mirror of
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98ff01e148
* [Luma] Print download URL of successful task result directly on nodes (#177) [Veo] Print download URL of successful task result directly on nodes (#184) [Recraft] Print download URL of successful task result directly on nodes (#183) [Pixverse] Print download URL of successful task result directly on nodes (#182) [Kling] Print download URL of successful task result directly on nodes (#181) [MiniMax] Print progress text and download URL of successful task result directly on nodes (#179) [Docs] Link to docs in `API_NODE` class property type annotation comment (#178) [Ideogram] Print download URL of successful task result directly on nodes (#176) [Kling] Print download URL of successful task result directly on nodes (#181) [Veo] Print download URL of successful task result directly on nodes (#184) [Recraft] Print download URL of successful task result directly on nodes (#183) [Pixverse] Print download URL of successful task result directly on nodes (#182) [MiniMax] Print progress text and download URL of successful task result directly on nodes (#179) [Docs] Link to docs in `API_NODE` class property type annotation comment (#178) [Luma] Print download URL of successful task result directly on nodes (#177) [Ideogram] Print download URL of successful task result directly on nodes (#176) Show output URL and progress text on Pika nodes (#168) [BFL] Print download URL of successful task result directly on nodes (#175) [OpenAI ] Print download URL of successful task result directly on nodes (#174) * fix ruff errors * fix 3.10 syntax error
802 lines
25 KiB
Python
802 lines
25 KiB
Python
from comfy.comfy_types.node_typing import IO, ComfyNodeABC, InputTypeDict
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from inspect import cleandoc
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from PIL import Image
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import numpy as np
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import io
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import torch
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from comfy_api_nodes.apis import (
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IdeogramGenerateRequest,
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IdeogramGenerateResponse,
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ImageRequest,
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IdeogramV3Request,
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IdeogramV3EditRequest,
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)
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from comfy_api_nodes.apis.client import (
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ApiEndpoint,
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HttpMethod,
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SynchronousOperation,
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)
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from comfy_api_nodes.apinode_utils import (
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download_url_to_bytesio,
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bytesio_to_image_tensor,
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resize_mask_to_image,
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)
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from server import PromptServer
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V1_V1_RES_MAP = {
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"Auto":"AUTO",
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"512 x 1536":"RESOLUTION_512_1536",
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"576 x 1408":"RESOLUTION_576_1408",
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"576 x 1472":"RESOLUTION_576_1472",
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"576 x 1536":"RESOLUTION_576_1536",
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"640 x 1024":"RESOLUTION_640_1024",
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"640 x 1344":"RESOLUTION_640_1344",
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"640 x 1408":"RESOLUTION_640_1408",
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"640 x 1472":"RESOLUTION_640_1472",
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"640 x 1536":"RESOLUTION_640_1536",
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"704 x 1152":"RESOLUTION_704_1152",
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"704 x 1216":"RESOLUTION_704_1216",
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"704 x 1280":"RESOLUTION_704_1280",
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"704 x 1344":"RESOLUTION_704_1344",
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"704 x 1408":"RESOLUTION_704_1408",
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"704 x 1472":"RESOLUTION_704_1472",
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"720 x 1280":"RESOLUTION_720_1280",
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"736 x 1312":"RESOLUTION_736_1312",
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"768 x 1024":"RESOLUTION_768_1024",
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"768 x 1088":"RESOLUTION_768_1088",
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"768 x 1152":"RESOLUTION_768_1152",
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"768 x 1216":"RESOLUTION_768_1216",
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"768 x 1232":"RESOLUTION_768_1232",
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"768 x 1280":"RESOLUTION_768_1280",
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"768 x 1344":"RESOLUTION_768_1344",
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"832 x 960":"RESOLUTION_832_960",
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"832 x 1024":"RESOLUTION_832_1024",
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"832 x 1088":"RESOLUTION_832_1088",
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"832 x 1152":"RESOLUTION_832_1152",
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"832 x 1216":"RESOLUTION_832_1216",
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"832 x 1248":"RESOLUTION_832_1248",
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"864 x 1152":"RESOLUTION_864_1152",
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"896 x 960":"RESOLUTION_896_960",
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"896 x 1024":"RESOLUTION_896_1024",
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"896 x 1088":"RESOLUTION_896_1088",
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"896 x 1120":"RESOLUTION_896_1120",
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"896 x 1152":"RESOLUTION_896_1152",
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"960 x 832":"RESOLUTION_960_832",
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"960 x 896":"RESOLUTION_960_896",
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"960 x 1024":"RESOLUTION_960_1024",
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"960 x 1088":"RESOLUTION_960_1088",
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"1024 x 640":"RESOLUTION_1024_640",
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"1024 x 768":"RESOLUTION_1024_768",
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"1024 x 832":"RESOLUTION_1024_832",
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"1024 x 896":"RESOLUTION_1024_896",
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"1024 x 960":"RESOLUTION_1024_960",
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"1024 x 1024":"RESOLUTION_1024_1024",
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"1088 x 768":"RESOLUTION_1088_768",
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"1088 x 832":"RESOLUTION_1088_832",
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"1088 x 896":"RESOLUTION_1088_896",
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"1088 x 960":"RESOLUTION_1088_960",
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"1120 x 896":"RESOLUTION_1120_896",
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"1152 x 704":"RESOLUTION_1152_704",
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"1152 x 768":"RESOLUTION_1152_768",
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"1152 x 832":"RESOLUTION_1152_832",
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"1152 x 864":"RESOLUTION_1152_864",
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"1152 x 896":"RESOLUTION_1152_896",
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"1216 x 704":"RESOLUTION_1216_704",
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"1216 x 768":"RESOLUTION_1216_768",
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"1216 x 832":"RESOLUTION_1216_832",
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"1232 x 768":"RESOLUTION_1232_768",
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"1248 x 832":"RESOLUTION_1248_832",
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"1280 x 704":"RESOLUTION_1280_704",
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"1280 x 720":"RESOLUTION_1280_720",
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"1280 x 768":"RESOLUTION_1280_768",
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"1280 x 800":"RESOLUTION_1280_800",
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"1312 x 736":"RESOLUTION_1312_736",
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"1344 x 640":"RESOLUTION_1344_640",
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"1344 x 704":"RESOLUTION_1344_704",
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"1344 x 768":"RESOLUTION_1344_768",
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"1408 x 576":"RESOLUTION_1408_576",
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"1408 x 640":"RESOLUTION_1408_640",
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"1408 x 704":"RESOLUTION_1408_704",
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"1472 x 576":"RESOLUTION_1472_576",
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"1472 x 640":"RESOLUTION_1472_640",
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"1472 x 704":"RESOLUTION_1472_704",
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"1536 x 512":"RESOLUTION_1536_512",
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"1536 x 576":"RESOLUTION_1536_576",
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"1536 x 640":"RESOLUTION_1536_640",
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}
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V1_V2_RATIO_MAP = {
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"1:1":"ASPECT_1_1",
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"4:3":"ASPECT_4_3",
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"3:4":"ASPECT_3_4",
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"16:9":"ASPECT_16_9",
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"9:16":"ASPECT_9_16",
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"2:1":"ASPECT_2_1",
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"1:2":"ASPECT_1_2",
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"3:2":"ASPECT_3_2",
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"2:3":"ASPECT_2_3",
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"4:5":"ASPECT_4_5",
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"5:4":"ASPECT_5_4",
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}
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V3_RATIO_MAP = {
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"1:3":"1x3",
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"3:1":"3x1",
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"1:2":"1x2",
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"2:1":"2x1",
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"9:16":"9x16",
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"16:9":"16x9",
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"10:16":"10x16",
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"16:10":"16x10",
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"2:3":"2x3",
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"3:2":"3x2",
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"3:4":"3x4",
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"4:3":"4x3",
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"4:5":"4x5",
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"5:4":"5x4",
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"1:1":"1x1",
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}
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V3_RESOLUTIONS= [
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"Auto",
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"512x1536",
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"576x1408",
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"576x1472",
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"576x1536",
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"640x1344",
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"640x1408",
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"640x1472",
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"640x1536",
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"704x1152",
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"704x1216",
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"704x1280",
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"704x1344",
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"704x1408",
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"704x1472",
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"736x1312",
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"768x1088",
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"768x1216",
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"768x1280",
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"768x1344",
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"800x1280",
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"832x960",
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"832x1024",
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"832x1088",
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"832x1152",
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"832x1216",
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"832x1248",
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"864x1152",
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"896x960",
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"896x1024",
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"896x1088",
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"896x1120",
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"896x1152",
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"960x832",
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"960x896",
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"960x1024",
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"960x1088",
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"1024x832",
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"1024x896",
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"1024x960",
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"1024x1024",
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"1088x768",
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"1088x832",
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"1088x896",
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"1088x960",
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"1120x896",
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"1152x704",
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"1152x832",
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"1152x864",
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"1152x896",
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"1216x704",
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"1216x768",
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"1216x832",
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"1248x832",
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"1280x704",
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"1280x768",
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"1280x800",
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"1312x736",
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"1344x640",
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"1344x704",
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"1344x768",
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"1408x576",
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"1408x640",
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"1408x704",
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"1472x576",
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"1472x640",
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"1472x704",
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"1536x512",
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"1536x576",
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"1536x640"
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]
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def download_and_process_images(image_urls):
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"""Helper function to download and process multiple images from URLs"""
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# Initialize list to store image tensors
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image_tensors = []
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for image_url in image_urls:
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# Using functions from apinode_utils.py to handle downloading and processing
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image_bytesio = download_url_to_bytesio(image_url) # Download image content to BytesIO
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img_tensor = bytesio_to_image_tensor(image_bytesio, mode="RGB") # Convert to torch.Tensor with RGB mode
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image_tensors.append(img_tensor)
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# Stack tensors to match (N, width, height, channels)
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if image_tensors:
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stacked_tensors = torch.cat(image_tensors, dim=0)
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else:
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raise Exception("No valid images were processed")
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return stacked_tensors
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def display_image_urls_on_node(image_urls, node_id):
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if node_id and image_urls:
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if len(image_urls) == 1:
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PromptServer.instance.send_progress_text(
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f"Generated Image URL:\n{image_urls[0]}", node_id
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)
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else:
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urls_text = "Generated Image URLs:\n" + "\n".join(
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f"{i+1}. {url}" for i, url in enumerate(image_urls)
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)
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PromptServer.instance.send_progress_text(urls_text, node_id)
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class IdeogramV1(ComfyNodeABC):
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"""
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Generates images using the Ideogram V1 model.
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"""
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(cls) -> InputTypeDict:
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return {
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"required": {
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"prompt": (
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IO.STRING,
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{
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"multiline": True,
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"default": "",
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"tooltip": "Prompt for the image generation",
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},
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),
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"turbo": (
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IO.BOOLEAN,
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{
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"default": False,
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"tooltip": "Whether to use turbo mode (faster generation, potentially lower quality)",
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}
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),
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},
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"optional": {
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"aspect_ratio": (
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IO.COMBO,
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{
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"options": list(V1_V2_RATIO_MAP.keys()),
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"default": "1:1",
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"tooltip": "The aspect ratio for image generation.",
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},
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),
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"magic_prompt_option": (
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IO.COMBO,
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{
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"options": ["AUTO", "ON", "OFF"],
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"default": "AUTO",
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"tooltip": "Determine if MagicPrompt should be used in generation",
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},
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),
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"seed": (
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IO.INT,
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{
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"default": 0,
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"min": 0,
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"max": 2147483647,
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"step": 1,
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"control_after_generate": True,
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"display": "number",
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},
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),
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"negative_prompt": (
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IO.STRING,
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{
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"multiline": True,
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"default": "",
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"tooltip": "Description of what to exclude from the image",
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},
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),
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"num_images": (
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IO.INT,
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{"default": 1, "min": 1, "max": 8, "step": 1, "display": "number"},
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),
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},
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"hidden": {
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"auth_token": "AUTH_TOKEN_COMFY_ORG",
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"comfy_api_key": "API_KEY_COMFY_ORG",
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"unique_id": "UNIQUE_ID",
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},
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}
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RETURN_TYPES = (IO.IMAGE,)
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FUNCTION = "api_call"
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CATEGORY = "api node/image/Ideogram/v1"
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DESCRIPTION = cleandoc(__doc__ or "")
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API_NODE = True
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def api_call(
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self,
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prompt,
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turbo=False,
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aspect_ratio="1:1",
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magic_prompt_option="AUTO",
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seed=0,
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negative_prompt="",
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num_images=1,
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unique_id=None,
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**kwargs,
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):
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# Determine the model based on turbo setting
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aspect_ratio = V1_V2_RATIO_MAP.get(aspect_ratio, None)
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model = "V_1_TURBO" if turbo else "V_1"
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operation = SynchronousOperation(
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endpoint=ApiEndpoint(
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path="/proxy/ideogram/generate",
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method=HttpMethod.POST,
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request_model=IdeogramGenerateRequest,
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response_model=IdeogramGenerateResponse,
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),
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request=IdeogramGenerateRequest(
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image_request=ImageRequest(
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prompt=prompt,
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model=model,
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num_images=num_images,
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seed=seed,
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aspect_ratio=aspect_ratio if aspect_ratio != "ASPECT_1_1" else None,
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magic_prompt_option=(
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magic_prompt_option if magic_prompt_option != "AUTO" else None
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),
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negative_prompt=negative_prompt if negative_prompt else None,
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)
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),
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auth_kwargs=kwargs,
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)
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response = operation.execute()
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if not response.data or len(response.data) == 0:
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raise Exception("No images were generated in the response")
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image_urls = [image_data.url for image_data in response.data if image_data.url]
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if not image_urls:
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raise Exception("No image URLs were generated in the response")
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display_image_urls_on_node(image_urls, unique_id)
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return (download_and_process_images(image_urls),)
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class IdeogramV2(ComfyNodeABC):
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"""
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Generates images using the Ideogram V2 model.
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"""
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(cls) -> InputTypeDict:
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return {
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"required": {
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"prompt": (
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IO.STRING,
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{
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"multiline": True,
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"default": "",
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"tooltip": "Prompt for the image generation",
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},
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),
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"turbo": (
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IO.BOOLEAN,
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{
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"default": False,
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"tooltip": "Whether to use turbo mode (faster generation, potentially lower quality)",
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}
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),
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},
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"optional": {
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"aspect_ratio": (
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IO.COMBO,
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{
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"options": list(V1_V2_RATIO_MAP.keys()),
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"default": "1:1",
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"tooltip": "The aspect ratio for image generation. Ignored if resolution is not set to AUTO.",
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},
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),
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"resolution": (
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IO.COMBO,
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{
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"options": list(V1_V1_RES_MAP.keys()),
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"default": "Auto",
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"tooltip": "The resolution for image generation. If not set to AUTO, this overrides the aspect_ratio setting.",
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},
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),
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"magic_prompt_option": (
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IO.COMBO,
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{
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"options": ["AUTO", "ON", "OFF"],
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"default": "AUTO",
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"tooltip": "Determine if MagicPrompt should be used in generation",
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},
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),
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"seed": (
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IO.INT,
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{
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"default": 0,
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"min": 0,
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"max": 2147483647,
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"step": 1,
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"control_after_generate": True,
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"display": "number",
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},
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),
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"style_type": (
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IO.COMBO,
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{
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"options": ["AUTO", "GENERAL", "REALISTIC", "DESIGN", "RENDER_3D", "ANIME"],
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"default": "NONE",
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"tooltip": "Style type for generation (V2 only)",
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},
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),
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"negative_prompt": (
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IO.STRING,
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{
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"multiline": True,
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"default": "",
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"tooltip": "Description of what to exclude from the image",
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},
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),
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"num_images": (
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IO.INT,
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{"default": 1, "min": 1, "max": 8, "step": 1, "display": "number"},
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),
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#"color_palette": (
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# IO.STRING,
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# {
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# "multiline": False,
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# "default": "",
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# "tooltip": "Color palette preset name or hex colors with weights",
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# },
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#),
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},
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"hidden": {
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"auth_token": "AUTH_TOKEN_COMFY_ORG",
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"comfy_api_key": "API_KEY_COMFY_ORG",
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"unique_id": "UNIQUE_ID",
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},
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}
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RETURN_TYPES = (IO.IMAGE,)
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FUNCTION = "api_call"
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CATEGORY = "api node/image/Ideogram/v2"
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DESCRIPTION = cleandoc(__doc__ or "")
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API_NODE = True
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def api_call(
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self,
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prompt,
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turbo=False,
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aspect_ratio="1:1",
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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
|
|
|
|
@classmethod
|
|
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",
|
|
}
|