feat: 新增启动欢迎通知、流式预览节点及多项功能更新
- 新增启动弹窗通知（绿色主题，支持关闭） - 新增 StreamPreview 流式文本预览节点 - 新增 fileUpload、updateNotifier 前端 JS 模块 - 重构多个 client，统一错误处理 - 删除废弃节点 batch_nano_banana_v2、quan_neng_sheng_tu 等 - 将 .config 纳入版本控制（已清空密钥）
This commit is contained in:
Jony
+56
-147
@@ -52,7 +52,7 @@ except ImportError:
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# ============================================================================
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# 是否启用调试日志（打印完整的 API 响应内容）
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# 设置为 True 以启用调试日志，False 以禁用
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DEBUG_LOG_ENABLED = False
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DEBUG_LOG_ENABLED = True
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# 是否启用请求体日志（打印发送给 API 的请求体，base64 图片数据将自动截断）
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# 设置为 True 以启用请求体日志，False 以禁用
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REQUEST_LOG_ENABLED = False
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@@ -177,18 +177,6 @@ class NanoBananaPro:
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"max": 1000,
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"step": 1
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}),
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"像素缩放": ("BOOLEAN", {
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"default": True,
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"label_on": "打开",
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"label_off": "关闭"
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}),
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"分辨率像素": ("FLOAT", {
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"default": 1.0,
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"min": 0.1,
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"max": 100.0,
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"step": 0.1,
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"display": "number"
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}),
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"谷歌搜索（联网）": (["关闭", "打开"], {
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"default": "关闭"
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}),
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@@ -199,11 +187,6 @@ class NanoBananaPro:
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"default": 0,
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"min": 0,
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"max": 0xffffffffffffffff
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}),
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"跳过错误": ("BOOLEAN", {
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"default": False,
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"label_on": "打开",
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"label_off": "关闭"
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})
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},
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"optional": optional_inputs
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@@ -309,14 +292,16 @@ class NanoBananaPro:
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global_task_index: int,
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enable_grounding: bool = False,
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enable_image_search: bool = False,
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save_to_disk: bool = True,
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) -> dict:
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"""执行单个生成任务，生成后立即保存到磁盘"""
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"""执行单个生成任务"""
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result = {
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"global_task_index": global_task_index,
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"prompt": prompt,
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"success": False,
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"generated_count": 0,
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"saved_files": [],
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"output_images": [],
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"error": None
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}
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@@ -335,20 +320,23 @@ class NanoBananaPro:
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)
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if gen_result:
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images_list, _ = gen_result
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for gen_img in images_list:
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output_path = generate_timestamp_filename(
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output_folder=output_folder,
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extension=".png"
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)
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save_image(gen_img, output_path)
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result["saved_files"].append(output_path)
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gen_img = None # 释放内存
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if save_to_disk:
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for gen_img in images_list:
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output_path = generate_timestamp_filename(
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output_folder=output_folder,
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extension=".png"
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)
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save_image(gen_img, output_path)
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result["saved_files"].append(output_path)
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gen_img = None
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else:
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result["output_images"] = images_list
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result["success"] = True
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result["generated_count"] = len(images_list)
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except Exception as e:
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result["error"] = str(e)
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return result
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async def _process_batch_async(
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@@ -363,8 +351,9 @@ class NanoBananaPro:
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pbar=None,
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enable_grounding: bool = False,
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enable_image_search: bool = False,
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save_to_disk: bool = True,
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) -> List[dict]:
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"""异步批量处理：每个提示词独立调用 API，生成后立即写磁盘"""
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"""异步批量处理：每个提示词独立调用 API"""
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# 构建任务列表：(prompt, sub_index) 用于 images_per_prompt > 1 的情况
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tasks_def = []
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for p_idx, prompt in enumerate(prompts):
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@@ -373,9 +362,8 @@ class NanoBananaPro:
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total_tasks = len(tasks_def)
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num_prompts = len(prompts)
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print(f"Nano Banana Pro: 批量提示词模式 | {num_prompts}个提示词 × {images_per_prompt}张/提示词 | 共{total_tasks}任务")
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max_concurrent = 10
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max_concurrent = 50
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num_batches = math.ceil(total_tasks / max_concurrent)
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all_results = []
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@@ -383,7 +371,7 @@ class NanoBananaPro:
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success_count = 0
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fail_count = 0
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connector = aiohttp.TCPConnector(limit=0, limit_per_host=0)
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connector = aiohttp.TCPConnector(ssl=False, limit=0, limit_per_host=0)
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async with aiohttp.ClientSession(connector=connector) as session:
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for batch_idx in range(num_batches):
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@@ -405,6 +393,7 @@ class NanoBananaPro:
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global_task_index=i,
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enable_grounding=enable_grounding,
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enable_image_search=enable_image_search,
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save_to_disk=save_to_disk,
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)
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)
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tasks.append(task)
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@@ -454,23 +443,18 @@ class NanoBananaPro:
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宽高比: str,
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分辨率: str,
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生图数量: int,
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像素缩放: bool,
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分辨率像素: float,
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seed: int,
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跳过错误: bool = False,
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**kwargs
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) -> Tuple[torch.Tensor]:
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"""
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生成图像
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Args:
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prompt: 提示词
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模型: 模型名称
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宽高比: 宽高比
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分辨率: 分辨率
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生图数量: 批次大小
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像素缩放: 是否启用像素缩放
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分辨率像素: 目标像素数（百万像素）
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seed: 随机种子
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**kwargs: 搜索开关（谷歌搜索（联网）/ 图片搜索（联网））及动态参考图输入 (参考图1-9)
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注：两个搜索参数名含全角括号，不能作为 Python 形参，从 kwargs 中提取
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@@ -550,15 +534,7 @@ class NanoBananaPro:
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raise ValueError(
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f"输入图像数量 {len(input_images)} 超过限制 14 张，请减少输入图像数量"
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)
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# 应用像素缩放（如果启用）
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if input_images and 像素缩放:
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scaled_images = []
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for img in input_images:
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scaled = self.resize_to_megapixels(img, 分辨率像素)
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scaled_images.append(scaled)
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input_images = scaled_images
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# 解析批量提示词
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batch_prompts = parse_batch_prompts(prompt)
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@@ -602,14 +578,13 @@ class NanoBananaPro:
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nonlocal success_count, fail_count
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if success:
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success_count += 1
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print(f"Nano Banana Pro: 任务 {current}/{total} 成功 ✓")
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else:
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fail_count += 1
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# 更新 ComfyUI 原生进度条
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if pbar is not None:
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pbar.update(1)
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# 内存监控（每完成10个任务检查一次）
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if MEMORY_MONITOR_AVAILABLE and total > 50 and current % 10 == 0:
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import gc
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@@ -627,21 +602,10 @@ class NanoBananaPro:
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num_prompts = len(batch_prompts)
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total_images = num_prompts * 生图数量
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# ===== 批量提示词模式：异步并发+磁盘保存 =====
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# ===== 批量提示词模式：异步并发，内存输出 =====
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if pbar is not None:
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pbar = ProgressBar(total_images)
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# 确定保存路径
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output_folder = ""
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if FOLDER_PATHS_AVAILABLE:
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output_folder = folder_paths.get_output_directory()
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print(f"Nano Banana Pro: 磁盘保存模式 → {output_folder}")
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else:
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raise ValueError("无法获取 ComfyUI output 目录，请检查 folder_paths 是否可用")
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import os
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os.makedirs(output_folder, exist_ok=True)
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def run_async_in_thread():
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loop = asyncio.new_event_loop()
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asyncio.set_event_loop(loop)
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@@ -654,10 +618,11 @@ class NanoBananaPro:
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aspect_ratio=宽高比,
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images_per_prompt=生图数量,
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input_images=input_images,
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output_folder=output_folder,
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output_folder="",
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pbar=pbar,
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enable_grounding=enable_grounding,
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enable_image_search=enable_image_search,
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save_to_disk=False,
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)
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)
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finally:
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@@ -666,23 +631,20 @@ class NanoBananaPro:
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with ThreadPoolExecutor(max_workers=1) as executor:
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future = executor.submit(run_async_in_thread)
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try:
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results = future.result(timeout=3600)
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results = future.result(timeout=900)
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except TimeoutError:
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raise RuntimeError("任务执行超时（1小时），请减少提示词数量或检查网络连接")
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raise RuntimeError("任务执行超时（900秒），请减少提示词数量或检查网络连接")
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# 统计结果
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success_count = sum(1 for r in results if r.get("success", False))
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fail_count = len(results) - success_count
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total_generated = sum(r.get("generated_count", 0) for r in results)
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all_saved_files = []
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for r in results:
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all_saved_files.extend(r.get("saved_files", []))
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elapsed = time.time() - start_time
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time_str = f"{elapsed:.3f}s" if elapsed < 1 else f"{elapsed:.2f}s"
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print(f"完成！总耗时 {time_str} | 成功: {success_count}/{total_images} | 失败: {fail_count}")
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# 失败详情
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failed_results = [r for r in results if not r.get("success", False)]
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if failed_results:
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@@ -691,24 +653,17 @@ class NanoBananaPro:
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prompt_snippet = (fr.get("prompt", "") or "")[:30]
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error_msg = fr.get("error", "未知错误")
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print(f" 失败 #{idx}: {prompt_snippet}{'...' if len(prompt_snippet) >= 30 else ''} → {error_msg}")
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# 从磁盘加载最后 10 张图片
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# 收集内存中的图像
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output_images = []
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max_output_images = 10
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recent_files = all_saved_files[-min(max_output_images, len(all_saved_files)):]
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for file_path in recent_files:
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try:
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img = Image.open(file_path)
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output_images.append(img)
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except Exception as e:
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print(f"Nano Banana Pro: 无法加载 {file_path} - {e}")
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for r in results:
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output_images.extend(r.get("output_images", []))
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if not output_images:
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placeholder = Image.new('RGB', (512, 512), color=(128, 128, 128))
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output_images = [placeholder]
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output_tensor = _images_to_tensor_safe(output_images, _NODE)
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print(f"Nano Banana Pro: 共保存 {len(all_saved_files)} 张图片到磁盘，节点输出最后 {len(output_images)} 张")
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import gc
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gc.collect()
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@@ -716,7 +671,7 @@ class NanoBananaPro:
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else:
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# 单提示词模式
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if 生图数量 == 1:
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# 单张：同步生成 + 保存到磁盘 + 输出 tensor
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# 单张：同步生成，输出 tensor
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generated_images = self.client.generate_sync(
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prompt=prompt,
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model=模型,
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@@ -730,35 +685,12 @@ class NanoBananaPro:
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enable_grounding=enable_grounding,
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enable_image_search=enable_image_search,
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)
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# 单张：保存到磁盘
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import os
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output_folder = ""
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if FOLDER_PATHS_AVAILABLE:
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output_folder = folder_paths.get_output_directory()
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print(f"Nano Banana Pro: 磁盘保存模式 → {output_folder}")
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else:
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raise ValueError("无法获取 ComfyUI output 目录，请检查 folder_paths 是否可用")
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os.makedirs(output_folder, exist_ok=True)
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for gen_img in generated_images:
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output_path = generate_timestamp_filename(output_folder=output_folder)
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save_image(gen_img, output_path)
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else:
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# 多张：异步并发 + 磁盘保存（与批量提示词逻辑一致）
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print(f"Nano Banana Pro: 单提示词×{生图数量}张 → 异步并发模式")
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# 多张：异步并发，内存输出
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if pbar is not None:
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pbar = ProgressBar(生图数量)
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output_folder = ""
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if FOLDER_PATHS_AVAILABLE:
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output_folder = folder_paths.get_output_directory()
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print(f"Nano Banana Pro: 磁盘保存模式 → {output_folder}")
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else:
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raise ValueError("无法获取 ComfyUI output 目录，请检查 folder_paths 是否可用")
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import os
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os.makedirs(output_folder, exist_ok=True)
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def run_async_in_thread():
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loop = asyncio.new_event_loop()
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asyncio.set_event_loop(loop)
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@@ -771,10 +703,11 @@ class NanoBananaPro:
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aspect_ratio=宽高比,
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images_per_prompt=生图数量,
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input_images=input_images,
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output_folder=output_folder,
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output_folder="",
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pbar=pbar,
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enable_grounding=enable_grounding,
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enable_image_search=enable_image_search,
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save_to_disk=False,
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)
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)
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finally:
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@@ -783,16 +716,13 @@ class NanoBananaPro:
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with ThreadPoolExecutor(max_workers=1) as executor:
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future = executor.submit(run_async_in_thread)
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try:
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results = future.result(timeout=3600)
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results = future.result(timeout=900)
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except TimeoutError:
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raise RuntimeError("任务执行超时（1小时），请减少生图数量或检查网络连接")
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raise RuntimeError("任务执行超时（900秒），请减少生图数量或检查网络连接")
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success_count = sum(1 for r in results if r.get("success", False))
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fail_count = len(results) - success_count
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total_generated = sum(r.get("generated_count", 0) for r in results)
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all_saved_files = []
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for r in results:
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all_saved_files.extend(r.get("saved_files", []))
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elapsed = time.time() - start_time
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time_str = f"{elapsed:.3f}s" if elapsed < 1 else f"{elapsed:.2f}s"
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@@ -806,24 +736,16 @@ class NanoBananaPro:
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error_msg = fr.get("error", "未知错误")
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print(f" 失败 #{idx}: {prompt[:30]}{'...' if len(prompt) >= 30 else ''} → {error_msg}")
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# 从磁盘加载最后 10 张图片
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# 收集内存中的图像
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output_images = []
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max_output_images = 10
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recent_files = all_saved_files[-min(max_output_images, len(all_saved_files)):]
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for file_path in recent_files:
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try:
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img = Image.open(file_path)
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output_images.append(img)
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except Exception as e:
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print(f"Nano Banana Pro: 无法加载 {file_path} - {e}")
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for r in results:
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output_images.extend(r.get("output_images", []))
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if not output_images:
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placeholder = Image.new('RGB', (512, 512), color=(128, 128, 128))
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output_images = [placeholder]
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output_tensor = _images_to_tensor_safe(output_images, _NODE)
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print(f"Nano Banana Pro: 共保存 {len(all_saved_files)} 张图片到磁盘，节点输出最后 {len(output_images)} 张")
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# 不生成 prompts_map.txt（单提示词无需映射）
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import gc
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gc.collect()
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@@ -851,9 +773,9 @@ class NanoBananaPro:
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# 打印最终汇总
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if fail_count > 0:
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print(f"[4/4] 完成！总耗时 {time_str} | 成功 {success_count}张 | 失败 {fail_count}张")
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print(f"完成！总耗时 {time_str} | 成功 {success_count}张 | 失败 {fail_count}张")
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else:
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print(f"[4/4] 完成！总耗时 {time_str} | 成功 {len(generated_images)}张")
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print(f"完成！总耗时 {time_str} | 成功 {len(generated_images)}张")
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# 最终内存清理
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||||
import gc
|
||||
@@ -861,7 +783,7 @@ class NanoBananaPro:
|
||||
if MEMORY_MONITOR_AVAILABLE and 生图数量 > 50:
|
||||
final_memory = process.memory_info().rss / 1024 / 1024
|
||||
print(f"Nano Banana Pro: 最终内存使用: {final_memory:.1f} MB")
|
||||
|
||||
|
||||
return (output_tensor,)
|
||||
|
||||
except ValueError as e:
|
||||
@@ -869,24 +791,12 @@ class NanoBananaPro:
|
||||
if str(e) == "未授权！":
|
||||
print("请联系作者授权后方可使用！")
|
||||
raise ValueError("未授权！") from None
|
||||
if 跳过错误:
|
||||
print("Nano Banana Pro: ⚠️ 跳过错误已开启，返回占位图继续执行队列")
|
||||
placeholder = Image.new('RGB', (512, 512), color=(128, 128, 128))
|
||||
return (pil_to_tensor([placeholder]),)
|
||||
raise ValueError(str(e)) from None
|
||||
|
||||
except RuntimeError as e:
|
||||
if 跳过错误:
|
||||
print("Nano Banana Pro: ⚠️ 跳过错误已开启，返回占位图继续执行队列")
|
||||
placeholder = Image.new('RGB', (512, 512), color=(128, 128, 128))
|
||||
return (pil_to_tensor([placeholder]),)
|
||||
raise RuntimeError(str(e)) from None
|
||||
|
||||
except Exception as e:
|
||||
if 跳过错误:
|
||||
print("Nano Banana Pro: ⚠️ 跳过错误已开启，返回占位图继续执行队列")
|
||||
placeholder = Image.new('RGB', (512, 512), color=(128, 128, 128))
|
||||
return (pil_to_tensor([placeholder]),)
|
||||
raise type(e)(str(e)) from None
|
||||
|
||||
finally:
|
||||
@@ -898,8 +808,7 @@ class NanoBananaPro:
|
||||
print(f"Nano Banana Pro: {balance_info}")
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
|
||||
# 最终内存清理
|
||||
import gc
|
||||
gc.collect()
|
||||
print(f"Nano Banana Pro: 最终内存清理完成")
|
||||
gc.collect()
|
||||
Reference in New Issue
Block a user