manueljpconde lets mikeEU run on your own hardware

A new self-hosted model option means operators can keep inference inside their own walls.

infrastructuresecurity

manueljpconde has wired mikeEU up to talk to local model runners like Ollama and LM Studio - tools that let you run an AI model on your own server instead of sending every conversation to a hosted provider. For firms with data-sensitivity concerns, that's the whole ballgame.

The plumbing is careful. The local endpoint's address and credentials stay on the backend; the user-facing app only learns that a local option exists and roughly what it can do. Function-calling - the AI's ability to invoke tools mid-conversation - is switched off by default, because many self-hosted models handle it unreliably. An operator has to explicitly turn it on, and until they do, the local provider quietly hides from the parts of the interface that would offer features it can't deliver.

So what Relevant to any legal team that has been told 'we can't send client data to a third-party AI' and wants to see what an on-premise path actually looks like.

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 manueljpconde/mikeEU, oldest first. Source extracted verbatim from the harvested git log.

SHA Subject Author Date
c0361944 feat: add self-hosted local llm provider Manuel Conde 2026-05-09 ↗ 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-255.md from inside the repo you want the changes in.

⬇ Download capture-thread-255.md