Introducing CHOMATO: A lightweight harness for LFM 2.5 with superpowers.

Have you ever wondered how cool it would be if your harness could: - Branch the KV-cache without huge buffers. - Attach precalculated context blocks however you please. - Give perfect structured responses in any shape you'd like. - Run on the backend, frontend, or anywhere WebGPU works. - Do all of that in less than 1 GB of RAM. I definitely wanted one, and since there wasn't any - I built my own. The GUI is mostly for diagnostics (styled after Classic Mac OS), but you can check out the live online demo here: https://3ksoft.github.io/chomato/ Code: https://github.com/3ksoft/chomato (AGPL-3.0). It also uses two libraries I've authored - they aren't on npm yet, but current versions are available on my GitHub under the MIT license. The API is a bit unusual if you're used to traditional ones: const result = await engine.generate( type({ id: "number", name: "string < 64" }), { checkpoint, blocks }, ); Basically, sparse (structured) mode is the engine default. If you just want plain text, you use type("string < max_length") . Hope you'll have as much fun using it as I had while building it! Top comments (0)