109 lines
5.6 KiB
Python
109 lines
5.6 KiB
Python
# SPDX-License-Identifier: Apache-2.0
|
|
# Copyright 2025-2026 Raykosan (RaykoStudio)
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
|
|
import folder_paths
|
|
import comfy.sd
|
|
import torch
|
|
import json
|
|
import hashlib
|
|
from nodes import UNETLoader, CLIPLoader, VAELoader, LoraLoader, DualCLIPLoader
|
|
|
|
class RaykoModelsLoaderPro:
|
|
@classmethod
|
|
def INPUT_TYPES(cls):
|
|
unet_files = ["None"] + folder_paths.get_filename_list("unet")
|
|
clip_files = ["None"] + folder_paths.get_filename_list("clip")
|
|
vae_files = ["None"] + folder_paths.get_filename_list("vae") + ["pixel_space"]
|
|
|
|
weight_dtype_opts = ["default", "fp8_e4m3fn", "fp8_e4m3fn_fast", "fp8_e5m2"]
|
|
clip_type_opts = [
|
|
"stable_diffusion", "stable_cascade", "sd3", "flux", "flux2", "lumina2", "ideogram4", "qwen_image", "boogu", "krea2", "ltxv", "wan", "minimax", "joyimage", "mage", "ace", "hunyuan_image", "hidream", "chroma", "mochi", "cosmos", "pixart", "kolors", "ultrapix", "omnigen2", "ovis", "longcat_image", "cogvideox", "lens", "pixeldit",
|
|
]
|
|
device_opts = ["default", "cpu", "cuda"]
|
|
|
|
required = {
|
|
"unet_name": (unet_files, {"default": "None", "tooltip": "Primary Diffusion model"}),
|
|
"unet_name2": (unet_files, {"default": "None", "tooltip": "Secondary Diffusion model (optional, e.g., Refiner)"}),
|
|
"weight_dtype": (weight_dtype_opts, {"default": "default"}),
|
|
"clip_name": (clip_files, {"default": "None", "tooltip": "Primary CLIP model"}),
|
|
"clip_name2": (clip_files, {"default": "None", "tooltip": "Secondary CLIP model (for dual-clip like Flux/SD3)"}),
|
|
"clip_type": (clip_type_opts, {"default": "stable_diffusion"}),
|
|
"clip_device": (device_opts, {"default": "default"}),
|
|
"vae_name": (vae_files, {"default": "None", "tooltip": "Primary VAE model"}),
|
|
"vae_name2": (vae_files, {"default": "None", "tooltip": "Secondary VAE model (optional)"}),
|
|
"lora_data": ("STRING", {"default": "[]", "multiline": False, "forceInput": False}),
|
|
}
|
|
return {"required": required}
|
|
|
|
RETURN_TYPES = ("MODEL", "MODEL", "CLIP", "VAE", "VAE")
|
|
RETURN_NAMES = ("MODEL", "MODEL 2", "CLIP", "VAE", "VAE 2")
|
|
FUNCTION = "load_models"
|
|
CATEGORY = "🦊 RaykoStudio"
|
|
DESCRIPTION = "Pro version: Combines loaders for up to 2 models, dual-clip, 2 VAEs and LoRAs. Leave fields as 'None' if not needed."
|
|
|
|
@classmethod
|
|
def IS_CHANGED(cls, lora_data="[]", **kwargs):
|
|
if lora_data is None: lora_data = "[]"
|
|
return hashlib.md5(lora_data.encode()).hexdigest()
|
|
|
|
def load_models(self, unet_name, unet_name2, weight_dtype, clip_name, clip_name2, clip_type, clip_device, vae_name, vae_name2, lora_data="[]"):
|
|
if not lora_data: lora_data = "[]"
|
|
|
|
wd = None if weight_dtype == "default" else weight_dtype
|
|
dev = None if clip_device == "default" else clip_device
|
|
|
|
model1 = UNETLoader().load_unet(unet_name=unet_name, weight_dtype=wd)[0] if unet_name != "None" else None
|
|
model2 = UNETLoader().load_unet(unet_name=unet_name2, weight_dtype=wd)[0] if unet_name2 != "None" else None
|
|
|
|
if clip_name2 != "None" and clip_name != "None":
|
|
clip = DualCLIPLoader().load_clip(clip_name1=clip_name, clip_name2=clip_name2, type=clip_type, device=dev)[0]
|
|
elif clip_name != "None":
|
|
clip = CLIPLoader().load_clip(clip_name=clip_name, type=clip_type, device=dev)[0]
|
|
elif clip_name2 != "None":
|
|
clip = CLIPLoader().load_clip(clip_name=clip_name2, type=clip_type, device=dev)[0]
|
|
else:
|
|
clip = CLIPLoader().load_clip(clip_name=clip_files[1], type=clip_type, device=dev)[0]
|
|
|
|
vae1 = VAELoader().load_vae(vae_name=vae_name)[0] if vae_name != "None" else None
|
|
vae2 = VAELoader().load_vae(vae_name=vae_name2)[0] if vae_name2 != "None" else None
|
|
|
|
if model1 is not None and clip is not None:
|
|
try:
|
|
loras = json.loads(lora_data) if lora_data else []
|
|
if not isinstance(loras, list): loras = []
|
|
except Exception:
|
|
loras = []
|
|
|
|
lora_loader = LoraLoader()
|
|
for lora in loras:
|
|
if not isinstance(lora, dict): continue
|
|
name = lora.get("name", "")
|
|
strength_model = float(lora.get("strength_model", 1.0))
|
|
strength_clip = float(lora.get("strength_clip", strength_model))
|
|
enabled = lora.get("enabled", True)
|
|
|
|
if name and name != "None" and enabled:
|
|
lora_relative_path = name.replace("\\", "/")
|
|
lora_full_path = folder_paths.get_full_path("loras", lora_relative_path)
|
|
if lora_full_path:
|
|
try:
|
|
model1, clip = lora_loader.load_lora(model1, clip, lora_relative_path, strength_model, strength_clip)
|
|
except Exception as e:
|
|
print(f"[Rayko Pro] ✗ LoRA Error: {e}")
|
|
|
|
return (model1, model2, clip, vae1, vae2)
|
|
|
|
NODE_CLASS_MAPPINGS = {"RaykoModelsLoaderPro": RaykoModelsLoaderPro}
|
|
NODE_DISPLAY_NAME_MAPPINGS = {"RaykoModelsLoaderPro": "🦊 RS Models Loader Pro"} |