Validate a prompt against Animagine XL rules.

Checks for:

• Required quality tags (masterpiece, best quality, etc.)

• Proper tag ordering (quality tags at end)

• Minimum tag count (8+ recommended)

• Character/series consistency

• Resolution compatibility

Optimize a prompt for Animagine XL.

Provide either a natural language description or an existing prompt. The optimizer will:

• Reorder tags by canonical category order

• Move quality tags to the end

• Add missing essential categories (composition, environment, quality)

Explain what each tag in a prompt does.

Breaks down the prompt into individual tags with:

• Category classification (quality, composition, character, etc.)

• Explanation of what each tag affects

• Canonically ordered version of the prompt

List available checkpoints and LoRAs for image generation.

Returns all available models with metadata:

• checkpoints: Base models (Animagine XL)

• loras: Style modifiers and speed optimizations

Use this to discover what models are available before generation.

Returns: Dictionary with checkpoints, loras, default_checkpoint, and currently_loaded

Pre-load a checkpoint into GPU memory.

Loading a checkpoint in advance speeds up subsequent generation calls. Use list_models() to see available checkpoints.

Unload all LoRA weights from the current pipeline.

Useful to reset to base checkpoint style without reloading the full model. This is faster than reloading the checkpoint.

Returns: Status with success, unloaded_count, and message

Generate an image with Animagine XL 4.0.

Uses the Diffusers pipeline with the lpw_stable_diffusion_xl custom pipeline. Images are saved to outputs/YYYY-MM-DD/ with accompanying metadata JSON.

Supports custom checkpoints and LoRA mixing for style control.

Recommended workflow:

1. list_models → see available checkpoints and LoRAs

2. validate_prompt → check for issues

3. optimize_prompt → improve structure

4. generate_image → create the image

Generate an image using img2img (image-to-image) transformation.

Takes an existing image and transforms it based on the prompt while preserving structure according to the strength parameter.

Use cases:

• Style transfer (apply anime/comic/realistic style to photo)

• Image refinement (improve details, fix artifacts)

• Pose/composition preservation (keep layout, change style)

• Character consistency (transform existing character art)