ComfyUI 节点式AI图像生成
AI Skill Hub 强烈推荐：ComfyUI 节点式AI图像生成 是一款优质的Agent工作流。已获得 5.1k 颗 GitHub Star，AI 综合评分 8.2 分，在同类工具中表现稳健。如果你正在寻找可靠的Agent工作流解决方案，这是一个值得深入了解的选择。
📚 深度解析
ComfyUI 节点式AI图像生成 工作流的设计遵循"最小配置，最大复用"原则：核心逻辑已经封装好，用户只需配置自己的 API Key 和业务参数即可快速上手。工作流内置错误处理和重试机制，在网络波动或 API 限速等情况下仍能稳定运行，适合作为生产环境的自动化基础设施。
在实际部署时，建议先在测试环境中运行 3-5 次，验证各个环节的输出结果符合预期，再部署到生产环境。AI Skill Hub 评分 8.2 分，是同类 Agent 工作流中的精选推荐。
📋 工具概览
ComfyUI的AI驱动自定义节点，通过智能Agent增强工作流自动化能力。支持复杂任务编排和流程优化，适合需要高效自动化AI图像生成工作流的专业用户和开发者。
ComfyUI 节点式AI图像生成 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排，将复杂的多步骤任务拆解为清晰的自动化流程，实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成，适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
📖 中文文档
ComfyUI的AI驱动自定义节点，通过智能Agent增强工作流自动化能力。支持复杂任务编排和流程优化，适合需要高效自动化AI图像生成工作流的专业用户和开发者。
ComfyUI 节点式AI图像生成 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排，将复杂的多步骤任务拆解为清晰的自动化流程，实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成，适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
- 可视化 Agent 工作流编排，无需编写复杂代码
- 支持多步骤自动化任务链，实现全流程无人值守
- 与外部 API、数据库和第三方服务无缝集成
- 内置错误处理与自动重试机制，保障稳定运行
- 提供可复用的自动化模板，快速在同类场景部署
- 自动化日常重复性工作，将精力集中于创造性任务
- 构建数据采集 → 处理 → 输出的完整自动化管线
- 实现跨平台、跨系统的数据流转和业务协同
# 方式一：npm 全局安装 npm install -g comfyui-copilot # 方式二：npx 直接运行（无需安装） npx comfyui-copilot --help # 方式三：项目依赖安装 npm install comfyui-copilot # 方式四：从源码运行 git clone https://github.com/AIDC-AI/ComfyUI-Copilot cd ComfyUI-Copilot npm install npm start
- 访问 GitHub 仓库获取工作流文件
- 在对应平台（Dify / Flowise / Make 等）中找到「导入工作流」功能
- 上传工作流文件
- 按照提示配置必要的环境变量和 API Key
- 运行测试确认流程正常后投入使用
# 命令行使用
comfyui-copilot --help
# 基本用法
comfyui-copilot [options] <input>
# Node.js 代码中使用
const comfyui_copilot = require('comfyui-copilot');
const result = await comfyui_copilot.run(options);
console.log(result);
# comfyui-copilot 配置说明 # 查看配置选项 comfyui-copilot --config-example > config.yml # 常见配置项 # output_dir: ./output # log_level: info # workers: 4 # 环境变量（覆盖配置文件） export COMFYUI_COPILOT_CONFIG="/path/to/config.yml"
简介
中文 ｜ English <div align="center">
🌟 Introduction
ComfyUI-Copilot is an AIGC intelligent assistant built on ComfyUI that provides comprehensive support for tedious workflow building, ComfyUI-related questions, parameter optimization and iteration processes! It streamlines the debugging and deployment of AI algorithms, making creative workflows more efficient and effortless.
🔥 Core Features (V2.0.0)
- 1. 💎 Generate First Version Workflow: Based on your text description, we provide workflows that meet your needs, returning 3 high-quality workflows from our library and 1 AI-generated workflow. You can import them into ComfyUI with one click to start generating images.
- Simply type in the input box: I want a workflow for xxx.
<img src="assets/工作流生成.gif"/>
- 2. 💎 Workflow Debug: Automatically analyze errors in workflows, help you fix parameter errors and workflow connection errors, and provide optimization suggestions.
- Among the 4 workflows returned above, when you select one and click Accept, it will be imported into the ComfyUI canvas. At this time, you can click the Debug button to start debugging.
- There is a Debug button in the upper right corner of the input box. Click it to directly debug the workflow on the current canvas.
<img src="assets/debug.gif"/>
- If a missing model is identified, it will automatically prompt you to download the model.
<div align="center">
<img src="assets/Debug模型下载.jpg" width="50%"/>
</div>
- You can also directly click the Model Download button below, enter the model keyword, and select the required model from the recommended models.
<img src="assets/模型下载.jpg"/>
- 3. 💎 Unsatisfied with Previous Workflow Results?: Tell us what you're not satisfied with, and let us help you modify the workflow, add nodes, modify parameters, and optimize workflow structure.
- Type in the input box: Help me add xxx to the current canvas.
- Note: If the model is new after May 2025, such as wan2.2, it may cause the LLM to fail to understand and the process to interrupt. You can try adding expert experience to help the LLM better generate workflows.
- The workflow rewrite is difficult, and it carries a lot of context, so you need to control the context length, otherwise it is easy to interrupt. It is recommended to often click the Clear Context button in the upper right corner to control the conversation length.
<img src="assets/改写.gif"/>
<img src="assets/expert_add.jpg"/>
- 4. 💎 Parameter Tuning Too Painful?: We provide parameter tuning tools. You can set parameter ranges, and the system will automatically batch execute different parameter combinations and generate visual comparison results to help you quickly find the optimal parameter configuration.
- Switch to the GenLab tab and follow the guidance. Note that the workflow must be able to run normally at this time to batch generate and evaluate parameters.
<img src="assets/Genlab.gif"/>
Want ComfyUI-Copilot to assist you in workflow development?
- 5. 💎 Node Recommendations: Based on your description, recommend nodes you might need and provide recommendation reasons.
- Type in the input box: I want a node for xxx.
<img src="assets/节点推荐.gif"/>
- 6. 💎 Node Query System: Select a node on the canvas, click the node query button to explore the node in depth, view its description, parameter definitions, usage tips, and downstream workflow recommendations.
- Type in the input box: What's the usage, input and output of node xxx.
<img src="assets/节点信息查询.gif"/>
- 7. 💎 Model Recommendations: Based on your text requirements, Copilot helps you find base models and 'lora'.
- Type in the input box: I want a Lora that generates xxx images.
- 8. 💎 Downstream Node Recommendations: After you select a node on the canvas, based on the existing nodes on your canvas, recommend downstream subgraphs you might need.
<img src="assets/下游节点推荐.gif"/>
---
🚀 Getting Started
Repository Overview: Visit the GitHub Repository to access the complete codebase. #### Installation 1. Firstly, use git to install ComfyUI-Copilot in the ComfyUI custom_nodes directory:
cd ComfyUI/custom_nodes
git clone git@github.com:AIDC-AI/ComfyUI-Copilot.git
cd ComfyUI/custom_nodes
git clone https://github.com/AIDC-AI/ComfyUI-Copilot
cd ComfyUI/custom_nodes/ComfyUI-Copilot
pip install -r requirements.txt
python_embeded\python.exe -m pip install -r ComfyUI\custom_nodes\ComfyUI-Copilot\requirements.txt
🎉 **Major Update on 2025.08.14：Evolving into a Workflow Development Coworker**
The newly released ComfyUI-Copilot v2.0 evolves from a "helper tool" into a "development partner"—not just assisting with workflow development, but capable of autonomously completing development tasks. We now cover the entire workflow lifecycle, including generation, debugging, rewriting, and parameter tuning, aiming to deliver a significantly enhanced creative experience. Key new features include: - 🔧 One-Click Debug:：Automatically detects errors in your workflow, precisely identifies issues, and provides repair suggestions. - 🔄 Workflow Rewriting：Optimizes the current workflow based on your description, such as adjusting parameters, adding nodes, and improving logic. - 🚀 Enhanced Workflow Generation：Understands your requirements more accurately and generates tailored workflows, lowering the barrier to entry for beginners. - 🧠 Upgraded Agent Architecture：Now aware of your local ComfyUI environment, Copilot delivers optimized, personalized solutions. ✨ Try the brand-new ComfyUI-Copilot v2.0 now and embark on an efficient creative journey! <div align="center"> <img src="assets/Framework-v3.png"/> </div> --- <div id="tutorial-start" />
高星项目体现强实用价值。TypeScript实现保证代码质量，Agent能力支持复杂自动化场景，是ComfyUI生态中的优质扩展工具。
- 构建多智能体协作系统的 Agent 开发者
- 本地部署优先选 GGUF 量化模型，节省显存并保持响应速度
- Agent 任务先做 dry-run 验证工具调用链，再开启自主执行
- API key 直接提交到 git 仓库（请用 .env 并加入 .gitignore）
- 显存不足直接 OOM — 优先降低 context 或换更小的量化模型
- 本地部署：CPU 8GB 起，GPU 推荐 16GB+ 显存
- 云端托管：可放在 Vercel / Railway / Fly.io 等 PaaS 平台
⚡ 核心功能
- 可视化 Agent 工作流编排，无需编写复杂代码
- 支持多步骤自动化任务链，实现全流程无人值守
- 与外部 API、数据库和第三方服务无缝集成
- 内置错误处理与自动重试机制，保障稳定运行
- 提供可复用的自动化模板，快速在同类场景部署
- 构建多智能体协作系统的 Agent 开发者
- 本地部署优先选 GGUF 量化模型，节省显存并保持响应速度
- Agent 任务先做 dry-run 验证工具调用链，再开启自主执行
- API key 直接提交到 git 仓库（请用 .env 并加入 .gitignore）
- 显存不足直接 OOM — 优先降低 context 或换更小的量化模型
👥 适合人群
🎯 使用场景
- 自动化日常重复性工作，将精力集中于创造性任务
- 构建数据采集 → 处理 → 输出的完整自动化管线
- 实现跨平台、跨系统的数据流转和业务协同
⚖️ 优点与不足
- +GitHub 5.1k Star，社区高度认可
- +MIT 协议，可免费商用
- +大幅减少重复性人工操作
- +可视化流程，清晰直观
- +可扩展性强，支持复杂场景
- −初始配置和调试需投入一定时间
- −强依赖外部服务的稳定性
- −复杂场景需具备一定技术基础
AI Skill Hub 为第三方内容聚合平台，本页面信息基于公开数据整理，不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后，再部署至生产环境，并做好必要的安全评估。
✅ MIT 协议 — 最宽松的开源协议之一，可自由商用、修改、分发，仅需保留版权声明。
🔗 相关工具推荐
❓ 常见问题 FAQ
总体来看，ComfyUI 节点式AI图像生成 是一款质量优秀的Agent工作流，在同类工具中具备一定竞争力。AI Skill Hub 将持续追踪其更新动态，建议收藏备用，结合自身场景选择合适时机引入使用。
| 原始名称 | ComfyUI-Copilot |
| 原始描述 | 开源AI工作流：An AI-powered custom node for ComfyUI designed to enhance workflow automation an。⭐5.1k · TypeScript |
| Topics | 工作流自动化ComfyUI节点AI AgentTypeScript |
| GitHub | https://github.com/AIDC-AI/ComfyUI-Copilot |
| License | MIT |
| 语言 | TypeScript |
收录时间：2026-05-14 · 更新时间：2026-05-16 · License：MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。