"""ComfyUI node: image edit / inpaint via OpenAI images.edit. Like node_generate, `model` is a DynamicCombo with a nested size combo. Reference images use an auto-growing input (up to 16). Behavior lives in build.run_edit(). """ from __future__ import annotations from comfy_api.latest import IO from . import build from . import params as params_mod from .node_generate import _gpt_image_2_inputs, _gpt_image_25_inputs, unpack_size _MAX_REFS = 16 class OpenAIImageEdit(IO.ComfyNode): @classmethod def define_schema(cls): return IO.Schema( node_id="ImagentOpenAIImageEdit", display_name="🤖 Imagent: OpenAI Image Edit", category="Imagent", description="BYOK image edit / inpaint / multi-reference compose via OpenAI " "gpt-image models (direct API, no proxy).", inputs=[ IO.String.Input("prompt", multiline=True, default="", placeholder="Describe the edit to apply…", tooltip="Describe the edit to apply to the reference image(s)."), IO.DynamicCombo.Input( "model", tooltip="OpenAI gpt-image model. Switching this changes the options below.", options=[ IO.DynamicCombo.Option("gpt-image-2.5-flare", _gpt_image_25_inputs()), IO.DynamicCombo.Option("gpt-image-2.5-sunburst", _gpt_image_25_inputs()), IO.DynamicCombo.Option("gpt-image-2", _gpt_image_2_inputs()), ], ), IO.Autogrow.Input( "images", template=IO.Autogrow.TemplateNames( IO.Image.Input("image"), names=[f"image_{i}" for i in range(1, _MAX_REFS + 1)], min=1), tooltip=f"Reference image(s) to edit; grows up to {_MAX_REFS}. A mask " "(if used) applies to the first image and requires exactly one image."), IO.Combo.Input("quality", options=params_mod.QUALITIES, default="auto", tooltip="Rendering quality. 'auto' lets the model decide; " "higher quality costs more. 'xhigh' and 'max' need " "gpt-image-2.5 and fall back to 'high' elsewhere."), IO.Combo.Input("output_format", options=params_mod.FORMATS, default="png", tooltip="Image file format returned by the API."), IO.Combo.Input("moderation", options=params_mod.MODERATIONS, default="auto", tooltip="Content moderation strictness. 'auto' (default) or " "'low'. Sent only when not 'auto'."), IO.Int.Input("n", default=1, min=params_mod.N_MIN, max=params_mod.N_MAX, step=1, tooltip="How many images to generate (1-8)."), IO.Mask.Input("mask", optional=True, tooltip="Inpaint mask: white marks the region to edit. Requires a " "single reference image."), ], outputs=[IO.Image.Output(display_name="image"), IO.Mask.Output(display_name="mask")], ) @classmethod def execute(cls, prompt, model, images, quality, output_format, moderation, n, mask=None) -> IO.NodeOutput: size, custom_width, custom_height = unpack_size(model) ref_tensors = [t for t in (images or {}).values() if t is not None] img, out_mask, _info = build.run_edit( prompt=prompt, model=model["model"], size=size, quality=quality, background=model["background"], output_format=output_format, n=n, images=ref_tensors, mask=mask, moderation=moderation, custom_width=custom_width, custom_height=custom_height) return IO.NodeOutput(img, out_mask)