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MooshieUI is a beginner-friendly graphical interface for ComfyUI, an open-source Stable Diffusion inference backend. It abstracts ComfyUI's node-graph system behind a clean, guided UI so users can generate images without manually building or editing workflow graphs.
Available as a desktop app (Windows/Linux via Tauri) and a self-hosted web app (Docker/LAN). Source builds are supported on macOS.
Generation Modes
- Text to Image: generate from prompts
- Image to Image: transform an existing image with adjustable denoise
- Inpainting: selectively repaint areas using a built-in mask editor
Notable Features
- Smart model detection: auto-applies optimal sampler, CFG, and resolution presets for 13 model architectures (SD 1.5, SDXL, Illustrious/NoobAI, Flux, Pony Diffusion, SD3/3.5, AuraFlow, Anima/COSMOS, and more)
- Tiled diffusion upscaling: built-in MultiDiffusion and SpotDiffusion for seamless high-resolution output
- Compare Grid (XYZ): multi-cell parameter sweeps that auto-stitch into a labelled comparison image
- LoRA support: unlimited LoRAs with per-LoRA strength sliders and enable/disable toggles
- Danbooru tag autocomplete: ~100k tag database for prompt assistance
- One-click installer: handles Python, PyTorch, and ComfyUI automatically on first launch; no manual setup required
- 11 languages: full i18n with 860+ translation keys
Custom Nodes
MooshieUI ships custom ComfyUI nodes auto-installed at launch:
- MooshieSoftGuidance: CFG rescale to reduce hallucinations during upscale passes
- MooshieSmartGuidance: positive-biased adaptive guidance
- Tiled Diffusion: MultiDiffusion and SpotDiffusion implementations
- MooshieFaceFix: YOLOv8-based face detection and re-denoising
- SDXL and Flux VAE adapter: for Mugen (128-channel Flux2 latent) models
- Nanosaur support: loader, text encoder, and VAE decode for the 1.2B DiT architecture
Links
- GitHub Repository
- License: GNU AGPL v3.0
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