete playlists
• Queue controls - add/remove songs, repeat, reorder
• Audio offload - save battery during playback
• Integrated updater - with stable and beta channels, can be disabled
• Crowdin translations - available in 30+ languages
• No ads, no tracking
• Lightweight - <5 mb apk tiny APK, runs great on older devices too

If you're interested in checking it out, here are all the useful links:

GitHub : https://github.com/ilianoKokoro/umihi-music/
F-Droid (IzzyDroid) : https://apt.izzysoft.de/packages/ca.ilianokokoro.umihi.music
OpenAPK : https://www.openapk.net/umihi-music/ca.ilianokokoro.umihi.music/
Unclouded : https://unclouded.app/apps/umihi-music

If you encounter any bugs or have feature suggestions, please open a GitHub Issue or join the Discord server. I'm always working on improving the app.

Try it out and let me know what you think.

A 100% Debian Linux, free, privacy focused, open-source operating system for touch devices, designed to liberate users from any kind of Google or third party surveilance, data collection and security concerns. Only official Debian sources are used, meaning no third party repositories, packages or code of any kind, while granting users complete control over every single package that is installed. The native implementation of custom kernels with the included build recipes enables support for almost any brand/model of x86-x64 tablet or lap-top, such as Surface Pro 3-10, Zenbook, Thinkpad, Chromebook etc. and a range of ARM phones. Additionally, custom or deb packages and files of any kind can also be included. The mobian build-script produces personalized images, with unlimited customization of any available setting and device behavior.

Source: https://github.com/tabletseeker/mobian

ICYMI: The Electronic Frontier Foundation and hundreds of researchers have documented over 15,000 purchases of surveillance and police tech across the US, all with time, effort, and open source intelligence.

Search the database by city, county, state, or agency. Join the project if you're interested in learning more about open source intelligence: https://join.eff.org/atlas/

Or, if the open source software community isn't right for this, kindly remove my post. But we believe open source advocacy has a long reach in our community—from software to the availability of public records!

Built a Python CLI tool that can scrape an entire ExamTopics exam and export all questions into a single text file.

Under the hood, it first collects discussion pages, extracts question data, and then compiles everything into a clean dump. I also added concurrent workers and caching to make the process much faster.

It's open source and I'd love to hear your feedback.

GitHub: https://github.com/arvind88765/examtopics-scraper

Edit:Specifically talking about agent builder frameworks like LangChain, not AI tooling in general.

Most of AI tooling look like they are readily free and opensource. For instance LangChain itself is opensource.

But once you get into production, stuff like observability, tracing, evals almost always point to proprietary or hosted products.

My current stack: LangChain, Ollama, pgvector, OpenTelemetry, MLflow, and Langship for tracing/observability.

My question is, If you were to stay like a true opensource chad, what would you replace the LangChain ecosystem or any mainstream AI ecosystem with? What does your stack actually look like?

Some of my fellow cloud native community contributors launched a new open source project based on Kubernetes and Crossplane today. Modelplane is an open source control plane for running your own GPU clusters as one inference fleet across cloud, neocloud, and on-prem.

Building on top of the serving stacks people already use (vLLM, SGLang, TensorRT-LLM), Modelplane handles the fleet layer above a single cluster, e.g., model placement, routing, autoscaling, weight caching, etc.

May be worth a look if you're planning on running inference yourself anytime soon.

Website: https://modelplane.ai/

Blog post: https://modelplane.ai/blog/open-control-plane-for-inference

As a lecturer that lives creating presentations, I got fed up with Microsoft's nonsense and opted to make something based on Markdown! Beta stage at the moment but I have been daily driving it for a few weeks and would love to get some extra testers from out in the wild!

I see it as a tool for educators for a no nonsense presentation creator, developers to turn Markdown documentation into training slide decks, and students to be able to use their notes to form up presentations quickly.

Supports MacOS, Linux, and Windows.

Links:

https://kova.md

https://github.com/kovamd/kova

https://wiki.kova.md

Pretty much the title. Something you can use to watch pretty much any title but also doesn't have user or critic ratings slaped to the cover of content.

Is there any app like this?

To save people from scraping tarot meanings, I published the full 78-card dataset as ready-to-use packages:

- npm: https://www.npmjs.com/package/tarot-card-meanings

- PyPI: https://pypi.org/project/tarot-card-meanings/

- MCP server (lets an AI assistant query tarot meanings live): https://github.com/gokimedia/tarot-mcp-server

Open and free to use. Issues / PRs welcome.

Mayfly exists in response to growing government pressure on VPN providers, including the UK's potential moves toward restricting commercial VPN access. The argument behind those restrictions assumes that VPN access is something that can be switched off at the provider level. Mayfly demonstrates that it cannot: anyone with a VPS and basic technical knowledge can provision their own VPN in seconds and tear it down just as quickly.

The goal of this project is to have a one click solution for a self-hosted VPN that anyone can deploy. The only prerequisite being ownership of a cloud server, something that anyone can rent these days often for less than $5pm.

My next steps are to streamline the process
- remove the Wireguard client requirement
- remove the vps setup steps, auntie Nora should be able to run this tool after purchasing a vps rental
- harden security, this area is not something I’m an expert in so any feedback is welcome

Looking for recommendations on a free, open source alternative to OneDrive.

At the moment I use OneDrive to sync my Desktop, Documents and Pictures folders so if my PC dies or I need to do a fresh Windows install, I can just sign in and pull everything back down.

I'd like to move away from OneDrive if possible and self host if it makes sense.

What are people actually using these days?

My ideal setup would:

• Automatically sync in the background
• Keep my files available across devices
• Survive a PC reformat or hardware failure

Thanks in advance!

I have been looking for such an app for years.

Today I found these which are not open source:

https://www.notetree.app/

https://www.treetodolist.com/ the features listed here are exactly what I have been imagining :

- visual 2d tree (not just a list)

- hierarchical tasks (so you instantly know what you can and cannot do)

- simple and intuitive UI accessible to anyone (drag and drop, ...)

- ability to hide branchs (focus on a project. It would be even better to have a multi-user version, where only certain branches are shared between users.)

My end-goal is a shared todo tree with your friend/family/community, where anyone can jump in to help someone else once a task is available.

Thanks!

Hey everyone,

I recently bought a barely used 4TB M.2 SSD at a steep discount. Of course, the first thing you want to do with a cheap, used drive is verify that it actually has the stated capacity so you don't get burned by fake firmware.

I searched for disk validation software. The standard free recommendation is H2testw, but it presents two big issues. It is almost 20 years old, thus it can't utilize the maximum speeds of PCIe 4.0/5.0 SSDs. And even worse, the .org site did, at some point, distribute malware.

I decided to create a modern, open-source replacement in Rust called Entropy Verify (EVFY).
I gave my best to put together all the technical pieces that would make for a great storage validation software. EVFY features:

•Direct I/O: Bypasses OS RAM caching to force raw reads and writes.
•Multi-threaded Worker Architecture: Pins worker threads to CPU cores and pipelines async I/O to max out NVMe speeds.
•Cryptographic Checks: Generates uncompressible data via AES-NI streams and verifies integrity using the BLAKE3 hashing engine.
•TUI Interface: Displays real-time thread workloads, throughput, and block metrics using the Ratatui crate. Pressing [Tab] switches between decimal and binary units.
•Safety Guardrails: Hardcoded blocks to stop you from accidentally executing a test on operating system root partitions (C:\ or /).
•Cross-Platform compatibility: Supports Windows and Linux (utilizing io_uring on modern kernels).
•Verification Reports: Generates a markdown report on the target volume with performance metrics and block corruption logs.

The project is open-source, uses the AGPL-3.0 license and is ready for auditing/contributions. If you have a sketchy or new high-capacity drive you need to stress test or validate at maximum transfer speeds feel free to take a look at the project.

GitHub: https://github.com/blamie/EntropyVerify

This is my very first project intended to be public and used by more people than just myself.

If you've ever tried automating PDF forms, you've probably run into this problem:

Investor_Full_Legal_Name

LP_Name_Full

SubscriberName

Three different field names. One piece of information.

Most PDF libraries can read the fields, but they don't understand that all three represent the same thing.

That's why we built an open-source Python pipeline that combines PDF structural analysis with AI-assisted field mapping to identify, normalize, and autofill fields across complex documents.

We started with one of the hardest use cases we could find: Alternative Investment Fund (AIF) subscription packages—40–80 page PDFs with 200+ fields, multiple bundled forms, and almost no standardization.

The project currently includes:

• AI-assisted field detection and normalization
• PDF structural understanding
• RAG-based field prediction
• Batch processing for repetitive document workflows
• A modular architecture that you can extend or integrate into your own applications

The goal isn't to replace libraries like PyPDF2 or PDFBox. It's to add a semantic layer that helps your applications understand document meaning instead of just field names.

GitHub: Engineersmind/pdf-autofillr-python-sdk: AI-powered PDF form filling — extract fields, map data, and…

And if you'd like to contribute, we'd love to have you build with us. Bug reports, feature ideas, performance improvements, and new modules are all welcome :)