re-categorize nodes, remove ideogram (for now)

comfy_api_nodes/nodes_api.py

@@ -56,159 +56,6 @@ def validate_and_cast_response (response):
     # Convert to torch tensor and add batch dimension
     return torch.from_numpy(img_array)[None,]
 
-class IdeogramTextToImage(ComfyNodeABC):
-    """
-    Generates images synchronously based on a given prompt and optional parameters.
-
-    Images links are available for a limited period of time; if you would like to keep the image, you must download it.
-    """
-    def __init__(self):
-        pass
-
-    @classmethod
-    def INPUT_TYPES(cls) -> InputTypeDict:
-        """
-            Return a dictionary which contains config for all input fields.
-            Some types (string): "MODEL", "VAE", "CLIP", "CONDITIONING", "LATENT", "IMAGE", "INT", "STRING", "FLOAT".
-            Input types "INT", "STRING" or "FLOAT" are special values for fields on the node.
-            The type can be a list for selection.
-
-            Returns: `dict`:
-                - Key input_fields_group (`string`): Can be either required, hidden or optional. A node class must have property `required`
-                - Value input_fields (`dict`): Contains input fields config:
-                    * Key field_name (`string`): Name of a entry-point method's argument
-                    * Value field_config (`tuple`):
-                        + First value is a string indicate the type of field or a list for selection.
-                        + Secound value is a config for type "INT", "STRING" or "FLOAT".
-        """
-        return {
-            "required": {
-                "prompt": (IO.STRING, {
-                    "multiline": True,
-                    "default": "",
-                    "tooltip": "Prompt for the image generation",
-                }),
-                "model": (IO.COMBO, { "options": ["V_2", "V_2_TURBO", "V_1", "V_1_TURBO"], "default": "V_2", "tooltip": "Model to use for image generation"}),
-            },
-            "optional": {
-                "aspect_ratio": (IO.COMBO, { "options": ["ASPECT_1_1", "ASPECT_4_3", "ASPECT_3_4", "ASPECT_16_9", "ASPECT_9_16", "ASPECT_2_1", "ASPECT_1_2", "ASPECT_3_2", "ASPECT_2_3", "ASPECT_4_5", "ASPECT_5_4"], "default": "ASPECT_1_1", "tooltip": "The aspect ratio for image generation. Cannot be used with resolution"
-                }),
-                "resolution": (IO.COMBO, { "options": ["1024x1024", "1024x1792", "1792x1024"],
-                    "default": "1024x1024",
-                    "tooltip": "The resolution for image generation (V2 only). Cannot be used with aspect_ratio"
-                }),
-                "magic_prompt_option": (IO.COMBO, { "options": ["AUTO", "ON", "OFF"],
-                    "default": "AUTO",
-                    "tooltip": "Determine if MagicPrompt should be used in generation"
-                }),
-                "seed": (IO.INT, {
-                    "default": 0,
-                    "min": 0,
-                    "max": 2147483647,
-                    "step": 1,
-                    "display": "number"
-                }),
-                "style_type": (IO.COMBO, { "options": ["NONE", "ANIME", "CINEMATIC", "CREATIVE", "DIGITAL_ART", "PHOTOGRAPHIC"],
-                    "default": "NONE",
-                    "tooltip": "Style type for generation (V2+ only)"
-                }),
-                "negative_prompt": (IO.STRING, {
-                    "multiline": True,
-                    "default": "",
-                    "tooltip": "Description of what to exclude from the image (V1/V2 only)"
-                }),
-                "num_images": (IO.INT, {
-                    "default": 1,
-                    "min": 1,
-                    "max": 8,
-                    "step": 1,
-                    "display": "number"
-                }),
-                "color_palette": (IO.STRING, {
-                    "multiline": False,
-                    "default": "",
-                    "tooltip": "Color palette preset name or hex colors with weights (V2/V2_TURBO only)"
-                }),
-            },
-            "hidden": {
-                "auth_token": "AUTH_TOKEN_COMFY_ORG"
-            }
-        }
-
-    RETURN_TYPES = (IO.IMAGE,)
-    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
-    FUNCTION = "api_call"
-    API_NODE = True
-    CATEGORY = "Example"
-
-    def api_call(self, prompt, model, aspect_ratio=None, resolution=None,
-                 magic_prompt_option="AUTO", seed=0, style_type="NONE",
-                 negative_prompt="", num_images=1, color_palette="", auth_token=None):
-
-        import numpy as np
-        import requests
-        import torch
-        from PIL import Image
-
-        operation = SynchronousOperation(
-            endpoint=ApiEndpoint(
-                path="/proxy/ideogram/generate",
-                method=HttpMethod.POST,
-                request_model=IdeogramGenerateRequest,
-                response_model=IdeogramGenerateResponse
-            ),
-            request=IdeogramGenerateRequest(
-                image_request=ImageRequest(
-                  prompt=prompt,
-                  model=model,
-                  num_images=num_images,
-                  seed=seed,
-                  aspect_ratio=aspect_ratio if aspect_ratio != "ASPECT_1_1" else None,
-                  resolution=resolution if resolution != "1024x1024" else None,
-                  magic_prompt_option=magic_prompt_option if magic_prompt_option != "AUTO" else None,
-                  style_type=style_type if style_type != "NONE" else None,
-                  negative_prompt=negative_prompt if negative_prompt else None,
-                  color_palette=None
-                )
-            ),
-            auth_token=auth_token
-        )
-
-        response = operation.execute()
-
-        if not response.data or len(response.data) == 0:
-            raise Exception("No images were generated in the response")
-        image_url = response.data[0].url
-
-        if not image_url:
-            raise Exception("No image URL was generated in the response")
-        img_response = requests.get(image_url)
-        if img_response.status_code != 200:
-            raise Exception("Failed to download the image")
-
-        img = Image.open(io.BytesIO(img_response.content))
-        img = img.convert("RGB")  # Ensure RGB format
-
-        # Convert to numpy array, normalize to float32 between 0 and 1
-        img_array = np.array(img).astype(np.float32) / 255.0
-
-        # Convert to torch tensor and add batch dimension
-        img_tensor = torch.from_numpy(img_array)[None,]
-
-        return (img_tensor,)
-
-    """
-        The node will always be re executed if any of the inputs change but
-        this method can be used to force the node to execute again even when the inputs don't change.
-        You can make this node return a number or a string. This value will be compared to the one returned the last time the node was
-        executed, if it is different the node will be executed again.
-        This method is used in the core repo for the LoadImage node where they return the image hash as a string, if the image hash
-        changes between executions the LoadImage node is executed again.
-    """
-    #@classmethod
-    #def IS_CHANGED(s, image, string_field, int_field, float_field, print_to_screen):
-    #    return ""
-
 class OpenAIDalle2(ComfyNodeABC):
     """
     Generates images synchronously via OpenAI's DALL·E 2 endpoint.
@@ -267,7 +114,7 @@ class OpenAIDalle2(ComfyNodeABC):
 
     RETURN_TYPES = (IO.IMAGE,)
     FUNCTION = "api_call"
-    CATEGORY = "Example"
+    CATEGORY = "api node"
     DESCRIPTION = cleandoc(__doc__ or "")
     API_NODE = True
 
@@ -380,7 +227,7 @@ class OpenAIDalle3(ComfyNodeABC):
 
     RETURN_TYPES = (IO.IMAGE,)
     FUNCTION = "api_call"
-    CATEGORY = "Example"
+    CATEGORY = "api node"
     DESCRIPTION = cleandoc(__doc__ or "")
     API_NODE = True
 
@@ -479,7 +326,7 @@ class OpenAIXXX(ComfyNodeABC):
 
     RETURN_TYPES = (IO.IMAGE,)
     FUNCTION = "api_call"
-    CATEGORY = "Example"
+    CATEGORY = "api node"
     DESCRIPTION = cleandoc(__doc__ or "")
     API_NODE = True