""" o1key GPT Image 节点 支持 gpt-image-1 / gpt-image-1.5 模型的文生图、图生图、图像编辑(带蒙版) """ import time import torch from ..clients.gpt_image_client import GptImageClient class O1keyGPTImage: """ o1key GPT Image 节点 功能: - 文生图:仅提供 prompt - 图生图:提供 prompt + 图片(无遮罩) - 图像编辑:提供 prompt + 图片 + 遮罩(白色区域将被替换) 参数: - prompt : 文本提示词(多行) - 模型 : 模型选择 - 分辨率 : 图像尺寸(auto 让 API 自动决定) - 生图数量 : 生成数量 1-8 - seed : 随机种子(0 表示不指定) - 图片 : 可选参考图(用于图生图或编辑) - 遮罩 : 可选蒙版(白色区域将被替换) """ @classmethod def INPUT_TYPES(cls): return { "required": { "prompt": ("STRING", { "default": "", "multiline": True, "tooltip": "Text prompt for GPT Image", }), }, "optional": { "模型": ([ "gpt-image-1", "gpt-image-1.5", "gpt-image-2-特价", "gpt-image-1-特价", "gpt-image-1.5-特价", ], { "default": "gpt-image-1.5", }), "分辨率": ([ "auto(默认)", "1024x1024(正方形)", "1536x1024(景观)", "1024x1536(肖像)", "2048x2048(2K 平方)", "2048x1152(2K 横屏)", "3840x2160(4K 横屏)", "2160x3840(4K 竖屏)", ], { "default": "auto(默认)", "tooltip": "Image size (auto = API decides)", }), "生图数量": ("INT", { "default": 1, "min": 1, "max": 8, "step": 1, "display": "number", "tooltip": "How many images to generate", }), "seed": ("INT", { "default": 0, "min": 0, "max": 2**31 - 1, "step": 1, "display": "number", "control_after_generate": True, "tooltip": "Random seed (0 = not specified)", }), "图片": ("IMAGE", { "tooltip": "Optional reference image for image editing.", }), "遮罩": ("MASK", { "tooltip": "Optional mask for inpainting (white areas will be replaced)", }), }, } RETURN_TYPES = ("IMAGE",) RETURN_NAMES = ("IMAGE",) FUNCTION = "generate" CATEGORY = "o1key/image" OUTPUT_NODE = False def generate( self, prompt: str, 模型: str = "gpt-image-1.5", 分辨率: str = "auto", 生图数量: int = 1, seed: int = 0, 图片=None, 遮罩=None, ): """ 生成图像(文生图 / 图生图 / 图像编辑) 路由逻辑: - 无图片 → generations 接口(文生图) - 有图片,无遮罩 → edits 接口(图生图) - 有图片,有遮罩 → edits 接口(图像编辑 + 蒙版) """ start_time = time.time() # ── 1. 参数校验 ─────────────────────────────────────────────────────── if not prompt or not prompt.strip(): raise ValueError("提示词不能为空") if 遮罩 is not None and 图片 is None: raise ValueError("提供了遮罩但未提供图片,请同时提供图片和遮罩") # ── 2. 解析分辨率显示值 → API 参数值 ────────────────────────────────── size = 分辨率.split("(")[0].strip() # ── 2. 创建客户端 ───────────────────────────────────────────────────── try: client = GptImageClient() except ValueError as e: if str(e) == "未授权!": print("[o1key GPT Image] 请联系作者授权后方可使用!") raise ValueError("未授权!") from None raise # ── 3. 调用 API ─────────────────────────────────────────────────────── try: pil_images = client.run_sync( prompt=prompt, model=模型, quality="low", background="auto", size=size, n=生图数量, seed=seed, image_tensor=图片, mask_tensor=遮罩, ) except Exception as e: error_msg = str(e).split('\n')[0] print(f"[o1key GPT Image] ❌ {error_msg}") raise RuntimeError(error_msg) from None # ── 4. PIL → tensor ─────────────────────────────────────────────────── output_tensor = GptImageClient._pil_list_to_tensor(pil_images) # ── 5. 完成日志 ─────────────────────────────────────────────────────── elapsed = time.time() - start_time print( f"[o1key GPT Image] 完成!耗时 {elapsed:.1f}s," f"输出 {output_tensor.shape[0]} 张 " f"{output_tensor.shape[2]}×{output_tensor.shape[1]}" ) return (output_tensor,)