Alexander Garzon
6d3d2fca46
BYOK OpenAI gpt-image generation and editing nodes for ComfyUI — calls go directly to the OpenAI API with your own key (no proxy, no credit markup). - Two nodes: "Imagent: OpenAI Image" (text-to-image) and "Imagent: OpenAI Image Edit" (edit / inpaint / multi-reference compose). - Models gpt-image-2 / gpt-image-1.5 / gpt-image-1 with a per-model dynamic UI (comfy_api DynamicCombo): size, background, custom WxH, and input_fidelity are revealed only for the models that support them. - Edit node accepts an auto-growing set of reference images (up to 16) plus an optional inpaint mask; generate supports batches up to 8. - API key via OPENAI_API_KEY or a local config.json. Requires ComfyUI >= 0.23.0.
117 lines
5.0 KiB
Python
117 lines
5.0 KiB
Python
"""Parameter constants, per-model capabilities, and size validation.
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Public entry points: capabilities_for(), validate_custom_dimensions(), resolve_size(),
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resolve_background(); plus the SIZE_PRESETS / QUALITIES / BACKGROUNDS / FORMATS /
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INPUT_FIDELITIES / MODERATIONS lists and the CUSTOM_DIM_* widget bounds.
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"""
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from __future__ import annotations
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import logging
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log = logging.getLogger("imagent")
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# Size presets. The base sizes work on every gpt-image model; the high-res presets
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# and 'custom' are gpt-image-2 only (gated in resolve_size to stay cross-model safe).
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_BASE_SIZES = ["auto", "1024x1024", "1024x1536", "1536x1024"]
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_GPT2_SIZES = ["2048x2048", "2048x1152", "1152x2048", "3840x2160", "2160x3840"]
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_GPT2_ONLY_SIZES = set(_GPT2_SIZES)
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SIZE_PRESETS = [*_BASE_SIZES, *_GPT2_SIZES, "custom"]
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# Per-model size option lists for the IO DynamicCombo (what each model can pick).
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SIZES_BASE = list(_BASE_SIZES) # gpt-image-1 / 1.5
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SIZES_GPT2 = [*_BASE_SIZES, *_GPT2_SIZES, "custom"] # gpt-image-2
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# custom_width / custom_height INT-widget bounds (mirror the official node).
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CUSTOM_DIM_MIN, CUSTOM_DIM_MAX, CUSTOM_DIM_STEP = 1024, 3840, 16
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# Per-model background option lists (gpt-image-2 cannot do transparent).
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BACKGROUNDS = ["auto", "opaque", "transparent"]
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BACKGROUNDS_GPT2 = ["auto", "opaque"]
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QUALITIES = ["auto", "low", "medium", "high"]
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FORMATS = ["png", "jpeg", "webp"]
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INPUT_FIDELITIES = ["high", "low"]
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MODERATIONS = ["auto", "low"]
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# Widget bounds shared by both nodes' IO schemas.
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N_MIN, N_MAX = 1, 8
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# Per-model capability flags. Keys (all default False for unknown models):
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# custom_size - arbitrary WxH sizes (gpt-image-2 only)
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# input_fidelity - edit input_fidelity param (gpt-image-1.x)
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# transparent_background - background="transparent" (NOT gpt-image-2, which errors)
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_DEFAULT_CAPS = {
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"custom_size": False, "input_fidelity": False, "transparent_background": False,
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}
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CAPABILITIES: dict[str, dict[str, bool]] = {
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"gpt-image-2": {"custom_size": True, "input_fidelity": False, "transparent_background": False},
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"gpt-image-1.5": {"custom_size": False, "input_fidelity": True, "transparent_background": True},
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"gpt-image-1": {"custom_size": False, "input_fidelity": True, "transparent_background": True},
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}
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# gpt-image-2 custom-resolution constraints (mirror the official node, 2026-06-08).
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_MAX_EDGE = 3840
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_MIN_TOTAL_PX = 655_360
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_MAX_TOTAL_PX = 8_294_400
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def capabilities_for(model: str) -> dict[str, bool]:
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"""Return a copy of the capability flags for *model*, defaulting to all-False."""
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return dict(CAPABILITIES.get(model, _DEFAULT_CAPS))
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def validate_custom_dimensions(width: int, height: int) -> str:
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"""Validate gpt-image-2 custom WxH dimensions; return the normalized 'WxH'.
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Rules match the official node: multiples of 16, max edge 3840, aspect <= 3:1,
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and total pixels between 655,360 and 8,294,400.
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"""
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try:
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w, h = int(width), int(height)
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except (TypeError, ValueError):
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raise ValueError(f"custom dimensions must be integers, got {width!r}x{height!r}") from None
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if w <= 0 or h <= 0:
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raise ValueError(f"custom dimensions must be positive, got {w}x{h}")
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if w % 16 or h % 16:
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raise ValueError(f"custom width and height must be multiples of 16, got {w}x{h}")
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if max(w, h) > _MAX_EDGE:
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raise ValueError(f"custom max edge must be <= {_MAX_EDGE}, got {w}x{h}")
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if max(w, h) / min(w, h) > 3:
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raise ValueError(f"custom aspect ratio must not exceed 3:1, got {w}x{h}")
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total = w * h
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if not (_MIN_TOTAL_PX <= total <= _MAX_TOTAL_PX):
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raise ValueError(
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f"custom total pixels must be between {_MIN_TOTAL_PX} and {_MAX_TOTAL_PX}, got {total}")
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return f"{w}x{h}"
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def resolve_size(size: str, custom_width: int, custom_height: int, model: str) -> str:
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"""Resolve the size parameter to a value the selected model accepts.
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'custom' and the high-res presets are gpt-image-2 only; for other models they
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fall back to 'auto' so switching models never sends an unsupported size.
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"""
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caps = capabilities_for(model)
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if size == "custom":
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if not caps["custom_size"]:
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log.info("imagent: %s does not support custom sizes; using 'auto'.", model)
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return "auto"
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return validate_custom_dimensions(custom_width, custom_height)
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if size in _GPT2_ONLY_SIZES and not caps["custom_size"]:
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log.info("imagent: size %s is gpt-image-2 only; using 'auto' for %s.", size, model)
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return "auto"
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return size
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def resolve_background(background: str, model: str) -> str:
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"""Drop an unsupported transparent background to 'auto'.
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gpt-image-2 errors on background='transparent'; only gpt-image-1.x supports
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it. Falling back to 'auto' keeps the node compatible across model switches.
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"""
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if background == "transparent" and not capabilities_for(model)["transparent_background"]:
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log.info("imagent: %s does not support a transparent background; using 'auto'.", model)
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return "auto"
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return background
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