Add ComfyUI-TkNodes pack with custom nodes, workflow, documentation, and dependencies

vae_encode_optional.py

@@ -0,0 +1,45 @@
+import torch
+from comfy.comfy_types import IO
+
+class VAEEncodeOptional:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "vae": ("VAE", {"tooltip": "The VAE model used for encoding the image to latent space."}),
+            },
+            "optional": {
+                "image": ("IMAGE", {"tooltip": "The image to encode to latent space. If not provided, returns None."}),
+            }
+        }
+
+    RETURN_TYPES = ("LATENT",)
+    RETURN_NAMES = ("LATENT",)
+    OUTPUT_TOOLTIPS = ("The encoded latent image, or None if no image is provided.",)
+    FUNCTION = "encode"
+
+    CATEGORY = "latent"
+    DESCRIPTION = "Encodes an image to latent space using a VAE model. If no image is provided, acts as a bypass and returns None."
+
+    def encode(self, vae, image=None):
+        # Modo bypass: si no hay imagen, devolver None
+        if image is None:
+            return (None,)
+
+        # Codificar la imagen con el VAE
+        try:
+            # Asegurarse de que la imagen solo use los canales RGB (ignorar alfa si existe)
+            latent = vae.encode(image[:,:,:,:3])
+            return ({"samples": latent},)
+        except Exception as e:
+            # En caso de error (por ejemplo, dimensiones inválidas), devolver None
+            return (None,)
+
+# Mapeo de nodos
+NODE_CLASS_MAPPINGS = {
+    "VAEEncodeOptional": VAEEncodeOptional
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "VAEEncodeOptional": "VAE Encode (Optional)"
+}