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import math
import re
from io import BytesIO
from typing_extensions import override
from comfy.utils import common_upscale
from comfy_api.latest import IO, ComfyExtension
from PIL import Image
import numpy as np
import torch
from comfy_api_nodes.apis.ideogram import (
Ideogram45Request,
IdeogramGenerateResponse,
IdeogramPImageRequest,
IdeogramV3Request,
IdeogramV3EditRequest,
IdeogramV4Request,
)
from comfy_api_nodes.util import (
ApiEndpoint,
bytesio_to_image_tensor,
download_url_as_bytesio,
download_url_to_image_tensor,
resize_mask_to_image,
sync_op,
tensor_to_bytesio,
validate_string,
)
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"
]
IDEOGRAM_45_GENERATE_PATH = "/proxy/ideogram/v2/image/generate/ideogram-4-5"
IDEOGRAM_45_PRECISE_EDIT_PATH = "/proxy/ideogram/v2/image/precise-edit/ideogram-4-5"
IDEOGRAM_45_MODELS = ["ideogram-4.5"]
IDEOGRAM_45_MAX_IMAGES = 5
IDEOGRAM_45_MAX_PIXELS = 4194304
IDEOGRAM_45_MAX_SIDE = 4608
IDEOGRAM_45_SIZES = [
"(2K) 2048x2048 (1:1)",
"(2K) 1440x2880 (1:2)",
"(2K) 2880x1440 (2:1)",
"(2K) 1664x2496 (2:3)",
"(2K) 2496x1664 (3:2)",
"(2K) 1792x2240 (4:5)",
"(2K) 2240x1792 (5:4)",
"(2K) 1440x2560 (9:16)",
"(2K) 2560x1440 (16:9)",
"(2K) 1600x2560 (5:8)",
"(2K) 2560x1600 (8:5)",
"(2K) 1728x2304 (3:4)",
"(2K) 2304x1728 (4:3)",
"(2K) 1296x3168 (9:22)",
"(2K) 3168x1296 (22:9)",
"(2K) 1152x2944 (9:23)",
"(2K) 2944x1152 (23:9)",
"(2K) 1248x3328 (3:8)",
"(2K) 3328x1248 (8:3)",
"(2K) 1280x3072 (5:12)",
"(2K) 3072x1280 (12:5)",
"(2K) 1024x3072 (1:3)",
"(2K) 3072x1024 (3:1)",
"(1K) 1024x1024 (1:1)",
"(1K) 896x1120 (4:5)",
"(1K) 1120x896 (5:4)",
"(1K) 864x1152 (3:4)",
"(1K) 1152x864 (4:3)",
"(1K) 832x1248 (2:3)",
"(1K) 1248x832 (3:2)",
"(1K) 800x1280 (5:8)",
"(1K) 1280x800 (8:5)",
"(1K) 720x1280 (9:16)",
"(1K) 1280x720 (16:9)",
"(1K) 720x1440 (1:2)",
"(1K) 1440x720 (2:1)",
]
IDEOGRAM_45_EDIT_SIZES = [
s for s in IDEOGRAM_45_SIZES if all(int(v) % 32 == 0 for v in s.split(" ")[1].split("x"))
]
_IMAGE_REF_RE = re.compile(r"@image(?P<idx>\d*)(?!\w)", re.IGNORECASE | re.ASCII)
async 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 = await download_url_as_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
class IdeogramV3(IO.ComfyNode):
@classmethod
def define_schema(cls):
return IO.Schema(
node_id="IdeogramV3",
display_name="Ideogram V3",
category="partner/image/Ideogram",
description="Generates images using the Ideogram V3 model. "
"Supports both regular image generation from text prompts and image editing with mask.",
inputs=[
IO.String.Input(
"prompt",
multiline=True,
default="",
tooltip="Prompt for the image generation or editing",
),
IO.Image.Input(
"image",
tooltip="Optional reference image for image editing.",
optional=True,
),
IO.Mask.Input(
"mask",
tooltip="Optional mask for inpainting (white areas will be replaced)",
optional=True,
),
IO.Combo.Input(
"aspect_ratio",
options=list(V3_RATIO_MAP.keys()),
default="1:1",
tooltip="The aspect ratio for image generation. Ignored if resolution is not set to Auto.",
optional=True,
),
IO.Combo.Input(
"resolution",
options=V3_RESOLUTIONS,
default="Auto",
tooltip="The resolution for image generation. "
"If not set to Auto, this overrides the aspect_ratio setting.",
optional=True,
),
IO.Combo.Input(
"magic_prompt_option",
options=["AUTO", "ON", "OFF"],
default="AUTO",
tooltip="Determine if MagicPrompt should be used in generation",
optional=True,
advanced=True,
),
IO.Int.Input(
"seed",
default=0,
min=0,
max=2147483647,
step=1,
control_after_generate=True,
display_mode=IO.NumberDisplay.number,
optional=True,
),
IO.Int.Input(
"num_images",
default=1,
min=1,
max=8,
step=1,
display_mode=IO.NumberDisplay.number,
optional=True,
),
IO.Combo.Input(
"rendering_speed",
options=["DEFAULT", "TURBO", "QUALITY"],
default="DEFAULT",
tooltip="Controls the trade-off between generation speed and quality",
optional=True,
advanced=True,
),
IO.Image.Input(
"character_image",
tooltip="Image to use as character reference.",
optional=True,
),
IO.Mask.Input(
"character_mask",
tooltip="Optional mask for character reference image.",
optional=True,
),
],
outputs=[
IO.Image.Output(),
],
hidden=[
IO.Hidden.auth_token_comfy_org,
IO.Hidden.api_key_comfy_org,
IO.Hidden.unique_id,
],
is_api_node=True,
price_badge=IO.PriceBadge(
depends_on=IO.PriceBadgeDepends(widgets=["rendering_speed", "num_images"], inputs=["character_image"]),
expr="""
(
$n := widgets.num_images;
$speed := widgets.rendering_speed;
$hasChar := inputs.character_image.connected;
$base :=
$contains($speed,"quality") ? ($hasChar ? 0.286 : 0.1287) :
$contains($speed,"default") ? ($hasChar ? 0.2145 : 0.0858) :
$contains($speed,"turbo") ? ($hasChar ? 0.143 : 0.0429) :
0.0858;
{"type":"usd","usd": $round($base * $n, 2)}
)
""",
),
)
@classmethod
async def execute(
cls,
prompt,
image=None,
mask=None,
resolution="Auto",
aspect_ratio="1:1",
magic_prompt_option="AUTO",
seed=0,
num_images=1,
rendering_speed="DEFAULT",
character_image=None,
character_mask=None,
):
if rendering_speed == "BALANCED": # for backward compatibility
rendering_speed = "DEFAULT"
character_img_binary = None
character_mask_binary = None
if character_image is not None:
input_tensor = character_image.squeeze().cpu()
if character_mask is not None:
character_mask = resize_mask_to_image(character_mask, character_image, allow_gradient=False)
character_mask = 1.0 - character_mask
if character_mask.shape[1:] != character_image.shape[1:-1]:
raise Exception("Character mask and image must be the same size")
mask_np = (character_mask.squeeze().cpu().numpy() * 255).astype(np.uint8)
mask_img = Image.fromarray(mask_np)
mask_byte_arr = BytesIO()
mask_img.save(mask_byte_arr, format="PNG")
mask_byte_arr.seek(0)
character_mask_binary = mask_byte_arr
character_mask_binary.name = "mask.png"
img_np = (input_tensor.numpy() * 255).astype(np.uint8)
img = Image.fromarray(img_np)
img_byte_arr = BytesIO()
img.save(img_byte_arr, format="PNG")
img_byte_arr.seek(0)
character_img_binary = img_byte_arr
character_img_binary.name = "image.png"
elif character_mask is not None:
raise Exception("Character mask requires character image to be present")
# Check if both image and mask are provided for editing mode
if image is not None and mask is not None:
# 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 = 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 = 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
files = {
"image": img_binary,
"mask": mask_binary,
}
if character_img_binary:
files["character_reference_images"] = character_img_binary
if character_mask_binary:
files["character_mask_binary"] = character_mask_binary
response = await sync_op(
cls,
ApiEndpoint(path="/proxy/ideogram/ideogram-v3/edit", method="POST"),
response_model=IdeogramGenerateResponse,
data=edit_request,
files=files,
content_type="multipart/form-data",
)
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:
# 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
files = {}
if character_img_binary:
files["character_reference_images"] = character_img_binary
if character_mask_binary:
files["character_mask_binary"] = character_mask_binary
if files:
gen_request.style_type = "AUTO"
response = await sync_op(
cls,
endpoint=ApiEndpoint(path="/proxy/ideogram/ideogram-v3/generate", method="POST"),
response_model=IdeogramGenerateResponse,
data=gen_request,
files=files if files else None,
content_type="multipart/form-data",
)
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")
return IO.NodeOutput(await download_and_process_images(image_urls))
class IdeogramV4(IO.ComfyNode):
@classmethod
def define_schema(cls):
return IO.Schema(
node_id="IdeogramV4",
display_name="Ideogram V4",
category="partner/image/Ideogram",
description="Generates images using the Ideogram 4.0 model from a text prompt.",
inputs=[
IO.String.Input(
"prompt",
multiline=True,
default="",
tooltip="Text prompt for the image generation.",
),
IO.Combo.Input(
"resolution",
options=[
"Auto",
"2048x2048 (1:1)",
"1440x2880 (1:2)",
"2880x1440 (2:1)",
"1664x2496 (2:3)",
"2496x1664 (3:2)",
"1792x2240 (4:5)",
"2240x1792 (5:4)",
"1440x2560 (9:16)",
"2560x1440 (16:9)",
"1600x2560 (5:8)",
"2560x1600 (8:5)",
"1728x2304 (3:4)",
"2304x1728 (4:3)",
"1296x3168 (9:22)",
"3168x1296 (22:9)",
"1152x2944 (9:23)",
"2944x1152 (23:9)",
"1248x3328 (3:8)",
"3328x1248 (8:3)",
"1280x3072 (5:12)",
"3072x1280 (12:5)",
],
default="Auto",
),
IO.Combo.Input(
"rendering_speed",
options=["DEFAULT", "TURBO", "QUALITY"],
default="DEFAULT",
tooltip="Controls the trade-off between generation speed and quality.",
),
IO.Int.Input(
"seed",
default=0,
min=0,
max=2147483647,
step=1,
control_after_generate=True,
display_mode=IO.NumberDisplay.number,
),
],
outputs=[
IO.Image.Output(),
],
hidden=[
IO.Hidden.auth_token_comfy_org,
IO.Hidden.api_key_comfy_org,
IO.Hidden.unique_id,
],
is_api_node=True,
price_badge=IO.PriceBadge(
depends_on=IO.PriceBadgeDepends(widgets=["rendering_speed"]),
expr="""
(
$speed := widgets.rendering_speed;
$price :=
$contains($speed,"turbo") ? 0.0429 :
$contains($speed,"quality") ? 0.143 :
0.0858;
{"type":"usd","usd": $price}
)
""",
),
)
@classmethod
async def execute(
cls,
prompt: str,
resolution: str,
rendering_speed: str,
seed: int,
):
validate_string(prompt, strip_whitespace=True, min_length=1)
response = await sync_op(
cls,
ApiEndpoint(path="/proxy/ideogram/ideogram-v4/generate", method="POST"),
response_model=IdeogramGenerateResponse,
data=IdeogramV4Request(
text_prompt=prompt,
resolution=resolution.split(" ")[0] if resolution != "Auto" else None,
rendering_speed=rendering_speed,
),
)
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")
return IO.NodeOutput(await download_and_process_images(image_urls))
class IdeogramPImage(IO.ComfyNode):
@classmethod
def define_schema(cls):
return IO.Schema(
node_id="IdeogramPImage",
display_name="Ideogram & Pruna P-Image",
category="partner/image/Ideogram",
description="Generates images using P-Image, Ideogram's fast text-to-image model. "
"Strong typography and photorealism; "
"supports Ideogram 4.0 structured JSON captions for exact text, "
"colors and layout.",
inputs=[
IO.String.Input(
"prompt",
multiline=True,
default="",
tooltip="Text prompt. Also accepts an Ideogram 4.0 structured JSON caption "
"(exact colors as #RRGGBB hexes, exact text strings, bounding-box "
"layout) — set prompt_upsampling to OFF to use it verbatim.",
),
IO.Combo.Input(
"quality",
options=["VERY_LOW", "LOW", "MEDIUM", "HIGH"],
default="MEDIUM",
tooltip="Speed/price/quality tier. MEDIUM is the everyday default; HIGH for "
"complex prompts, fine detail and difficult text; VERY_LOW/LOW for "
"drafts at scale. Difficult text renders poorly below MEDIUM.",
),
IO.Combo.Input(
"resolution",
options=["1K", "2K"],
default="1K",
tooltip="Output size class (exact pixels follow the aspect ratio, e.g. "
"16:9 gives 1280x720 at 1K and 2560x1440 at 2K). "
"Prefer HIGH + 2K for crisp typography.",
),
IO.Combo.Input(
"aspect_ratio",
options=list(V3_RATIO_MAP.keys()),
default="1:1",
tooltip="The aspect ratio for image generation.",
),
IO.Combo.Input(
"prompt_upsampling",
options=["AUTO", "ON", "OFF"],
default="AUTO",
tooltip="Expands short prompts into a detailed structured caption before "
"generation (the rewritten prompt is returned as final_prompt). "
"Set OFF when supplying your own JSON caption or exact wording.",
),
IO.Int.Input(
"seed",
default=42,
min=0,
max=2147483647,
step=1,
control_after_generate=True,
display_mode=IO.NumberDisplay.number,
optional=True,
tooltip="Seed for reproducible generation. With prompt_upsampling OFF, "
"the same seed and settings return the same image; with ON/AUTO "
"the prompt rewrite varies per run — reproduce a result by reusing "
"its final_prompt output with prompt_upsampling OFF and the same "
"seed.",
),
],
outputs=[
IO.Image.Output(),
IO.String.Output(
"final_prompt",
tooltip="The prompt the image was actually generated from (the rewritten "
"structured caption when prompt_upsampling ran, else your prompt). "
"Feed it back with prompt_upsampling OFF and the same seed to "
"reproduce this image.",
),
],
hidden=[
IO.Hidden.auth_token_comfy_org,
IO.Hidden.api_key_comfy_org,
IO.Hidden.unique_id,
],
is_api_node=True,
price_badge=IO.PriceBadge(
depends_on=IO.PriceBadgeDepends(widgets=["quality", "resolution"]),
expr="""
(
$q := widgets.quality;
$is2k := $contains(widgets.resolution, "2k");
$usd :=
$contains($q, "very_low") ? ($is2k ? 0.00858 : 0.00429) :
$contains($q, "high") ? ($is2k ? 0.0429 : 0.02145) :
$contains($q, "medium") ? ($is2k ? 0.0286 : 0.0143) :
($is2k ? 0.02145 : 0.010725);
{"type": "usd", "usd": $usd}
)
""",
),
)
@classmethod
async def execute(
cls,
prompt: str,
quality: str = "MEDIUM",
resolution: str = "1K",
aspect_ratio: str = "1:1",
prompt_upsampling: str = "AUTO",
seed: int = 42,
):
validate_string(prompt, strip_whitespace=True, min_length=1)
request = IdeogramPImageRequest(
prompt=prompt,
quality=quality,
resolution=resolution,
aspect_ratio=V3_RATIO_MAP[aspect_ratio],
prompt_upsampling=prompt_upsampling,
seed=seed,
)
response = await sync_op(
cls,
ApiEndpoint(path="/proxy/ideogram/text-to-image/p-image-ideogram", method="POST"),
response_model=IdeogramGenerateResponse,
data=request,
)
if not response.data:
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:
if any(image_data.is_image_safe is False for image_data in response.data):
raise Exception(
"The generation was blocked by Ideogram's content safety filter. "
"Adjust the prompt and try again."
)
raise Exception("No image URLs were generated in the response")
return IO.NodeOutput(
await download_and_process_images(image_urls),
response.data[0].prompt or prompt,
)
def _resolve_image_refs(prompt: str, total_images: int) -> str:
parts = []
pos = 0
prev_end = -1
for match in _IMAGE_REF_RE.finditer(prompt):
start = match.start()
if start > 0 and start != prev_end and (prompt[start - 1].isalnum() or prompt[start - 1] == "_"):
continue
idx = int(match.group("idx") or 1)
if not 1 <= idx <= total_images:
raise ValueError(
f"The prompt references @Image{idx}, but only {total_images} images "
f"are connected (a batched input counts once per image)."
)
parts.append(prompt[pos:start])
parts.append(f"image {idx}")
pos = match.end()
prev_end = match.end()
parts.append(prompt[pos:])
return "".join(parts)
def _ideogram_45_images(model: dict) -> list[torch.Tensor]:
images = [image for key in model["images"] for image in model["images"][key]]
if len(images) > IDEOGRAM_45_MAX_IMAGES:
raise ValueError(
f"A maximum of {IDEOGRAM_45_MAX_IMAGES} images is supported; got {len(images)} "
f"(a batched input counts once per image)."
)
for i, image in enumerate(images, start=1):
height, width = image.shape[0], image.shape[1]
if max(width, height) > 6 * min(width, height):
raise ValueError(f"Image {i} is {width}x{height}; its aspect ratio must be between 1:6 and 6:1.")
return images
def _ideogram_45_image_file(image: torch.Tensor) -> BytesIO:
image = image.unsqueeze(0)
height, width = image.shape[1], image.shape[2]
scale = min(1.0, IDEOGRAM_45_MAX_SIDE / max(width, height), math.sqrt(IDEOGRAM_45_MAX_PIXELS / (width * height)))
while True:
new_width, new_height = max(1, round(width * scale)), max(1, round(height * scale))
if math.ceil(new_width / 32) * math.ceil(new_height / 32) * 1024 <= IDEOGRAM_45_MAX_PIXELS:
break
scale *= 0.995
if (new_width, new_height) != (width, height):
image = common_upscale(image.movedim(-1, 1), new_width, new_height, "lanczos", "disabled").movedim(1, -1)
return tensor_to_bytesio(image, total_pixels=None, mime_type="image/png")
async def _ideogram_45_output(cls: type[IO.ComfyNode], response: IdeogramGenerateResponse) -> torch.Tensor:
data = response.data or []
urls = [item.url for item in data if item.url]
if not urls:
if any(item.is_image_safe is False for item in data):
raise Exception(
"The result was blocked by Ideogram's content safety filter. "
"Adjust the prompt or images and try again."
)
raise Exception("No images were generated in the response")
return torch.cat([await download_url_to_image_tensor(url, cls=cls) for url in urls])
def _ideogram_45_quality_input(options: list[str]) -> IO.Combo.Input:
return IO.Combo.Input(
"quality",
options=options,
default="medium",
tooltip="Quality tier. Higher tiers cost more and take longer.",
)
def _ideogram_45_seed_input(tooltip: str) -> IO.Int.Input:
return IO.Int.Input(
"seed",
default=42,
min=0,
max=2147483647,
step=1,
control_after_generate=True,
display_mode=IO.NumberDisplay.number,
tooltip=tooltip,
)
def _ideogram_45_edit_inputs(with_size: bool) -> list:
inputs = [
IO.Autogrow.Input(
"images",
template=IO.Autogrow.TemplateNames(
IO.Image.Input("image"),
names=[f"image_{i}" for i in range(1, IDEOGRAM_45_MAX_IMAGES + 1)],
min=1,
),
tooltip="Image 1 is the image to edit; images 2-5 are optional references. "
"Refer to them in the prompt as @Image1, @Image2, ...; a batched input counts once per image.",
),
IO.String.Input(
"prompt",
multiline=True,
default="",
tooltip="Editing instructions. Supports @Image1-style references to the input images.",
),
]
if with_size:
inputs.extend(
[
IO.Combo.Input(
"size",
options=["auto", "source", *IDEOGRAM_45_EDIT_SIZES, "custom"],
default="auto",
tooltip="Output size. 'auto' picks a ~2K canvas from the images and prompt, 'source' keeps "
"the size of image 1 (images above ~4 MP are scaled down first), and a preset with a different "
"aspect ratio recomposes the scene. Select 'custom' to use the width and height below.",
),
IO.Int.Input(
"width",
default=2048,
min=256,
max=IDEOGRAM_45_MAX_SIDE,
step=32,
tooltip="Custom output width. Used only when size is set to 'custom'.",
),
IO.Int.Input(
"height",
default=2048,
min=256,
max=IDEOGRAM_45_MAX_SIDE,
step=32,
tooltip="Custom output height. Used only when size is set to 'custom'.",
),
]
)
inputs.extend(
[
_ideogram_45_quality_input(["very_low", "low", "medium", "high"]),
_ideogram_45_seed_input("Seed for generation. The same images, prompt, settings and seed give the same result."),
]
)
return inputs
def _ideogram_45_price_badge() -> IO.PriceBadge:
return IO.PriceBadge(
depends_on=IO.PriceBadgeDepends(widgets=["model", "model.quality"]),
expr="""
(
$q := $lookup(widgets, "model.quality");
{"type": "usd", "usd": $q = "very_low" ? 0.01144 : $q = "low" ? 0.0429 : $q = "high" ? 0.286 : 0.0858}
)
""",
)
class IdeogramTextToImageApi(IO.ComfyNode):
@classmethod
def define_schema(cls):
return IO.Schema(
node_id="IdeogramTextToImageApi",
display_name="Ideogram 4.5 Text to Image",
category="partner/image/Ideogram",
description="Generates images from a text prompt using Ideogram 4.5.",
inputs=[
IO.DynamicCombo.Input(
"model",
options=[
IO.DynamicCombo.Option(
model_id,
[
IO.String.Input(
"prompt",
multiline=True,
default="",
tooltip="Text prompt. Also accepts an Ideogram structured JSON caption, "
"for example a previous final_prompt.",
),
IO.Combo.Input(
"size",
options=["auto", *IDEOGRAM_45_SIZES],
default="auto",
tooltip="Output size. 'auto' lets the model pick a canvas that suits the prompt.",
),
_ideogram_45_quality_input(["low", "medium", "high"]),
IO.Combo.Input(
"magic_prompt",
options=["auto", "on", "off"],
default="auto",
tooltip="Rewrites the prompt into a detailed structured caption before "
"generating; 'off' keeps your wording as literal as possible. "
"The caption is returned as final_prompt.",
advanced=True,
),
_ideogram_45_seed_input(
"Seed for generation. Text-to-image is not reproducible from the seed alone "
"because the prompt is rewritten on every run; to reproduce an image, reuse "
"its final_prompt with magic_prompt set to 'off' and the same seed."
),
],
)
for model_id in IDEOGRAM_45_MODELS
],
tooltip="Model to use.",
),
],
outputs=[
IO.Image.Output(),
IO.String.Output(
"final_prompt",
tooltip="The structured caption the image was generated from. Feed it back with "
"magic_prompt set to 'off' and the same seed to reproduce the image.",
),
],
hidden=[
IO.Hidden.auth_token_comfy_org,
IO.Hidden.api_key_comfy_org,
IO.Hidden.unique_id,
],
is_api_node=True,
price_badge=_ideogram_45_price_badge(),
)
@classmethod
async def execute(cls, model: dict):
validate_string(model["prompt"], strip_whitespace=True, min_length=1, max_length=10000)
response = await sync_op(
cls,
ApiEndpoint(path=IDEOGRAM_45_GENERATE_PATH, method="POST"),
response_model=IdeogramGenerateResponse,
data=Ideogram45Request(
prompt=model["prompt"],
quality=model["quality"],
seed=model["seed"],
size=None if model["size"] == "auto" else model["size"].split(" ")[1],
magic_prompt=model["magic_prompt"],
),
)
image = await _ideogram_45_output(cls, response)
return IO.NodeOutput(image, response.data[0].prompt or model["prompt"])
class IdeogramEditApi(IO.ComfyNode):
@classmethod
def define_schema(cls):
return IO.Schema(
node_id="IdeogramEditApi",
display_name="Ideogram 4.5 Edit",
category="partner/image/Ideogram",
description="Edits or combines up to 5 images guided by a text prompt using Ideogram 4.5. "
"Re-renders the whole image and can change its size or aspect ratio; "
"use Ideogram 4.5 Precise Edit to keep untouched pixels unchanged.",
inputs=[
IO.DynamicCombo.Input(
"model",
options=[
IO.DynamicCombo.Option(model_id, _ideogram_45_edit_inputs(with_size=True))
for model_id in IDEOGRAM_45_MODELS
],
tooltip="Model to use.",
),
],
outputs=[
IO.Image.Output(),
],
hidden=[
IO.Hidden.auth_token_comfy_org,
IO.Hidden.api_key_comfy_org,
IO.Hidden.unique_id,
],
is_api_node=True,
price_badge=_ideogram_45_price_badge(),
)
@classmethod
async def execute(cls, model: dict):
validate_string(model["prompt"], strip_whitespace=True, min_length=1, max_length=10000)
images = _ideogram_45_images(model)
size = model["size"]
if size == "custom":
width, height = model["width"], model["height"]
if width * height > IDEOGRAM_45_MAX_PIXELS:
raise ValueError(
f"Custom size {width}x{height} exceeds the maximum of {IDEOGRAM_45_MAX_PIXELS} pixels (2048x2048)."
)
if max(width, height) > 6 * min(width, height):
raise ValueError(f"Custom size {width}x{height} exceeds the maximum aspect ratio of 6:1.")
size = f"{width}x{height}"
elif size == "auto":
size = None
elif size != "source":
size = size.split(" ")[1]
prompt = _resolve_image_refs(model["prompt"], len(images))
response = await sync_op(
cls,
ApiEndpoint(path=IDEOGRAM_45_GENERATE_PATH, method="POST"),
response_model=IdeogramGenerateResponse,
data=Ideogram45Request(prompt=prompt, quality=model["quality"], seed=model["seed"], size=size),
files=[
("images", (f"image_{i}.png", _ideogram_45_image_file(image), "image/png"))
for i, image in enumerate(images, start=1)
],
content_type="multipart/form-data",
)
return IO.NodeOutput(await _ideogram_45_output(cls, response))
class IdeogramPreciseEditApi(IO.ComfyNode):
@classmethod
def define_schema(cls):
return IO.Schema(
node_id="IdeogramPreciseEditApi",
display_name="Ideogram 4.5 Precise Edit",
category="partner/image/Ideogram",
description="Edits an image guided by a text prompt using Ideogram 4.5 precise editing: only what the "
"prompt asks for changes, untouched pixels stay identical and the output keeps the size of image 1 "
"(images above ~4 MP are scaled down first). Accepts up to 4 reference images.",
inputs=[
IO.DynamicCombo.Input(
"model",
options=[
IO.DynamicCombo.Option(model_id, _ideogram_45_edit_inputs(with_size=False))
for model_id in IDEOGRAM_45_MODELS
],
tooltip="Model to use.",
),
],
outputs=[
IO.Image.Output(),
],
hidden=[
IO.Hidden.auth_token_comfy_org,
IO.Hidden.api_key_comfy_org,
IO.Hidden.unique_id,
],
is_api_node=True,
price_badge=_ideogram_45_price_badge(),
)
@classmethod
async def execute(cls, model: dict):
validate_string(model["prompt"], strip_whitespace=True, min_length=1, max_length=10000)
images = _ideogram_45_images(model)
prompt = _resolve_image_refs(model["prompt"], len(images))
files = [("image", ("image_1.png", _ideogram_45_image_file(images[0]), "image/png"))]
files.extend(
("reference_images", (f"image_{i}.png", _ideogram_45_image_file(image), "image/png"))
for i, image in enumerate(images[1:], start=2)
)
response = await sync_op(
cls,
ApiEndpoint(path=IDEOGRAM_45_PRECISE_EDIT_PATH, method="POST"),
response_model=IdeogramGenerateResponse,
data=Ideogram45Request(prompt=prompt, quality=model["quality"], seed=model["seed"]),
files=files,
content_type="multipart/form-data",
)
return IO.NodeOutput(await _ideogram_45_output(cls, response))
class IdeogramExtension(ComfyExtension):
@override
async def get_node_list(self) -> list[type[IO.ComfyNode]]:
return [
IdeogramV3,
IdeogramV4,
IdeogramPImage,
IdeogramTextToImageApi,
IdeogramEditApi,
IdeogramPreciseEditApi,
]
async def comfy_entrypoint() -> IdeogramExtension:
return IdeogramExtension()

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