CLI and core features

• Z-Image-Turbo Model: Utilizes the high-quality Tongyi-MAI/Z-Image-Turbo model and quatized variants via diffusers.
• MPS Acceleration: Optimized for Mac users with Apple Silicon.
• ROCm Support: Explicitly supported on Linux for AMD GPUs.
• Intel XPU Support: Supports Intel XPU when running an Intel-enabled PyTorch build.
• Attention Slicing Auto-detection: Automatically manages memory usage (e.g., enables attention slicing for systems with lower RAM/VRAM) to prevent Out-of-Memory errors and optimize performance.
• Seed Control: Reproducible image generation via CLI or Web UI.
• Multiple LoRA Support: Upload/manage LoRAs in the web UI, apply up to 4 with per-LoRA strengths in a single generation; CLI supports multiple --lora entries with optional strengths.
• Automatic Dimension Adjustment: Ensures image dimensions are compatible (multiples of 16).
• Customizable Output Directory: Image output directory can be customized via config file and environment variable.

Web UI features

• Multilanguage Support: English, Japanese, Chinese Simplified (zh-CN), and Chinese Traditional (zh-TW) are supported.
• History Browser: E...