NSFW_LEVELS = {
    "PG": 1,
    "PG13": 2,
    "R": 4,
    "X": 8,
    "XXX": 16,
    "Blocked": 32,  # Probably not actually visible through the API without being logged in on model owner account?
}

# Node type constants
NODE_TYPES = {
    "Lora Loader (LoraManager)": 1,
    "Lora Stacker (LoraManager)": 2,
    "WanVideo Lora Select (LoraManager)": 3,
}

# Default ComfyUI node color when bgcolor is null
DEFAULT_NODE_COLOR = "#353535"

# preview extensions
PREVIEW_EXTENSIONS = [
    ".webp",
    ".preview.webp",
    ".preview.png",
    ".preview.jpeg",
    ".preview.jpg",
    ".preview.mp4",
    ".png",
    ".jpeg",
    ".jpg",
    ".mp4",
    ".gif",
    ".webm",
]

# Card preview image width
CARD_PREVIEW_WIDTH = 480

# Width for optimized example images
EXAMPLE_IMAGE_WIDTH = 832

# Supported media extensions for example downloads
SUPPORTED_MEDIA_EXTENSIONS = {
    "images": [".jpg", ".jpeg", ".png", ".webp", ".gif"],
    "videos": [".mp4", ".webm"],
}

# Valid sub-types for each scanner type
VALID_LORA_SUB_TYPES = ["lora", "locon", "dora"]
VALID_CHECKPOINT_SUB_TYPES = ["checkpoint", "diffusion_model"]
VALID_EMBEDDING_SUB_TYPES = ["embedding"]

# Backward compatibility alias
VALID_LORA_TYPES = VALID_LORA_SUB_TYPES

# Supported Civitai model types for user model queries (case-insensitive)
CIVITAI_USER_MODEL_TYPES = [
    *VALID_LORA_TYPES,
    "textualinversion",
    "checkpoint",
]

# Default chunk size in megabytes used for hashing large files.
DEFAULT_HASH_CHUNK_SIZE_MB = 4

# Auto-organize settings
AUTO_ORGANIZE_BATCH_SIZE = (
    50  # Process models in batches to avoid overwhelming the system
)

# Civitai model tags in priority order for subfolder organization
CIVITAI_MODEL_TAGS = [
    "character",
    "concept",
    "clothing",
    "realistic",
    "anime",
    "toon",
    "furry",
    "style",
    "poses",
    "background",
    "tool",
    "vehicle",
    "buildings",
    "objects",
    "assets",
    "animal",
    "action",
]

# Default priority tag configuration strings for each model type
DEFAULT_PRIORITY_TAG_CONFIG = {
    "lora": ", ".join(CIVITAI_MODEL_TAGS),
    "checkpoint": ", ".join(CIVITAI_MODEL_TAGS),
    "embedding": ", ".join(CIVITAI_MODEL_TAGS),
}

# baseModel values from CivitAI that should be treated as diffusion models (unet)
# These model types are incorrectly labeled as "checkpoint" by CivitAI but are actually diffusion models
DIFFUSION_MODEL_BASE_MODELS = frozenset(
    [
        "ZImageTurbo",
        "Wan Video 1.3B t2v",
        "Wan Video 14B t2v",
        "Wan Video 14B i2v 480p",
        "Wan Video 14B i2v 720p",
        "Wan Video 2.2 TI2V-5B",
        "Wan Video 2.2 I2V-A14B",
        "Wan Video 2.2 T2V-A14B",
        "Wan Video 2.5 T2V",
        "Wan Video 2.5 I2V",
        "Qwen",
    ]
)