mirror of
https://github.com/willmiao/ComfyUI-Lora-Manager.git
synced 2026-09-21 03:01:27 -03:00
Will Miao
1fd7cc0123
The SHA256 of an empty byte string (written by repackaging tools into safetensors metadata, or produced by hashing an empty/unreadable file) was previously resolved against CivitAI's by-hash API, which can contain polluted entries for it (e.g. a broken SD 1.5 LoRA whose AutoV3 equals the placeholder) and falsely attributed the wrong model to a recipe. Guard all lookup paths for the 10/12/64-char AutoV2/AutoV3/full-SHA256 spellings: CivitaiClient.get_model_by_hash/_fetch_version_by_hash return not-found without a request, and ModelHashIndex ignores the placeholder in has_hash/get_path/add_autov3. The Automatic1111 metadata parser keeps the LoRA item itself when its hash is the placeholder: it matches by filename locally, or retains the entry with an empty hash flagged hashInvalid (unresolvable-hash state in the UI, with reconnect as the remedy) instead of dropping it or resolving it to a polluted CivitAI entry.
294 lines
7.6 KiB
Python
294 lines
7.6 KiB
Python
from typing import Any
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NSFW_LEVELS = {
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"PG": 1,
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"PG13": 2,
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"R": 4,
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"X": 8,
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"XXX": 16,
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"Blocked": 32, # Probably not actually visible through the API without being logged in on model owner account?
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}
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# Node type constants
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NODE_TYPES = {
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"Lora Loader (LoraManager)": 1,
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"Lora Stacker (LoraManager)": 2,
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"WanVideo Lora Select (LoraManager)": 3,
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"Create Hook LoRA (LoraManager)": 4,
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}
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# Default ComfyUI node color when bgcolor is null
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DEFAULT_NODE_COLOR = "#353535"
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# preview extensions
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PREVIEW_EXTENSIONS = [
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".webp",
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".preview.webp",
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".preview.png",
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".preview.jpeg",
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".preview.jpg",
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".preview.mp4",
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".png",
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".jpeg",
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".jpg",
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".mp4",
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".gif",
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".webm",
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".avif",
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".jxl",
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]
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# Card preview image width
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CARD_PREVIEW_WIDTH = 480
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# Width for optimized example images
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EXAMPLE_IMAGE_WIDTH = 832
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# Supported media extensions for example downloads
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SUPPORTED_MEDIA_EXTENSIONS = {
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"images": [".jpg", ".jpeg", ".png", ".webp", ".gif", ".avif", ".jxl"],
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"videos": [".mp4", ".webm"],
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}
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# Model weight file extensions recognised by scanners.
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# This is the union of all scanner extensions (lora, checkpoint, embedding).
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MODEL_FILE_EXTENSIONS = {
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".safetensors",
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".ckpt",
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".pt",
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".pt2",
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".bin",
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".pth",
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".pkl",
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".sft",
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".gguf",
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}
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# CivitAI ModelFile.type values eligible as the main download file.
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# Mirrors CivitAI's getPrimaryFile() (model-helpers.ts): weight types are
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# preferred, but any file CivitAI marks `primary` is accepted — newer types
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# like 'Enhancement LoRA' (Anima/AIR image-editing LoRAs) are valid primary
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# files despite not being in the traditional weights allowlist.
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MODEL_WEIGHT_FILE_TYPES = (
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"Model",
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"Pruned Model",
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"Negative",
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"UNet",
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"Diffusion Model",
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"Enhancement LoRA",
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)
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# Valid sub-types for each scanner type
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VALID_LORA_SUB_TYPES = ["lora", "locon", "dora"]
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VALID_CHECKPOINT_SUB_TYPES = ["checkpoint", "diffusion_model"]
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VALID_EMBEDDING_SUB_TYPES = ["embedding"]
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# Backward compatibility alias
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VALID_LORA_TYPES = VALID_LORA_SUB_TYPES
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# Supported Civitai model types for user model queries (case-insensitive)
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CIVITAI_USER_MODEL_TYPES = [
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*VALID_LORA_TYPES,
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"textualinversion",
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"checkpoint",
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]
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# Default chunk size in megabytes used for hashing large files.
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DEFAULT_HASH_CHUNK_SIZE_MB = 4
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# Upper bound for a safetensors header block (bytes). Real headers are at most
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# a few MB (tensor name/shape lists); the cap prevents a crafted file with an
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# absurd 64-bit header length from forcing a multi-GB allocation during scan.
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MAX_SAFETENSORS_HEADER_BYTES = 64 * 1024 * 1024
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# SHA256 of an empty byte string. Some (re-packaging) training tools write a
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# truncated form of this placeholder into safetensors metadata (as
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# ``modelspec.hash_sha256`` / ``sshs_model_hash``), and hashing an empty or
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# unreadable file produces it directly. It must never be treated as a valid
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# hash: several broken models share it, CivitAI's by-hash index can contain
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# such polluted entries, and matching it falsely attributes recipes.
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EMPTY_HASH_SHA256 = "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855"
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INVALID_AUTOV3_EMPTY_HASH = EMPTY_HASH_SHA256[:12]
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INVALID_AUTOV2_EMPTY_HASH = EMPTY_HASH_SHA256[:10]
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def is_empty_placeholder_hash(value: Any) -> bool:
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"""True for a 10/12/64-hex-char spelling of the empty-hash placeholder.
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These are the AutoV2, AutoV3 and full-SHA256 forms of the placeholder;
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such values identify no real model and must never be resolved against
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local files or CivitAI.
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"""
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if not isinstance(value, str):
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return False
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v = value.strip().lower()
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if len(v) not in (10, 12, 64):
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return False
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return v == EMPTY_HASH_SHA256[: len(v)]
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# Auto-organize settings
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AUTO_ORGANIZE_BATCH_SIZE = (
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50 # Process models in batches to avoid overwhelming the system
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)
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# Civitai model tags in priority order for subfolder organization
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CIVITAI_MODEL_TAGS = [
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"character",
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"concept",
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"clothing",
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"realistic",
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"anime",
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"toon",
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"furry",
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"style",
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"poses",
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"background",
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"tool",
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"vehicle",
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"buildings",
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"objects",
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"assets",
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"animal",
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"action",
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]
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# Default priority tag configuration strings for each model type
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DEFAULT_PRIORITY_TAG_CONFIG = {
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"lora": ", ".join(CIVITAI_MODEL_TAGS),
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"checkpoint": ", ".join(CIVITAI_MODEL_TAGS),
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"embedding": ", ".join(CIVITAI_MODEL_TAGS),
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}
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# baseModel values from CivitAI that should be treated as diffusion models (unet)
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# These model types are incorrectly labeled as "checkpoint" by CivitAI but are actually diffusion models
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DIFFUSION_MODEL_BASE_MODELS = frozenset(
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[
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"Anima",
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# Flux series — DiT architecture, loaded via UNETLoader in ComfyUI
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"Flux.1 D",
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"Flux.1 S",
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"Flux.1 Krea",
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"Flux.1 Kontext",
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"Flux.2 D",
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"Flux.2 Klein 9B",
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"Flux.2 Klein 9B-base",
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"Flux.2 Klein 4B",
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"Flux.2 Klein 4B-base",
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# Non-UNet / DiT image diffusion models
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"AuraFlow",
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"Chroma",
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"HiDream",
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"Hunyuan 1",
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"Kolors",
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"Lumina",
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"PixArt a",
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"PixArt E",
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# Video diffusion models
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"CogVideoX",
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"Hunyuan Video",
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"LTXV",
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"LTXV2",
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"LTXV 2.3",
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"Mochi",
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"SVD",
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"Wan Video",
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"Wan Video 1.3B t2v",
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"Wan Video 14B t2v",
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"Wan Video 14B i2v 480p",
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"Wan Video 14B i2v 720p",
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"Wan Video 2.2 TI2V-5B",
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"Wan Video 2.2 I2V-A14B",
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"Wan Video 2.2 T2V-A14B",
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"Wan Video 2.5 T2V",
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"Wan Video 2.5 I2V",
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# Other diffusion models
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"Ernie",
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"Ernie Turbo",
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"Nucleus",
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"Qwen",
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"ZImageBase",
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"ZImageTurbo",
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# Krea 2 — loaded via UNETLoader in ComfyUI
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"Krea 2",
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]
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)
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# Supported baseModel values for download exclusion settings.
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# Keep this aligned with static/js/utils/constants.js, excluding the generic "Other" value.
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SUPPORTED_DOWNLOAD_SKIP_BASE_MODELS = frozenset(
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[
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"SD 1.4",
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"SD 1.5",
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"SD 1.5 LCM",
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"SD 1.5 Hyper",
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"SD 2.0",
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"SD 2.1",
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"SD 3",
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"SD 3.5",
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"SD 3.5 Medium",
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"SD 3.5 Large",
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"SD 3.5 Large Turbo",
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"SDXL 1.0",
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"SDXL Lightning",
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"SDXL Hyper",
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"Flux.1 D",
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"Flux.1 S",
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"Flux.1 Krea",
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"Flux.1 Kontext",
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"Flux.2 D",
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"Flux.2 Klein 9B",
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"Flux.2 Klein 9B-base",
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"Flux.2 Klein 4B",
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"Flux.2 Klein 4B-base",
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"AuraFlow",
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"Chroma",
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"PixArt a",
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"PixArt E",
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"Hunyuan 1",
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"Lumina",
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"Kolors",
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"NoobAI",
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"Illustrious",
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"Pony",
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"Pony V7",
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"HiDream",
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"Qwen",
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"ZImageTurbo",
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"ZImageBase",
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"SVD",
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"LTXV",
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"LTXV2",
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"LTXV 2.3",
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"CogVideoX",
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"Mochi",
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"Wan Video",
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"Wan Video 1.3B t2v",
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"Wan Video 14B t2v",
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"Wan Video 14B i2v 480p",
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"Wan Video 14B i2v 720p",
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"Wan Video 2.2 TI2V-5B",
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"Wan Video 2.2 T2V-A14B",
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"Wan Video 2.2 I2V-A14B",
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"Wan Video 2.5 T2V",
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"Wan Video 2.5 I2V",
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"Hunyuan Video",
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"Anima",
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"ACE Audio",
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"Boogu",
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"Ernie",
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"Ernie Turbo",
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"Grok",
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"HappyHorse",
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"HiDream-O1",
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"Ideogram 4.0",
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"Krea 2",
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"Lens",
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"MAI",
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"Nucleus",
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"Qwen 2",
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"Upscaler",
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"Wan Image 2.7",
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"Wan Video 2.7",
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]
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)
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