I still haven't found an open source note taking app I like, that I can also self-host and access remotely. I tried Logseq but that wasn't for me, which means for now I am stuck with Obsidian which is good but unfortunately closed source. Its also unfortunately local only and any established ways to get remote access has essentially been using KasmVNC, not a very convenient solution.

So, Ignis shims the Electron and Node APIs that Obsidian uses, and by doing so lets the app run in a browser. It works mostly just like on desktop, with some features requiring more involved workarounds. And naturally plugins may or may not work depending on what APIs are used and if they've been shimmed yet.

No obsidian code is shipped with the project, the docker image downloads the official obsidian release and serves it unmodified into the shimmed page.

License: AGPL-3.0
Live Demo: https://ignis-demo.thiefling.com/

Hi, I made this tool because I really like automation. I also don't really like electron apps and AHK for me just isn't cut for the job. I pretty much got incredibly tired of fighting Windows to do basic system automation. AHK scripts broke the second a window loses focus, and scheduler is a nightmare to manage sometimes.

I call it project arbiter, its basically just a system tray app with apis open and listening for inputs or files which consumes around 6-14 mb of ram in my experience. Arbiter also has a forge ui executable to basically allow the user to draft and create the rules (decrees). Also a lot of other context variable and security related rulings. Pretty glad that I got this application up and running, would love to hear what yall will say.

Repo: [Sid-352/Project-Arbiter: Automation engine written in rust](https://github.com/Sid-352/Project-Arbiter)

License: MIT

Hey guys! We finally opened up the codebase for something we've been working on for over a year.

I joined a company that spent 3 years (and counting) trying to ship products on locked down edge hardware. Every product kept hitting the same walls: deployments and monitoring were a black box, machines on the same LAN couldn't reliably find each other, and every new app had to reimplement the same WS/MQTT logics just to stay in touch with the cloud.

So we built Edge Core to solve these pain points. In V1, we used Headscale/Tailscale for the VPN. It worked mostly for what we wanted (remote execution, SSH, metrics aggregation, etc.), but couldn't scale past ~100 nodes (mesh explosion with O(n2)) and gave us no isolation between different projects (each project must spin up its own core, though ACLs exist). In V2 (current version), we moved towards Netmaker for a proper mesh/network segmentation solution, added a forward proxy + dynamic proxy chaining for cloud-to-edge communication, and built the whole orchestration layer on top.

Some stuff that might interest you:
- API-first control plane and MCP server that mirrors the full REST API, basically every API endpoint is also an MCP tool that AI agents can drive the whole fleet.
- Clustering HTTP/SOCKS5 admin proxy servers allow cloud-to-edge communication through just good old HTTP. WS/MQTT can now be an option, not the default. You can even proxy chain requests to reach any devices in the LAN without them even participating in the system at all.
- First class fleet metrics aggregations through admin with discovery + scraping that are Prometheus compatible.
- Webhook and event broker integration for async events with 7 adapters: NATS, Kafka, AMQP 0.9.1/RabbitMQ, Redis, MQTT, AWS SNS, and GCP Pub/Sub.
- Masterless clustering for the control plane: no (strong) leader election, no Raft consensus. Admins coordinate via in memory registry and Postgres. Each admin runs the same deterministic sharding algorithm and converges independently. We do support Sqlite for small deployments but it won't be able to cluster when you need to scale up later.
- Agent and shared libs are Apache 2.0. Admin is ELv2.

Links:
- Repo: https://github.com/wenet-ec/edge-core
- Docs: https://wenet-ec.github.io/edge-core/
- Learn about edge core's concepts: https://wenet-ec.github.io/edge-core/guide/
- Architecture: https://wenet-ec.github.io/edge-core/architecture/

Hey Reddit,
I am the creator of agent-qa.

AI has accelerated development which allows devs to build products at lightning speed. But the confidence whether it works isn't there. Though coding agents can write tests on their own but they greedily writes tests to make them pass.

The intention of building agent-qa is to provide an AI native solution to E2E testing.
I have used playwright as a kernel for executing planned actions in the QA harness.

Looking forward to feedback.

GitHub - https://github.com/vostride/agent-qa
Consider giving it a ⭐
Thanks!

Demo - vostride.com/

I created this website in my spare time https://hospitalpricesearch.org/

You can search by procedure name or code, filter by your insurance and search the entire state or in your vicinity.

This is free open source software. More details and the code at https://github.com/githubbar/hospital-price-transparency

Hi everyone! I’m hoping to crowdsource some ideas.

Long story short I’m a Physician Assistant interested in using an AI scribe to help me with my notes, which are the most tedious aspect of my job.

However, I have severe distrust in any of the big tech companies and pre-existing AI scribes.

Obviously, I have concerns over how any AI company will utilize my user generated data, and I certainly don’t want any of my medical decision making to be used to train an AI model in the future. (Laugh all you want, I’m putting on the tin foil hat as I type)

I’ve done some research on open-source AIs that run locally on a personal device. They’re free and don’t come with the potential for misuse of my personal data by a third-party.

Does anyone on this sub have any good suggestions for an open source AI that could potentially be used as a medical scribe? What sort of hardware would I need? For example could it run off of a raspberry pi?

Thanks!

Edit: to be clear my plan is to use it primarily to write the discussion/plan section of my notes which for me is typically free text and takes the most amount of time. I’m not interested in having a fully integrated AI that can pre-select orders for me. At least that’s my vision for it right now haha!

I’ve spent the last few weeks testing a few of the big names:

• Crew Ai
• LangGraph
• Lyzr AI
• Microsoft Autogen

My quick take:

• CrewAI is probably the easiest to get started with if you want role-based multi-agent workflows.
• LangGraph gives you the most control and is great when you need complex, stateful workflows.
• AutoGen is very flexible, but I found the learning curve a bit steeper than some of the newer frameworks.
• Lyzr Architect stood out to me because it abstracts away a lot of the infrastructure and deployment work, making it easier to go from idea to production faster.

Each one has a different philosophy but it's impressive how much engineering effort these tools can save if you're building agent-based applications.

Curious what others are using and which framework has held up best in real-world projects.

Quick question about GPL compliance: Is u/Revopoint3D-Official aware that any software incorporating GPLv3 code must also be open-source and have its source code published?

I'm open to being corrected here, but looking at how the current BambuLab situation plays out, shouldn't Revopoint be publishing the source code they use to stay compliant?

I bring this up specifically because of Revo Mirror, which openly utilizes LizardByte’s Sunshine (licensed under GPLv3). Which can be easily found by browsing the installation directory - example from the "sunshine.log" in the "Revo Mirror\config" directory:

https://preview.redd.it/bmc9etor0y1h1.png?width=956&format=png&auto=webp&s=3a119bc0113c874ed4937734034d62fc78cee8fb

Maybe I am just blind, but I haven't been able to find any open repository publishing the source code they are using.

Just shipped MAGDA 0.8.0 and thought people here might find the DSP side interesting.

MAGDA is an open source cross-platform DAW (JUCE + Tracktion Engine) and this release is heavily built around FAUST. Almost the entire FX bank is now written in FAUST and compiled to native C++ at build time.

The new filter device alone includes SVF, Ladder, Korg35, Oberheim SEM, Sallen-Key and diode ladder models. Reverbs, modulation FX, delays, dynamics, pitch FX, etc are now FAUST-based too.

There’s also a Faust device inside the DAW where users can write .dsp directly in-app, or generate FAUST code from a natural language prompt through the AI panel. Right now this path uses the interpreter (not JIT yet), so CPU usage is much higher than the build-time compiled devices.

Project: https://github.com/Conceptual-Machines/magda-core
Download: https://magda.land
FAUST: https://faust.grame.fr/

Happy to answer questions about the integration/build pipeline if anyone’s interested.