Adding the RS Models Loader node

2026-03-18 03:58:30 +03:00
parent 731fc4b2f5
commit 4bf632435e
6 changed files with 494 additions and 0 deletions
@@ -0,0 +1,107 @@
+import folder_paths
+import comfy.sd
+import json
+import os
+from nodes import UNETLoader, CLIPLoader, VAELoader, LoraLoader
+from server import PromptServer
+import aiohttp
+
+print("\033[93m🦊\033[0m \033[93mRaykoStudio - RS Models Loader \033[92mLOADED\033[0m")
+
+class RaykoModelsLoader:
+    @classmethod
+    def INPUT_TYPES(cls):
+        unet_files = folder_paths.get_filename_list("unet")
+        clip_files = folder_paths.get_filename_list("clip")
+        vae_files = folder_paths.get_filename_list("vae")
+
+        weight_dtype_opts = ["default", "fp8_e4m3fn", "fp8_e4m3fn_fast", "fp8_e5m2"]
+        
+        clip_type_opts = [
+            "stable_diffusion", "stable_cascade", "sd3", "flux", "flux2", "lumina2", "qwen_image", "ltxv", "wan", "ace", "hunyuan_image", "hidream", "chroma", "mochi", "cosmos", "pixart", "kolors", "ultrapix",
+        ]
+        
+        device_opts = ["default", "cpu", "cuda"]
+
+        required = {
+            "unet_name": (unet_files, {"tooltip": "Модель диффузии (UNET)"}),
+            "weight_dtype": (weight_dtype_opts, {"default": "default"}),
+            "clip_name": (clip_files, {"tooltip": "CLIP модель"}),
+            "clip_type": (clip_type_opts, {"default": "stable_diffusion"}),
+            "clip_device": (device_opts, {"default": "default"}),
+            "vae_name": (vae_files, {"tooltip": "VAE модель"}),
+            "lora_data": ("STRING", {"default": "[]", "multiline": False, "forceInput": False}),
+        }
+        return {"required": required}
+
+    RETURN_TYPES = ("MODEL", "CLIP", "VAE")
+    RETURN_NAMES = ("MODEL", "CLIP", "VAE")
+    FUNCTION = "load_models"
+    CATEGORY = "RS Loaders"
+
+    @classmethod
+    def IS_CHANGED(cls, lora_data="[]", **kwargs):
+        import hashlib
+        return hashlib.md5(lora_data.encode()).hexdigest()
+
+    def load_models(self, unet_name, weight_dtype, clip_name, clip_type, clip_device, vae_name, lora_data="[]"):
+        print(f"\n[Rayko] === ЗАПУСК load_models ===")
+        print(f"[Rayko] lora_data RAW: {lora_data}")
+        
+        wd = None if weight_dtype == "default" else weight_dtype
+        model = UNETLoader().load_unet(unet_name=unet_name, weight_dtype=wd)[0]
+        print(f"[Rayko] UNET: {unet_name}")
+
+        dev = None if clip_device == "default" else clip_device
+        clip = CLIPLoader().load_clip(clip_name=clip_name, type=clip_type, device=dev)[0]
+        print(f"[Rayko] CLIP: {clip_name}")
+
+        vae = VAELoader().load_vae(vae_name=vae_name)[0]
+        print(f"[Rayko] VAE: {vae_name}")
+
+        try:
+            loras = json.loads(lora_data) if lora_data else []
+            print(f"[Rayko] LoRA count: {len(loras)}")
+        except Exception as e:
+            loras = []
+            print(f"[Rayko] Parse error: {e}")
+
+        lora_loader = LoraLoader()
+
+        for i, lora in enumerate(loras):
+            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)
+
+            print(f"[Rayko] LoRA[{i}]: {name} | strength={strength_model} | enabled={enabled}")
+
+            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:
+                        print(f"[Rayko] Applying LoRA: {lora_relative_path} (strength={strength_model})")
+                        model, clip = lora_loader.load_lora(
+                            model, clip, 
+                            lora_relative_path,
+                            strength_model, 
+                            strength_clip
+                        )
+                        print(f"[Rayko] ✓ LoRA applied successfully")
+                    except Exception as e:
+                        print(f"[Rayko] ✗ Error: {e}")
+                else:
+                    print(f"[Rayko] ✗ LoRA file not found: {lora_relative_path}")
+
+        print(f"[Rayko] === ЗАВЕРШЕНО ===\n")
+        return (model, clip, vae)
+
+NODE_CLASS_MAPPINGS = {"RaykoModelsLoader": RaykoModelsLoader}
+NODE_DISPLAY_NAME_MAPPINGS = {"RaykoModelsLoader": "🦊 RS Models Loader"}
+
+@PromptServer.instance.routes.get("/rayko/get_loras")
+async def get_loras(request):
+    loras = folder_paths.get_filename_list("loras")
+    return aiohttp.web.json_response(sorted(loras, key=lambda x: x.lower()))