elitan teaches Mike to run its AI on your own hardware

A fourth model option lets the fork answer without ever calling a cloud provider.

infrastructureintegration

elitan wired in Ollama, a tool for running AI models locally on your own machine, as a fourth engine alongside the cloud heavyweights the fork already speaks to (Anthropic's Claude, Google's Gemini, and OpenAI). It ships switched off by default; an operator turns it on with a single configuration flag, after which the local models show up in the picker.

The interface side is just as plain. When a local engine is available, the models page grows a one-click button to swap whatever cloud model you're on for a local equivalent. Nothing about the existing cloud paths changes - this is a bolt-on alternative, not a rewrite. The set of local models on offer is deliberately small, so any team adopting it would pick its own.

So what Worth a look for any practice that can't or won't send client material to a third-party AI service and wants the option to keep everything on its own machines.

View this fork on GitHub →

Spotted something wrong? Or know the PR text has fresher detail than the writeup above?

Commits in this thread

1 commit from elitan/mike, oldest first. Source extracted verbatim from the harvested git log.

SHA Subject Author Date
ee082703 feat(llm): add ollama support Johan Eliasson 2026-05-15 ↗ GitHub

Capture this thread into my fork

Download a single Markdown prompt that tells Claude how to port every commit above into your working tree — adapting paths and structure to match your repo. Run it via claude -p < capture-thread-412.md from inside the repo you want the changes in.

⬇ Download capture-thread-412.md