Args:
    pipeline: Pipeline to use — "sd15", "sdxl", or "illustrious"
    positive_prompt: Text prompt describing the desired image
    model_checkpoint: Model checkpoint filename to use
    negative_prompt: Negative prompt (things to avoid)
    width: Image width in pixels (256-2048)
    height: Image height in pixels (256-2048)
    steps: Number of inference steps (1-150)
    cfg_scale: Classifier-free guidance scale (1-30)
    seed: Random seed (-1 for random)
    scheduler: Noise scheduler name
    loras: Optional list of LoRA configs, each with "name" (str) and optional "strength" (float 0-1)
    custom_vae: Optional custom VAE checkpoint filename

Args:
    pipeline: Pipeline to use — "sd15", "sdxl", or "illustrious"
    positive_prompt: Text prompt describing what to paint in the masked region
    model_checkpoint: Model checkpoint filename to use
    image_base64: Base64-encoded input image
    mask_base64: Base64-encoded mask image (white = inpaint region)
    negative_prompt: Negative prompt (things to avoid)
    steps: Number of inference steps (1-150)
    cfg_scale: Classifier-free guidance scale (1-30)
    seed: Random seed (-1 for random)
    scheduler: Noise scheduler name
    loras: Optional list of LoRA configs, each with "name" (str) and optional "strength" (float 0-1)
    custom_vae: Optional custom VAE checkpoint filename

Args:
    pipeline: Pipeline to use — "sd15", "sdxl", or "illustrious"
    positive_prompt: Text prompt describing the desired image
    model_checkpoint: Model checkpoint filename to use
    negative_prompt: Negative prompt (things to avoid)
    width: Image width in pixels (256-2048)
    height: Image height in pixels (256-2048)
    steps: Number of inference steps (1-150)
    cfg_scale: Classifier-free guidance scale (1-30)
    seed: Random seed (-1 for random)
    scheduler: Noise scheduler name
    loras: Optional list of LoRA configs, each with "name" (str) and optional "strength" (float 0-1)
    custom_vae: Optional custom VAE checkpoint filename

Args:
    pipeline: Pipeline to use — "sd15", "sdxl", or "illustrious"
    positive_prompt: Text prompt describing what to paint in the masked region
    model_checkpoint: Model checkpoint filename to use
    image_base64: Base64-encoded input image
    mask_base64: Base64-encoded mask image (white = inpaint region)
    negative_prompt: Negative prompt (things to avoid)
    steps: Number of inference steps (1-150)
    cfg_scale: Classifier-free guidance scale (1-30)
    seed: Random seed (-1 for random)
    scheduler: Noise scheduler name
    loras: Optional list of LoRA configs, each with "name" (str) and optional "strength" (float 0-1)
    custom_vae: Optional custom VAE checkpoint filename

Args:
    pipeline: Pipeline to use — "sd15", "sdxl", or "illustrious"
    requests: List of generation request objects, each with at least "positive_prompt" and "model_checkpoint"

Args:
    pipeline: Pipeline to use — "sd15", "sdxl", or "illustrious"
    positive_prompt: Text prompt for all models
    models: List of model checkpoint filenames to compare (2-6)
    negative_prompt: Negative prompt (things to avoid)
    width: Image width in pixels (256-2048)
    height: Image height in pixels (256-2048)
    steps: Number of inference steps (1-150)
    cfg_scale: Classifier-free guidance scale (1-30)
    seed: Fixed seed for fair comparison (default 42)
    scheduler: Noise scheduler name

Args:
    model_type: Model architecture — "sd15" or "sdxl"
    resource_type: Resource category — "checkpoints", "loras", or "vaes"

Args:
    model_type: Model architecture — "sd15" or "sdxl"
    resource_type: Resource category — "checkpoints", "loras", or "vaes"
    model_name: Model filename

Args:
    job_id: The job identifier returned when the job was submitted

Args:
    job_id: The job identifier to cancel

Args:
    model_type: Model architecture — "sd15" or "sdxl"
    base_model: Base model checkpoint filename
    target_model: Target model checkpoint filename
    output_name: Output checkpoint filename for the merged model
    method: Merge method — "linear", "slerp", "additive", or "subtract"
    alpha: Merge strength (0.0-1.0)
    preserve_metadata: Whether to preserve model metadata

Args:
    model_type: Model architecture — "sd15" or "sdxl"
    base_model: Base model checkpoint filename
    target_models: List of target model checkpoint filenames
    method: Merge method — "linear", "slerp", "additive", or "subtract"
    alpha: Merge strength (0.0-1.0)
    output_subdir: Output subdirectory name for merged models
    preserve_metadata: Whether to preserve model metadata

Args:
    model_type: Model architecture — "sd15" or "sdxl"
    base_model: Base model checkpoint filename
    steps: List of merge steps, each with "target_model" (str), "method" (str), and "alpha" (float 0-1)
    output_name: Output checkpoint filename for the final merged model