Handle inputs that need arrays

node.py

@@ -13,6 +13,7 @@ from .schema_to_node import (
     schema_to_comfyui_input_types,
     get_return_type,
     name_and_version,
+    inputs_that_need_arrays,
 )
 
 
@@ -33,7 +34,17 @@ def create_comfyui_node(schema):
         FUNCTION = "run_replicate_model"
         CATEGORY = "Replicate"
 
-        def convert_image_to_base64(self, image):
+        def convert_input_images_to_base64(self, kwargs):
+            for key, value in kwargs.items():
+                if value is not None:
+                    input_type = (
+                        self.INPUT_TYPES()["required"].get(key, (None,))[0]
+                        or self.INPUT_TYPES().get("optional", {}).get(key, (None,))[0]
+                    )
+                    if input_type == "IMAGE":
+                        kwargs[key] = self.image_to_base64(value)
+
+        def image_to_base64(self, image):
             if isinstance(image, torch.Tensor):
                 image = image.permute(0, 3, 1, 2).squeeze(0)
                 to_pil = transforms.ToPILImage()
@@ -47,6 +58,18 @@ def create_comfyui_node(schema):
             img_str = base64.b64encode(buffer.getvalue()).decode()
             return f"data:image/png;base64,{img_str}"
 
+        def handle_array_inputs(self, kwargs):
+            array_inputs = inputs_that_need_arrays(schema)
+            for input_name in array_inputs:
+                if input_name in kwargs:
+                    if isinstance(kwargs[input_name], str):
+                        if kwargs[input_name] == "":
+                            kwargs[input_name] = []
+                        else:
+                            kwargs[input_name] = kwargs[input_name].split("\n")
+                    else:
+                        kwargs[input_name] = [kwargs[input_name]]
+
         def log_input(self, kwargs):
             truncated_kwargs = {
                 k: v[:20] + "..."
@@ -88,15 +111,8 @@ def create_comfyui_node(schema):
                 return None
 
         def run_replicate_model(self, **kwargs):
-            for key, value in kwargs.items():
-                if value is not None:
-                    input_type = (
-                        self.INPUT_TYPES()["required"].get(key, (None,))[0]
-                        or self.INPUT_TYPES().get("optional", {}).get(key, (None,))[0]
-                    )
-                    if input_type == "IMAGE":
-                        kwargs[key] = self.convert_image_to_base64(value)
-
+            self.handle_array_inputs(kwargs)
+            self.convert_input_images_to_base64(kwargs)
             self.log_input(kwargs)
             output = replicate.run(replicate_model, input=kwargs)
             print(f"Output: {output}")