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TensorVizionย 
posted an update about 1 month ago
unmodeled-tylerย 
posted an update about 2 months ago
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Centauri ADE: https://github.com/unmodeled-tyler/centauri

This is Centauri - It's a lightweight Agent Development Environment for Linux with git source control and codebase understanding.

I've tried out several different IDE/ADEs and nothing has really worked as well as I'd like for what I need. For the options that I did like, BYOK was second-class, or in the case of a full IDE, it sometimes felt like I was trying to get an airliner into low-earth-orbit.

Enter: Centauri - a simple local-first CLI harness wrapper with a focused git source-control workspace.

It gives you a clean side-by-side flow:
- run your preferred CLI coding agent in an embedded terminal
- watch repository changes appear in the Changes panel
- generate an industry-standard commit message
- commit and push without leaving the app

It's designed to complement tools like Claude Code, Codex, Pi, OpenCode, etc. It does not replace Git, your terminal, or your existing credentials - it wraps the tools you already use into a tighter cohesive workspace optimized for engineering with an agent.

I built Centauri for myself after trying way too many different options. It solves several pain points for me and I'm sharing it in case it solves some for you too!
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unmodeled-tylerย 
posted an update 2 months ago
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The UFO/UAP Dataset is complete!

unmodeled-tyler/DoW-UFO-UAP-1

The most recent release from the Department of War is there up in full and ready for analysis!

The dataset ships with an Hermes Agent Skill so you can quickly and easily start parsing through the data immediately.

Go chase some anomalies! ๐Ÿš€

unmodeled-tylerย 
posted an update 2 months ago
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Just started a fun project!

unmodeled-tyler/DoW-UFO-UAP-1

I'm getting the recently released DoW UFO/UAP documents (https://war.gov/ufo) cleaned and converted into a dataset here on Hugging Face!

There 161 different files in the gov release (pdfs, images, videos, audio, etc) and my current plan is to do it all in 1 dataset with 4 different shards - that way you can just call whichever tables you want/need when you import the dataset.

This is an ongoing project (I'm doing it on the side + my regular projects) so it's a bit of a growing entity. I'll also continuously refine the data over time to make sure it's as clean as possible.

Check it out! Who knows what you'll find in there?
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