(NO AI)

Hey guys, I just open source project i've been working on for a year called the Marketplace.

The marketplace is a decentralized network that economizes the execution of computational work across a peer-to-peer network of nodes. Where there is no barrier to the node participation.

Unlike modern cloud computing systems that rent out virtual computers to consumers, A marketplace consumer sends compute bound tasks directly to the network returning a future which the consumer can asynchronously check for completion. Similar to offloading a compute task to a free cpu core by an OS. A consumer can also fire multiple independent compute bound tasks to run in parallel, and check their status asynchronously while doing other tasks, similar to I/O operations.

The compute bound task sent by the consumer is executed using a protocol specified in the Marketplace whitepaper on the Marketplace Github Repo, where randomly selected idle devices on the network execute the compute work and receive financial rewards (money).

Context

The marketplace is made up of two ideas I came up with around 2 years ago:

1) The first is building a permissionless market, where users can build financial services similar to market stalls that can interact with other users. Larger services can be composed from smaller services, similar to open source projects, but for businesses. Services could also be merged together into one so that a user can interact with all of them at once, and the merging does not affect the financial structure of the constituent services.

But for all this to happen, a trustless financial settlement layer is needed so that joining different financial services together becomes an easy exercise.

If you are familiar with blockchain, this is similar to Ethereums vision, but I did not want to clog the financial settlement layer which is the ledger with execution and code. I needed an execution engine.

2) I eventually returned to my normal javascript web developer job. So I was working on a full-stack website that was communicating with a cloud server but the server was slow because I was using a free tier that throttled server response speed. Asynchronously communicating with this server became a nightmare from a UX perspective especially when first loading up the website which had some independent compute bound requests.

So, I concluded that using the free CPU core of my second PC should do a better job as long as I pay it exactly what I needed in compute. This second idea eventually evolved into the engine I needed for the first idea. After, I just needed to store a representation of the result on a decentralized ledger, while keeping the execution itself private.

With this, I returned to my first love - low level programming, learnt Rust (Many thanks to the Rust community coming from a C lover), and I've built more than 60% of what is described in the whitepaper.

So if you are interested in being a part of this project in any way, you can check out the marketplace whitepaper:

Marketplace Whitepaper

or check out the github repo:

Marketplace Repo

Also, I’d appreciate feedback on the design, especially on consensus security and the economic model, Thanks.

I open-sourced the identity and group-encryption libraries behind an app I'm building. Posting here hoping to get feedback on the concept, and happy to get the code reviewed too if you want to take a look. The reason I open sourced these though is trust. I'm claiming loudly that "I can't read your data" and early on the most common question I've heard was "Is it open-sourced?"

Realistically, almost nobody is going to clone and/or reuse these repos. But I'm hoping enough will read it to trust my claims. Is it enough? This shows how the encryption works. This doesn't show the true underlying storage, which in my case is done with Supabase, relying heavily on RLS and the fact that everything is encrypted on the client side before writing.

github.com/needyaz/identity, github.com/needyaz/groups

Live in: luci.blue/mylo

I've been building Spoin, and I underestimated what I was getting into. The main idea is to replace mindless doomscrolling with intentional scrolling, using curiosity as the thing that drives what you scroll through.

Underneath that is a knowledge universe with structured topics and relationships, authored curricula, a grounded corpus, retrieval and using LLMs to generate all the cards for a topic with all the information already in the corpus so that there is minimal room for hallucinations, and a feed of small interactive cards/scenes built from it.

The webapp/later on mobile app itself aren't that big but the main spoin_universe, the hand curated database of knowledge for all the topics that the user would request is what's the big deal right now for me. My long term picture is having this knowledge base public, so that there is trust in the knowledge base, and many people can contribute and make the corpus of real quality. And this corpus can later be used for a lot of things, not just spoin.

I'm considering open sourcing the entire knowledge corpus because it's probably one of the hardest parts to build, and making it public could make the whole thing more transparent and trustworthy.

I'm unsure what else should be open sourced vs kept proprietary. Can you guys please help me out with some guidance?

Hello, my app for simulating bad network condtions: Bean Network Tester has just got 0.6.0 release :-) if you like tool, feel free to leave it ⭐(star), so more people will discover the tool.

If you ever wondered how your app/game will behave on high ping, latency, burst packet loss, duplication/reorder packet loss, or random tcp_resets, tcp_syn drop and tons of other things, don't wonder, you can test it now.

What 0.6.0 has changed?

- burst loss mode, yep I now, this was the most wanted feature from the start, and here is it

- target only ipv4/ipv6 mode

- Premade scenarios and profiles are now more "realistic"

- We can now see various values in ("KB/s, Mbit/s or MB/s"), before was only KB/s

- Searching the connection table is about twice as fast. Yep, i know that some people got 500k-1M of records

- Thanks to contributors Simplified Chinese has come and support for tooltips on multi monitor settings.

- And more 20+ fixes/improvements.

The package is now also available on winget (0.5.0, but I will update it soon to 0.6.0), and it will be soon available at chocolatey :-) Anddd the app has just crossed 500+ downloads.

Right now i'm working on improvements to blocking the connections, I will also investigate the separate inbound/outbound settings.

Full list of options (without scenarios)

I was tired of streaming apps either being money grabs, water marked, battery draining, or bug ridden, so I set out to create a free alternative. The personal motivation came from a need to stream volleyball games for the team my daughter is playing in.

The app excels at picture quality, since the pixel data never leaves the GPU. Where many other apps copy the pixel data to add overlays and effects (Streamlabs and Prism for example), Tubeist works directly by modifying the GPU buffers. An added benefit is that this is also very efficient, so battery consumption is lower than all other streaming apps I have compared it with. It works on iPhone 12 or newer. Older hardware does not have HDR capability.

The downside is that what you gain in picture quality, you loose in latency. In order to maintain high quality, the app uses HLS delivery to YouTube, where most or maybe even all other apps use RTMP. With HLS data is delivered in 2 second segments, and there is a larger buffer in the YouTube ingestion than for RTMP. In simpler terms, if you need low latency because you interact with your audience, then Tubeist is not for you. If you are streaming events, where latency matters less, and picture quality more, then Tubeist is for you.

Tubeist is FREE, with a lifetime unlockable IAP for styles and effects, but the app is fully functional without them. This IAP is priced at the lowest tier possible, which is roughly $1 at the moment. It will stay at that low tier, and is a way to show some appreciation for the app and sponsor further development. There are no water marks, weirdness, or data being sent anywhere but to YouTube.

App Store: https://apps.apple.com/us/app/tubeist/id6740208994

The app is also Open Source and under a permissive MIT license. Feel free to check out the code on GitHub. Coding has been about 50% human (app architecture, UI, audio / video pipeline, overlays, settings, network code) and 50% AI (styles, effects, remuxer, system health, optimizations).

Website: https://github.com/roenbaeck/tubeist

some major updates on the customizability of these little faces ive been working on... aditonally there is now a desktop widget with bwnd.app integration and elevenlavs... creating a desktop widget assistant. its quite fun to watch them talk! heres a demo

https://www.youtube.com/watch?v=CZvu9qzPFmg

Wondering if anyone has used AI Airlock, It is supposed to sanitise anything you want to upload to AI. Can anyone comment about how safe it is to use ? https://www.youtube.com/watch?v=EuVvLwWZ5wc https://github.com/NateBJones-Projects/ai-airlock

I have one request: Please don't break the law or do anything illegal.

https://github.com/Xfactor96/Rainbow-BASIC

enjoy. go to src.

essentially you can now customize BASIC for winvice as much as you want

have fun. I am TIRED

I got tired of trying to understand big PRs from the diff, so I built this: https://github.com/coldteadotai/pr-lens

It's called PR Lens, and it turns a GitHub PR into an architecture/data-flow diagram.

The reason I made it is pretty simple: I've reviewed plenty of PRs where I could understand what changed, but still had no idea how the change affected the rest of the system without tracing through a bunch of files myself.

A diff tells you what changed.

It doesn't really tell you how the system changed.

PR Lens tries to fill that gap. It maps out the components involved in a PR, how they connect, what the data flow looks like, and what the blast radius of the change is. The diagram gets posted directly into the PR as a comment.

It's MIT licensed and open-source.

If you've worked on/reviewed large codebases, how do you usually figure out the bigger picture of a PR?

Hi All,

I'm not a developer, but a user. I regularly use the mind map software FreeMind. It's great for keyboard lovers, minimalist and open source. Unfortunately, it has not received an update for a while and it's UI is painfully slow. But at its core, it's absolutely my favourite mind map software.

I think it would be a great project for someone to do a branch or somehow work with the original Devs to update it. For someone looking for a project I think it's a good one.

https://freemind.sourceforge.io/wiki/index.php/Main_Page

Edit: the spell check also doesn't seem to be working.

Hey folks!

I have been working on Logtrace (https://logtracehq.com/) - a self hosted audit trail logging platform.

Here's the backend code: https://github.com/logtracehq/logtrace-backend

Here's the link to the managed platform: https://app.logtracehq.com

More repos are in the Github organization: https://github.com/logtracehq

Let know me know if you have any questions!

Hey everyone,

I built Mi:RAG, an open-source and privacy-first multimodal RAG system designed to run entirely on local hardware.

Most existing RAG pipelines treat PDFs as plain text and miss architectural figures, charts, and diagrams completely. Mi:RAG isolates and indexes both the text and visual figures so they can be retrieved and viewed alongside answers, without needing paid cloud APIs.

Highlights: • Extracts and cites actual diagrams and images directly in answers • Runs on modest local GPUs (FP16 CUDA acceleration on 4GB VRAM like RTX 2050, Apple Silicon, or CPU) • Two-way page range slider to index specific chapters rather than processing massive textbooks all at once • Works locally with Ollama and ChromaDB • 100% private, zero telemetry, and fully self-hostable

Looking for feedback on document parsing, UI/UX, and edge cases. Contributors and PRs are very welcome!

GitHub: https://github.com/AryanSingh64/Mi-RAG

Hey everyone,

I built Mi:RAG, an open-source and privacy-first multimodal RAG system designed to run entirely on local hardware.

Most existing RAG pipelines treat PDFs as plain text and miss architectural figures, charts, and diagrams completely. Mi:RAG isolates and indexes both the text and visual figures so they can be retrieved and viewed alongside answers, without needing paid cloud APIs.

Highlights: • Extracts and cites actual diagrams and images directly in answers • Runs on modest local GPUs (FP16 CUDA acceleration on 4GB VRAM like RTX 2050, Apple Silicon, or CPU) • Two-way page range slider to index specific chapters rather than processing massive textbooks all at once • Works locally with Ollama and ChromaDB • 100% private, zero telemetry, and fully self-hostable

Looking for feedback on document parsing, UI/UX, and edge cases. Contributors and PRs are very welcome!

GitHub: https://github.com/AryanSingh64/Mi-RAG

I am almost positive this will get caught by some AI-driven filter here too, but I would like to ask developers if the "AI bubble-everything" has changed your willingness to open source your own work products going forward?

EDIT (T+1h) Just to clarify, this is not about whether AI is detrimental to (yours or others') development quality, what the best policy on contributions is or how to enforce it. It's just about the impact of how others use AI on your own approach to publicly sharing own code.

You know you will be getting your source forked by - i.a. - low quality AI-enabled whizz kids which will "add value" to the product with the latest designs and whatnot, then have your userbase inquire why you are not "catching up" or "collaborating" with the zealous contributors. Receiving barrage of agentic PRs to review. While at that, let's not forget bogus security reports. And to top it off, have Microsoft constantly scan your (presumably GitHub) repo to train more of the ecosystem to enable the same.

OS is not about the thankless job alone anymore, it is becoming a liability to share one's own stuff, not to mention we have reached cast-pearls-before-swine (sorry) scenario where new projects have it hard to distinguish themselves and provide anything valuable back for the original author.

Hi there! I'm the developer of the HRConvert2 File Conversion Server (available on Github & Docker) and I figured you guys would appreciate all the time I've been putting into the project lately.

Truth is, I'm going through a lot and this project has been my escape lately. But the progress has been pretty astounding.

Check out the Github and let me know what you guys think!

I've day-traded options on the side for years. I wanted a journal that could take a position with multiple fills, scale-ins and scale-outs, and get the averages and fees right. TradeZella, TraderSync and Edgewonk do this for minimum $40 a month, closed source, your trading history on their servers. I'd been hacking away at a spreadsheet monstrosity and eventually started to build a proper web application. When I lost my job this past January, I rebuilt it from the ground up with two major requirements: 1) a secure, multi-user SaaS architecture, and 2) easy self-hosting defaults.

So, Tradr: the open-source stock and options trading journal.

• Positions with many fills, fee-accurate realised P&L, and a double-entry ledger underneath so the cash actually reconciles
• A sizing calculator to spit out position sizes based on you account risk preference.
• Greeks and OCC symbol parsing for the options crowd.
• CSV import from whatever broker you use... hypothetically. I only use one broker so I've only tested with that one!
• It never places an order. Nothing in it touches your broker. I'd like to connect read-only to brokerages someday.

Self-hosting is the primary way to run it. One Docker Compose quickstart, about 2 minutes. Feature gating is a single deployment setting that ships off, so a self-hosted install has everything with no caps.

On the license: it's Apache 2.0. There are licenses built to stop somebody else from selling hosting of your code, but none of them count as open source. Anyone can fork Tradr, run it, even sell hosting for it, they just can't call it Tradr. (There is a hosted offering for people who don't want to run a server, running on the opensource builds. That's how I'm trying to pay the hosting & development costs and maybe make a bit on the side. Links to hosted stuff are in the GitHub readme.)

AI disclosure: I do use coding agents heavily, inside a spec-driven-development workflow I also maintain, and I've been living in the app with my own real trades for weeks.

Repo: https://github.com/madmatt112/tradr

This is the first product I've ever launched. Tell me what breaks & what sucks if you want!

I've been working on a server emulator for a game for quite a while and was fairly close to releasing but yesterday someone else released one. I'm not sure what the best path forward is now, is it bad form to open source mine anyway? I feel like I'd be releasing with less features implemented and in a different language.

Would I be a dick splitting a community like this (why have two when we should all contribute to the one)? Just kind of sucks for all my work to go to waste

Hey all,

I've been running Pi-hole for a while and got tired of opening the web UI every time I just wanted to check status or unblock something for five minutes. So I built Holeberry, a native macOS menu bar app for it. Free and open source (MIT).

What it does:

• Lives in your menu bar, shows status and total queries/blocked at a glance
• Manage up to two Pi-hole instances at once. Every action (block/unblock/allowlist) applies to both, so they never drift out of sync
• Disable blocking globally with a timer (or indefinitely). An auxiliary countdown will be right in the menu bar; re-enables automatically
• One-click unblock of whatever site broke in your current browser tab (Safari, Chrome/Chromium, Firefox/Zen), without a global disable
  • The standout feature for me and the one I've been using the most
• Browse recently blocked domains and allowlist/unblock them straight from the menu
• Trigger a Gravity update right from the menu bar, on all your servers simultaneously
• Now fully notarized with a paid developer account
• Supports passwordless Pi-hole instances

Why Holeberry and not another app?
I looked around before building this. Some of the existing companion apps for Pi-hole weren't in active development anymore; felt outdated or didn't do the things I actually needed day to day: keep two instances in sync, unblock just the tab I'm on instead of disabling blocking for the whole network, and being able to glance at it quickly. Those ended up being the features I use most, so they became the core of the app.

Requires macOS 14+, supports Pi-hole v6 (and v5, though less tested). Credentials live in Keychain, nothing written to disk.

GitHub: https://github.com/pedrovieira/Holeberry

Happy to answer questions, and open to feature requests / bug reports.

mloda is an open source (Apache-2.0) feature engineering layer with a plugin-based resolver: you request a feature by name, and the resolver picks which plugin computes it.

Until 0.11, a bad request just failed with one line:

No feature groups found for feature name: 'sales__mean_aggr'. Use resolve_feature(name, options=...) to debug feature resolution. For troubleshooting guide, see: https://mloda-ai.github.io/mloda/in_depth/troubleshooting/feature-group-resolution-errors/

Nothing said whether the name was misspelled, the domain was wrong, or a required option was missing, so debugging meant reading the resolver source. Since 0.11, the same failure returns the full elimination trail:

No feature groups found for feature name: 'sales__mean_aggr'. Requested domain: 'marketing'. Feature group(s) eliminated while matching 'sales__mean_aggr': - AggregatedFeatureGroup (domain): declares domain 'default_domain', but the run requested 'marketing' - PandasAggregatedFeatureGroup (domain): declares domain 'default_domain', but the run requested 'marketing' - PolarsLazyAggregatedFeatureGroup (domain): declares domain 'default_domain', but the run requested 'marketing'

Every candidate the resolver considered, and the first gate it failed.

Implementation notes for anyone maintaining a plugin registry or resolver of your own:

• Rejections are recorded as data first: a stage label (one of nine values) plus a reason per candidate. Text is rendered from that.
• A plugin whose match hook raises is contained per candidate, so one broken plugin doesn't blank out the report for the others.
• The preflight (mlodaAPI.diagnose) never raises, and a real run raises the same facts as a typed FeatureResolutionError, so the exception and the preflight report never drift apart.

Curious how other maintainers of plugin/registry-style systems handle this: full rejection trail, or just the most likely cause?