import code

README.md

@@ -1,2 +1,3 @@
-# comfyui-checkpoint-extract
+# ComfyUI Checkpoint Extract
+
 Extract CLIP and VAE models from a loaded checkpoint in ComfyUI

__init__.py

@@ -0,0 +1,13 @@
+from .model_savers import CLIPModelSaver, VAEModelSaver
+
+NODE_CLASS_MAPPINGS = {
+    "VAEModelSaver": VAEModelSaver,
+    "CLIPModelSaver": CLIPModelSaver
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "VAEModelSaver": "VAE Model Saver",
+    "CLIPModelSaver": "CLIP Model Saver"
+}
+
+__all__ = ['NODE_CLASS_MAPPINGS', 'NODE_DISPLAY_NAME_MAPPINGS']

model_savers.py

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+import os
+import safetensors.torch
+
+from comfy.comfy_types import IO
+# from comfy.sd import detect_te_model, TEModel
+
+class CLIPModelSaver:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "clip": (IO.CLIP,),  # Input type for CLIP models in ComfyUI
+                "output_name": ("STRING", {"default": "extracted_model", "tooltip": "The model file name without extension ('_clip.safetensors' will be appended automatically)."}),
+                "output_folder": ("STRING", {"default": "models/text_encoders", "tooltip": "The destination folder to output the model to."})
+            }
+        }
+
+    RETURN_TYPES = ()
+    RETURN_NAMES = ()
+    FUNCTION = "save_clip_model"
+    OUTPUT_NODE = True
+    CATEGORY = "Models Savers"
+
+    def save_clip_model(self, clip, output_name, output_folder):
+        # clip is a comfy.sd.CLIP object
+        sd_clip = clip.get_sd()
+
+        # Detect Dual CLIP model parts (if available) and set flags accordingly
+        clip_g, clip_l = False, False
+        for layer_name in sd_clip.keys():
+            if layer_name.startswith("clip_g.transformer."):
+                clip_g = True
+                if clip_l:
+                    break
+            elif layer_name.startswith("clip_l.transformer."):
+                clip_l = True
+                if clip_g:
+                    break
+
+        # If dual CLIP model parts are detected, handle them separately
+        if clip_g and clip_l:
+            print("Dual CLIP model detected. Saving both parts separately and removing layer names prefix.")
+            # Clip G
+            clip_g_weights = {
+                key.removeprefix("clip_g.transformer."): value
+                for key, value in sd_clip.items()
+                if key.startswith("clip_g.transformer.")
+            }
+            output_path = os.path.join(os.path.normpath(output_folder), f"{output_name}_clip-g.safetensors")
+            print(f"CLIP Model Saver: Saving CLIP G model to: {output_path}")
+            safetensors.torch.save_file(clip_g_weights, output_path)
+            # Clip L
+            clip_l_weights = {
+                key.removeprefix("clip_l.transformer."): value
+                for key, value in sd_clip.items()
+                if key.startswith("clip_l.transformer.")
+            }
+            output_path = os.path.join(os.path.normpath(output_folder), f"{output_name}_clip-l.safetensors")
+            print(f"CLIP Model Saver: Saving CLIP L model to: {output_path}")
+            safetensors.torch.save_file(clip_l_weights, output_path)
+        else:
+            output_path = os.path.join(os.path.normpath(output_folder), f"{output_name}_clip.safetensors")
+            print(f"CLIP Model Saver: Saving CLIP L model to: {output_path}")
+            safetensors.torch.save_file(sd_clip, output_path)
+
+        return ()
+
+
+class VAEModelSaver:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "vae": (IO.VAE,),  # Input type for VAE models in ComfyUI
+                "output_name": ("STRING", {"default": "extracted_model", "tooltip": "The model file name without extension ('_vae.safetensors' will be appended automatically)."}),
+                "output_folder": ("STRING", {"default": "models/vae", "tooltip": "The destination folder to output the model to."})
+            }
+        }
+
+    RETURN_TYPES = ()
+    RETURN_NAMES = ()
+    FUNCTION = "save_vae_model"
+    OUTPUT_NODE = True
+    CATEGORY = "Models Savers"
+
+    def save_vae_model(self, vae, output_name, output_folder):
+        # vae is a comfy.sd.VAE object
+        output_path = os.path.join(os.path.normpath(output_folder), f"{output_name}_vae.safetensors")
+        print(f"VAE Model Saver: Saving VAE model to: {output_path}")
+        safetensors.torch.save_file(vae.get_sd(), output_path)
+        return ()