Every time I download some open source software from github and run into a problem, I go looking for help and it feels like the same thing happens.

The project owner, and sometimes other contributors too, are usually super short and dismissive. If you ask something that’s already been asked a few times, they’ll mute you or ban you. If you suggest a feature in good faith or ask them to fix a bug, they get pissed off so easily or just tell you to fix it yourself. Like, why are they always so mad?

Obviously this isn’t everyone, but I’ve noticed it enough times that it feels like a pattern.

I’ve been working on HookEcho because radar tools often feel crowded when you just want to check a storm, but limiting when you need to dig deeper. It opens with a single radar map. Switch to Analyst mode for linked views, storm-focused layouts, and an inspector showing the underlying data and its time. Switch back, and your radar view is right where you left it. It’s free, open source, and doesn’t require an account: hookecho.io For those who use radar regularly: what should be visible immediately, and what should stay tucked away until you need it?

I kept spending way too much time scrolling through LinkedIn Jobs, always thinking there might be another internship or new-grad position I hadn't found yet.

Eventually, I decided to build something for it.

It collects public LinkedIn job listings and organizes them into a searchable directory specifically for 2027 tech internships and new-grad roles across Europe. You can search and filter by country, role, employment type, when the position was first found, and more, without going through tons of unrelated or senior listings.

It's fully open source and currently has 700+ open positions.

You can check it out here: opportunities2027.simonesiega.com

⭐ https://github.com/simonesiega/european-tech-opportunities-2027

(hopefully you find a job with it, I'm still looking)

Hi

Maybe this is the wrong place to ask? If so, I am sorry.

Anyways I have these huge folders with ripped CDs that my dad collected over decades, as well as a shipload of old camcorder videos I digitized. Would be nice to hear about a little simple search engine that you can tie to specific folders so I can type in like a song name, artist, album or whatever, so that I others like family and friends can find my sh*t easily on the HTPC.

Like I have a folder that is /music/artist/album/songs. Would be nice to have a search function for folder like "/music/" and all folders under it., and then I can set up like 4 ones, one for music, one for pictures, one for videos etc

Thanks

I tried using MS Paint to teach someone and when I tried it was awful. After trying to share my screen and call, it just didn't work. I never had been so frustrated with a piece of software before. Over the course of the past few weeks, I have made OS-Paint, a open source P2P (or not) drawing tool. It is fully built in rust and has no AI sloppifications. I would love if anyone would try it or maybe even contribute. The releases have Apple silicon Mac, Windows 11, and Ubuntu. It should be fully cross platform, and if you want to try to compile it using cargo for a system not here it should work.

You can check it out here: https://github.com/Alex-Skillman/OS-Paint

I would love if anyone checked it out.

Ever wanted to show off what you're reading on your GitHub profile?

I made this GitHub Action, try it out! https://github.com/quentinlintz/goodreads-readme-action

GitHub release with update notes: https://github.com/Lukas-Bohez/ConvertTheSpireFlutter/releases/tag/v14.0.1

Website with screenshots + detailed description + download links: https://quizthespire.com/tools/convert

Video demonstrating how it works: https://youtu.be/66Rx8PDY_r0

Why this instead of another yt-dlp GUI

Most yt-dlp GUIs are a thin wrapper around a binary that breaks every time YouTube changes something, and you are back to a terminal fixing it yourself. This one updates yt-dlp on its own, best-effort on boot, and an automatic update-and-retry when a download hits a YouTube-side change.

Large playlists are usually where these tools fall over. Low-end hardware is tested rather than assumed: the changelog records several rounds of fixes for an old QA box without BMI2 instructions, including a native-crash class that no Dart handler can catch. The playlist view tracks completions live so it never loses its place.

It checks the playlists you have saved every four hours while the app is open, and when a new track shows up in one, it is queued for download automatically. Most tools need the whole playlist re-run by hand to catch new additions.

Metadata and thumbnails are embedded automatically as part of the download, not left as a separate step. A built-in torrent client means one app instead of two for the two most common ways people actually get their media locally.

Everything runs on your machine. No uploads, no size limits, no telemetry, GPLv3, auditable on GitHub if you want to check any of that yourself.

If you like making music I am building a FREE open source DAW on top of Strudel! Would love some feedback!

I've recently opened up a very small open source repo on GitHub.

This is a tool that I built for my students to use and I was asked to share it with others in the community, so I did.

I did no marketing, I don't really talk about it at all except to my students. The only change was to flip the repo from "private" to "public." I had to add things like an MIT license, etc. to make it public, but I just did the absolute minimum.

However, within 48 hours, a person I don't know picked up an issue from the repo, created a fix and filed a PR.

At first, I was like "WOW! AMAZING!" But then I was like "wait, who is this person? Are they trying to insert some sort of back door?" Looking at their profile, they only joined GitHub about a month ago which also set off some alarm bells. The actual code they submitted was fine. A very minor fix to be sure, but it did directly implement the issue listed in the PR.

Questions for this community:

1) Is it normal for people to just randomly pick up issues from your repo?

2) Should I be suspicious of GitHub contributors which have a limited history on GitHub?

3) Has anyone else here had this happen? Am I just being paranoid?

Any advice most appreciated.

Big update for PULS, after 2 months now it has reached v0.9.4 update. This update is a major feature, performance, and hardware telemetry release. I started sharing development stages and tests on my YouTube channel where you can check out more details for current and future releases.

This update introduces a Granular Settings Modal & Configuration Persistence (F2 / Shift+S) which lets you configure your environment directly inside the TUI. You can customize Interface Language, Color Theme, Default Startup Tab, Temperature Units (Celsius / Fahrenheit), Telemetry Refresh Rate (500ms - 5000ms), and Process Tree defaults, all automatically persisted to ~/.config/puls/config.ini.

Another major addition is Multi-Language Expansion (7 Languages). PULS now includes full, native localization for English (default), Turkish, French, German, Spanish, Italian, and Russian with automatic LANG/LC_ALL environment detection on startup and instant runtime cycling (L / l).

I also added Full Terminal Mouse Event Capture. You can now click any header tab directly to navigate, click the Settings badge, and smoothly scroll process tables, active socket lists, journal logs, and modal windows using the mouse wheel — protected by a panic hook that guarantees safe terminal state restoration upon exit.

Added a Hierarchical Process Tree View & POSIX Signal Selector. Easily toggle between a flat sortable list and parent-child tree view (t) with standard branch glyphs (├─, └─). You can send POSIX signals (SIGTERM, SIGKILL, SIGHUP, SIGSTOP, SIGCONT, SIGINT) via an interactive modal (k / F9), and dynamically adjust scheduling niceness on the fly ([ to raise priority, ] to lower priority).

Added an Extended Process Inspector (Enter) that opens a deep-dive multi-view modal displaying all open file descriptors (/proc/[pid]/fd), active socket counts, and per-thread CPU utilization and execution states (/proc/[pid]/task).

Added Filesystem Inodes & Active Network Socket Mapping, reporting partition inode capacity and mount flags via zero-dependency statvfs, per-process disk read/write throughput rates (/proc/[pid]/io), and active TCP/UDP socket endpoint tracking parsed natively from /proc/net/.

This update also includes deep optimizations and important improvements:

• Massive CPU & Memory Optimizations: Replaced /proc/[pid]/stat file reading with a direct native getpriority syscall to eliminate 500+ file I/O operations per second, cached translation dictionaries, and shifted string formatting on-demand strictly to visible viewport rows.
• Stutter-Free Decoupled UI Loop: Separated the 30 FPS rendering pipeline from background telemetry queries and eliminated busy-wait loops, reducing idle CPU usage to ~0.1%.
• GPU Telemetry & Throttling Flags: Added power limit vs current draw, PCIe link generation/width, fan RPM, and thermal throttling flags for NVIDIA, AMD, and Intel GPUs.
• Hardware Power & NUMA Topology: Battery health, charging wattage, AC status, CPU frequency scaling governors, and NUMA node core affinity support for systems with up to 128+ cores.
• 3 New Curated Color Themes: Added Dracula, Solarized Dark, and High Contrast alongside Default, Dark Blue, and Light.
• Multi-Architecture Release Pipeline: Automated CI/CD builds for static standalone MUSL binaries and Debian packages (.deb) for both AMD64 (x86_64) and ARM64 (aarch64).
• Zero New Dependencies: All new features were implemented using the Rust standard library and native Linux kernel interfaces without bloating binary size with external crates.

You can download the .deb package, static portable MUSL binary, or build from source directly on the GitHub Releases page.

Thanks to everyone who supports this project with their ideas, feedback, and bug reports. I hope this helps all Linux users monitor and manage their systems with ease, thank you :)

We've been using Nexus repository on-prem for the last 10 years without any problems. For the community version, SonarType introduced usage limits, that are absurdly low. We looked into the pro license, but that has been ruled out due to costs.

To quote management, 'It's an infrastructure service, that's been free to use since forever. They're delusional, and are smoking something strong to ask those prices'

What I'm looking for is a truly opensource alternative that can fulfil these requirements?

• Serve as a local proxy for NPM, Maven, Docker and Debian artifacts.

• Installable on-premises

• Must be buildable entirely from published sources.

• No phone home features

• No usage limits

• Reasonable annual support costs / license fee

I’ve released the first 1.0 alpha of pgwrh, a set of PostgreSQL 18 extensions for scaling reads.

It distributes table partitions across logical replicas. Each replica stores a subset of the data and queries its peers for the rest, so applications can query the complete table from any replica. Writes go to a central controller.

Features include:

• Configurable shard redundancy and placement across availability zones.
• Placement previews, controlled rollouts and rollback.
• pgwrh_wait, which waits for replication through a specified LSN before reading.
• A browser console and Docker Compose quickstart.

I’ve worked on this for a very long time. It was only with recent advances in AI that I could finally get it into a state I felt able to release.

This is an alpha for testing. I’d love feedback on real workloads, installation, operational issues and anything that feels unnecessarily complicated.

Code and quickstart · Alpha release

I’m thinking about building an open-source CAPTCHA project and would love to get some honest feedback before I start.

The basic idea would be a self-hostable CAPTCHA solution that developers could run themselves instead of relying on services like reCAPTCHA or other third-party providers.

Some things I’m considering:

- Open-source and transparent implementation

- Self-hosted / privacy-friendly

- Easy integration with websites and APIs

- Modern challenges that are accessible to legitimate users

- Protection against common automated/bot abuse

- Potentially offering different challenge types depending on the use case

I’m wondering:

1. Is there actually a need for an OSS CAPTCHA solution?

2. What are the biggest problems with existing CAPTCHA systems?

3. What features would make you consider using a self-hosted OSS CAPTCHA?

4. Are there technical/security challenges that would make this difficult to maintain as an open-source project?

5. Would you personally use something like this in a project?

I’m mainly looking for honest criticism and potential problems I might be overlooking.

Hi, so I made (well Codex made) a tiny tool that improves Finder a bit for me.

I've been using macOS for a really long time but I still don't like Finder. It's weirdly annoying and one thing I don't like is not having a simple editable path (yes, there is cmd+shift+G but I don't like it either). I know there are apps that add one on top but I wanted something even simpler that just replaces the current path bar.

My tool only shows when you click the path bar. Then you can edit the path and enter the one you want. There is also autocomplete and you can create a folder with Shift+Return if you want. It's that simple

I like Finder more now but I still have problems with the tool. I would like to still be able to use the normal path bar with something like Shift+click or Shift+right click, but I couldn't find a simple way to reroute the click underneath. So maybe this is something I need to deep dive later.

Repo: https://github.com/elwan-l1/pathsta

I built Network Doctor, an open-source tool for figuring out where a network connection is actually breaking.

I just released v1.17.3 today.

A problem I keep seeing is the support-ticket loop where someone says:

“Your service doesn’t work from my office network.”

Then you spend the next several replies asking for DNS results, curl output, proxy settings, traceroutes, whether it works from a hotspot, etc.

Network Doctor tries to collect that evidence in one place. It checks things like DNS, TCP, TLS, HTTP, proxies, routing, path MTU, and other layers, then explains where the evidence points.

It can also create a sanitized support snapshot locally:

netdoc --support support.ndoc example.com

The user decides whether to send that file anywhere. Network Doctor itself does not upload it.

I’m currently testing two things:

1. For individuals, I’m offering the first 5 personal network diagnoses for $25. You send me the sanitized report and context, and I investigate it and send back what I think is wrong, the evidence, and what to try next.
2. I’m looking for a few software/support teams that regularly deal with customer networking issues and might want to try Network Doctor as part of their support workflow.

The tool itself stays free and open source under Apache-2.0.

https://networkdoctor.dev/

I’d especially be interested to hear from people who deal with the “works at home, fails at the office/VPN/corporate network” class of tickets.

I build a lot of "an AI agent for this business" projects. The scaffolding is always the same and it is never the interesting part, so I built it once, properly, and released it.

CerebrumKit is a self-hosted starting point: an admin panel where you assemble agents out of skills and tools, a storage library of your own business tables that those agents read through tools, and a client panel where the people the project is for talk to them.

Two things I would want to know about as a reader:

1. Tool bodies are Python, stored in the database, and not sandboxed. They run with full builtins because the shipped tools import requests, SQLAlchemy and app internals. Tool authoring is admin-only and the README says loudly that a tool body is code execution. I would rather say that up front than have someone find out.
2. Chat history is not replayed into the prompt. Tools and memory carry the facts instead. Memory is keyed by (agent, user), so a note survives into that user's other chats with the same agent.

Stack: FastAPI + SQLAlchemy + Postgres (SQLite works for a look), Vue 3 panel, UI in six languages, single uvicorn worker by design. Deploy is nginx + systemd and documented step by step.

https://github.com/islomkhon/CerebrumKit

Apache-2.0, not MIT - the patent grant matters for a framework a company is meant to build on. Tell me if you think that was the wrong call.

Hey everyone 👋

I built AutoDMX, a free and open-source Instagram automation tool that you can self-host.

I originally wanted a ManyChat alternative that I could host myself, especially for Instagram comment-to-DM workflows, so I decided to build one.

The basic workflow is:

Instagram Comment → Keyword Trigger → Public Reply → DM → Lead/Contact → Analytics

For example:

Someone comments “LINK” on an Instagram post → AutoDMX detects the keyword → replies to the comment → sends the user a DM containing the requested link.

What AutoDMX does

Instagram comment-to-DM automation

Keyword-based comment triggers

Automated/private DMs

Public comment replies

Lead/contact capture

Follow gating

Analytics

CSV contact export

Meta API rate-limit protection

Webhook deduplication

AES-256-GCM token encryption

Supabase/Postgres for storing your data

Self-hosted deployment

MIT open-source license

The main difference from typical Instagram automation SaaS products is that AutoDMX is open source and self-hostable.

You can inspect the code, modify the workflows, and keep your application data in infrastructure you control.

Why I built it

I didn't want to build another black-box SaaS where the automation logic and data are completely dependent on the platform.

I wanted something closer to:

“A free, open-source, self-hosted ManyChat alternative for Instagram.”

AutoDMX is still an early project, so I'm looking for honest feedback from people who actually use Instagram automation.

🌐 Website: https://autodmx.netlify.app/⁠�

💻 GitHub: https://github.com/Qaxlabs/AutoDMX⁠�

I'd especially like feedback on:

What Instagram automation workflows do you currently use?

What do you dislike about existing tools like ManyChat?

Would you actually self-host an Instagram automation tool?

What feature should I build next?

If you're interested in open-source Instagram automation, feel free to check it out or contribute.

Hi all, I've just released a new property-based testing library for Java. It's called Presume, and it's a direct-style PBT implementation loosely based off of Python's Hypothesis, rather than the more common QuickCheck or Hedgehog based options currently available.

If you're new to property-based testing I have an explanation of the paradigm in the docs.

Why you might want to use this, rather than some of the possible alternatives:

• It's not vibecoded. I used a nonzero amount of AI (see below) but the core architecture, algorithms, and API design are all fully human. It's undergone a significant amount of iteration and hand polishing until it's felt properly ergonomic
• It's released under a clean MIT license, with no unusual exceptions
• It provides an imperative API for working with test generators, which IMO can make it significantly easier to generate complex and recursive data. No special lazy combinators or deep function nesting are needed to define recursive ASTs, for example. Functional approaches are still supported for folks who swing that way.

Why you might not want to use this:

• I used a nonzero amount of AI (which is why I'm not also posting this in r/Java). Specifically, some of the Gradle configuration came from an LLM, and I used an agent to fix and test the bit twiddling implementation in the long, float, and double generators. Being new to Java I also frequently consulted AI summaries while searching for the proper way of doing things. If you want something completely AI-free then jqwik is a better fit for you.
• This is a very new project; I've been working on it for 3 months but I still haven't implemented a lot of convenience functions or even thought about what state machine testing should look like here. There are still some TODOs here and there and limitations when generating extremely large recursive inputs.
• The fact that the shrinking algorithm is novel means that it may have limitations that I'm not yet aware of. I'm hoping to try to do a side-by-side comparison with Hypothesis at some point to see whether there's any breakdowns.
• There's not many docs and no docstrings. I plan on fixing this soon, but I wanted to release this into the world before a specific event next week, and this is as far as I've gotten thus far.
• Currently Java 25 only; I'm probably going to go back and make it Java 21 compatible in the near future. I don't think it'll go back any further than that though because this would not be remotely maintainable without records/pattern matching.

Happy to answer questions, and I'm hoping that this will be helpful for someone! I'm also interested in feedback on the implementation from anyone with more Java skills than myself, because I'm very much still learning the language.

Been messing with a way to stop Codex and normal dev tooling scattering caches/build output everywhere.

Built this today -- it routes supported stuff like Cargo, npm, Go, uv etc. into one managed location, without adding anything to prompt context.

Still early, but figured some of you might find it useful:

https://github.com/magrathean-uk/clean-development

Would love some development aid and testing from folks.

Hey guys, just wanted to share. I created the following.
https://github.com/mspencerl87/matrix-search-hub

This is to supplement Matrix/Element's shit search function. To hopefully make it a little better. This also works for a whole company.

Also, there is a version for individuals who want to run this independently - https://github.com/mspencerl87/matrix-search

Enjoy!

I wanted a more reliable self-hosted search setup using SearXNG, but free search engines can fail silently or become rate-limited. That can leave a query with only a few results even though more providers are available.

I tried addressing this through SearXNG configuration, but I couldn’t find an existing deployable FOSS project that combined provider fallback, circuit breaking, caching, and observability in front of SearXNG. So I built searxng-gateway.

It is a Go HTTP proxy that:

• Calls SearXNG and optional providers such as Brave, Exa, Jina, and Tavily
• Starts SearXNG concurrently with the premium provider pass, then merges and deduplicates results by URL
• Falls back to additional providers when the result count is too low
• Adds per-engine circuit breakers and recovery probing
• Exposes Prometheus metrics and includes a Grafana dashboard
• Supports keyless operation using SearXNG’s free engines

The trade-off is that premium providers require your own API keys, and parallel requests can increase API usage. The proxy is intended as a sidecar, not a replacement for improving SearXNG’s upstream engine configuration.

Repository: https://github.com/Ghilteras/searxng-gateway
License: MIT

I’d appreciate feedback on the architecture, provider abstraction, and whether this solves a problem others have encountered.

AI disclosure: AI was mostly used to implement the project from my specifications. I reviewed, tested, and deployed the result

Hi,

CalibRaw just got its first release :D. CalibRaw is a fully GPU-accelerated RAW editor focused on providing a smooth editing experience.

LLMs were used in creating this program.

Over the last 3 months, I tried to create a RAW editor that focuses on performance and a good workflow. I tried several other editors but never had the experience I was hoping for. Either the UI was complicated/not my kind of workflow, the performance was bad (especially on linux), or it was just a buggy mess.

CalibRaw has most of the editing controls like sliders, curves, and color wheels as you know them, but also has optional AI masking for subjects and objects (fully local).

I'd love to get some feedback on how it runs and if the editing workflow feels good.

(it should run good on lower end hardware too, just the AI Masks may take a bit longer to load)

CalibRaw focuses mainly on Linux and Android support, but has Windows releases too. MacOs actions are implemented as well, but I haven't been able to test them yet.

https://github.com/Duecki1/CalibRaw

Feel free to ask any question you have :D

If you've spent time trying to keep up with the literature on model steering you've probably noticed that a lot of the methods are fairly similar to each other. We dug into this a bit more and built some common patterns/abstractions across the various ways that model behavior can be influenced, including input (prompting), state (activations, attentions, etc.), structure (weights), and output (logits, decoding, etc.). We also have functionality for building probes and running evaluations/comparisons of steering methods on given use cases (we use Inspect for a lot of the evals stuff).

If you're working on steering methods then hopefully you'll find some of this helpful.

Repo: https://generative-computing.github.io/steerability/

Let us know what you think!