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70 lines
2.4 KiB
Python
70 lines
2.4 KiB
Python
"""Small helpers for recognizing image-generation model IDs."""
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from __future__ import annotations
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import math
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_IMAGE_MODEL_PREFIXES = (
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"gpt-image",
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"dall-e",
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"chatgpt-image",
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"hidream",
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"qwen-image",
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"z-image",
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"flux",
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"stable-diffusion",
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"sdxl",
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"boogu",
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"krea-2",
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)
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def model_id_leaf(model_id: str) -> str:
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"""Return the provider-stripped model id leaf in lowercase."""
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return str(model_id or "").strip().split("/")[-1].lower()
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def image_edit_size(model_id: str, width: int, height: int) -> str:
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"""Match source geometry within the fixed GPT Image 1 output sizes."""
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if width <= 0 or height <= 0:
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raise ValueError("Image dimensions must be positive")
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leaf = model_id_leaf(model_id)
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if leaf in {"gpt-image-1", "gpt-image-1-mini", "gpt-image-1.5",
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"gpt-5-image", "gpt-5-image-mini"}:
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sizes = ((1024, 1024), (1536, 1024), (1024, 1536))
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width, height = min(sizes, key=lambda candidate: (
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abs(math.log((candidate[0] / candidate[1]) / (width / height))),
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abs(candidate[0] * candidate[1] - width * height),
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))
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return f"{width}x{height}"
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def image_aspect_ratio(width: int, height: int) -> str:
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"""Choose the nearest common Image API ratio, without distorting pixels."""
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if width <= 0 or height <= 0:
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raise ValueError("Image dimensions must be positive")
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ratios = ((1, 1), (16, 9), (9, 16), (3, 2), (2, 3), (4, 3), (3, 4), (21, 9))
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w, h = min(ratios, key=lambda ratio: abs(math.log((ratio[0] / ratio[1]) / (width / height))))
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return f"{w}:{h}"
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def looks_like_image_generation_model(model_id: str) -> bool:
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"""Return True when a model id should use image generation routes.
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API providers can namespace image models, e.g. ``openai/gpt-5-image``.
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Classify by the leaf so mixed endpoints can expose chat and image models
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without marking the whole endpoint as image-only.
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"""
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mid = str(model_id or "").strip().lower()
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leaf = model_id_leaf(mid)
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if not leaf:
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return False
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if any(leaf.startswith(prefix) for prefix in _IMAGE_MODEL_PREFIXES):
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return True
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# Newer OpenAI image models use names like gpt-5-image instead of
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# gpt-image-1. Keep this pattern provider-agnostic.
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return (leaf.startswith("gpt-") and "-image" in leaf) or (
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leaf.startswith("gemini-") and "image" in leaf
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)
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