feat: 新增 Grok 图像节点、前端 UI 增强、重构 nano-banana 系列
- 新增 Grok Image 节点及客户端 - 新增 save_image_format 节点 - 新增前端 JS 扩展：画笔工具、点阵网格、侧边栏隐藏、资源切换、重命名等 - 重构 nano-banana 节点，移除 pro 版本 - 移除 multi_res_preview 节点 - 新增 http_error 工具模块 - 各客户端和节点优化改进 Co-Authored-By: Claude Opus 4.6 <[email protected]>
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Jony
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"""
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o1key Grok Image 节点
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支持 Grok Image / Grok Image Pro 模型的文生图和图生图
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"""
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import time
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from ..clients.grok_image_client import GrokImageClient
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from ..utils.image_utils import parse_batch_prompts
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from ..utils.config import NETWORK_ROUTE_OPTIONS
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try:
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from comfy.model_management import processing_interrupted, InterruptProcessingException
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_INTERRUPT_AVAILABLE = True
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except ImportError:
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_INTERRUPT_AVAILABLE = False
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processing_interrupted = lambda: False
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InterruptProcessingException = RuntimeError
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_ASPECT_RATIOS = [
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"auto", "1:1", "16:9", "9:16", "4:3", "3:4",
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"3:2", "2:3", "2:1", "1:2", "19.5:9", "9:19.5", "20:9", "9:20",
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]
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class O1keyGrokImage:
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@classmethod
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def INPUT_TYPES(cls):
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optional_inputs = {}
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for i in range(1, 4):
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optional_inputs[f"参考图{i}"] = ("IMAGE", {
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"tooltip": f"Optional reference image {i}",
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})
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return {
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"required": {
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"prompt": ("STRING", {
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"default": "",
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"multiline": True,
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"tooltip": "文本提示词，用 --- 独占一行分隔批量提示词",
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}),
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},
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"optional": {
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"模型": (["Grok Image", "Grok Image Pro"], {
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"default": "Grok Image Pro",
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}),
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"宽高比": (_ASPECT_RATIOS, {
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"default": "auto",
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}),
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"分辨率": (["1k", "2k"], {
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"default": "1k",
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}),
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"生图数量": ("INT", {
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"default": 1,
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"min": 1,
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"max": 4,
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"step": 1,
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"display": "number",
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}),
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"网络线路": (NETWORK_ROUTE_OPTIONS, {
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"default": NETWORK_ROUTE_OPTIONS[0],
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}),
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"seed": ("INT", {
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"default": 0,
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"min": 0,
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"max": 2**31 - 1,
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"step": 1,
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"display": "number",
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"control_after_generate": True,
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}),
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**optional_inputs,
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},
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}
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RETURN_TYPES = ("IMAGE",)
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RETURN_NAMES = ("IMAGE",)
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FUNCTION = "generate"
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CATEGORY = "o1key/image"
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OUTPUT_NODE = False
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def generate(
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self,
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prompt: str,
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模型: str = "Grok Image Pro",
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宽高比: str = "auto",
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分辨率: str = "1k",
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生图数量: int = 1,
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网络线路: str = "全球加速",
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seed: int = 0,
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**kwargs,
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):
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start_time = time.time()
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reference_tensors = []
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for i in range(1, 4):
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key = f"参考图{i}"
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if key in kwargs and kwargs[key] is not None:
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reference_tensors.append(kwargs[key])
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image_list = reference_tensors if reference_tensors else None
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try:
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client = GrokImageClient(route=网络线路)
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except ValueError as e:
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if str(e) == "未授权！":
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print("[o1key Grok Image] 请联系作者授权后方可使用！")
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raise ValueError("未授权！") from None
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raise
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try:
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batch_prompts = parse_batch_prompts(prompt)
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all_pil_images = []
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if batch_prompts:
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total = len(batch_prompts)
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print(f"[o1key Grok Image] 批量模式 | {total} 条提示词 | 每条生成 {生图数量} 张")
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for idx, p in enumerate(batch_prompts, 1):
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if _INTERRUPT_AVAILABLE and processing_interrupted():
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print("[o1key Grok Image] 用户取消")
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raise InterruptProcessingException()
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try:
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pil_images = client.run_sync(
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prompt=p, model=模型, aspect_ratio=宽高比,
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resolution=分辨率, n=生图数量, image_list=image_list,
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)
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all_pil_images.extend(pil_images)
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snippet = p[:30] + ("..." if len(p) >= 30 else "")
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print(f"[o1key Grok Image] [{idx}/{total}] done: {snippet}")
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except InterruptProcessingException:
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raise
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except Exception as e:
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error_msg = str(e).split('\n')[0]
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snippet = p[:30] + ("..." if len(p) >= 30 else "")
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print(f"[o1key Grok Image] [{idx}/{total}] fail: {snippet} → {error_msg}")
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else:
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if not prompt or not prompt.strip():
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raise ValueError("提示词不能为空")
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pil_images = client.run_sync(
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prompt=prompt, model=模型, aspect_ratio=宽高比,
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resolution=分辨率, n=生图数量, image_list=image_list,
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)
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all_pil_images.extend(pil_images)
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if not all_pil_images:
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raise RuntimeError("所有提示词均生成失败，无可用图像输出")
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output_tensor = GrokImageClient._pil_list_to_tensor(all_pil_images)
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elapsed = time.time() - start_time
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print(
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f"[o1key Grok Image] 完成！耗时 {elapsed:.1f}s，"
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f"输出 {output_tensor.shape[0]} 张 "
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f"{output_tensor.shape[2]}x{output_tensor.shape[1]}"
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)
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return (output_tensor,)
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finally:
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self._print_balance(client)
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def _print_balance(self, client):
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try:
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balance_data = client.query_balance_sync()
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balance_info = client.format_balance_info(balance_data)
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print(f"[o1key Grok Image] {balance_info}")
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except Exception:
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pass
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