manueljpconde plugs Mike into self-hosted local models

A fourth model option lets self-hosters point Mike at a model running on their own hardware instead of a cloud provider.

infrastructuresecurity

The fork adds a 'local' provider that talks to any OpenAI-compatible endpoint - meaning tools like Ollama or LM Studio, which let you run open-weight models on your own server. The switch is backend-only: the admin sets the model and credentials in environment variables, and the browser only ever learns a friendly label and whether it's turned on. Secrets stay on the server.

The interesting work is in the guardrails. Many self-hosted models can't reliably use tools, so when tools are off, the system prompt explicitly warns the model not to pretend it did. The tabular-review feature, which depends on tools, is hard-blocked from running on a local model unless the admin confirms tool support - quietly falling back to a known-good model instead. The dropdowns hide the local option entirely until the backend says it's ready.

So what Relevant for any firm or legal-ops team weighing on-prem AI for confidentiality or cost reasons - this is a credible path to keeping client data off third-party model providers.

View this fork on GitHub →

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

Commits in this thread

2 commits from manueljpconde/mikept, 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
c8ef360f Merge pull request #2 from manueljpconde/codex/local-llm-provider Manuel Conde 2026-05-09 ↗ GitHub
Add self-hosted local LLM provider support

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