Comfyui Automation Skill

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Install skill "Comfyui Automation Skill" with this command: npx skills add wuxiaosa86-cmd/comfyui-automation-skill


name: "comfyui_automation_skill" version: "1.0.0" author: "OpenClaw" tags: ["comfyui", "automation", "workflow"] dependencies: ["python", "requests"] permissions: ["network"]

comfyui_automation_skill

适用场景

  • 需要自动执行ComfyUI工作流的场景
  • 批量处理图像、视频等素材的自动化任务
  • 需要根据工作流需求收集素材并执行的场景
  • 希望通过API接口控制ComfyUI工作流的场景
  • 需要监控工作流执行状态并获取结果的场景

前置条件

  • 输入要求:工作流标识信息(workflowId或工作流昵称)
  • 环境依赖:Python 3.6+,requests库
  • 权限要求:需要网络访问权限以调用RunningHub API
  • API Key:需要RunningHub API密钥

参数定义

  • workflow_identifier (string): 工作流标识信息,可以是workflowId或工作流昵称
  • api_key (string): RunningHub API密钥
  • webhook_url (string) [optional]: 用于接收任务完成通知的webhook URL

执行步骤

  1. 技能启动阶段:接收用户提供的工作流标识信息
  2. 工作流分析阶段:自动获取工作流JSON结构,分析需要用户输入的节点
  3. 节点选择阶段:显示所有识别到的节点,用户选择需要配置的节点
  4. 智能参数收集阶段:对选中的节点进行配置,支持图片上传、文本输入等
  5. 素材完整性检查:验证所有必要的素材是否已收集完整
  6. 执行确认阶段:请求用户确认是否执行运行操作
  7. 工作流执行阶段:使用ComfyUI任务1-简易或任务2-高级接口执行工作流
  8. 结果反馈阶段:监控执行状态,获取返回结果并反馈给用户

支持的节点类型

  • LoadImage: 加载图片节点(支持本地文件或URL)
  • CLIPTextEncode / CLIPTextEncode (NSP): CLIP文本编码器
  • Seed (rgthree): 随机种子节点
  • RH_Translator: RunningHub翻译器
  • KSampler: K采样器(支持seed、steps、cfg、denoise)
  • easy sam3ImageSegmentation: 图像分割
  • ControlNetInpaintingAliMamaApply: ControlNet应用
  • ModelSamplingAuraFlow: 模型采样

异常处理

  • API调用失败:重试3次,每次间隔2秒
  • 工作流执行超时:设置300秒超时
  • 素材格式错误:提示用户重新上传正确格式的素材

最佳实践

  • 确保提供的工作流标识信息正确无误
  • 准备好所有必要的素材文件
  • 在执行前仔细确认工作流参数
  • 建议在 RunningHub 平台先测试工作流

完整文档

详细使用说明请参考 README.md 文件。

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