omm import
Scan every supported local AI app for .gguf files omm doesn't manage yet, and offer to adopt each one into the hub.
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Overview
Reach for import when omm scan's "Found model file(s) outside the omm hub" note shows up, or any time you know a runner has models you downloaded outside of omm. It scans every supported app's model directory (and an optional extra path you pass) for files not yet registered, then offers to adopt each one — moving it into the central hub and linking it back in, so a byte-identical copy stops sitting in two places.
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Options
Every flag this command accepts, and what it defaults to when you leave it out.
[path]—Default: none — scans the usual app directoriesAn extra directory to also scan, beyond the usual app directories.
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Examples
From a plain search to something you'd put in a script.
Scan the usual app directories.
$ omm importAlso scan an extra directory.
$ omm import ~/DownloadsAdopt everything found without asking about each one.
$ omm import --yes04 / 06
A real run
Real omm import run, 2026-08-25, driven end to end through a real terminal: two copies of the same real GGUF (one already installed on this dev machine) were planted under a throwaway extra directory so import would find a genuine duplicate to adopt, instead of a real ~/Downloads that happened to have nothing stray in it. import found both real copies, asked to confirm, showed the real pre-checked picker, and actually moved the file into a throwaway hub — the 0.5 GB saved is real disk space reclaimed by deduplication, the whole reason this command exists.
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If something goes wrong
Every message below is one this command actually prints. Find yours, read why it happened, then do the last line.
No externally-managed .gguf files found.- why
- Every supported app directory (and any extra path passed) came back with nothing import doesn't already manage.
- what to do
- Nothing to do — there's nothing stray to adopt right now.
- source
- src/omm/cli.py:1421
Not a directory: /definitely/not/a/real/directory- why
- The extra path passed doesn't exist or isn't a directory.
- what to do
- Double check the path, or omit it to just scan the usual app directories.
- source
- src/omm/cli.py:1490
Still stuck? Open an issue with the exact message you saw.
All commands
- omm searchFind a model across the curated catalog, HuggingFace and ModelScope.
- omm installDownload a model into the hub and link it into every installed runner.
- omm runChat with an installed model — in the terminal for Ollama, or by opening the app for GUI runners.
- omm recommendGet a model suggestion ranked for this machine's hardware, with an offer to install it.
- omm contributeBenchmark models in a loop, uploading telemetry to improve recommend for hardware like yours.
- omm setupRe-run the hardware scan and runner-install checklist, any time.
- omm scanPrint this machine's hardware, detected runners, and models — no flags needed.
- omm tuneGet recommended context length, GPU offload, threads, and batch size for a model.
- omm fitSee whether a model fits this machine's free memory right now, installed or not.
- omm helpShow omm's own command summary, or the full reference with --all.
- omm uninstallRemove a model and clean up its symlinks and manifests. Alias: rm.
- omm listShow every model omm has installed and which runners each is linked into. Alias: ls.
- omm infoShow full detail — repo, version, size, links, run commands — for one installed model.
- omm upgradeRefresh installed models against their source — only re-downloads what's actually changed. Alias: up.
- omm linkRe-verify and repair every installed model's runner links, or link into a custom directory.
- omm cleanupClean up leftover partial downloads and broken runner symlinks in one pass — no flags needed.
- omm verifyProve that an installed model actually loads and generates text on this machine.
- omm benchmarkLocal quality and speed smoke evidence for one or more installed models.
- omm updateReinstall omm from the latest source and refresh its recommendation data.
- omm settingView or change omm's settings — telemetry, outbound data, theme, update channel, and more.
- omm doctorDiagnose the omm install and Ollama links, read-only — no flags needed.
- omm engine installInstall one local AI runner program directly, skipping the setup checklist.
- omm logRead the local run log: what omm ran, when, and whether it worked.
- README — UsageEvery omm command, one line each.