v1.1.1 - 2026-07-22

Release Notes

Tool calling now reaches the models served by the Python sidecars (#5). MLX builds from the Hugging Face cache — Llama and Qwen instruct models among them — can drive the coding harnesses and serve tool requests over the gateway, closing the gap where capable weights sat out of hedos launch because their runtime never forwarded tools.

• The mlx-lm sidecar renders a request's tools through the model's own chat template, so each model family sees tools in the exact format it was trained on. A template with no tool support gets a generic system-prompt description of the tools instead, and a template that rejects a system role gets it folded into the first user turn — the request degrades gracefully rather than failing.
• Tool calls are parsed back out of the model's reply in each family's own format — Qwen/Hermes <tool_call> blocks, Mistral [TOOL_CALLS], Llama's python tag and bare JSON — and served over the gateway as structured calls in every dialect. A reply that contains no call streams as plain text, exactly as before.
• mlx-vlm gets the same treatment, so tool-driving harnesses can also seat vision models.
• Models served by these runtimes now carry the tools capability on the shelf and appear in the hedos launch picker; an existing shelf picks this up automatically on the next command, no rescan needed.

Install

curl -fsSL https://hedos.ai/install | bash

Cargo

cargo install hedos

Homebrew

brew install theiskaa/tap/hedos

File	Platform	Checksum
hedos-aarch64-apple-darwin.tar.xz	Apple Silicon macOS	checksum
hedos-x86_64-apple-darwin.tar.xz	Intel macOS	checksum
hedos-aarch64-unknown-linux-gnu.tar.xz	ARM64 Linux	checksum
hedos-x86_64-unknown-linux-gnu.tar.xz	x64 Linux	checksum