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UniRig

Process
@DrHepa· Jul 2026
About

Modly extension for UniRig processing, automatic rigging, and 3D character rig preparation.

Repository
https://github.com/DrHepa/UniRig-workspace_extension_modly
View on GitHub
Install in Modly
  1. 1
    Open “Models” in the app
    Go to the Models page and click Install from GitHub.
  2. 2
    Paste the repository URL
    Use the Copy button above, then confirm the installation.
  3. 3
    Download the model
    Once installed, download the model or one of its variants.
Documentation

From the project README

This repository is a thin wrapper around upstream UniRig for Modly's public process contract.

The wrapper owns only three things: the stable Modly entrypoint (manifest.json → processor.py) deterministic upstream staging and readiness verification in setup.py protocol adaptation plus sidecar handoff in src/unirigext/

Everything else is upstream-first: the wrapper stages a pinned UniRig checkout, verifies it, then delegates extract/inference work to upstream commands.

What stays stable node id: rig-mesh stdin payload: input.filePath, input.nodeId, optional params.seed, params.metadatamode, params.generationprofile, plus top-level host workspace fields such as workspaceDir / tempDir stdout event types: progress, log, done, error success result shape: {"filePath": "...unirig.glb"}

The processor emits Modly-visible log events for each upstream stage start: extract-prepare, skeleton, extract-skin, skin, and merge. Stage failures keep the public JSON event shape stable, but the error.message now includes a bounded Diagnostics: block with runid, stage, errorcode, expectedoutput, stagelog, return code, and sanitized stdouttail / stderrtail excerpts.

Read the full README on GitHub →
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