功能修改

README.en.md

@@ -38,11 +38,136 @@ https://github.com/comfyanonymous/ComfyUI/releases/download/latest/ComfyUI_windo
    Extraction Code: b4yy
    Extract to the directory ..\ComfyUI\models\roop-face-swap
 
-6. Modify the execution.py file in the comfyUI root directory. Modify the content, search for "Return type mismatch between linked nodes," find the corresponding line, and replace
-   ```python
-   if r[val[1]] != type_input:
-   ```
-   with
-   ```python
-   if type_input !="*" and r[val[1]] != type_input:
-   ```
+6. Modify the execution.py file in the comfyUI root directory. 
+搜索 “def recursive_execute” 
+位置参考图如下：
+![Alt text](修改位置.png)
+新增内容：
+```python
+#循环添加代码----------开始----------
+def get_del_keys(key, prompt,uniqueIds):
+    keys=[]
+    for k,v in prompt.items():
+        if k in uniqueIds :
+            continue
+        for k1,v1 in v['inputs'].items():
+            if type(v1)==list and v1[0]==key:
+                keys.append(k)
+                keys=keys+get_del_keys(k,prompt,uniqueIds)
+    return keys
+#循环添加代码-----------结束---------
+```
+```python
+#循环添加代码----------开始----------
+    startNum=None
+    startData={}
+    delKeys=[]
+    backhaul={}
+    clTypes=['ForInnerEnd','IfInnerExecute','DoWhileEnd']
+    oldPrompt=None
+    if class_type in clTypes:
+        oldPrompt=copy.deepcopy(prompt)
+
+    if class_type=='ForInnerEnd':
+        startNum=prompt[unique_id]['inputs']['total'][0]
+        inputNum=prompt[unique_id]['inputs']['obj'][0]
+        maxKeyStr=sorted(list(prompt.keys()), key=lambda x: int(x.split(':')[0]))[-1]
+        maxKey = int(maxKeyStr.split(':')[0])
+        delKeys=list(set(get_del_keys(startNum,prompt,[startNum,unique_id]))) 
+        delKeys.append(startNum)
+        delKeys = list(filter(lambda x: x != inputNum, delKeys))
+        for key in delKeys:
+            outputs.pop(key, None)
+        
+        startInput=prompt[startNum]['inputs']
+        if isinstance(startInput['total'],list) or isinstance(startInput['stop'],list) or isinstance(startInput['i'],list):
+            result = recursive_execute(server, prompt, outputs, startNum, extra_data, executed, prompt_id, outputs_ui, object_storage)
+            if result[0] is not True:
+                    return result
+            
+        for x in startInput:
+            input_data = startInput[x]
+            if isinstance(input_data, list):
+                startData[x]=outputs[input_data[0]][input_data[1]][0]
+            else:
+                startData[x]=input_data
+
+        for i in range(startData['i']+1,startData['total'],startData['stop']):
+            prompt[str(maxKey+i)]=prompt[inputNum]
+            prompt[unique_id]['inputs']['obj'+str(i)]=[str(maxKey+i),prompt[unique_id]['inputs']['obj'][-1]]
+            if i==startInput['i']+1:
+                backhaul['obj'+str(i)]=prompt[unique_id]['inputs']['obj']
+            else:
+                backhaul['obj'+str(i)]=[str(maxKey+i-startInput['stop']),prompt[unique_id]['inputs']['obj'][-1]]
+    elif class_type=='DoWhileEnd':
+        startNum=prompt[unique_id]['inputs']['start'][0]
+        inputNum=prompt[unique_id]['inputs']['ANY'][0]
+        delKeys=list(set(get_del_keys(startNum,prompt,[startNum,unique_id]))) 
+        delKeys.append(startNum)
+        delKeys.append(inputNum)
+
+    #循环添加代码-----------结束---------
+```
+```python
+                #循环添加代码----------开始----------
+                if class_type=='ForInnerEnd' and x !='obj' and x.startswith('obj'):
+                    if startNum!=None:
+                        if isinstance(prompt[startNum]['inputs']['i'],list):
+                            prompt[startNum]['inputs']['i']=startData['i']+startData['stop']
+                        else:
+                            prompt[startNum]['inputs']['i']=prompt[startNum]['inputs']['i']+startData['stop']
+                        prompt[startNum]['inputs']['obj']=backhaul[x]
+                        for key in delKeys:
+                            outputs.pop(key, None)
+                #循环添加代码-----------结束---------
+```
+```python
+                #判断选择添加代码-----------开始---------
+                if class_type=='DoWhileEnd' and x == 'ANY':
+                    any=outputs[inputNum][prompt[unique_id]['inputs']['ANY'][1]][0]
+                    i=0
+                    while any:
+                        for key in delKeys:
+                            outputs.pop(key, None)
+                        i=i+1
+                        outputs['i']=[[i]]
+                        prompt[startNum]['inputs']['i']=['i',0]
+                        result = recursive_execute(server, prompt, outputs, input_unique_id, extra_data, executed, prompt_id, outputs_ui, object_storage)
+                        if result[0] is not True:
+                            return result
+                        any=outputs[inputNum][prompt[unique_id]['inputs']['ANY'][1]][0]
+            
+            if class_type=='IfInnerExecute' and x=='ANY':
+                if outputs[input_unique_id][output_index][0]:
+                    inputs['IF_FALSE']=oldPrompt[unique_id]['inputs']['IF_TRUE']
+                else:
+                    inputs['IF_TRUE']=oldPrompt[unique_id]['inputs']['IF_FALSE']
+            #判断选择添加代码-----------结束---------
+```
+```python
+        #循环添加代码----------开始----------
+        if class_type=='ForInnerEnd' or class_type=='DoWhileEnd':
+            prompt[startNum]['inputs']=oldPrompt[startNum]['inputs']
+            prompt[unique_id]['inputs']=oldPrompt[unique_id]['inputs']
+            outputs.pop(startNum, None)
+            result = recursive_execute(server, prompt, outputs, startNum, extra_data, executed, prompt_id, outputs_ui, object_storage)
+            if result[0] is not True:
+                   return result
+        if class_type=='IfInnerExecute':
+            prompt[unique_id]['inputs']=oldPrompt[unique_id]['inputs']
+        #循环添加代码-----------结束---------
+```
+搜索 “def validate_prompt
+```python
+'''优化输出开始'''
+    inputKeys=[]
+    for k,v in prompt.items():
+        for k1,v1 in v['inputs'].items():
+            if type(v1)==list and len(v1)==2:
+                inputKeys.append(v1[0])
+    for x in prompt:
+        class_ = nodes.NODE_CLASS_MAPPINGS[prompt[x]['class_type']]
+        if hasattr(class_, 'OUTPUT_NODE') and class_.OUTPUT_NODE == True and x not in inputKeys:
+            outputs.add(x)
+    '''优化输出结束'''
+``` 

README.md

@@ -42,56 +42,136 @@ https://github.com/xinntao/facexlib/releases/download/v0.2.2/parsing_parsenet.pt
 解压到 ..\ComfyUI\models\roop-face-swap 目录
 
 
-6. 修改comfyUI根目录下的execution.py文件，修改内容为,搜索“Return type mismatch between linked nodes”找到对应行，
-替换
-```python
-if r[val[1]] != type_input:
-```
-为 
-```python
-if type_input !="*" and r[val[1]] != type_input:
-```
-
+6. 修改comfyUI根目录下的execution.py文件，修改内容
 搜索 “def recursive_execute” 
 位置参考图如下：
 ![Alt text](修改位置.png)
 新增内容：
 ```python
 #循环添加代码----------开始----------
-def get_del_keys(key, prompt):
+def get_del_keys(key, prompt,uniqueIds):
     keys=[]
     for k,v in prompt.items():
+        if k in uniqueIds :
+            continue
         for k1,v1 in v['inputs'].items():
             if type(v1)==list and v1[0]==key:
                 keys.append(k)
-                keys=keys+get_del_keys(k,prompt)
+                keys=keys+get_del_keys(k,prompt,uniqueIds)
     return keys
 #循环添加代码-----------结束---------
 ```
 ```python
-    #循环添加代码----------开始----------
+#循环添加代码----------开始----------
     startNum=None
+    startData={}
     delKeys=[]
+    backhaul={}
+    clTypes=['ForInnerEnd','IfInnerExecute','DoWhileEnd']
+    oldPrompt=None
+    if class_type in clTypes:
+        oldPrompt=copy.deepcopy(prompt)
+
     if class_type=='ForInnerEnd':
         startNum=prompt[unique_id]['inputs']['total'][0]
-        inputNum=prompt[unique_id]['inputs']['images'][0]
-        startInput=prompt[startNum]['inputs']
-        maxKey = int(sorted(list(prompt.keys()), key=lambda x: int(x))[-1])
-        delKeys=list(set(get_del_keys(startNum,prompt)))
+        inputNum=prompt[unique_id]['inputs']['obj'][0]
+        maxKeyStr=sorted(list(prompt.keys()), key=lambda x: int(x.split(':')[0]))[-1]
+        maxKey = int(maxKeyStr.split(':')[0])
+        delKeys=list(set(get_del_keys(startNum,prompt,[startNum,unique_id]))) 
         delKeys.append(startNum)
         delKeys = list(filter(lambda x: x != inputNum, delKeys))
-        for i in range(startInput['i']+1,startInput['total'],startInput['stop']):
+        for key in delKeys:
+            outputs.pop(key, None)
+        
+        startInput=prompt[startNum]['inputs']
+        if isinstance(startInput['total'],list) or isinstance(startInput['stop'],list) or isinstance(startInput['i'],list):
+            result = recursive_execute(server, prompt, outputs, startNum, extra_data, executed, prompt_id, outputs_ui, object_storage)
+            if result[0] is not True:
+                    return result
+            
+        for x in startInput:
+            input_data = startInput[x]
+            if isinstance(input_data, list):
+                startData[x]=outputs[input_data[0]][input_data[1]][0]
+            else:
+                startData[x]=input_data
+
+        for i in range(startData['i']+1,startData['total'],startData['stop']):
             prompt[str(maxKey+i)]=prompt[inputNum]
-            prompt[unique_id]['inputs']['images'+str(i)]=[str(maxKey+i),prompt[unique_id]['inputs']['images'][-1]]
+            prompt[unique_id]['inputs']['obj'+str(i)]=[str(maxKey+i),prompt[unique_id]['inputs']['obj'][-1]]
+            if i==startInput['i']+1:
+                backhaul['obj'+str(i)]=prompt[unique_id]['inputs']['obj']
+            else:
+                backhaul['obj'+str(i)]=[str(maxKey+i-startInput['stop']),prompt[unique_id]['inputs']['obj'][-1]]
+    elif class_type=='DoWhileEnd':
+        startNum=prompt[unique_id]['inputs']['start'][0]
+        inputNum=prompt[unique_id]['inputs']['ANY'][0]
+        delKeys=list(set(get_del_keys(startNum,prompt,[startNum,unique_id]))) 
+        delKeys.append(startNum)
+        delKeys.append(inputNum)
 
     #循环添加代码-----------结束---------
 ```
 ```python
                 #循环添加代码----------开始----------
-                if class_type=='ForInnerEnd' and x !='images' and x.startswith('images'):
+                if class_type=='ForInnerEnd' and x !='obj' and x.startswith('obj'):
                     if startNum!=None:
-                        prompt[startNum]['inputs']['i']=prompt[startNum]['inputs']['i']+prompt[startNum]['inputs']['stop']
+                        if isinstance(prompt[startNum]['inputs']['i'],list):
+                            prompt[startNum]['inputs']['i']=startData['i']+startData['stop']
+                        else:
+                            prompt[startNum]['inputs']['i']=prompt[startNum]['inputs']['i']+startData['stop']
+                        prompt[startNum]['inputs']['obj']=backhaul[x]
                         for key in delKeys:
                             outputs.pop(key, None)
                 #循环添加代码-----------结束---------
-```
+```
+```python
+                #判断选择添加代码-----------开始---------
+                if class_type=='DoWhileEnd' and x == 'ANY':
+                    any=outputs[inputNum][prompt[unique_id]['inputs']['ANY'][1]][0]
+                    i=0
+                    while any:
+                        for key in delKeys:
+                            outputs.pop(key, None)
+                        i=i+1
+                        outputs['i']=[[i]]
+                        prompt[startNum]['inputs']['i']=['i',0]
+                        result = recursive_execute(server, prompt, outputs, input_unique_id, extra_data, executed, prompt_id, outputs_ui, object_storage)
+                        if result[0] is not True:
+                            return result
+                        any=outputs[inputNum][prompt[unique_id]['inputs']['ANY'][1]][0]
+            
+            if class_type=='IfInnerExecute' and x=='ANY':
+                if outputs[input_unique_id][output_index][0]:
+                    inputs['IF_FALSE']=oldPrompt[unique_id]['inputs']['IF_TRUE']
+                else:
+                    inputs['IF_TRUE']=oldPrompt[unique_id]['inputs']['IF_FALSE']
+            #判断选择添加代码-----------结束---------
+```
+```python
+        #循环添加代码----------开始----------
+        if class_type=='ForInnerEnd' or class_type=='DoWhileEnd':
+            prompt[startNum]['inputs']=oldPrompt[startNum]['inputs']
+            prompt[unique_id]['inputs']=oldPrompt[unique_id]['inputs']
+            outputs.pop(startNum, None)
+            result = recursive_execute(server, prompt, outputs, startNum, extra_data, executed, prompt_id, outputs_ui, object_storage)
+            if result[0] is not True:
+                   return result
+        if class_type=='IfInnerExecute':
+            prompt[unique_id]['inputs']=oldPrompt[unique_id]['inputs']
+        #循环添加代码-----------结束---------
+```
+搜索 “def validate_prompt
+```python
+'''优化输出开始'''
+    inputKeys=[]
+    for k,v in prompt.items():
+        for k1,v1 in v['inputs'].items():
+            if type(v1)==list and len(v1)==2:
+                inputKeys.append(v1[0])
+    for x in prompt:
+        class_ = nodes.NODE_CLASS_MAPPINGS[prompt[x]['class_type']]
+        if hasattr(class_, 'OUTPUT_NODE') and class_.OUTPUT_NODE == True and x not in inputKeys:
+            outputs.add(x)
+    '''优化输出结束'''
+``` 

config/settings_nodes.json

@@ -0,0 +1 @@
+{}

config/weChat.yaml

@@ -0,0 +1,116 @@
+wechat:
+  appid: wx1c2b19f7af1d6241                        #公众号appid 
+  secret: 915d587b5ae4e148e100429e11ca4d60         #公众号秘钥
+  serverAddress: http://139.9.53.208/ #服务器地址 微信公众配置地址的前缀
+  freeSize: 3 #免费使用次数
+  isEnterprise: false #是否为企业微信
+  adminNo: b0pOVFM2dnRsZkdLeWl2Zlk2bG9MTFNjUTNGUQ== #管理员微信编号启动会后可发送我的编号获取
+  adminWeChat: yanlang123456                        #管理员微信号
+  access_token: '' #不用填系统用于保存临时值
+  access_token_expires_at: 0 #默认0
+  commands:                                        #功能列表
+    图生视频:
+      filename: img2video.json                     #功能流程图json文件
+      params:                                      #参数列表
+        image:                                     #参数名称(几个固定参数名称必须如下：图片：image  随机种子：seed 正向提示词：prompt 反向提示词：negative) 
+          isRequired: true                         #是否必填
+          keys:                                    #参数对应json中对应的key
+          - '38'
+          - inputs
+          - image_path
+          zhName: 图片                             #参数中文名称
+        motion_bucket:
+          default: 127
+          isRequired: true
+          keys:
+          - '12'
+          - inputs
+          - motion_bucket_id
+          max: 200
+          min: 0
+          type: number
+          zhName: 运动量
+        seed:
+          default: -1
+          isRequired: true
+          keys:
+          - '3'
+          - inputs
+          - seed
+          type: text
+          zhName: 随机种子
+      replyText: 请发送您的图片发送“ok”开始任务，如：“ok”     #指令说明回复
+    文生图:
+      filename: text2img.json
+      params:
+        ckpt:
+          isRequired: false
+          keys:
+          - '4'
+          - inputs
+          - ckpt_name
+          options:          #选项参数
+            冷却混合料SD1.5: chilloutmix_NiPrunedFp32Fix.safetensors #中文名称:英文名称
+            卡通动画片SD1.5: yamer_Cartoon_xenoArcadiaCD.safetensors
+            无法控制的SDXL: juggernautXL_version6Rundiffusion.safetensors
+            梦想塑造者SD1.5: dreamshaper_8.safetensors
+          zhName: 基础模型
+        height:
+          default: 512     #默认值
+          isRequired: false
+          keys:
+          - '14'
+          - inputs
+          - height
+          max: 1024         #最大值
+          min: 512          #最小值
+          type: number      #类型(输入型参数目前只支持 number/text)
+          zhName: 高度
+        lora:
+          isRequired: false
+          keys:
+          - '10'
+          - inputs
+          - lora_name
+          options:
+            SD1.5-LCM加速: lcm-lora-sdv1-5.safetensors
+            SDXL-LCM加速: lcm-lora-sdxl.safetensors
+          zhName: LoRA
+        negative:
+          isRequired: false
+          keys:
+          - '7'
+          - inputs
+          - text
+          zhName: 反向提示词
+        prompt:
+          isRequired: true
+          keys:
+          - '20'
+          - inputs
+          - text_trans
+          zhName: 正向提示词
+        seed:
+          default: -1
+          isRequired: true
+          keys:
+          - '3'
+          - inputs
+          - seed
+          type: text
+          zhName: 随机种子
+        width:
+          default: 512
+          isRequired: false
+          keys:
+          - '14'
+          - inputs
+          - width
+          max: 1024
+          min: 512
+          type: number
+          zhName: 宽度
+      replyText: 请发送您的中文或英文提示词用“ok”结束，如：“一只小狗ok”
+  query_commands: #查询指令（固定）
+  - 查询排队情况
+  - 我的编号

config/weChat.yaml.template

@@ -0,0 +1,284 @@
+wechat:
+  appid: wxa50ed345b253964d                        #公众号appid 
+  secret: 327ac9ba06d214d2fcfe2e9ed0520684         #公众号秘钥
+  serverAddress: http://119.123.205.233/ #服务器地址 微信公众配置地址的前缀
+  freeSize: 3 #免费使用次数
+  isEnterprise: true #是否为企业微信
+  adminNo: b0pOVFM2dnRsZkdLeWl2Zlk2bG9MTFNjUTNGUQ== #管理员微信编号启动会后可发送我的编号获取
+  adminWeChat: yanlang123456                        #管理员微信号
+  access_token: '' #不用填系统用于保存临时值
+  access_token_expires_at: 0 #默认0
+  commands:                                        #功能列表
+    简笔画:
+      filename: line2drawing.json
+      type: paint-board
+      params:
+        ckpt:
+          isRequired: false
+          keys:
+          - '1'
+          - inputs
+          - ckpt_name
+          options:          #选项参数
+            卡通动画片SD1.5: yamer_Cartoon_xenoArcadiaCD.safetensors
+            冷却混合料SD1.5: chilloutmix_NiPrunedFp32Fix.safetensors #中文名称:英文名称
+            梦想塑造者SD1.5: dreamshaper_8.safetensors
+          zhName: 基础模型
+        prompt:
+          isRequired: false
+          keys:
+          - '17'
+          - inputs
+          - text_trans
+          zhName: 正向提示词
+        seed:
+          default: -1
+          isRequired: true
+          keys:
+          - '8'
+          - inputs
+          - seed
+          type: text
+          zhName: 随机种子
+        image:
+          isRequired: true
+          keys:
+          - '15'
+          - inputs
+          - image
+          type: text
+          zhName: 输入图片
+    水彩画:
+      filename: color2painting.json
+      type: paint-board
+      params:
+        ckpt:
+          isRequired: false
+          keys:
+          - '4'
+          - inputs
+          - ckpt_name
+          options:          #选项参数
+            卡通动画片SD1.5: yamer_Cartoon_xenoArcadiaCD.safetensors
+            冷却混合料SD1.5: chilloutmix_NiPrunedFp32Fix.safetensors #中文名称:英文名称
+            梦想塑造者SD1.5: dreamshaper_8.safetensors
+          zhName: 基础模型
+        prompt:
+          isRequired: false
+          keys:
+          - '27'
+          - inputs
+          - text_trans
+          zhName: 正向提示词
+        seed:
+          default: -1
+          isRequired: true
+          keys:
+          - '3'
+          - inputs
+          - seed
+          type: text
+          zhName: 随机种子
+        denoise:
+          default: 0.65     #默认值
+          isRequired: false
+          keys:
+          - '3'
+          - inputs
+          - denoise
+          max: 100         #最大值
+          min: 0          #最小值
+          original: 1     #原始最大值（用来换算滑块比例）
+          type: number      #类型(输入型参数目前只支持 number/text)
+          zhName: 重绘幅度
+        image:
+          isRequired: true
+          keys:
+          - '25'
+          - inputs
+          - image
+          type: text
+          zhName: 输入图片
+    图片修改:
+      filename: imageEdit.json
+      params:
+        image:
+          isRequired: true
+          keys:
+          - '48'
+          - inputs
+          - image_path
+          zhName: 图片
+        prompt:
+          isRequired: true
+          keys:
+          - '47'
+          - inputs
+          - text_trans
+          zhName: 正向提示词
+        seed:
+          default: -1
+          isRequired: true
+          keys:
+          - '37:1'
+          - inputs
+          - noise_seed
+          type: text
+          zhName: 随机种子
+      replyText: 请发送您的图片发送正向提示词用“ok”结尾开始任务，如：“漫画风格ok”
+    风格转绘:
+      filename: img2imgStyle.json
+      replyText: 请上传需转绘的图片和参考风格图发送“ok”开始任务，如：“ok”     #指令说明回复
+      params:
+        image:                                     #参数名称(几个固定参数名称必须如下：图片：image  随机种子：seed 正向提示词：prompt 反向提示词：negative) 
+          isRequired: true                         #是否必填
+          keys:                                    #参数对应json中对应的key
+          - '110'
+          - inputs
+          - image_path
+          zhName: 待转绘图       
+          type: image
+        styleImage:                                     #参数名称(几个固定参数名称必须如下：图片：image  随机种子：seed 正向提示词：prompt 反向提示词：negative) 
+          isRequired: true                         #是否必填
+          keys:                                    #参数对应json中对应的key
+          - '111'
+          - inputs
+          - image_path
+          zhName: 风格参考图
+          type: image
+          default: 发送图片
+    文生二维码:
+      filename: text2qrcode.json
+      replyText: 请发送二维码内容，和提示词发送“ok”开始任务，如：“花朵ok”     #指令说明回复
+      params:
+        prompt:
+          isRequired: true
+          keys:
+          - '75'
+          - inputs
+          - text_trans
+          zhName: 正向提示词
+        seed:
+          default: -1
+          isRequired: true
+          keys:
+          - '3'
+          - inputs
+          - seed
+          type: text
+          zhName: 随机种子
+        qrText:
+          default: "https://u.wechat.com/EEy4mPvfXdYO-MvStE4S2m0"
+          isRequired: true
+          keys:
+          - '16'
+          - inputs
+          - text
+          type: text
+          zhName: 二维码内容
+
+    图生视频:
+      filename: img2video.json                     #功能流程图json文件
+      params:                                      #参数列表
+        image:                                     #参数名称(几个固定参数名称必须如下：图片：image  随机种子：seed 正向提示词：prompt 反向提示词：negative) 
+          isRequired: true                         #是否必填
+          keys:                                    #参数对应json中对应的key
+          - '38'
+          - inputs
+          - image_path
+          zhName: 图片                             #参数中文名称
+        motion_bucket:
+          default: 127
+          isRequired: true
+          keys:
+          - '12'
+          - inputs
+          - motion_bucket_id
+          max: 200
+          min: 0
+          type: number
+          zhName: 运动量
+        seed:
+          default: -1
+          isRequired: true
+          keys:
+          - '3'
+          - inputs
+          - seed
+          type: text
+          zhName: 随机种子
+      replyText: 请发送您的图片发送“ok”开始任务，如：“ok”     #指令说明回复
+    文生图:
+      filename: text2img.json
+      params:
+        ckpt:
+          isRequired: false
+          keys:
+          - '4'
+          - inputs
+          - ckpt_name
+          options:          #选项参数
+            冷却混合料SD1.5: chilloutmix_NiPrunedFp32Fix.safetensors #中文名称:英文名称
+            卡通动画片SD1.5: yamer_Cartoon_xenoArcadiaCD.safetensors
+            无法控制的SDXL: juggernautXL_version6Rundiffusion.safetensors
+            梦想塑造者SD1.5: dreamshaper_8.safetensors
+          zhName: 基础模型
+        height:
+          default: 512     #默认值
+          isRequired: false
+          keys:
+          - '14'
+          - inputs
+          - height
+          max: 1024         #最大值
+          min: 512          #最小值
+          type: number      #类型(输入型参数目前只支持 number/text)
+          zhName: 高度
+        lora:
+          isRequired: false
+          keys:
+          - '10'
+          - inputs
+          - lora_name
+          options:
+            SD1.5-LCM加速: lcm-lora-sdv1-5.safetensors
+            SDXL-LCM加速: lcm-lora-sdxl.safetensors
+          zhName: LoRA
+        negative:
+          isRequired: false
+          keys:
+          - '7'
+          - inputs
+          - text
+          zhName: 反向提示词
+        prompt:
+          isRequired: true
+          keys:
+          - '20'
+          - inputs
+          - text_trans
+          zhName: 正向提示词
+        seed:
+          default: -1
+          isRequired: true
+          keys:
+          - '3'
+          - inputs
+          - seed
+          type: text
+          zhName: 随机种子
+        width:
+          default: 512
+          isRequired: false
+          keys:
+          - '14'
+          - inputs
+          - width
+          max: 1024
+          min: 512
+          type: number
+          zhName: 宽度
+      replyText: 请发送您的中文或英文提示词用“ok”结束，如：“一只小狗ok”
+  query_commands: #查询指令（固定）
+  - 查询排队情况
+  - 我的编号

config/workflow/color2painting.json

@@ -0,0 +1,192 @@
+{
+  "3": {
+    "inputs": {
+      "seed": 611578276912800,
+      "steps": 8,
+      "cfg": 1,
+      "sampler_name": "euler_ancestral",
+      "scheduler": "normal",
+      "denoise": 0.65,
+      "model": [
+        "21",
+        0
+      ],
+      "positive": [
+        "6",
+        0
+      ],
+      "negative": [
+        "7",
+        0
+      ],
+      "latent_image": [
+        "19",
+        0
+      ]
+    },
+    "class_type": "KSampler",
+    "_meta": {
+      "title": "K采样器"
+    }
+  },
+  "4": {
+    "inputs": {
+      "ckpt_name": "yamer_Cartoon_xenoArcadiaCD.safetensors"
+    },
+    "class_type": "CheckpointLoaderSimple",
+    "_meta": {
+      "title": "Checkpoint加载器(简易)"
+    }
+  },
+  "6": {
+    "inputs": {
+      "text": [
+        "27",
+        0
+      ],
+      "clip": [
+        "21",
+        1
+      ]
+    },
+    "class_type": "CLIPTextEncode",
+    "_meta": {
+      "title": "CLIP文本编码器"
+    }
+  },
+  "7": {
+    "inputs": {
+      "text": [
+        "28",
+        0
+      ],
+      "clip": [
+        "4",
+        1
+      ]
+    },
+    "class_type": "CLIPTextEncode",
+    "_meta": {
+      "title": "CLIP文本编码器"
+    }
+  },
+  "8": {
+    "inputs": {
+      "samples": [
+        "3",
+        0
+      ],
+      "vae": [
+        "4",
+        2
+      ]
+    },
+    "class_type": "VAEDecode",
+    "_meta": {
+      "title": "VAE解码"
+    }
+  },
+  "9": {
+    "inputs": {
+      "filename_prefix": "ComfyUI",
+      "images": [
+        "8",
+        0
+      ]
+    },
+    "class_type": "SaveImage",
+    "_meta": {
+      "title": "保存图像"
+    }
+  },
+  "10": {
+    "inputs": {
+      "lora_name": "lcm-lora-sdv1-5.safetensors",
+      "strength_model": 1,
+      "strength_clip": 1,
+      "model": [
+        "4",
+        0
+      ],
+      "clip": [
+        "4",
+        1
+      ]
+    },
+    "class_type": "LoraLoader",
+    "_meta": {
+      "title": "LoRA加载器"
+    }
+  },
+  "19": {
+    "inputs": {
+      "pixels": [
+        "25",
+        0
+      ],
+      "vae": [
+        "23",
+        0
+      ]
+    },
+    "class_type": "VAEEncode",
+    "_meta": {
+      "title": "VAE编码"
+    }
+  },
+  "21": {
+    "inputs": {
+      "lora_name": "可爱少女厚涂风.safetensors",
+      "strength_model": 0,
+      "strength_clip": 1,
+      "model": [
+        "10",
+        0
+      ],
+      "clip": [
+        "10",
+        1
+      ]
+    },
+    "class_type": "LoraLoader",
+    "_meta": {
+      "title": "LoRA加载器"
+    }
+  },
+  "23": {
+    "inputs": {
+      "vae_name": "clearvae_v23.safetensors"
+    },
+    "class_type": "VAELoader",
+    "_meta": {
+      "title": "VAE加载器"
+    }
+  },
+  "25": {
+    "inputs": {
+      "image": ""
+    },
+    "class_type": "ETN_LoadImageBase64",
+    "_meta": {
+      "title": "Load Image (Base64)"
+    }
+  },
+  "27": {
+    "inputs": {
+      "text_trans": ""
+    },
+    "class_type": "ZhPromptTranslator",
+    "_meta": {
+      "title": "正向提示词"
+    }
+  },
+  "28": {
+    "inputs": {
+      "text_trans": ""
+    },
+    "class_type": "ZhPromptTranslator",
+    "_meta": {
+      "title": "反向提示词"
+    }
+  }
+}

config/workflow/imageEdit.json

@@ -0,0 +1,262 @@
+{
+  "4": {
+    "inputs": {
+      "ckpt_name": "cosxl_edit.safetensors"
+    },
+    "class_type": "CheckpointLoaderSimple",
+    "_meta": {
+      "title": "Checkpoint加载器(简易)"
+    }
+  },
+  "6": {
+    "inputs": {
+      "text": [
+        "47",
+        0
+      ],
+      "clip": [
+        "4",
+        1
+      ]
+    },
+    "class_type": "CLIPTextEncode",
+    "_meta": {
+      "title": "CLIP文本编码器"
+    }
+  },
+  "7": {
+    "inputs": {
+      "text": "",
+      "clip": [
+        "4",
+        1
+      ]
+    },
+    "class_type": "CLIPTextEncode",
+    "_meta": {
+      "title": "CLIP文本编码器"
+    }
+  },
+  "8": {
+    "inputs": {
+      "samples": [
+        "37:8",
+        0
+      ],
+      "vae": [
+        "4",
+        2
+      ]
+    },
+    "class_type": "VAEDecode",
+    "_meta": {
+      "title": "VAE解码"
+    }
+  },
+  "9": {
+    "inputs": {
+      "filename_prefix": "ComfyUI",
+      "images": [
+        "8",
+        0
+      ]
+    },
+    "class_type": "SaveImage",
+    "_meta": {
+      "title": "保存图像"
+    }
+  },
+  "41": {
+    "inputs": {
+      "width": 960,
+      "height": 0,
+      "interpolation": "nearest",
+      "keep_proportion": true,
+      "condition": "always",
+      "image": [
+        "48",
+        0
+      ]
+    },
+    "class_type": "ImageResize+",
+    "_meta": {
+      "title": "图像缩放"
+    }
+  },
+  "42": {
+    "inputs": {
+      "image": [
+        "48",
+        0
+      ]
+    },
+    "class_type": "GetImage_(Width&Height) _O",
+    "_meta": {
+      "title": "GetImage_(Width&Height) _O"
+    }
+  },
+  "44": {
+    "inputs": {
+      "expression": "p0>960",
+      "p0": [
+        "42",
+        0
+      ]
+    },
+    "class_type": "MultiParamFormula",
+    "_meta": {
+      "title": "多参代码表达式"
+    }
+  },
+  "46": {
+    "inputs": {
+      "ANY": [
+        "44",
+        0
+      ],
+      "IF_TRUE": [
+        "41",
+        0
+      ],
+      "IF_FALSE": [
+        "48",
+        0
+      ]
+    },
+    "class_type": "IfInnerExecute",
+    "_meta": {
+      "title": "判断选择"
+    }
+  },
+  "47": {
+    "inputs": {
+      "text_trans": "秋天"
+    },
+    "class_type": "ZhPromptTranslator",
+    "_meta": {
+      "title": "中文翻译"
+    }
+  },
+  "48": {
+    "inputs": {
+      "image_path": "./ComfyUI/input/example.png",
+      "RGBA": "false",
+      "filename_text_extension": "true"
+    },
+    "class_type": "LamLoadPathImage",
+    "_meta": {
+      "title": "加载网络图片或本地图片"
+    }
+  },
+  "37:0": {
+    "inputs": {
+      "sampler_name": "euler"
+    },
+    "class_type": "KSamplerSelect",
+    "_meta": {
+      "title": "K采样器选择"
+    }
+  },
+  "37:1": {
+    "inputs": {
+      "noise_seed": 173148692406184
+    },
+    "class_type": "RandomNoise",
+    "_meta": {
+      "title": "随机噪波"
+    }
+  },
+  "37:3": {
+    "inputs": {
+      "scheduler": "normal",
+      "steps": 20,
+      "denoise": 1,
+      "model": [
+        "4",
+        0
+      ]
+    },
+    "class_type": "BasicScheduler",
+    "_meta": {
+      "title": "基础调度器"
+    }
+  },
+  "37:6": {
+    "inputs": {
+      "positive": [
+        "6",
+        0
+      ],
+      "negative": [
+        "7",
+        0
+      ],
+      "vae": [
+        "4",
+        2
+      ],
+      "pixels": [
+        "46",
+        0
+      ]
+    },
+    "class_type": "InstructPixToPixConditioning",
+    "_meta": {
+      "title": "InstructPixToPix条件"
+    }
+  },
+  "37:7": {
+    "inputs": {
+      "cfg_conds": 5,
+      "cfg_cond2_negative": 1.5,
+      "model": [
+        "4",
+        0
+      ],
+      "cond1": [
+        "37:6",
+        0
+      ],
+      "cond2": [
+        "37:6",
+        1
+      ],
+      "negative": [
+        "7",
+        0
+      ]
+    },
+    "class_type": "DualCFGGuider",
+    "_meta": {
+      "title": "双CFG引导"
+    }
+  },
+  "37:8": {
+    "inputs": {
+      "noise": [
+        "37:1",
+        0
+      ],
+      "guider": [
+        "37:7",
+        0
+      ],
+      "sampler": [
+        "37:0",
+        0
+      ],
+      "sigmas": [
+        "37:3",
+        0
+      ],
+      "latent_image": [
+        "37:6",
+        2
+      ]
+    },
+    "class_type": "SamplerCustomAdvanced",
+    "_meta": {
+      "title": "自定义采样器(高级)"
+    }
+  }
+}

config/workflow/img2imgStyle.json

@@ -0,0 +1,651 @@
+{
+  "3": {
+    "inputs": {
+      "seed": 20,
+      "steps": 25,
+      "cfg": 6,
+      "sampler_name": "dpmpp_2m",
+      "scheduler": "karras",
+      "denoise": 0.9,
+      "model": [
+        "105",
+        0
+      ],
+      "positive": [
+        "64",
+        0
+      ],
+      "negative": [
+        "64",
+        1
+      ],
+      "latent_image": [
+        "64",
+        2
+      ]
+    },
+    "class_type": "KSampler",
+    "_meta": {
+      "title": "K采样器"
+    }
+  },
+  "4": {
+    "inputs": {
+      "ckpt_name": "dreamshaper_8.safetensors"
+    },
+    "class_type": "CheckpointLoaderSimple",
+    "_meta": {
+      "title": "Checkpoint加载器(简易)"
+    }
+  },
+  "6": {
+    "inputs": {
+      "text": [
+        "72",
+        0
+      ],
+      "clip": [
+        "4",
+        1
+      ]
+    },
+    "class_type": "CLIPTextEncode",
+    "_meta": {
+      "title": "CLIP文本编码器"
+    }
+  },
+  "7": {
+    "inputs": {
+      "text": "blurry, noisy, messy, glitch, distorted, malformed, ill, horror, naked, nipples",
+      "clip": [
+        "4",
+        1
+      ]
+    },
+    "class_type": "CLIPTextEncode",
+    "_meta": {
+      "title": "CLIP文本编码器"
+    }
+  },
+  "8": {
+    "inputs": {
+      "samples": [
+        "3",
+        0
+      ],
+      "vae": [
+        "4",
+        2
+      ]
+    },
+    "class_type": "VAEDecode",
+    "_meta": {
+      "title": "VAE解码"
+    }
+  },
+  "29": {
+    "inputs": {
+      "width": 960,
+      "height": 0,
+      "interpolation": "nearest",
+      "keep_proportion": true,
+      "condition": "always",
+      "multiple_of": 0,
+      "image": [
+        "110",
+        0
+      ]
+    },
+    "class_type": "ImageResize+",
+    "_meta": {
+      "title": "图像缩放"
+    }
+  },
+  "48": {
+    "inputs": {
+      "preset": "STANDARD (medium strength)",
+      "model": [
+        "4",
+        0
+      ]
+    },
+    "class_type": "IPAdapterUnifiedLoader",
+    "_meta": {
+      "title": "IPAdapter加载器"
+    }
+  },
+  "50": {
+    "inputs": {
+      "interpolation": "LANCZOS",
+      "crop_position": "pad",
+      "sharpening": 0,
+      "image": [
+        "111",
+        0
+      ]
+    },
+    "class_type": "PrepImageForClipVision",
+    "_meta": {
+      "title": "CLIP视觉图像处理"
+    }
+  },
+  "51": {
+    "inputs": {
+      "strength": 0.55,
+      "start_percent": 0,
+      "end_percent": 0.75,
+      "positive": [
+        "6",
+        0
+      ],
+      "negative": [
+        "7",
+        0
+      ],
+      "control_net": [
+        "52",
+        0
+      ],
+      "image": [
+        "83",
+        0
+      ]
+    },
+    "class_type": "ControlNetApplyAdvanced",
+    "_meta": {
+      "title": "ControlNet应用(高级)"
+    }
+  },
+  "52": {
+    "inputs": {
+      "control_net_name": "control_v11p_sd15_lineart.pth"
+    },
+    "class_type": "ControlNetLoader",
+    "_meta": {
+      "title": "ControlNet加载器"
+    }
+  },
+  "55": {
+    "inputs": {
+      "strength": 1,
+      "start_percent": 0,
+      "end_percent": 0.3,
+      "positive": [
+        "51",
+        0
+      ],
+      "negative": [
+        "51",
+        1
+      ],
+      "control_net": [
+        "56",
+        0
+      ],
+      "image": [
+        "57",
+        0
+      ]
+    },
+    "class_type": "ControlNetApplyAdvanced",
+    "_meta": {
+      "title": "ControlNet应用(高级)"
+    }
+  },
+  "56": {
+    "inputs": {
+      "control_net_name": "control_v11f1p_sd15_depth.pth"
+    },
+    "class_type": "ControlNetLoader",
+    "_meta": {
+      "title": "ControlNet加载器"
+    }
+  },
+  "57": {
+    "inputs": {
+      "ckpt_name": "depth_anything_vits14.pth",
+      "resolution": 960,
+      "image": [
+        "71",
+        0
+      ]
+    },
+    "class_type": "DepthAnythingPreprocessor",
+    "_meta": {
+      "title": "DA深度预处理器"
+    }
+  },
+  "63": {
+    "inputs": {
+      "interpolation": "LANCZOS",
+      "crop_position": "pad",
+      "sharpening": 0,
+      "image": [
+        "71",
+        0
+      ]
+    },
+    "class_type": "PrepImageForClipVision",
+    "_meta": {
+      "title": "CLIP视觉图像处理"
+    }
+  },
+  "64": {
+    "inputs": {
+      "positive": [
+        "55",
+        0
+      ],
+      "negative": [
+        "55",
+        1
+      ],
+      "vae": [
+        "4",
+        2
+      ],
+      "pixels": [
+        "71",
+        0
+      ]
+    },
+    "class_type": "InstructPixToPixConditioning",
+    "_meta": {
+      "title": "InstructPixToPix条件"
+    }
+  },
+  "69": {
+    "inputs": {
+      "image": [
+        "110",
+        0
+      ]
+    },
+    "class_type": "GetImage_(Width&Height) _O",
+    "_meta": {
+      "title": "GetImage_(Width&Height) _O"
+    }
+  },
+  "70": {
+    "inputs": {
+      "expression": "p0>960",
+      "p0": [
+        "69",
+        0
+      ]
+    },
+    "class_type": "MultiParamFormula",
+    "_meta": {
+      "title": "多参代码表达式"
+    }
+  },
+  "71": {
+    "inputs": {
+      "ANY": [
+        "70",
+        0
+      ],
+      "IF_TRUE": [
+        "29",
+        0
+      ],
+      "IF_FALSE": [
+        "110",
+        0
+      ]
+    },
+    "class_type": "IfInnerExecute",
+    "_meta": {
+      "title": "判断选择"
+    }
+  },
+  "72": {
+    "inputs": {
+      "model": "wd-v1-4-moat-tagger-v2",
+      "threshold": 0.35,
+      "character_threshold": 1,
+      "exclude_tags": "",
+      "image": [
+        "71",
+        0
+      ]
+    },
+    "class_type": "WD14Tagger|pysssss",
+    "_meta": {
+      "title": "WD14反推提示词"
+    }
+  },
+  "76": {
+    "inputs": {
+      "preset": "PLUS FACE (portraits)",
+      "model": [
+        "103",
+        0
+      ]
+    },
+    "class_type": "IPAdapterUnifiedLoader",
+    "_meta": {
+      "title": "IPAdapter加载器"
+    }
+  },
+  "83": {
+    "inputs": {
+      "coarse": "disable",
+      "image": [
+        "71",
+        0
+      ]
+    },
+    "class_type": "LineArtPreprocessor",
+    "_meta": {
+      "title": "LineArt艺术线预处理器"
+    }
+  },
+  "86": {
+    "inputs": {
+      "filename_prefix": "ComfyUI",
+      "images": [
+        "8",
+        0
+      ]
+    },
+    "class_type": "SaveImage",
+    "_meta": {
+      "title": "保存图像"
+    }
+  },
+  "88": {
+    "inputs": {
+      "expression": "p0[p1:p1+1]",
+      "p0": [
+        "108",
+        0
+      ],
+      "p1": [
+        "89",
+        1
+      ]
+    },
+    "class_type": "MultiParamFormula",
+    "_meta": {
+      "title": "多参代码表达式"
+    }
+  },
+  "89": {
+    "inputs": {
+      "total": [
+        "90",
+        0
+      ],
+      "stop": 1,
+      "i": 0
+    },
+    "class_type": "ForInnerStart",
+    "_meta": {
+      "title": "计次内循环首"
+    }
+  },
+  "90": {
+    "inputs": {
+      "expression": "len(p0)",
+      "p0": [
+        "108",
+        1
+      ]
+    },
+    "class_type": "MultiParamFormula",
+    "_meta": {
+      "title": "多参代码表达式"
+    }
+  },
+  "91": {
+    "inputs": {
+      "expression": "p0[p1]",
+      "p0": [
+        "108",
+        1
+      ],
+      "p1": [
+        "89",
+        1
+      ]
+    },
+    "class_type": "MultiParamFormula",
+    "_meta": {
+      "title": "多参代码表达式"
+    }
+  },
+  "92": {
+    "inputs": {
+      "total": [
+        "89",
+        0
+      ],
+      "obj": [
+        "97",
+        0
+      ]
+    },
+    "class_type": "ForInnerEnd",
+    "_meta": {
+      "title": "计次内循环尾"
+    }
+  },
+  "94": {
+    "inputs": {
+      "ANY": [
+        "95",
+        0
+      ],
+      "IF_TRUE": [
+        "96",
+        0
+      ],
+      "IF_FALSE": [
+        "89",
+        3
+      ]
+    },
+    "class_type": "IfInnerExecute",
+    "_meta": {
+      "title": "判断选择"
+    }
+  },
+  "95": {
+    "inputs": {
+      "expression": "p0==0",
+      "p0": [
+        "89",
+        1
+      ]
+    },
+    "class_type": "MultiParamFormula",
+    "_meta": {
+      "title": "多参代码表达式"
+    }
+  },
+  "96": {
+    "inputs": {
+      "preset": "FACEID PLUS V2",
+      "lora_strength": 0.39,
+      "provider": "CPU",
+      "model": [
+        "76",
+        0
+      ],
+      "ipadapter": [
+        "76",
+        1
+      ]
+    },
+    "class_type": "IPAdapterUnifiedLoaderFaceID",
+    "_meta": {
+      "title": "IPAdapterFaceID加载器"
+    }
+  },
+  "97": {
+    "inputs": {
+      "weight": 1,
+      "weight_faceidv2": 2,
+      "weight_type": "linear",
+      "combine_embeds": "concat",
+      "start_at": 0,
+      "end_at": 1,
+      "embeds_scaling": "V only",
+      "model": [
+        "94",
+        0
+      ],
+      "ipadapter": [
+        "96",
+        1
+      ],
+      "image": [
+        "88",
+        0
+      ],
+      "attn_mask": [
+        "91",
+        0
+      ]
+    },
+    "class_type": "IPAdapterFaceID",
+    "_meta": {
+      "title": "应用IPAdapterFaceID"
+    }
+  },
+  "102": {
+    "inputs": {
+      "weight": 1,
+      "weight_type": "style transfer",
+      "combine_embeds": "concat",
+      "start_at": 0,
+      "end_at": 1,
+      "embeds_scaling": "V only",
+      "model": [
+        "48",
+        0
+      ],
+      "ipadapter": [
+        "48",
+        1
+      ],
+      "image": [
+        "50",
+        0
+      ]
+    },
+    "class_type": "IPAdapterAdvanced",
+    "_meta": {
+      "title": "应用IPAdapter(高级)"
+    }
+  },
+  "103": {
+    "inputs": {
+      "weight": 1,
+      "weight_type": "composition",
+      "combine_embeds": "concat",
+      "start_at": 0,
+      "end_at": 1,
+      "embeds_scaling": "V only",
+      "model": [
+        "102",
+        0
+      ],
+      "ipadapter": [
+        "48",
+        1
+      ],
+      "image": [
+        "63",
+        0
+      ]
+    },
+    "class_type": "IPAdapterAdvanced",
+    "_meta": {
+      "title": "应用IPAdapter(高级)"
+    }
+  },
+  "104": {
+    "inputs": {
+      "expression": "len(p0)>0",
+      "p0": [
+        "108",
+        1
+      ]
+    },
+    "class_type": "MultiParamFormula",
+    "_meta": {
+      "title": "多参代码表达式"
+    }
+  },
+  "105": {
+    "inputs": {
+      "ANY": [
+        "104",
+        0
+      ],
+      "IF_TRUE": [
+        "92",
+        1
+      ],
+      "IF_FALSE": [
+        "103",
+        0
+      ]
+    },
+    "class_type": "IfInnerExecute",
+    "_meta": {
+      "title": "判断选择"
+    }
+  },
+  "108": {
+    "inputs": {
+      "crop_padding_factor": 0.25,
+      "analysis_models": [
+        "109",
+        0
+      ],
+      "image": [
+        "71",
+        0
+      ]
+    },
+    "class_type": "ImageCropFaces",
+    "_meta": {
+      "title": "多人面部裁剪"
+    }
+  },
+  "109": {
+    "inputs": {
+      "library": "insightface",
+      "provider": "CPU"
+    },
+    "class_type": "FaceAnalysisModels",
+    "_meta": {
+      "title": "面部分析模型"
+    }
+  },
+  "110": {
+    "inputs": {
+      "image_path": "./ComfyUI/input/example.png",
+      "RGBA": "false",
+      "filename_text_extension": "true"
+    },
+    "class_type": "LamLoadPathImage",
+    "_meta": {
+      "title": "需转绘的图"
+    }
+  },
+  "111": {
+    "inputs": {
+      "image_path": "./ComfyUI/input/example.png",
+      "RGBA": "false",
+      "filename_text_extension": "true"
+    },
+    "class_type": "LamLoadPathImage",
+    "_meta": {
+      "title": "风格参考图片"
+    }
+  }
+}

config/workflow/img2video.json

@@ -0,0 +1,142 @@
+{
+    "3": {
+      "inputs": {
+        "seed": 801899397770458,
+        "steps": 4,
+        "cfg": 1,
+        "sampler_name": "lcm",
+        "scheduler": "karras",
+        "denoise": 1,
+        "model": [
+          "14",
+          0
+        ],
+        "positive": [
+          "12",
+          0
+        ],
+        "negative": [
+          "12",
+          1
+        ],
+        "latent_image": [
+          "12",
+          2
+        ]
+      },
+      "class_type": "KSampler"
+    },
+    "8": {
+      "inputs": {
+        "samples": [
+          "3",
+          0
+        ],
+        "vae": [
+          "15",
+          2
+        ]
+      },
+      "class_type": "VAEDecode"
+    },
+    "12": {
+      "inputs": {
+        "width": [
+          "30",
+          0
+        ],
+        "height": [
+          "30",
+          1
+        ],
+        "video_frames": 25,
+        "motion_bucket_id": 127,
+        "fps": 6,
+        "augmentation_level": 0,
+        "clip_vision": [
+          "15",
+          1
+        ],
+        "init_image": [
+          "38",
+          0
+        ],
+        "vae": [
+          "15",
+          2
+        ]
+      },
+      "class_type": "SVD_img2vid_Conditioning"
+    },
+    "14": {
+      "inputs": {
+        "min_cfg": 1,
+        "model": [
+          "33",
+          0
+        ]
+      },
+      "class_type": "VideoLinearCFGGuidance"
+    },
+    "15": {
+      "inputs": {
+        "ckpt_name": "AnimateLCM-SVD-xt-1-1_fp16_comfy.safetensors"
+      },
+      "class_type": "ImageOnlyCheckpointLoader"
+    },
+    "25": {
+      "inputs": {
+        "frame_rate": 8,
+        "loop_count": 0,
+        "filename_prefix": "AnimateDiff",
+        "format": "video/h265-mp4",
+        "pingpong": false,
+        "save_image": true,
+        "Sync playback": null,
+        "images": [
+          "8",
+          0
+        ]
+      },
+      "class_type": "VHS_VideoCombine"
+    },
+    "30": {
+      "inputs": {
+        "image": [
+          "31",
+          0
+        ]
+      },
+      "class_type": "Get image size"
+    },
+    "31": {
+      "inputs": {
+        "upscale_method": "nearest-exact",
+        "scale_by": 0.7000000000000001,
+        "image": [
+          "38",
+          0
+        ]
+      },
+      "class_type": "ImageScaleBy"
+    },
+    "33": {
+      "inputs": {
+        "lora_name": "lcm-lora-sdv1-5.safetensors",
+        "strength_model": 1,
+        "model": [
+          "15",
+          0
+        ]
+      },
+      "class_type": "LoraLoaderModelOnly"
+    },
+    "38": {
+      "inputs": {
+        "image_path": "http://127.0.0.1:8188/view?filename=ComfyUI_00402_.png&type=input&subfolder=&rand=0.9232966295130483",
+        "RGBA": "false",
+        "filename_text_extension": "true"
+      },
+      "class_type": "LamLoadPathImage"
+    }
+  }

config/workflow/line2drawing.json

@@ -0,0 +1,239 @@
+{
+  "1": {
+    "inputs": {
+      "ckpt_name": "yamer_Cartoon_xenoArcadiaCD.safetensors"
+    },
+    "class_type": "CheckpointLoaderSimple",
+    "_meta": {
+      "title": "Checkpoint加载器(简易)"
+    }
+  },
+  "2": {
+    "inputs": {
+      "width": [
+        "16",
+        0
+      ],
+      "height": [
+        "16",
+        1
+      ],
+      "batch_size": 1
+    },
+    "class_type": "EmptyLatentImage",
+    "_meta": {
+      "title": "空Latent"
+    }
+  },
+  "3": {
+    "inputs": {
+      "text": [
+        "17",
+        0
+      ],
+      "clip": [
+        "1",
+        1
+      ]
+    },
+    "class_type": "CLIPTextEncode",
+    "_meta": {
+      "title": "CLIP文本编码器"
+    }
+  },
+  "4": {
+    "inputs": {
+      "text": [
+        "18",
+        0
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+      "clip": [
+        "1",
+        1
+      ]
+    },
+    "class_type": "CLIPTextEncode",
+    "_meta": {
+      "title": "CLIP文本编码器"
+    }
+  },
+  "6": {
+    "inputs": {
+      "control_net_name": "control_v11p_sd15_lineart.pth"
+    },
+    "class_type": "ControlNetLoader",
+    "_meta": {
+      "title": "ControlNet加载器"
+    }
+  },
+  "7": {
+    "inputs": {
+      "strength": 1,
+      "conditioning": [
+        "3",
+        0
+      ],
+      "control_net": [
+        "6",
+        0
+      ],
+      "image": [
+        "22",
+        0
+      ]
+    },
+    "class_type": "ControlNetApply",
+    "_meta": {
+      "title": "ControlNet应用"
+    }
+  },
+  "8": {
+    "inputs": {
+      "seed": 275540587861329,
+      "steps": 8,
+      "cfg": 1,
+      "sampler_name": "lcm",
+      "scheduler": "karras",
+      "denoise": 1,
+      "model": [
+        "14",
+        0
+      ],
+      "positive": [
+        "7",
+        0
+      ],
+      "negative": [
+        "4",
+        0
+      ],
+      "latent_image": [
+        "2",
+        0
+      ]
+    },
+    "class_type": "KSampler",
+    "_meta": {
+      "title": "K采样器"
+    }
+  },
+  "9": {
+    "inputs": {
+      "samples": [
+        "8",
+        0
+      ],
+      "vae": [
+        "1",
+        2
+      ]
+    },
+    "class_type": "VAEDecode",
+    "_meta": {
+      "title": "VAE解码"
+    }
+  },
+  "14": {
+    "inputs": {
+      "lora_name": "lcm-lora-sdv1-5.safetensors",
+      "strength_model": 1,
+      "model": [
+        "1",
+        0
+      ]
+    },
+    "class_type": "LoraLoaderModelOnly",
+    "_meta": {
+      "title": "LoRA加载器(仅模型)"
+    }
+  },
+  "15": {
+    "inputs": {
+      "image": ""
+    },
+    "class_type": "ETN_LoadImageBase64",
+    "_meta": {
+      "title": "Load Image (Base64)"
+    }
+  },
+  "16": {
+    "inputs": {
+      "image": [
+        "22",
+        0
+      ]
+    },
+    "class_type": "GetImage_(Width&Height) _O",
+    "_meta": {
+      "title": "GetImage_(Width&Height) _O"
+    }
+  },
+  "17": {
+    "inputs": {
+      "text_trans": ""
+    },
+    "class_type": "ZhPromptTranslator",
+    "_meta": {
+      "title": "正向提示词"
+    }
+  },
+  "18": {
+    "inputs": {
+      "text_trans": ""
+    },
+    "class_type": "ZhPromptTranslator",
+    "_meta": {
+      "title": "反向提示词"
+    }
+  },
+  "19": {
+    "inputs": {
+      "filename_prefix": "ComfyUI",
+      "images": [
+        "9",
+        0
+      ]
+    },
+    "class_type": "SaveImage",
+    "_meta": {
+      "title": "保存图像"
+    }
+  },
+  "20": {
+    "inputs": {
+      "channel": "red",
+      "image": [
+        "15",
+        0
+      ]
+    },
+    "class_type": "ImageToMask",
+    "_meta": {
+      "title": "图像到遮罩"
+    }
+  },
+  "21": {
+    "inputs": {
+      "mask": [
+        "20",
+        0
+      ]
+    },
+    "class_type": "InvertMask",
+    "_meta": {
+      "title": "遮罩反转"
+    }
+  },
+  "22": {
+    "inputs": {
+      "mask": [
+        "21",
+        0
+      ]
+    },
+    "class_type": "MaskToImage",
+    "_meta": {
+      "title": "遮罩到图像"
+    }
+  }
+}

config/workflow/text2img.json

@@ -0,0 +1,125 @@
+{
+  "3": {
+    "inputs": {
+      "seed": 1068764177227380,
+      "steps": 5,
+      "cfg": 1,
+      "sampler_name": "lcm",
+      "scheduler": "normal",
+      "denoise": 1,
+      "model": [
+        "10",
+        0
+      ],
+      "positive": [
+        "6",
+        0
+      ],
+      "negative": [
+        "7",
+        0
+      ],
+      "latent_image": [
+        "5",
+        0
+      ]
+    },
+    "class_type": "KSampler"
+  },
+  "4": {
+    "inputs": {
+      "ckpt_name": "dreamshaper_8.safetensors"
+    },
+    "class_type": "CheckpointLoaderSimple"
+  },
+  "5": {
+    "inputs": {
+      "width": [
+        "14",
+        0
+      ],
+      "height": [
+        "14",
+        1
+      ],
+      "batch_size": 1
+    },
+    "class_type": "EmptyLatentImage"
+  },
+  "6": {
+    "inputs": {
+      "text": [
+        "20",
+        0
+      ],
+      "clip": [
+        "10",
+        1
+      ]
+    },
+    "class_type": "CLIPTextEncode"
+  },
+  "7": {
+    "inputs": {
+      "text": "undefined",
+      "clip": [
+        "4",
+        1
+      ]
+    },
+    "class_type": "CLIPTextEncode"
+  },
+  "8": {
+    "inputs": {
+      "samples": [
+        "3",
+        0
+      ],
+      "vae": [
+        "4",
+        2
+      ]
+    },
+    "class_type": "VAEDecode"
+  },
+  "9": {
+    "inputs": {
+      "filename_prefix": "ComfyUI",
+      "images": [
+        "8",
+        0
+      ]
+    },
+    "class_type": "SaveImage"
+  },
+  "10": {
+    "inputs": {
+      "lora_name": "lcm-lora-sdv1-5.safetensors",
+      "strength_model": 1,
+      "strength_clip": 1,
+      "model": [
+        "4",
+        0
+      ],
+      "clip": [
+        "4",
+        1
+      ]
+    },
+    "class_type": "LoraLoader"
+  },
+  "14": {
+    "inputs": {
+      "aspect_ratio": "1152×896 ∣ 9:7",
+      "width": 512,
+      "height": 512
+    },
+    "class_type": "AspectRatio"
+  },
+  "20": {
+    "inputs": {
+      "text_trans": "一只小狗"
+    },
+    "class_type": "ZhPromptTranslator"
+  }
+}

config/workflow/text2qrcode.json

@@ -0,0 +1,235 @@
+{
+  "3": {
+    "inputs": {
+      "seed": 1092890374757226,
+      "steps": 8,
+      "cfg": 1,
+      "sampler_name": "lcm",
+      "scheduler": "normal",
+      "denoise": 1,
+      "model": [
+        "74",
+        0
+      ],
+      "positive": [
+        "73",
+        0
+      ],
+      "negative": [
+        "73",
+        1
+      ],
+      "latent_image": [
+        "42",
+        0
+      ]
+    },
+    "class_type": "KSampler",
+    "_meta": {
+      "title": "K采样器"
+    }
+  },
+  "4": {
+    "inputs": {
+      "ckpt_name": "dreamshaper_8.safetensors"
+    },
+    "class_type": "CheckpointLoaderSimple",
+    "_meta": {
+      "title": "Checkpoint加载器(简易)"
+    }
+  },
+  "6": {
+    "inputs": {
+      "text": [
+        "75",
+        0
+      ],
+      "clip": [
+        "4",
+        1
+      ]
+    },
+    "class_type": "CLIPTextEncode",
+    "_meta": {
+      "title": "CLIP文本编码器"
+    }
+  },
+  "7": {
+    "inputs": {
+      "text": "",
+      "clip": [
+        "4",
+        1
+      ]
+    },
+    "class_type": "CLIPTextEncode",
+    "_meta": {
+      "title": "CLIP文本编码器"
+    }
+  },
+  "8": {
+    "inputs": {
+      "samples": [
+        "3",
+        0
+      ],
+      "vae": [
+        "4",
+        2
+      ]
+    },
+    "class_type": "VAEDecode",
+    "_meta": {
+      "title": "VAE解码"
+    }
+  },
+  "9": {
+    "inputs": {
+      "filename_prefix": "ComfyUI",
+      "images": [
+        "8",
+        0
+      ]
+    },
+    "class_type": "SaveImage",
+    "_meta": {
+      "title": "保存图像"
+    }
+  },
+  "16": {
+    "inputs": {
+      "text": "https://u.wechat.com/EEy4mPvfXdYO-MvStE4S2m0",
+      "version": 2,
+      "box_size": 30,
+      "border": 5
+    },
+    "class_type": "QRCode",
+    "_meta": {
+      "title": "二维码生成"
+    }
+  },
+  "35": {
+    "inputs": {
+      "image": [
+        "16",
+        0
+      ]
+    },
+    "class_type": "GetImage_(Width&Height) _O",
+    "_meta": {
+      "title": "GetImage_(Width&Height) _O"
+    }
+  },
+  "41": {
+    "inputs": {
+      "control_net_name": "明暗控制controlNet.safetensors"
+    },
+    "class_type": "ControlNetLoader",
+    "_meta": {
+      "title": "ControlNet加载器"
+    }
+  },
+  "42": {
+    "inputs": {
+      "width": [
+        "35",
+        0
+      ],
+      "height": [
+        "35",
+        1
+      ],
+      "batch_size": 1
+    },
+    "class_type": "EmptyLatentImage",
+    "_meta": {
+      "title": "空Latent"
+    }
+  },
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+    "inputs": {
+      "control_net_name": "control_v1p_sd15_qrcode_monster_v2.safetensors"
+    },
+    "class_type": "ControlNetLoader",
+    "_meta": {
+      "title": "ControlNet加载器"
+    }
+  },
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+      "start_percent": 0,
+      "end_percent": 1,
+      "positive": [
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+      "image": [
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+        0
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+    },
+    "class_type": "ControlNetApplyAdvanced",
+    "_meta": {
+      "title": "ControlNet应用(高级)"
+    }
+  },
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+    },
+    "class_type": "ControlNetApplyAdvanced",
+    "_meta": {
+      "title": "ControlNet应用(高级)"
+    }
+  },
+  "74": {
+    "inputs": {
+      "lora_name": "lcm-lora-sdv1-5.safetensors",
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+      "model": [
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+    "class_type": "LoraLoaderModelOnly",
+    "_meta": {
+      "title": "LoRA加载器(仅模型)"
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+  },
+  "75": {
+    "inputs": {
+      "text_trans": "汽车修理店，车轮"
+    },
+    "class_type": "ZhPromptTranslator",
+    "_meta": {
+      "title": "中文翻译"
+    }
+  }
+}