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on
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from comfy.comfy_types.node_typing import IO, ComfyNodeABC, InputTypeDict | |
from inspect import cleandoc | |
from PIL import Image | |
import numpy as np | |
import io | |
import torch | |
from comfy_api_nodes.apis import ( | |
IdeogramGenerateRequest, | |
IdeogramGenerateResponse, | |
ImageRequest, | |
IdeogramV3Request, | |
IdeogramV3EditRequest, | |
) | |
from comfy_api_nodes.apis.client import ( | |
ApiEndpoint, | |
HttpMethod, | |
SynchronousOperation, | |
) | |
from comfy_api_nodes.apinode_utils import ( | |
download_url_to_bytesio, | |
bytesio_to_image_tensor, | |
resize_mask_to_image, | |
) | |
from server import PromptServer | |
V1_V1_RES_MAP = { | |
"Auto":"AUTO", | |
"512 x 1536":"RESOLUTION_512_1536", | |
"576 x 1408":"RESOLUTION_576_1408", | |
"576 x 1472":"RESOLUTION_576_1472", | |
"576 x 1536":"RESOLUTION_576_1536", | |
"640 x 1024":"RESOLUTION_640_1024", | |
"640 x 1344":"RESOLUTION_640_1344", | |
"640 x 1408":"RESOLUTION_640_1408", | |
"640 x 1472":"RESOLUTION_640_1472", | |
"640 x 1536":"RESOLUTION_640_1536", | |
"704 x 1152":"RESOLUTION_704_1152", | |
"704 x 1216":"RESOLUTION_704_1216", | |
"704 x 1280":"RESOLUTION_704_1280", | |
"704 x 1344":"RESOLUTION_704_1344", | |
"704 x 1408":"RESOLUTION_704_1408", | |
"704 x 1472":"RESOLUTION_704_1472", | |
"720 x 1280":"RESOLUTION_720_1280", | |
"736 x 1312":"RESOLUTION_736_1312", | |
"768 x 1024":"RESOLUTION_768_1024", | |
"768 x 1088":"RESOLUTION_768_1088", | |
"768 x 1152":"RESOLUTION_768_1152", | |
"768 x 1216":"RESOLUTION_768_1216", | |
"768 x 1232":"RESOLUTION_768_1232", | |
"768 x 1280":"RESOLUTION_768_1280", | |
"768 x 1344":"RESOLUTION_768_1344", | |
"832 x 960":"RESOLUTION_832_960", | |
"832 x 1024":"RESOLUTION_832_1024", | |
"832 x 1088":"RESOLUTION_832_1088", | |
"832 x 1152":"RESOLUTION_832_1152", | |
"832 x 1216":"RESOLUTION_832_1216", | |
"832 x 1248":"RESOLUTION_832_1248", | |
"864 x 1152":"RESOLUTION_864_1152", | |
"896 x 960":"RESOLUTION_896_960", | |
"896 x 1024":"RESOLUTION_896_1024", | |
"896 x 1088":"RESOLUTION_896_1088", | |
"896 x 1120":"RESOLUTION_896_1120", | |
"896 x 1152":"RESOLUTION_896_1152", | |
"960 x 832":"RESOLUTION_960_832", | |
"960 x 896":"RESOLUTION_960_896", | |
"960 x 1024":"RESOLUTION_960_1024", | |
"960 x 1088":"RESOLUTION_960_1088", | |
"1024 x 640":"RESOLUTION_1024_640", | |
"1024 x 768":"RESOLUTION_1024_768", | |
"1024 x 832":"RESOLUTION_1024_832", | |
"1024 x 896":"RESOLUTION_1024_896", | |
"1024 x 960":"RESOLUTION_1024_960", | |
"1024 x 1024":"RESOLUTION_1024_1024", | |
"1088 x 768":"RESOLUTION_1088_768", | |
"1088 x 832":"RESOLUTION_1088_832", | |
"1088 x 896":"RESOLUTION_1088_896", | |
"1088 x 960":"RESOLUTION_1088_960", | |
"1120 x 896":"RESOLUTION_1120_896", | |
"1152 x 704":"RESOLUTION_1152_704", | |
"1152 x 768":"RESOLUTION_1152_768", | |
"1152 x 832":"RESOLUTION_1152_832", | |
"1152 x 864":"RESOLUTION_1152_864", | |
"1152 x 896":"RESOLUTION_1152_896", | |
"1216 x 704":"RESOLUTION_1216_704", | |
"1216 x 768":"RESOLUTION_1216_768", | |
"1216 x 832":"RESOLUTION_1216_832", | |
"1232 x 768":"RESOLUTION_1232_768", | |
"1248 x 832":"RESOLUTION_1248_832", | |
"1280 x 704":"RESOLUTION_1280_704", | |
"1280 x 720":"RESOLUTION_1280_720", | |
"1280 x 768":"RESOLUTION_1280_768", | |
"1280 x 800":"RESOLUTION_1280_800", | |
"1312 x 736":"RESOLUTION_1312_736", | |
"1344 x 640":"RESOLUTION_1344_640", | |
"1344 x 704":"RESOLUTION_1344_704", | |
"1344 x 768":"RESOLUTION_1344_768", | |
"1408 x 576":"RESOLUTION_1408_576", | |
"1408 x 640":"RESOLUTION_1408_640", | |
"1408 x 704":"RESOLUTION_1408_704", | |
"1472 x 576":"RESOLUTION_1472_576", | |
"1472 x 640":"RESOLUTION_1472_640", | |
"1472 x 704":"RESOLUTION_1472_704", | |
"1536 x 512":"RESOLUTION_1536_512", | |
"1536 x 576":"RESOLUTION_1536_576", | |
"1536 x 640":"RESOLUTION_1536_640", | |
} | |
V1_V2_RATIO_MAP = { | |
"1:1":"ASPECT_1_1", | |
"4:3":"ASPECT_4_3", | |
"3:4":"ASPECT_3_4", | |
"16:9":"ASPECT_16_9", | |
"9:16":"ASPECT_9_16", | |
"2:1":"ASPECT_2_1", | |
"1:2":"ASPECT_1_2", | |
"3:2":"ASPECT_3_2", | |
"2:3":"ASPECT_2_3", | |
"4:5":"ASPECT_4_5", | |
"5:4":"ASPECT_5_4", | |
} | |
V3_RATIO_MAP = { | |
"1:3":"1x3", | |
"3:1":"3x1", | |
"1:2":"1x2", | |
"2:1":"2x1", | |
"9:16":"9x16", | |
"16:9":"16x9", | |
"10:16":"10x16", | |
"16:10":"16x10", | |
"2:3":"2x3", | |
"3:2":"3x2", | |
"3:4":"3x4", | |
"4:3":"4x3", | |
"4:5":"4x5", | |
"5:4":"5x4", | |
"1:1":"1x1", | |
} | |
V3_RESOLUTIONS= [ | |
"Auto", | |
"512x1536", | |
"576x1408", | |
"576x1472", | |
"576x1536", | |
"640x1344", | |
"640x1408", | |
"640x1472", | |
"640x1536", | |
"704x1152", | |
"704x1216", | |
"704x1280", | |
"704x1344", | |
"704x1408", | |
"704x1472", | |
"736x1312", | |
"768x1088", | |
"768x1216", | |
"768x1280", | |
"768x1344", | |
"800x1280", | |
"832x960", | |
"832x1024", | |
"832x1088", | |
"832x1152", | |
"832x1216", | |
"832x1248", | |
"864x1152", | |
"896x960", | |
"896x1024", | |
"896x1088", | |
"896x1120", | |
"896x1152", | |
"960x832", | |
"960x896", | |
"960x1024", | |
"960x1088", | |
"1024x832", | |
"1024x896", | |
"1024x960", | |
"1024x1024", | |
"1088x768", | |
"1088x832", | |
"1088x896", | |
"1088x960", | |
"1120x896", | |
"1152x704", | |
"1152x832", | |
"1152x864", | |
"1152x896", | |
"1216x704", | |
"1216x768", | |
"1216x832", | |
"1248x832", | |
"1280x704", | |
"1280x768", | |
"1280x800", | |
"1312x736", | |
"1344x640", | |
"1344x704", | |
"1344x768", | |
"1408x576", | |
"1408x640", | |
"1408x704", | |
"1472x576", | |
"1472x640", | |
"1472x704", | |
"1536x512", | |
"1536x576", | |
"1536x640" | |
] | |
def download_and_process_images(image_urls): | |
"""Helper function to download and process multiple images from URLs""" | |
# Initialize list to store image tensors | |
image_tensors = [] | |
for image_url in image_urls: | |
# Using functions from apinode_utils.py to handle downloading and processing | |
image_bytesio = download_url_to_bytesio(image_url) # Download image content to BytesIO | |
img_tensor = bytesio_to_image_tensor(image_bytesio, mode="RGB") # Convert to torch.Tensor with RGB mode | |
image_tensors.append(img_tensor) | |
# Stack tensors to match (N, width, height, channels) | |
if image_tensors: | |
stacked_tensors = torch.cat(image_tensors, dim=0) | |
else: | |
raise Exception("No valid images were processed") | |
return stacked_tensors | |
def display_image_urls_on_node(image_urls, node_id): | |
if node_id and image_urls: | |
if len(image_urls) == 1: | |
PromptServer.instance.send_progress_text( | |
f"Generated Image URL:\n{image_urls[0]}", node_id | |
) | |
else: | |
urls_text = "Generated Image URLs:\n" + "\n".join( | |
f"{i+1}. {url}" for i, url in enumerate(image_urls) | |
) | |
PromptServer.instance.send_progress_text(urls_text, node_id) | |
class IdeogramV1(ComfyNodeABC): | |
""" | |
Generates images using the Ideogram V1 model. | |
""" | |
def __init__(self): | |
pass | |
def INPUT_TYPES(cls) -> InputTypeDict: | |
return { | |
"required": { | |
"prompt": ( | |
IO.STRING, | |
{ | |
"multiline": True, | |
"default": "", | |
"tooltip": "Prompt for the image generation", | |
}, | |
), | |
"turbo": ( | |
IO.BOOLEAN, | |
{ | |
"default": False, | |
"tooltip": "Whether to use turbo mode (faster generation, potentially lower quality)", | |
} | |
), | |
}, | |
"optional": { | |
"aspect_ratio": ( | |
IO.COMBO, | |
{ | |
"options": list(V1_V2_RATIO_MAP.keys()), | |
"default": "1:1", | |
"tooltip": "The aspect ratio for image generation.", | |
}, | |
), | |
"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, | |
"control_after_generate": True, | |
"display": "number", | |
}, | |
), | |
"negative_prompt": ( | |
IO.STRING, | |
{ | |
"multiline": True, | |
"default": "", | |
"tooltip": "Description of what to exclude from the image", | |
}, | |
), | |
"num_images": ( | |
IO.INT, | |
{"default": 1, "min": 1, "max": 8, "step": 1, "display": "number"}, | |
), | |
}, | |
"hidden": { | |
"auth_token": "AUTH_TOKEN_COMFY_ORG", | |
"comfy_api_key": "API_KEY_COMFY_ORG", | |
"unique_id": "UNIQUE_ID", | |
}, | |
} | |
RETURN_TYPES = (IO.IMAGE,) | |
FUNCTION = "api_call" | |
CATEGORY = "api node/image/Ideogram/v1" | |
DESCRIPTION = cleandoc(__doc__ or "") | |
API_NODE = True | |
def api_call( | |
self, | |
prompt, | |
turbo=False, | |
aspect_ratio="1:1", | |
magic_prompt_option="AUTO", | |
seed=0, | |
negative_prompt="", | |
num_images=1, | |
unique_id=None, | |
**kwargs, | |
): | |
# Determine the model based on turbo setting | |
aspect_ratio = V1_V2_RATIO_MAP.get(aspect_ratio, None) | |
model = "V_1_TURBO" if turbo else "V_1" | |
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, | |
magic_prompt_option=( | |
magic_prompt_option if magic_prompt_option != "AUTO" else None | |
), | |
negative_prompt=negative_prompt if negative_prompt else None, | |
) | |
), | |
auth_kwargs=kwargs, | |
) | |
response = operation.execute() | |
if not response.data or len(response.data) == 0: | |
raise Exception("No images were generated in the response") | |
image_urls = [image_data.url for image_data in response.data if image_data.url] | |
if not image_urls: | |
raise Exception("No image URLs were generated in the response") | |
display_image_urls_on_node(image_urls, unique_id) | |
return (download_and_process_images(image_urls),) | |
class IdeogramV2(ComfyNodeABC): | |
""" | |
Generates images using the Ideogram V2 model. | |
""" | |
def __init__(self): | |
pass | |
def INPUT_TYPES(cls) -> InputTypeDict: | |
return { | |
"required": { | |
"prompt": ( | |
IO.STRING, | |
{ | |
"multiline": True, | |
"default": "", | |
"tooltip": "Prompt for the image generation", | |
}, | |
), | |
"turbo": ( | |
IO.BOOLEAN, | |
{ | |
"default": False, | |
"tooltip": "Whether to use turbo mode (faster generation, potentially lower quality)", | |
} | |
), | |
}, | |
"optional": { | |
"aspect_ratio": ( | |
IO.COMBO, | |
{ | |
"options": list(V1_V2_RATIO_MAP.keys()), | |
"default": "1:1", | |
"tooltip": "The aspect ratio for image generation. Ignored if resolution is not set to AUTO.", | |
}, | |
), | |
"resolution": ( | |
IO.COMBO, | |
{ | |
"options": list(V1_V1_RES_MAP.keys()), | |
"default": "Auto", | |
"tooltip": "The resolution for image generation. If not set to AUTO, this overrides the aspect_ratio setting.", | |
}, | |
), | |
"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, | |
"control_after_generate": True, | |
"display": "number", | |
}, | |
), | |
"style_type": ( | |
IO.COMBO, | |
{ | |
"options": ["AUTO", "GENERAL", "REALISTIC", "DESIGN", "RENDER_3D", "ANIME"], | |
"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", | |
}, | |
), | |
"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", | |
# }, | |
#), | |
}, | |
"hidden": { | |
"auth_token": "AUTH_TOKEN_COMFY_ORG", | |
"comfy_api_key": "API_KEY_COMFY_ORG", | |
"unique_id": "UNIQUE_ID", | |
}, | |
} | |
RETURN_TYPES = (IO.IMAGE,) | |
FUNCTION = "api_call" | |
CATEGORY = "api node/image/Ideogram/v2" | |
DESCRIPTION = cleandoc(__doc__ or "") | |
API_NODE = True | |
def api_call( | |
self, | |
prompt, | |
turbo=False, | |
aspect_ratio="1:1", | |
resolution="Auto", | |
magic_prompt_option="AUTO", | |
seed=0, | |
style_type="NONE", | |
negative_prompt="", | |
num_images=1, | |
color_palette="", | |
unique_id=None, | |
**kwargs, | |
): | |
aspect_ratio = V1_V2_RATIO_MAP.get(aspect_ratio, None) | |
resolution = V1_V1_RES_MAP.get(resolution, None) | |
# Determine the model based on turbo setting | |
model = "V_2_TURBO" if turbo else "V_2" | |
# Handle resolution vs aspect_ratio logic | |
# If resolution is not AUTO, it overrides aspect_ratio | |
final_resolution = None | |
final_aspect_ratio = None | |
if resolution != "AUTO": | |
final_resolution = resolution | |
else: | |
final_aspect_ratio = aspect_ratio if aspect_ratio != "ASPECT_1_1" else None | |
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=final_aspect_ratio, | |
resolution=final_resolution, | |
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=color_palette if color_palette else None, | |
) | |
), | |
auth_kwargs=kwargs, | |
) | |
response = operation.execute() | |
if not response.data or len(response.data) == 0: | |
raise Exception("No images were generated in the response") | |
image_urls = [image_data.url for image_data in response.data if image_data.url] | |
if not image_urls: | |
raise Exception("No image URLs were generated in the response") | |
display_image_urls_on_node(image_urls, unique_id) | |
return (download_and_process_images(image_urls),) | |
class IdeogramV3(ComfyNodeABC): | |
""" | |
Generates images using the Ideogram V3 model. Supports both regular image generation from text prompts and image editing with mask. | |
""" | |
def __init__(self): | |
pass | |
def INPUT_TYPES(cls) -> InputTypeDict: | |
return { | |
"required": { | |
"prompt": ( | |
IO.STRING, | |
{ | |
"multiline": True, | |
"default": "", | |
"tooltip": "Prompt for the image generation or editing", | |
}, | |
), | |
}, | |
"optional": { | |
"image": ( | |
IO.IMAGE, | |
{ | |
"default": None, | |
"tooltip": "Optional reference image for image editing.", | |
}, | |
), | |
"mask": ( | |
IO.MASK, | |
{ | |
"default": None, | |
"tooltip": "Optional mask for inpainting (white areas will be replaced)", | |
}, | |
), | |
"aspect_ratio": ( | |
IO.COMBO, | |
{ | |
"options": list(V3_RATIO_MAP.keys()), | |
"default": "1:1", | |
"tooltip": "The aspect ratio for image generation. Ignored if resolution is not set to Auto.", | |
}, | |
), | |
"resolution": ( | |
IO.COMBO, | |
{ | |
"options": V3_RESOLUTIONS, | |
"default": "Auto", | |
"tooltip": "The resolution for image generation. If not set to Auto, this overrides the aspect_ratio setting.", | |
}, | |
), | |
"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, | |
"control_after_generate": True, | |
"display": "number", | |
}, | |
), | |
"num_images": ( | |
IO.INT, | |
{"default": 1, "min": 1, "max": 8, "step": 1, "display": "number"}, | |
), | |
"rendering_speed": ( | |
IO.COMBO, | |
{ | |
"options": ["BALANCED", "TURBO", "QUALITY"], | |
"default": "BALANCED", | |
"tooltip": "Controls the trade-off between generation speed and quality", | |
}, | |
), | |
}, | |
"hidden": { | |
"auth_token": "AUTH_TOKEN_COMFY_ORG", | |
"comfy_api_key": "API_KEY_COMFY_ORG", | |
"unique_id": "UNIQUE_ID", | |
}, | |
} | |
RETURN_TYPES = (IO.IMAGE,) | |
FUNCTION = "api_call" | |
CATEGORY = "api node/image/Ideogram/v3" | |
DESCRIPTION = cleandoc(__doc__ or "") | |
API_NODE = True | |
def api_call( | |
self, | |
prompt, | |
image=None, | |
mask=None, | |
resolution="Auto", | |
aspect_ratio="1:1", | |
magic_prompt_option="AUTO", | |
seed=0, | |
num_images=1, | |
rendering_speed="BALANCED", | |
unique_id=None, | |
**kwargs, | |
): | |
# Check if both image and mask are provided for editing mode | |
if image is not None and mask is not None: | |
# Edit mode | |
path = "/proxy/ideogram/ideogram-v3/edit" | |
# Process image and mask | |
input_tensor = image.squeeze().cpu() | |
# Resize mask to match image dimension | |
mask = resize_mask_to_image(mask, image, allow_gradient=False) | |
# Invert mask, as Ideogram API will edit black areas instead of white areas (opposite of convention). | |
mask = 1.0 - mask | |
# Validate mask dimensions match image | |
if mask.shape[1:] != image.shape[1:-1]: | |
raise Exception("Mask and Image must be the same size") | |
# Process image | |
img_np = (input_tensor.numpy() * 255).astype(np.uint8) | |
img = Image.fromarray(img_np) | |
img_byte_arr = io.BytesIO() | |
img.save(img_byte_arr, format="PNG") | |
img_byte_arr.seek(0) | |
img_binary = img_byte_arr | |
img_binary.name = "image.png" | |
# Process mask - white areas will be replaced | |
mask_np = (mask.squeeze().cpu().numpy() * 255).astype(np.uint8) | |
mask_img = Image.fromarray(mask_np) | |
mask_byte_arr = io.BytesIO() | |
mask_img.save(mask_byte_arr, format="PNG") | |
mask_byte_arr.seek(0) | |
mask_binary = mask_byte_arr | |
mask_binary.name = "mask.png" | |
# Create edit request | |
edit_request = IdeogramV3EditRequest( | |
prompt=prompt, | |
rendering_speed=rendering_speed, | |
) | |
# Add optional parameters | |
if magic_prompt_option != "AUTO": | |
edit_request.magic_prompt = magic_prompt_option | |
if seed != 0: | |
edit_request.seed = seed | |
if num_images > 1: | |
edit_request.num_images = num_images | |
# Execute the operation for edit mode | |
operation = SynchronousOperation( | |
endpoint=ApiEndpoint( | |
path=path, | |
method=HttpMethod.POST, | |
request_model=IdeogramV3EditRequest, | |
response_model=IdeogramGenerateResponse, | |
), | |
request=edit_request, | |
files={ | |
"image": img_binary, | |
"mask": mask_binary, | |
}, | |
content_type="multipart/form-data", | |
auth_kwargs=kwargs, | |
) | |
elif image is not None or mask is not None: | |
# If only one of image or mask is provided, raise an error | |
raise Exception("Ideogram V3 image editing requires both an image AND a mask") | |
else: | |
# Generation mode | |
path = "/proxy/ideogram/ideogram-v3/generate" | |
# Create generation request | |
gen_request = IdeogramV3Request( | |
prompt=prompt, | |
rendering_speed=rendering_speed, | |
) | |
# Handle resolution vs aspect ratio | |
if resolution != "Auto": | |
gen_request.resolution = resolution | |
elif aspect_ratio != "1:1": | |
v3_aspect = V3_RATIO_MAP.get(aspect_ratio) | |
if v3_aspect: | |
gen_request.aspect_ratio = v3_aspect | |
# Add optional parameters | |
if magic_prompt_option != "AUTO": | |
gen_request.magic_prompt = magic_prompt_option | |
if seed != 0: | |
gen_request.seed = seed | |
if num_images > 1: | |
gen_request.num_images = num_images | |
# Execute the operation for generation mode | |
operation = SynchronousOperation( | |
endpoint=ApiEndpoint( | |
path=path, | |
method=HttpMethod.POST, | |
request_model=IdeogramV3Request, | |
response_model=IdeogramGenerateResponse, | |
), | |
request=gen_request, | |
auth_kwargs=kwargs, | |
) | |
# Execute the operation and process response | |
response = operation.execute() | |
if not response.data or len(response.data) == 0: | |
raise Exception("No images were generated in the response") | |
image_urls = [image_data.url for image_data in response.data if image_data.url] | |
if not image_urls: | |
raise Exception("No image URLs were generated in the response") | |
display_image_urls_on_node(image_urls, unique_id) | |
return (download_and_process_images(image_urls),) | |
NODE_CLASS_MAPPINGS = { | |
"IdeogramV1": IdeogramV1, | |
"IdeogramV2": IdeogramV2, | |
"IdeogramV3": IdeogramV3, | |
} | |
NODE_DISPLAY_NAME_MAPPINGS = { | |
"IdeogramV1": "Ideogram V1", | |
"IdeogramV2": "Ideogram V2", | |
"IdeogramV3": "Ideogram V3", | |
} | |