Setmaster
e9e3ade3f0
- Add model usage tracking via PromptExecutor hook - Support 12+ loader node types (checkpoints, LoRAs, VAEs, etc.) - Pattern matching for custom node loaders - Cross-platform file locking (Windows/Unix) - JSON storage with schema migrations - REST API endpoints for usage data - Sidebar panel with timeframe filtering and sorting - Stale model highlighting (>30 days unused)
93 lines
2.5 KiB
Python
93 lines
2.5 KiB
Python
"""
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ModelPulse - Model Type Definitions
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Maps ComfyUI loader node types to their model categories and input keys.
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"""
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# Standard ComfyUI model loaders
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# Format: "NodeClassName": ("category", "input_key" or ["input_key1", "input_key2"])
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MODEL_LOADERS: dict[str, tuple[str, str | list[str]]] = {
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# Checkpoint loaders
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"CheckpointLoaderSimple": ("checkpoint", "ckpt_name"),
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"CheckpointLoader": ("checkpoint", "ckpt_name"),
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# LoRA loaders
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"LoraLoader": ("lora", "lora_name"),
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"LoraLoaderModelOnly": ("lora", "lora_name"),
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# VAE loaders
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"VAELoader": ("vae", "vae_name"),
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# ControlNet loaders
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"ControlNetLoader": ("controlnet", "control_net_name"),
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# CLIP loaders
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"CLIPLoader": ("clip", "clip_name"),
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"DualCLIPLoader": ("clip", ["clip_name1", "clip_name2"]),
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# UNET loaders
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"UNETLoader": ("unet", "unet_name"),
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# Upscaler loaders
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"UpscaleModelLoader": ("upscaler", "model_name"),
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# Style model loaders
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"StyleModelLoader": ("style_model", "style_model_name"),
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# GLIGEN loaders
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"GLIGENLoader": ("gligen", "gligen_name"),
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}
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# Patterns for detecting custom node loaders (Impact Pack, Efficiency Nodes, etc.)
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# These are checked if the node class name isn't in MODEL_LOADERS
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LOADER_PATTERNS: list[tuple[str, str, list[str]]] = [
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# (pattern_in_class_name, category, possible_input_keys)
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("Checkpoint", "checkpoint", ["ckpt_name", "checkpoint", "model_name"]),
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("Lora", "lora", ["lora_name", "lora"]),
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("VAE", "vae", ["vae_name", "vae"]),
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("ControlNet", "controlnet", ["control_net_name", "controlnet", "control_net"]),
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("CLIP", "clip", ["clip_name", "clip"]),
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("UNET", "unet", ["unet_name", "unet"]),
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("Upscale", "upscaler", ["model_name", "upscale_model"]),
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]
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# Model categories for display purposes
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MODEL_CATEGORIES: dict[str, dict[str, str]] = {
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"checkpoint": {
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"name": "Checkpoints",
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"icon": "pi-box",
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},
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"lora": {
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"name": "LoRAs",
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"icon": "pi-sparkles",
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},
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"vae": {
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"name": "VAEs",
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"icon": "pi-cog",
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},
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"controlnet": {
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"name": "ControlNets",
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"icon": "pi-sitemap",
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},
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"clip": {
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"name": "CLIP Models",
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"icon": "pi-comments",
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},
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"unet": {
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"name": "UNETs",
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"icon": "pi-server",
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},
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"upscaler": {
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"name": "Upscalers",
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"icon": "pi-expand",
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},
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"style_model": {
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"name": "Style Models",
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"icon": "pi-palette",
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},
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"gligen": {
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"name": "GLIGEN",
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"icon": "pi-th-large",
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},
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}
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