Maverick XR Agent for Unity 1.0.0

Maverick XR Agent for Unity 1.0.0

Maverick brings local natural-language scene control to Unity. Give it an English command such as “put the red mug on the counter” or “find the broom,” and it selects tools and objects from the scene description supplied by your application. When several objects fit, it can ask the user to choose.

This is the first GitHub distribution of the Unity package previously published on Hugging Face. It includes the runtime and editor source, an expanded installation guide, integration examples, model download instructions, and documentation of the published evaluation and current limitations.

View the 30-second demo (MP4, 7 MB).

Install

In Unity, open Window > Package Manager > + > Add package from git URL:

https://github.com/ErenAta16/Maverick-Unity.git#v1.0.0

Choose Tools > Scene Agent > Open Model Folder, then add a compatible Windows llama.cpp runtime and the GGUF model to Assets/StreamingAssets/SceneAgent/.

Download the Q4_K_M model · Installation guide · Model checksum

The model is approximately 2.50 GB and remains hosted on Hugging Face. The source archives for this release contain the Unity package and documentation; they do not include model weights or inference binaries.

Included in this release

• Local llama.cpp server startup and shutdown, with a GPU-first launch path and CPU fallback.
• Eleven tools for object interaction, room changes, search, and clarification.
• Output checking and scene-level action constraints.
• A command session interface for typed text or speech-recognition transcripts.
• Mouse or camera-center gaze targeting and a desktop chat interface.
• Editor tools for setup, object registration, and scene validation.
• A command script runner that records tool results, scene signatures, and timings.

The documented configuration targets Unity 2022.3 or later on Windows x64. The published measurements used an RTX 3050 Ti laptop GPU under Windows 11, with Unity rendering at 30 FPS. Standalone XR headsets, Linux, and macOS have not been validated.

Voice recognition, XR interface design, player rig movement, and scene-specific animations are supplied by your application. See the integration guide and known issues.

The runtime code matches the previously published Hugging Face package at revision 1bb8c83224fd470b1a25fac1ee74ce83ac489c44. The GitHub release adds documentation and repository metadata; it does not introduce new model weights or claim a new benchmark run.

The Unity package is available under the MIT License. The model is distributed separately under Apache-2.0.

Developed by Eren Ata at the Extended Reality Laboratory (XRLab), Manisa Celal Bayar University.