Everlock 0.6.2
The 0.6.2 release brings captions to photo frames and a round of substance fixes: self-update no longer needs three binaries' worth of memory, image previews cache like the immutable content they are,
Documentation
Tag: ai
AI model variants
Every Everlock build embeds **one** vision-language model, and which one it carries decides the AI runtime's capabilities — how strong its answers and captions are, and how much memory and disk it nee
The gguf-runner inference engine
Everlock runs its AI features on its own inference engine, [**gguf-runner**](https://github.com/apimeister/gguf-runner) — a self-developed, from-scratch GGUF runtime written for this project. It is em
AI backend
The AI backend is Everlock's built-in operator assistant and shared vision runtime. It is exposed in two places: - an interactive prompt mode inside the admin SSH session - image captioning for the im
AI runtime and access model
Everlock embeds a small LLM and exposes it in two places: 1. as a free-text prompt mode inside the admin SSH session (`backend-ai-ssh` + `backend-admin-ssh` + `frontend-ssh`) 2. as an image-caption
Shared AI runtime crate
The embedded LLM that powers the admin SSH prompt mode has been factored out of `backend-ai-ssh` into its own shared crate, `everlock-ai-runtime`. - A new `crates/ai-runtime` crate owns the heavy reso