Initial Commit

__init__.py

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+from .loader import DiffusersLoader, SDXLDiffusersLoader
+
+NODE_CLASS_MAPPINGS = {
+    "Diffusers_Loader": DiffusersLoader,
+    "SDXL_Diffusers_Loader": SDXLDiffusersLoader,
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "Diffusers_Loader": "Diffusers Loader",
+    "SDXL_Diffusers_Loader": "SDXL Diffusers Loader",
+}
+
+__all__ = ["NODE_CLASS_MAPPINGS", "NODE_DISPLAY_NAME_MAPPINGS"]

folder_paths.py

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+import os
+
+def get_comfyui_base_path():
+    # Assuming the script is in the standard directory structure
+    return os.path.abspath(os.path.join(os.path.dirname(__file__), "..", ".."))
+
+def get_folder_paths(folder_type):
+    base_path = get_comfyui_base_path()
+    
+    if folder_type == "diffusers":
+        return [os.path.join(base_path, "models", "diffusers")]
+    if folder_type == "embeddings":
+        return [os.path.join(base_path, "models", "embeddings")]
+    
+    return []
+
+# Example usage:
+if __name__ == "__main__":
+    print(get_folder_paths("diffusers"))  # Should print the path to the diffusers models
+    print(get_folder_paths("embeddings"))  # Should print the path to the embeddings

loader.py

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+import os
+from .utils import load_diffusers_model, load_diffusers_sdxl_model
+from .folder_paths import get_folder_paths
+
+class DiffusersLoader:
+    @classmethod
+    def INPUT_TYPES(cls):
+        paths = []
+        for search_path in get_folder_paths("diffusers"):
+            if os.path.exists(search_path):
+                for root, subdir, files in os.walk(search_path, followlinks=True):
+                    if "model_index.json" in files:
+                        paths.append(os.path.relpath(root, start=search_path))
+
+        return {"required": {"model_path": (paths,)}}
+
+    RETURN_TYPES = ("MODEL", "CLIP", "VAE")
+    FUNCTION = "load_checkpoint"
+    CATEGORY = "advanced/loaders/diffusers"
+
+    def load_checkpoint(self, model_path, output_vae=True, output_clip=True):
+        for search_path in get_folder_paths("diffusers"):
+            if os.path.exists(search_path):
+                path = os.path.join(search_path, model_path)
+                if os.path.exists(path):
+                    model_path = path
+                    break
+
+        return load_diffusers_model(model_path, output_vae=output_vae, output_clip=output_clip)
+
+
+class SDXLDiffusersLoader:
+    @classmethod
+    def INPUT_TYPES(cls):
+        paths = []
+        for search_path in get_folder_paths("diffusers"):
+            if os.path.exists(search_path):
+                for root, subdir, files in os.walk(search_path, followlinks=True):
+                    if "model_index.json" in files:
+                        paths.append(os.path.relpath(root, start=search_path))
+
+        return {"required": {"model_path": (paths,)}}
+
+    RETURN_TYPES = ("MODEL", "CLIP", "VAE", "TEXT_ENCODER_2")
+    FUNCTION = "load_checkpoint"
+    CATEGORY = "advanced/loaders/sdxl"
+
+    def load_checkpoint(self, model_path, output_vae=True, output_clip=True):
+        for search_path in get_folder_paths("diffusers"):
+            if os.path.exists(search_path):
+                path = os.path.join(search_path, model_path)
+                if os.path.exists(path):
+                    model_path = path
+                    break
+
+        return load_diffusers_sdxl_model(model_path, output_vae=output_vae, output_clip=output_clip)

test.py

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+import os
+import torch
+
+def check_file_permissions(file_path):
+    try:
+        if os.access(file_path, os.R_OK | os.W_OK):
+            print(f"Read and write permissions are available for {file_path}")
+        else:
+            raise PermissionError(f"Permission issue with {file_path}")
+    except Exception as e:
+        print(f"Error checking permissions for {file_path}: {e}")
+        raise
+
+def test_loading_file(file_path):
+    try:
+        check_file_permissions(file_path)
+        print(f"Attempting to load file: {file_path}")
+        data = torch.load(file_path)
+        print(f"Successfully loaded file: {file_path}")
+    except PermissionError as e:
+        print(f"Permission denied when accessing {file_path}. Please check the file permissions.")
+    except Exception as e:
+        print(f"Error loading file {file_path}: {e}")
+
+# Paths to test
+test_paths = [
+    "C:\\Users\\Admin\\Desktop\\ComfyUI_windows_portable\\ComfyUI\\models\\diffusers\\raemumix_v90\\model_index.json",
+    "C:\\Users\\Admin\\Desktop\\ComfyUI_windows_portable\\ComfyUI\\models\\diffusers\\raemumix_v90\\vae\\diffusion_pytorch_model.safetensors",
+    "C:\\Users\\Admin\\Desktop\\ComfyUI_windows_portable\\ComfyUI\\models\\diffusers\\raemumix_v90\\unet\\diffusion_pytorch_model.safetensors",
+    "C:\\Users\\Admin\\Desktop\\ComfyUI_windows_portable\\ComfyUI\\models\\diffusers\\raemumix_v90\\text_encoder\\model.safetensors",
+]
+
+for path in test_paths:
+    test_loading_file(path)

test2.py

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+import os
+import utils
+
+# Define the base model path
+base_model_path = "C:\\Users\\Admin\\Desktop\\ComfyUI_windows_portable\\ComfyUI\\models\\diffusers\\raemumix_v90"
+
+# Test loading the main model
+try:
+    model = utils.load_model_from_path(os.path.join(base_model_path, "model_index.json"))
+    print("Main model loaded successfully.")
+except Exception as e:
+    print(f"Error loading main model: {e}")
+
+# Test loading the VAE model
+try:
+    vae = utils.load_vae_from_path(base_model_path)
+    print("VAE model loaded successfully.")
+except Exception as e:
+    print(f"Error loading VAE model: {e}")
+
+# Test loading the CLIP model
+try:
+    clip = utils.load_text_encoder_from_path(base_model_path, encoder_id=None)
+    print("CLIP model loaded successfully.")
+except Exception as e:
+    print(f"Error loading CLIP model: {e}")
+
+# Test loading the text encoders for SDXL
+try:
+    text_encoder_1 = utils.load_text_encoder_from_path(base_model_path, 1)
+    print("Text encoder 1 loaded successfully.")
+except Exception as e:
+    print(f"Error loading text encoder 1: {e}")
+
+try:
+    text_encoder_2 = utils.load_text_encoder_from_path(base_model_path, 2)
+    print("Text encoder 2 loaded successfully.")
+except Exception as e:
+    print(f"Error loading text encoder 2: {e}")

utils.py

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+import os
+import json
+import torch
+from safetensors import safe_open
+
+def load_diffusers_model(model_path, output_vae=True, output_clip=True):
+    try:
+        model = load_model_from_path(model_path)
+        vae = load_vae_from_path(model_path) if output_vae else None
+        clip = load_text_encoder_from_path(model_path, encoder_id=None) if output_clip else None
+        return model, vae, clip
+    except Exception as e:
+        print(f"Error loading diffusers model from {model_path}: {e}")
+        raise
+
+def load_diffusers_sdxl_model(model_path, output_vae=True, output_clip=True, embedding_directory=None):
+    try:
+        model = load_model_from_path(model_path)
+        vae = load_vae_from_path(model_path) if output_vae else None
+        clip = load_text_encoder_from_path(model_path, encoder_id=1) if output_clip else None
+        text_encoder_2 = load_text_encoder_from_path(model_path, encoder_id=2)
+        
+        if embedding_directory:
+            # Load or handle embeddings if applicable
+            pass
+
+        return model, vae, clip, text_encoder_2
+    except Exception as e:
+        print(f"Error loading SDXL diffusers model from {model_path}: {e}")
+        raise
+
+def load_model_from_path(model_path):
+    try:
+        print(f"Loading model from {model_path}")
+        check_file_permissions(model_path)
+        if model_path.endswith('.safetensors'):
+            model = load_safetensors(model_path)
+        else:
+            model = load_json(model_path)
+        return model
+    except PermissionError as e:
+        print(f"Permission denied when accessing {model_path}. Please check the file permissions.")
+        raise
+    except Exception as e:
+        print(f"Error loading model from {model_path}: {e}")
+        raise
+
+def load_vae_from_path(model_path):
+    try:
+        print(f"Loading VAE from {model_path}")
+        vae_path = os.path.join(model_path, "vae", "diffusion_pytorch_model.safetensors")
+        check_file_permissions(vae_path)
+        vae = load_safetensors(vae_path)
+        return vae
+    except PermissionError as e:
+        print(f"Permission denied when accessing {vae_path}. Please check the file permissions.")
+        raise
+    except Exception as e:
+        print(f"Error loading VAE from {vae_path}: {e}")
+        raise
+
+def load_clip_from_path(model_path):
+    try:
+        print(f"Loading CLIP model from {model_path}")
+        clip_path = os.path.join(model_path, "clip", "diffusion_pytorch_model.safetensors")
+        check_file_permissions(clip_path)
+        clip = load_safetensors(clip_path)
+        return clip
+    except PermissionError as e:
+        print(f"Permission denied when accessing {clip_path}. Please check the file permissions.")
+        raise
+    except Exception as e:
+        print(f"Error loading CLIP model from {clip_path}: {e}")
+        raise
+
+def load_text_encoder_from_path(model_path, encoder_id=None):
+    try:
+        if encoder_id is not None:
+            encoder_path = os.path.join(model_path, f"text_encoder_{encoder_id}", "model.safetensors")
+            print(f"Loading text encoder {encoder_id} from {encoder_path}")
+        else:
+            encoder_path = os.path.join(model_path, "text_encoder", "model.safetensors")
+            print(f"Loading text encoder from {encoder_path}")
+        
+        check_file_permissions(encoder_path)
+        text_encoder = load_safetensors(encoder_path)
+        return text_encoder
+    except PermissionError as e:
+        print(f"Permission denied when accessing {encoder_path}. Please check the file permissions.")
+        raise
+    except Exception as e:
+        print(f"Error loading text encoder from {encoder_path}: {e}")
+        raise
+
+def load_json(json_path):
+    try:
+        print(f"Loading JSON from {json_path}")
+        with open(json_path, 'r') as f:
+            return json.load(f)
+    except Exception as e:
+        print(f"Error loading JSON from {json_path}: {e}")
+        raise
+
+def load_safetensors(file_path):
+    try:
+        print(f"Loading safetensors from {file_path}")
+        with safe_open(file_path, framework="pt", device="cpu") as f:
+            return {k: f.get_tensor(k) for k in f.keys()}
+    except Exception as e:
+        print(f"Error loading safetensors from {file_path}: {e}")
+        raise
+
+def check_file_permissions(file_path):
+    try:
+        if os.access(file_path, os.R_OK | os.W_OK):
+            print(f"Read and write permissions are available for {file_path}")
+        else:
+            raise PermissionError(f"Permission issue with {file_path}")
+    except Exception as e:
+        print(f"Error checking permissions for {file_path}: {e}")
+        raise