z-vision-generator 0.6.2

Z-Vision Generator — cross-platform AI image and video generator

Z-Vision Generator

Local AI image and video generation — hassle-free and fun. No tangled node graphs, no cloud dependencies, just prompts and results. Runs on macOS (Apple Silicon / MLX) and Windows (NVIDIA / CUDA), tuned for an M-series Mac with 32 GB unified memory and an NVIDIA RTX 3080.

Features

• Image generation — text-to-image with Z-Image and FLUX.2 Klein (4B/9B) model families
• Video generation — text-to-video and image-to-video with LTX-2.3 (macOS)
• Cross-platform — automatic backend selection: MLX on macOS, CUDA on Windows
• Prompt system — YAML prompt files with variables, structured prompts, snippets, and batch runs
• Model store — central ~/.ziv/ directory with bare-name resolution and HuggingFace fallback
• LoRA support — single or stacked, configurable weights, bare-name resolution
• Image upscale — generate small → Lanczos → img2img refine → CAS sharpen
• Video upscale — distilled-only two-stage 2× spatial upscaling
• Reference images — img2img steering from any starting image
• Quantization — 4-bit and 8-bit on both platforms
• Post-processing — contrast, saturation, and CAS sharpening (image only)
• Interactive controls — skip, quit, pause, and repeat during batch runs (image only)

Platform Support

Platform	Image Generation	Video Generation
macOS (Apple Silicon)	✅ Z-Image / FLUX via mflux/MLX	✅ LTX-2.3 via MLX
Windows (NVIDIA GPU)	✅ Z-Image / FLUX via diffusers/CUDA	❌ Not supported

Installation

Requires Python 3.14+ and uv.

uv is required. This package cannot be installed with pip — some dependencies require uv-specific resolution that pip does not support. All commands below use uv.

# Install globally from PyPI
uv tool install z-vision-generator

# Install globally from repository
uv tool install -e git+https://github.com/knuthelge/ZVisionGenerator.git

# Development setup
git clone https://github.com/knuthelge/ZVisionGenerator && cd ZVisionGenerator
uv sync

Video generation requires ffmpeg. On macOS, ziv-video offers to install it via Homebrew on first run.

Quick Start

# Generate an image (bare name from ~/.ziv/models/)
ziv -m my-model --prompt "a beautiful sunset"

# Generate from a HuggingFace model
ziv -m Tongyi-MAI/Z-Image-Turbo --prompt "a cat in a garden"

# Batch run from a prompts file
ziv -m my-model -p prompts.yaml -r 3

# Generate a video
ziv-video -m dgrauet/ltx-2.3-mlx-q4 --prompt "A cat walking through a garden"

# Image-to-video
ziv-video -m dgrauet/ltx-2.3-mlx-q4 --image photo.jpg --prompt "Camera zooms in slowly"

Documentation

Full documentation is available at knuthelge.github.io/ZVisionGenerator.

• Getting Started — installation, model store, quick start
• Image Guide — aliases, sizes, reference images, LoRA, upscaling, quantization
• Video Guide — T2V, I2V, upscale, audio, LoRA, constraints
• Prompts Guide — prompt files, variables, structured prompts, snippets
• Converter Guide — checkpoint conversion, LoRA import, asset listing
• CLI Reference — full argument tables for all commands
• Development — setup, testing, architecture

Contributing

Contributions are welcome! See CONTRIBUTING.md for guidelines.

License

This project is licensed under the GNU Affero General Public License v3.0 or later.