ComfyUI V8 秋叶中文版助手 / ComfyUI V8 Aki Bundle Assistant#

功能概览 / Features#

功能描述🔍 环境检测检测整合包安装状态、模型、依赖🚀 一键启动启动绘世启动器或ComfyUI核心服务🎨 工作流生成文生图、图生图、ControlNet、InstantID、扩图、局部重绘⚙️ 参数优化显存优化、常用参数推荐🐛 故障排查常见错误诊断与修复方案📦 模型管理Checkpoint/LoRA/ControlNet 模型切换🔄 批量生成多提示词批量出图🔗 增强功能绘世启动器/300+节点/国内加速/FLUX支持📊 工作流管理导出/导入/复制/对比

触发词 / Triggers#

ComfyUI, comfyui, 秋叶, 绘世启动器, 文生图, 图生图, ControlNet, InstantID, 扩图, 局部重绘, 工作流, comfy workflow

使用方法 / Usage#

命令格式 / Command Format#

text

检测ComfyUI环境        # 环境检测
启动ComfyUI            # 一键启动
生成文生图工作流        # 文生图
生成图生图工作流        # 图生图
生成ControlNet工作流    # ControlNet
生成InstantID工作流     # InstantID
生成扩图工作流          # 扩图
生成局部重绘工作流       # 局部重绘
优化ComfyUI参数         # 参数优化
ComfyUI故障排查         # 故障排查
批量生成图片            # 批量生成
管理ComfyUI模型         # 模型管理

核心参数 / Core Parameters#

文生图 / Text-to-Image#

参数默认值说明prompt高质量, 8k, 高清, 细节丰富正向提示词negative_prompt模糊, 低分辨率, 畸形, 水印负向提示词modelsdxl_base.safetensors模型选择width1024宽度height1024高度steps28采样步数cfg7CFG强度samplerdpmpp_2m采样器schedulerkarras调度器

模型类型 / Model Types#

• SDXL Base: sdxl_base.safetensors (1024x1024 推荐)
• SD 1.5: sd15_base.safetensors (512x512 推荐)
• FLUX: flux_dev.safetensors / flux_schnell.safetensors (1024x1024+)
• InstantID: 需要 antelopev2 embeddings + ip-adapter-instantid-sdxl.safetensors

工作流 JSON 结构（秋叶V8标准）/ Workflow JSON Structure#

json

{
  "name": "秋叶V8-文生图",
  "nodes": [
    {"type": "CheckpointLoaderSimple", "inputs": {"ckpt_name": "sdxl_base.safetensors"}},
    {"type": "CLIPTextEncode", "inputs": {"text": "正向提示词"}},
    {"type": "CLIPTextEncode", "inputs": {"text": "负向提示词"}},
    {"type": "EmptyLatentImage", "inputs": {"width": 1024, "height": 1024, "batch_size": 1}},
    {"type": "KSampler", "inputs": {"steps": 28, "cfg": 7, "sampler_name": "dpmpp_2m", "scheduler": "karras"}},
    {"type": "VAEDecode", "inputs": {}},
    {"type": "SaveImage", "inputs": {"filename_prefix": "txt2img"}}
  ]
}

故障排查 / Troubleshooting#

错误现象解决方案启动闪退安装 .NET Framework 4.8+、以管理员运行、检查路径无中文/空格显存不足开启 --lowvram 模式、降低分辨率、分块加载模型模型加载失败检查模型完整性、确认放置在正确目录 (models/checkpoints)节点缺失绘世启动器 → 拓展管理 → 一键安装缺失节点中文乱码秋叶V8已内置中文，无需修改，重启即可卡在 "Loading models"检查网络/磁盘空间、手动下载模型到 models/checkpoints

显存优化方案 / VRAM Optimization#

显存推荐方案< 6GB4bit量化、SD 1.5/7B小模型、关闭高分辨率6-12GB8bit量化、1024x1024、启用VAE分块解码> 12GBFP16原生、1536x1536高分辨率、批量生成bash

# 启动参数（编辑 启动ComfyUI.bat）
# 低显存模式
.\python_embeded\python.exe .\main.py --lowvram --cpu

# 中等显存（RTX 3060 12G）
.\python_embeded\python.exe .\main.py --normalvram

# 秋叶V8启动器勾选「低显存模式」即可

模型目录结构 / Model Directory Structure#

text

ComfyUI-aki-V8/
├── models/
│   ├── checkpoints/          # SD/SDXL/FLUX 主模型
│   ├── lora/                  # LoRA 模型
│   ├── controlnet/            # ControlNet 模型
│   ├── embeddings/           # Textual Inversion / InstantID
│   ├── vae/                   # VAE 模型
│   └── upscale_models/        # 放大模型 (ESRGAN等)
├── user/
│   └── default/
│       └── workflows/         # 默认工作流存储
└── 启动ComfyUI.bat            # 启动脚本

工作流模板（秋叶V8标准节点）/ Workflow Templates#

1. 文生图 (Text-to-Image)#

json

{
  "name": "秋叶V8-文生图",
  "nodes": [
    {"type": "CheckpointLoaderSimple", "inputs": {"ckpt_name": "sdxl_base.safetensors"}},
    {"type": "CLIPTextEncode", "inputs": {"text": "正向提示词"}},
    {"type": "CLIPTextEncode", "inputs": {"text": "负向提示词"}},
    {"type": "EmptyLatentImage", "inputs": {"width": 1024, "height": 1024, "batch_size": 1}},
    {"type": "KSampler", "inputs": {"steps": 28, "cfg": 7, "sampler_name": "dpmpp_2m", "scheduler": "karras"}},
    {"type": "VAEDecode", "inputs": {}},
    {"type": "SaveImage", "inputs": {"filename_prefix": "txt2img"}}
  ]
}

2. 图生图 (Image-to-Image)#

json

{
  "name": "秋叶V8-图生图",
  "nodes": [
    {"type": "CheckpointLoaderSimple", "inputs": {"ckpt_name": "sdxl_base.safetensors"}},
    {"type": "CLIPTextEncode", "inputs": {"text": "正向提示词"}},
    {"type": "CLIPTextEncode", "inputs": {"text": "负向提示词"}},
    {"type": "LoadImage", "inputs": {"image": "input.png"}},
    {"type": "VAEEncode", "inputs": {}},
    {"type": "KSampler", "inputs": {"steps": 28, "cfg": 7, "sampler_name": "dpmpp_2m", "scheduler": "karras"}},
    {"type": "VAEDecode", "inputs": {}},
    {"type": "SaveImage", "inputs": {"filename_prefix": "img2img"}}
  ]
}

3. ControlNet 线稿/边缘/姿态控制#

json

{
  "name": "秋叶V8-ControlNet",
  "nodes": [
    {"type": "CheckpointLoaderSimple", "inputs": {"ckpt_name": "sdxl_base.safetensors"}},
    {"type": "CLIPTextEncode", "inputs": {"text": "正向提示词"}},
    {"type": "CLIPTextEncode", "inputs": {"text": "负向提示词"}},
    {"type": "LoadImage", "inputs": {"image": "control.png"}},
    {"type": "ControlNetLoader", "inputs": {"control_net_name": "canny.safetensors"}},
    {"type": "ControlNetApply", "inputs": {"strength": 0.8}},
    {"type": "EmptyLatentImage", "inputs": {"width": 1024, "height": 1024, "batch_size": 1}},
    {"type": "KSampler", "inputs": {"steps": 28, "cfg": 7, "sampler_name": "dpmpp_2m", "scheduler": "karras"}},
    {"type": "VAEDecode", "inputs": {}},
    {"type": "SaveImage", "inputs": {"filename_prefix": "controlnet"}}
  ]
}

4. InstantID 人脸一致性#

json

{
  "name": "秋叶V8-InstantID人脸",
  "nodes": [
    {"type": "CheckpointLoaderSimple", "inputs": {"ckpt_name": "ip-adapter-instantid-sdxl.safetensors"}},
    {"type": "CLIPTextEncode", "inputs": {"text": "正向提示词"}},
    {"type": "CLIPTextEncode", "inputs": {"text": "负向提示词"}},
    {"type": "LoadImage", "inputs": {"image": "face.png"}},
    {"type": "InstantIDModelLoader", "inputs": {}},
    {"type": "InstantIDApply", "inputs": {"strength": 0.7}},
    {"type": "EmptyLatentImage", "inputs": {"width": 1024, "height": 1024, "batch_size": 1}},
    {"type": "KSampler", "inputs": {"steps": 28, "cfg": 7, "sampler_name": "dpmpp_2m", "scheduler": "karras"}},
    {"type": "VAEDecode", "inputs": {}},
    {"type": "SaveImage", "inputs": {"filename_prefix": "instantid"}}
  ],
  "models_required": ["antelopev2", "ip-adapter-instantid-sdxl"]
}

5. 扩图 (Outpainting)#

json

{
  "name": "秋叶V8-智能扩图",
  "nodes": [
    {"type": "CheckpointLoaderSimple", "inputs": {"ckpt_name": "sdxl_base.safetensors"}},
    {"type": "CLIPTextEncode", "inputs": {"text": "正向提示词"}},
    {"type": "CLIPTextEncode", "inputs": {"text": "负向提示词"}},
    {"type": "LoadImage", "inputs": {"image": "base.png"}},
    {"type": "ImageResize", "inputs": {"width": 2048, "height": 2048, "method": "lanczos"}},
    {"type": "VAEEncode", "inputs": {}},
    {"type": "KSampler", "inputs": {"steps": 28, "cfg": 7, "sampler_name": "dpmpp_2m", "scheduler": "karras"}},
    {"type": "VAEDecode", "inputs": {}},
    {"type": "SaveImage", "inputs": {"filename_prefix": "outpaint"}}
  ]
}

6. 局部重绘 (Inpainting)#

json

{
  "name": "秋叶V8-局部重绘",
  "nodes": [
    {"type": "CheckpointLoaderSimple", "inputs": {"ckpt_name": "sdxl_base.safetensors"}},
    {"type": "CLIPTextEncode", "inputs": {"text": "正向提示词"}},
    {"type": "CLIPTextEncode", "inputs": {"text": "负向提示词"}},
    {"type": "LoadImage", "inputs": {"image": "base.png"}},
    {"type": "LoadImage", "inputs": {"image": "mask.png"}},
    {"type": "VAEEncodeForInpaint", "inputs": {}},
    {"type": "KSampler", "inputs": {"steps": 28, "cfg": 7, "sampler_name": "dpmpp_2m", "scheduler": "karras"}},
    {"type": "VAEDecode", "inputs": {}},
    {"type": "SaveImage", "inputs": {"filename_prefix": "inpaint"}}
  ]
}

常见报错修复 / Common Error Fixes#

错误修复方法缺少.NET安装.NET 6.0桌面运行时，绘世启动器会自动引导下载显存不足启动器勾选低显存、4bit量化、减小尺寸节点缺失绘世启动器 → 拓展管理 → 一键安装缺失节点模型加载失败模型路径无中文/空格，放到models/checkpoints中文乱码秋叶V8已内置中文，无需修改，重启即可

注意事项 / Notes#

• 秋叶V8已内置中文界面，无需额外汉化
• 模型建议放置在 models/checkpoints/ 目录
• FLUX 模型需要更多显存 (建议 16GB+)
• 定期使用绘世启动器更新内核和插件
• 工作流保存路径： user/default/workflows/

秋叶V8专属增强功能 / Aki V8 Exclusive Features#

功能说明绘世启动器内核/插件/模型/更新 一站式管理300+预装节点ControlNet/InstantID/LayerDiffusion/IC-Light中文界面节点/菜单/提示/日志 全汉化国内加速GitHub镜像 + 模型下载加速全模型支持FLUX / SD3 / SDXL / SD1.5一键备份工作流/模型/配置 备份还原

机器人触发指令 / Bot Commands#

指令功能ComfyUI检测环境检测启动ComfyUI一键启动生成文生图工作流生成txt2img生成ControlNet工作流生成ControlNetComfyUI显存优化VRAM优化ComfyUI修复报错修复ComfyUI增强功能查看V8增强功能