v0.18.0

Fix chinese translate

.gitignore

@@ -3,4 +3,5 @@ https/
 nodes/config.json
 workflow/my_workflow.json
 workflow/my_workflow_app.json
-app/*
+workflow/prompt_result.json
+app/*

README.md

@@ -1,6 +1,6 @@
 > 适配了最新版comfyui的py3.11 ，torch 2.1.2+cu121
 
-> [discord](https://discord.gg/cXs9vZSqeK)
+> [Mixlab nodes discord](https://discord.gg/cXs9vZSqeK)
 
 #### 
 [comfyui-ultralytics-yolo](https://github.com/shadowcz007/comfyui-ultralytics-yolo)
@@ -45,7 +45,12 @@ APP-JSON:
 
 > seed统一输入控件，支持：SamplerCustom、KSampler
 
-> [ps插件](https://github.com/shadowcz007/comfyui-ps-plugin)
+> 配套[ps插件](https://github.com/shadowcz007/comfyui-ps-plugin)
+
+> 如果遇到上传图片不成功，请检查下：局域网或者是云服务，请使用https，端口8189这个服务（ 感谢 @Damien 反馈问题）
+
+> If you encounter difficulties in uploading images, please check the following: for local network or cloud services, please use HTTPS and the service on port 8189. (Thanks to @Damien for reporting the issue.)
+
 
 
 ## 🏃🚗🚚🚀  Real-time Design
@@ -68,7 +73,7 @@ https://github.com/shadowcz007/comfyui-mixlab-nodes/assets/12645064/e7e77f90-e43
 [Voice + Real-time Face Swap Workflow](./workflow/语音+实时换脸workflow.json)
 
 ### GPT
-> Support for calling multiple GPTs.ChatGPT、ChatGLM3 , Some code provided by rui. If you are using OpenAI's service, fill in https://api.openai.com/v1 . If you are using a local LLM service, fill in http://127.0.0.1:xxxx/v1 .  Azure OpenAI:https://xxxx.openai.azure.com 
+> Support for calling multiple GPTs.ChatGPT、ChatGLM3 、ChatGLM4 , Some code provided by rui. If you are using OpenAI's service, fill in https://api.openai.com/v1 . If you are using a local LLM service, fill in http://127.0.0.1:xxxx/v1 .  Azure OpenAI:https://xxxx.openai.azure.com 
 
 ![gpt-workflow.svg](./assets/gpt-workflow.svg)
 
@@ -120,6 +125,12 @@ https://github.com/shadowcz007/comfyui-mixlab-nodes/assets/12645064/e7e77f90-e43
 > Conveniently load images from a fixed address on the internet to ensure that default images in the workflow can be executed.
 
 
+## Style
+> Apply VisualStyle Prompting , Modified from [ComfyUI_VisualStylePrompting](https://github.com/ExponentialML/ComfyUI_VisualStylePrompting) 
+
+![](./assets/VisualStylePrompting.png)
+
+
 ## Utils
 > The Color node provides a color picker for easy color selection, the Font node offers built-in font selection for use with TextImage to generate text images, and the DynamicDelayByText node allows delayed execution based on the length of the input text.
 
@@ -163,6 +174,7 @@ from [simple-lama-inpainting](https://github.com/enesmsahin/simple-lama-inpainti
 
 "briarmbg","u2net","u2netp","u2net_human_seg","u2net_cloth_seg","silueta","isnet-general-use","isnet-anime"
 
+*** briarmbg ***  model was developed by BRlA Al and can be used as an open-source model for non-commercial purposes
 
 
 ### Improvement 
@@ -226,6 +238,14 @@ pip3 install -r requirements.txt
 访问 [www.mixcomfy.com](https://www.mixcomfy.com)，获得更多内测功能，关注微信公众号：Mixlab无界社区
 
 
+
+
+#### 
+File / LoadImagesFromPath SaveImageToLocal LoadImagesFromURL
+
+
+
+
 #### discussions:
 [discussions](https://github.com/shadowcz007/comfyui-mixlab-nodes/discussions)
 

__init__.py

@@ -6,7 +6,7 @@ import sys,json
 import urllib
 import hashlib
 import datetime
-
+import folder_paths
 
 python = sys.executable
 
@@ -252,7 +252,8 @@ def get_my_workflow_for_app(filename="my_workflow_app.json",category="",is_all=F
                                 "name":x['app']['name'],
                                 "version":x['app']['version'],
                                 "input":input,
-                                "output":output
+                                "output":output,
+                                "id":x['app']['id']
                             }
                         },
                         "date":item["date"]
@@ -300,7 +301,8 @@ def get_my_workflow_for_app(filename="my_workflow_app.json",category="",is_all=F
                                 "name":x['app']['name'],
                                 "version":x['app']['version'],
                                 "input":input,
-                                "output":output
+                                "output":output,
+                                "id":x['app']['id']
                             }
                         },
                         "date":item["date"]
@@ -308,6 +310,31 @@ def get_my_workflow_for_app(filename="my_workflow_app.json",category="",is_all=F
 
     return apps
 
+# 历史记录
+def save_prompt_result(id,data):
+    prompt_result_path=os.path.join(current_path, "workflow/prompt_result.json")
+    prompt_result={}
+    if os.path.exists(prompt_result_path):
+        with open(prompt_result_path) as json_file:
+            prompt_result = json.load(json_file)
+    
+    prompt_result[id]=data
+    
+    with open(prompt_result_path, 'w') as file:
+        json.dump(prompt_result, file)
+    return prompt_result_path
+
+def get_prompt_result():
+    prompt_result_path=os.path.join(current_path, "workflow/prompt_result.json")
+    prompt_result={}
+    if os.path.exists(prompt_result_path):
+        with open(prompt_result_path) as json_file:
+            prompt_result = json.load(json_file)
+    res=list(prompt_result.values())
+    # print(res)
+    return res
+
+
 def save_workflow_json(data):
     workflow_path=os.path.join(current_path, "workflow/my_workflow.json")
     with open(workflow_path, 'w') as file:
@@ -518,6 +545,40 @@ async def nodes_map_hander(request):
     return web.json_response(result)
 
 
+@routes.post("/mixlab/folder_paths")
+async def get_checkpoints(request):
+    data = await request.json()
+    t="checkpoints"
+    try:
+        t=data['type']
+    except Exception as e:
+        print('/mixlab/folder_paths',False,e)
+    
+    names = folder_paths.get_filename_list(t)
+
+    return web.json_response({"names":names,"types":list(folder_paths.folder_names_and_paths.keys())})
+
+
+@routes.post("/mixlab/prompt_result")
+async def post_prompt_result(request):
+    data = await request.json()
+    res=None
+    # print(data)
+    try:
+        action=data['action']
+        if action=='save':
+            result=data['data']
+            res=save_prompt_result(result['prompt_id'],result)
+        elif action=='all':
+            res=get_prompt_result()
+    except Exception as e:
+        print('/mixlab/prompt_result',False,e)
+    
+    return web.json_response({"result":res})
+
+
+
+
 # 扩展api接口
 # from server import PromptServer
 # from aiohttp import web
@@ -535,11 +596,12 @@ from .nodes.ImageNode import SaveImageToLocal,SplitImage,GridOutput,GetImageSize
 # from .nodes.Vae import VAELoader,VAEDecode
 from .nodes.ScreenShareNode import ScreenShareNode,FloatingVideo
 
-from .nodes.ChatGPT import ChatGPTNode,ShowTextForGPT,CharacterInText
+from .nodes.ChatGPT import ChatGPTNode,ShowTextForGPT,CharacterInText,TextSplitByDelimiter
 from .nodes.Audio import GamePal,SpeechRecognition,SpeechSynthesis
 from .nodes.Utils import CreateLoraNames,CreateSampler_names,CreateCkptNames,CreateSeedNode,TESTNODE_,TESTNODE_TOKEN,AppInfo,IntNumber,FloatSlider,TextInput,ColorInput,FontInput,TextToNumber,DynamicDelayProcessor,LimitNumber,SwitchByIndex,MultiplicationNode
 from .nodes.Mask import OutlineMask,FeatheredMask
 
+from .nodes.Style import ApplyVisualStylePrompting
 
 # 要导出的所有节点及其名称的字典
 # 注意：名称应全局唯一
@@ -548,6 +610,7 @@ NODE_CLASS_MAPPINGS = {
     "TESTNODE_":TESTNODE_,
     "TESTNODE_TOKEN":TESTNODE_TOKEN,
     "RandomPrompt":RandomPrompt,
+    # "LoraPrompt":LoraPrompt,
     "EmbeddingPrompt":EmbeddingPrompt,
     "PromptSlide":PromptSlide,
     "PromptSimplification":PromptSimplification,
@@ -584,6 +647,7 @@ NODE_CLASS_MAPPINGS = {
     "ChatGPTOpenAI":ChatGPTNode,
     "ShowTextForGPT":ShowTextForGPT,
     "CharacterInText":CharacterInText,
+    "TextSplitByDelimiter":TextSplitByDelimiter,
     "SpeechRecognition":SpeechRecognition,
     "SpeechSynthesis":SpeechSynthesis,
     "Color":ColorInput,
@@ -602,7 +666,8 @@ NODE_CLASS_MAPPINGS = {
     "Seed_":CreateSeedNode,
     "CkptNames_":CreateCkptNames,
     "SamplerNames_":CreateSampler_names,
-    "LoraNames_":CreateLoraNames
+    "LoraNames_":CreateLoraNames,
+    "ApplyVisualStylePrompting_":ApplyVisualStylePrompting
     # "LaMaInpainting":LaMaInpainting
     # "GamePal":GamePal
 }
@@ -630,7 +695,8 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "ChinesePrompt_Mix":"ChinesePrompt ♾️Mixlab",
     "GamePal":"GamePal ♾️Mixlab",
     "RembgNode_Mix":"Removebg",
-    "LoraNames_":"LoraName_TriggerWords.safetensors"
+    "LoraNames_":"LoraName",
+    "ApplyVisualStylePrompting_":"Apply VisualStyle Prompting"
 }
 
 # web ui的节点功能

data/loras_tags.json

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

nodes/ChatGPT.py

@@ -4,7 +4,7 @@ import urllib.error
 import re,json,os,string,random
 import folder_paths
 import hashlib
-
+from zhipuai import ZhipuAI
 def get_unique_hash(string):
     hash_object = hashlib.sha1(string.encode())
     unique_hash = hash_object.hexdigest()
@@ -46,6 +46,11 @@ def openai_client(key,url):
     base_url=url
     )
     return client
+def ZhipuAI_client(key):
+    client = ZhipuAI(
+        api_key=key, # 填写您的 APIKey
+    ) 
+    return client
 
 
 
@@ -100,7 +105,7 @@ class ChatGPTNode:
                                        "default": "You are ChatGPT, a large language model trained by OpenAI. Answer as concisely as possible.", 
                                        "multiline": True,"dynamicPrompts": False
                                        }),
-                "model": (["gpt-3.5-turbo","gpt-35-turbo","gpt-3.5-turbo-16k", "gpt-3.5-turbo-16k-0613", "gpt-4-0613","gpt-4-1106-preview"], 
+                "model": (["gpt-3.5-turbo","gpt-35-turbo","gpt-3.5-turbo-16k", "gpt-3.5-turbo-16k-0613", "gpt-4-0613","gpt-4-1106-preview","glm-4"], 
                           {"default": "gpt-3.5-turbo"}),
                 "seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff, "step": 1}),
                 "context_size":("INT", {"default": 1, "min": 0, "max":30, "step": 1}),
@@ -114,7 +119,7 @@ class ChatGPTNode:
     RETURN_TYPES = ("STRING","STRING","STRING",)
     RETURN_NAMES = ("text","messages","session_history",)
     FUNCTION = "generate_contextual_text"
-    CATEGORY = "♾️Mixlab/GPT"
+    CATEGORY = "♾️Mixlab/Prompt/GPT"
     INPUT_IS_LIST = False
     OUTPUT_IS_LIST = (False,False,False,)
 
@@ -143,8 +148,13 @@ class ChatGPTNode:
         if is_azure_url(api_url):
             client=azure_client(api_key,api_url)
         else:
-            client=openai_client(api_key,api_url)
-            print('openai url')
+            # 根据用户选择的模型，设置相应的接口和模型名称
+            if model == "glm-4" :
+                client = ZhipuAI_client(api_key)  # 使用 Zhipuai 的接口
+                print('using Zhipuai interface')
+            else :
+                client = openai_client(api_key,api_url)  # 使用 ChatGPT  的接口
+                print('using ChatGPT interface')
 
         # 把用户的提示添加到会话历史中
         # 调用API时传递整个会话历史
@@ -199,7 +209,7 @@ class ShowTextForGPT:
     OUTPUT_NODE = True
     OUTPUT_IS_LIST = (True,)
 
-    CATEGORY = "♾️Mixlab/GPT"
+    CATEGORY = "♾️Mixlab/Prompt/GPT"
 
     def run(self, text,output_dir=[""]):
         
@@ -283,7 +293,7 @@ class CharacterInText:
     # OUTPUT_NODE = True
     OUTPUT_IS_LIST = (False,)
 
-    CATEGORY = "♾️Mixlab/GPT"
+    CATEGORY = "♾️Mixlab/Prompt/GPT"
 
     def run(self, text,character,start_index):
         # print(text,character,start_index)
@@ -291,3 +301,52 @@ class CharacterInText:
         
         return (b+start_index,)
 
+class TextSplitByDelimiter:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                 "text": ("STRING", {"multiline": True,"dynamicPrompts": False}),
+                "delimiter":(["newline","comma"],),
+                "start_index": ("INT", {
+                    "default": 0,
+                    "min": 0, #Minimum value
+                    "max": 1000, #Maximum value
+                    "step": 1, #Slider's step
+                    "display": "number" # Cosmetic only: display as "number" or "slider"
+                }),
+                 "skip_every": ("INT", {
+                    "default": 0,
+                    "min": 0, #Minimum value
+                    "max": 10, #Maximum value
+                    "step": 1, #Slider's step
+                    "display": "number" # Cosmetic only: display as "number" or "slider"
+                }),
+                "max_count": ("INT", {
+                    "default": 10,
+                    "min": 1, #Minimum value
+                    "max": 1000, #Maximum value
+                    "step": 1, #Slider's step
+                    "display": "number" # Cosmetic only: display as "number" or "slider"
+                }),
+            }
+        }
+
+    INPUT_IS_LIST = False
+    RETURN_TYPES = ("STRING",)
+    FUNCTION = "run"
+    # OUTPUT_NODE = True
+    OUTPUT_IS_LIST = (True,)
+
+    CATEGORY = "♾️Mixlab/Prompt/GPT"
+
+    def run(self, text,delimiter,start_index,skip_every,max_count):
+        arr=[]
+        if delimiter=='newline':
+            arr = [line for line in text.split('\n') if line.strip()]
+        elif delimiter=='comma':
+            arr = [line for line in text.split(',') if line.strip()]
+        
+        arr= arr[start_index:start_index + max_count * (skip_every+1):(skip_every+1)]
+
+        return (arr,)

nodes/ImageNode.py

@@ -1720,17 +1720,24 @@ class SplitImage:
     # OUTPUT_IS_LIST = (True,)
 
     def run(self,image,num,seed):
+        
+        if type(seed) == list and len(seed)==1:
+            seed=seed[0]
+
         image=tensor2pil(image)
         
         grids=splitImage(image,num)
 
         if seed>num:
-            num=int(seed / 500 * num)-1
+            num=seed % (num + 1)
         else:
             num=seed-1
+        
+        print('#SplitImage',seed)
 
         num=max(0,num) 
-
+        num=min(num,len(grids)-1)
+        
         g=grids[num]
 
         x,y,w,h=g
@@ -2408,7 +2415,7 @@ class SaveImageToLocal:
         full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(filename_prefix, self.output_dir, images[0].shape[1], images[0].shape[0])
         
     
-        if not os.path.exists(file_path) and not extension:
+        if not os.path.exists(file_path):
             # 使用os.makedirs函数创建新目录
             os.makedirs(file_path)
             print("目录已创建")

nodes/PromptNode.py

@@ -6,6 +6,12 @@ from urllib import request, parse
 import folder_paths
 from PIL import Image, ImageOps,ImageFilter,ImageEnhance,ImageDraw,ImageSequence, ImageFont
 from PIL.PngImagePlugin import PngInfo
+
+import hashlib
+import requests
+import json
+
+
 # def queue_prompt(prompt_workflow):
 #     p = {"prompt": prompt_workflow}
 #     data = json.dumps(p).encode('utf-8')
@@ -15,6 +21,7 @@ from PIL.PngImagePlugin import PngInfo
 embeddings_path=os.path.join(folder_paths.models_dir, "embeddings")
 
 def get_files_with_extension(directory, extension):
+    
     file_list = []
     for root, dirs, files in os.walk(directory):
         for file in files:
@@ -28,6 +35,50 @@ def join_with_(text_list,delimiter):
     return joined_text
 
 
+
+def load_json(file_path):
+    try:
+        with open(file_path, 'r') as json_file:
+            data = json.load(json_file)
+            return data
+    except FileNotFoundError:
+        print(f"File not found: {file_path}")
+        return None
+    except json.JSONDecodeError:
+        print(f"Error decoding JSON in file: {file_path}")
+        return None
+
+def save_json(data_dict, file_path):
+    try:
+        with open(file_path, 'w') as json_file:
+            json.dump(data_dict, json_file, indent=4)
+            print(f"Data saved to {file_path}")
+    except Exception as e:
+        print(f"Error saving JSON to file: {e}")
+
+# pysss的lora加载器
+# def get_model_version_info(hash_value):
+#     # http://127.0.0.1:1082
+#     proxies = {'http': 'http://127.0.0.1:1082', 'https': 'https://127.0.0.1:1082'}
+#     api_url = f"https://civitai.com/api/v1/model-versions/by-hash/{hash_value}"
+#     print(api_url)
+#     response = requests.get(api_url,proxies=proxies, verify=False)
+    
+#     if response.status_code == 200:
+#         return response.json()
+#     else:
+#         return None
+    
+# def calculate_sha256(file_path):
+#     sha256_hash = hashlib.sha256()
+#     with open(file_path, "rb") as f:
+#         for chunk in iter(lambda: f.read(4096), b""):
+#             sha256_hash.update(chunk)
+#     return sha256_hash.hexdigest()
+
+
+
+
 class AnyType(str):
   """A special class that is always equal in not equal comparisons. Credit to pythongosssss"""
 
@@ -385,16 +436,92 @@ class RandomPrompt:
         return {"ui": {"prompts": prompts}, "result": (prompts,)}
 
 
+# class LoraPrompt:
+#     @classmethod
+#     def INPUT_TYPES(s):
+#         return {
+#             "required": {
+#                 "lora_name":(sorted(folder_paths.get_filename_list("loras"), key=str.lower),),
+#                 "weight": ("FLOAT", {"default": 1, "min": -2, "max": 2,"step":0.01 ,"display": "slider"}),
+#                 "force_update": ("BOOLEAN", {"default": False}),
+#                 },
+                
+#             }
+    
+#     RETURN_TYPES = ("STRING","STRING",any_type)
+#     RETURN_NAMES = ("lora_name","prompt","tags",)
+
+#     FUNCTION = "run"
+
+#     CATEGORY = "♾️Mixlab/Prompt"
+
+#     OUTPUT_IS_LIST = (False,False,True,)
+#     # OUTPUT_NODE = True
+
+#     # 运行的函数
+#     def run(self,lora_name,weight,force_update=False):
+       
+#         # print('##LoraPrompt',__file__)
+#         # 从本地数据库读取
+#         json_tags_path = os.path.join(os.path.dirname(os.path.dirname(__file__)),r'data/loras_tags.json')
+
+#         if not os.path.exists(json_tags_path):
+#             save_json({},json_tags_path)
+
+#         lora_tags = load_json(json_tags_path)
+#         output_tags = lora_tags.get(lora_name, None) if lora_tags is not None else None
+#         if output_tags is not None:
+#             output_tags = ",".join(output_tags)
+#             print("trainedWords:",output_tags)
+#         else:
+#             output_tags = ""
 
 
+#         lora_path = folder_paths.get_full_path("loras", lora_name)
+#         if output_tags == "" or force_update:
+#             print("calculating lora hash")
+#             LORAsha256 = calculate_sha256(lora_path)
+#             print("requesting infos")
+#             model_info = get_model_version_info(LORAsha256)
+#             if model_info is not None:
+#                 if "trainedWords" in model_info:
+#                     print("tags found!")
+#                     if lora_tags is None:
+#                         lora_tags = {}
+#                     lora_tags[lora_name] = model_info["trainedWords"]
+#                     save_json(lora_tags,json_tags_path)
+#                     output_tags = ",".join(model_info["trainedWords"])
+#                     print("trainedWords:",output_tags)
+#             else:
+#                 print("No informations found.")
+#                 if lora_tags is None:
+#                     lora_tags = {}
+#                 lora_tags[lora_name] = []
+#                 save_json(lora_tags,json_tags_path)
 
 
+#         weight = round(weight, 3)
+#         prompt=[]
+#         for p in output_tags.split(','):
+            
+#             if weight!=1:
+#                 prompt.append('('+p+':'+str(weight)+')')
+#             else:
+#                 prompt.append(p)
+
+#         prompt=",".join(prompt)
+
+#         return (lora_name,prompt,output_tags.split(','),)
+
+
+import folder_paths
 class EmbeddingPrompt:
     @classmethod
     def INPUT_TYPES(s):
+
         return {
             "required": {
-                "embedding":(get_files_with_extension(embeddings_path,'.pt'),),
+                "embedding":(folder_paths.get_filename_list("embeddings"),),
                 "weight": ("FLOAT", {"default": 1, "min": -2, "max": 2,"step":0.01 ,"display": "slider"}),
                 },
                 
@@ -426,7 +553,7 @@ class JoinWithDelimiter:
     def INPUT_TYPES(s):
         return {"required": {
                     "text_list": (any_type,),
-                    "delimiter":(["newline","comma"],),
+                    "delimiter":(["newline","comma","backslash","space"],),
                              },
                 }
     
@@ -445,6 +572,10 @@ class JoinWithDelimiter:
             delimiter='\n'
         elif delimiter=='comma':
             delimiter=','
+        elif delimiter=='backslash':
+            delimiter='\\'
+        elif delimiter=='space':
+            delimiter=' '
         t=''
         if isinstance(text_list, list):
             t=join_with_(text_list,delimiter)

nodes/Style.py

@@ -0,0 +1,76 @@
+import comfy
+import torch
+
+from .VisualStylePrompting.attention_functions import VisualStyleProcessor
+
+class ApplyVisualStylePrompting:
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "reference_image": ("IMAGE",),
+                "reference_image_text": ("STRING", {"multiline": True}),
+                "model": ("MODEL",),
+                "clip": ("CLIP", ),
+                "vae": ("VAE", ),
+                "positive": ("CONDITIONING",),
+                "negative": ("CONDITIONING", ),
+                "enabled": ("BOOLEAN", {"default": True}),
+                "denoise": ("FLOAT", {"default": 1., "min": 0., "max": 1., "step": 1e-2}),
+                "batch_size": ("INT", {"default": 1, "min": 1, "max": 4096,"step":2})
+            }
+        }
+
+    RETURN_TYPES = ("MODEL", "CONDITIONING","CONDITIONING", "LATENT")
+    RETURN_NAMES = ("model", "positive", "negative", "latents")
+    
+    CATEGORY = "♾️Mixlab/Style"
+
+    FUNCTION = "run"
+
+    def run(
+        self, 
+        reference_image, 
+        reference_image_text,
+        model: comfy.model_patcher.ModelPatcher, 
+        clip,
+        vae,
+        positive,
+        negative, 
+        enabled,
+        denoise,
+        batch_size=1
+    ):
+        
+        tokens = clip.tokenize(reference_image_text)
+        cond, pooled = clip.encode_from_tokens(tokens, return_pooled=True)
+        reference_image_prompt=[[cond, {"pooled_output": pooled}]]
+   
+        reference_image = reference_image.repeat(((batch_size+1)//2, 1,1,1))
+
+        self.model = model
+        reference_latent = vae.encode(reference_image[:,:,:,:3])
+        
+        for n, m in model.model.diffusion_model.named_modules():
+            if m.__class__.__name__  == "CrossAttention":
+                processor = VisualStyleProcessor(m, enabled=enabled)
+                setattr(m, 'forward', processor.visual_style_forward)
+
+        conditioning_prompt = reference_image_prompt + positive
+        negative_prompt = negative * 2 
+
+        latents = torch.zeros_like(reference_latent) 
+        latents = torch.cat([latents] * 2)
+
+        if denoise < 1.0:
+            latents[::1] = reference_latent[:1]
+        else:
+            latents[::2] = reference_latent
+
+        denoise_mask = torch.ones_like(latents)[:, :1, ...] * denoise
+
+        denoise_mask[0] = 0.
+
+        return (model, conditioning_prompt, negative_prompt, {"samples": latents, "noise_mask": denoise_mask})    
+

nodes/TextGenerateNode.py

@@ -62,7 +62,14 @@ except:
 
 
 
-def translate(zh_en_tokenizer,zh_en_model,text):
+def translate(text):
+    global text_pipe,zh_en_model,zh_en_tokenizer
+    
+    if zh_en_model==None:
+        zh_en_model = AutoModelForSeq2SeqLM.from_pretrained(zh_en_model_path).eval()
+        zh_en_tokenizer = AutoTokenizer.from_pretrained(zh_en_model_path,padding=True, truncation=True)
+    
+    zh_en_model.to("cuda" if torch.cuda.is_available() else "cpu")
     with torch.no_grad():
         encoded = zh_en_tokenizer([text], return_tensors="pt")
         encoded.to(zh_en_model.device)
@@ -104,16 +111,22 @@ import re
 
 def correct_prompt_syntax(prompt):
 
-    print("input prompt",prompt)
+    # print("input prompt",prompt)
     corrected_elements = []
     # 处理成统一的英文标点
     prompt = prompt.replace('（', '(').replace('）', ')').replace('，', ',').replace(';', ',').replace('。', '.').replace('：',':')
     # 删除多余的空格
     prompt = re.sub(r'\s+', ' ', prompt).strip()
+    prompt = prompt.replace("< ","<").replace(" >",">").replace("( ","(").replace(" )",")").replace("[ ","[").replace(' ]',']')
 
     # 分词
     prompt_elements = prompt.split(',')
 
+    def balance_brackets(element, open_bracket, close_bracket):
+        open_brackets_count = element.count(open_bracket)
+        close_brackets_count = element.count(close_bracket)
+        return element + close_bracket * (open_brackets_count - close_brackets_count)
+
     for element in prompt_elements:
         element = element.strip()
 
@@ -133,21 +146,118 @@ def correct_prompt_syntax(prompt):
         corrected_elements.append(corrected_element)
 
     # 重组修正后的prompt
-    corrected_prompt = ', '.join(corrected_elements)
-    print("output prompt",corrected_prompt)
-    return corrected_prompt
+    return  ','.join(corrected_elements)
 
-def balance_brackets(element, open_bracket, close_bracket):
-    open_brackets_count = element.count(open_bracket)
-    close_brackets_count = element.count(close_bracket)
-    return element + close_bracket * (open_brackets_count - close_brackets_count)
 
 # # 示例使用
 # test_prompt = "((middle-century castles)), [forsaken: 0.8], (mystery dragons: 1.3, mist forests, sunsets, quiet; (((dummy)), [fisting city: 0.5] background, radiant, soft and flavoured,] promising mountains, ((starry: 1.6), [[crowds], [middle-century castle: urban landscapes of the future: 0.5], [yellow: bright sun: 0.7], overlooking"
 # corrected_prompt = correct_prompt_syntax(test_prompt)
 # print(corrected_prompt)
 
+def detect_language(input_str):
+    # 统计中文和英文字符的数量
+    count_cn = count_en = 0
+    for char in input_str:
+        if '\u4e00' <= char <= '\u9fff':
+            count_cn += 1
+        elif char.isalpha():
+            count_en += 1
+
+    # 根据统计的字符数量判断主要语言
+    if count_cn > count_en:
+        return "cn"
+    elif count_en > count_cn:
+        return "en"
+    else:
+        return "unknow"
+
+
+
+
+#定义Prompt文法
+grammar = """
+start: sentence
+sentence: phrase ("," phrase)*
+phrase: emphasis | weight | word | lora | embedding | schedule
+emphasis: "(" sentence ")" -> emphasis
+        | "[" sentence "]" -> weak_emphasis
+weight: "(" word ":" NUMBER ")"
+schedule: "[" word ":" word ":" NUMBER "]"
+lora: "<" WORD ":" WORD (":" NUMBER)? (":" NUMBER)? ">"
+embedding: "embedding" ":" WORD (":" NUMBER)? (":" NUMBER)?
+word: WORD
+
+NUMBER: /\s*-?\d+(\.\d+)?\s*/
+WORD: /[^,:\(\)\[\]<>]+/
+"""
+
+from lark import Lark, Transformer, v_args
+
+@v_args(inline=True)  # Decorator to flatten the tree directly into the function arguments
+class ChinesePromptTranslate(Transformer):
+ 
+    def sentence(self, *args):
+        return ", ".join(args)
+
+    def phrase(self, *args):
+        return "".join(args)
+
+    def emphasis(self, *args):
+        # Reconstruct the emphasis with translated content
+        return "(" + "".join(args) + ")"
+
+    def weak_emphasis(self, *args):
+        print('weak_emphasis:',args)
+        return "[" + "".join(args) + "]"
+    
+    def embedding(self,*args):
+        print('prompt embedding',args[0])
+        if len(args) == 1:
+            # print('prompt embedding',str(args[0]))
+            # 只传递了一个参数，意味着只有embedding名称没有数字
+            embedding_name = str(args[0])
+            return f"embedding:{embedding_name}"
+        elif len(args) > 1:
+            embedding_name,*numbers = args
+           
+            if len(numbers)==2:
+                return f"embedding:{embedding_name}:{numbers[0]}:{numbers[1]}"
+            elif len(numbers)==1:
+                return f"embedding:{embedding_name}:{numbers[0]}"
+            else:
+                return f"embedding:{embedding_name}"
+
+    def lora(self,*args):
+        print('lora prompt',*args)
+        if len(args) == 1:
+            return f"<lora:{loar_name}>"
+        elif len(args) > 1: 
+            # print('lora', args)
+            _,loar_name,*numbers = args
+            loar_name = str(loar_name).strip()
+            if len(numbers)==2:
+                return f"<lora:{loar_name}:{numbers[0]}:{numbers[1]}>"
+            elif len(numbers)==1:
+                return f"<lora:{loar_name}:{numbers[0]}>"
+            else:
+                return f"<lora:{loar_name}>"
+    
+    def weight(self, word,number):
+        translated_word = translate(str(word)).rstrip('.')
+        return f"({translated_word}:{str(number).strip()})"
+    
+    def schedule(self,*args):
+        print('prompt schedule',args)
+        data = [str(arg).strip() for arg in args] 
         
+        return f"[{':'.join(data)}]"
+
+    def word(self, word):
+        # Translate each word using the dictionary
+        if detect_language(str(word)) == "cn":
+            return  translate(str(word)).rstrip('.')
+        else:
+            return str(word).rstrip('.')
         
 class ChinesePrompt:
 
@@ -185,16 +295,17 @@ class ChinesePrompt:
     zh_en_tokenizer=None 
 
     def run(self,text,seed,generation):
-        global text_pipe,zh_en_model,zh_en_tokenizer
+        
 
         seed=seed[0]
         generation=generation[0]
 
         # 进度条
         pbar = comfy.utils.ProgressBar(len(text)+1)
-        
         texts = [correct_prompt_syntax(t) for t in text]
-        print('correct_prompt_syntax::',texts)
+
+
+        global text_pipe,zh_en_model,zh_en_tokenizer
         if zh_en_model==None:
             zh_en_model = AutoModelForSeq2SeqLM.from_pretrained(zh_en_model_path).eval()
             zh_en_tokenizer = AutoTokenizer.from_pretrained(zh_en_model_path,padding=True, truncation=True)
@@ -210,9 +321,15 @@ class ChinesePrompt:
 
         # print('zh_en_model device',zh_en_model.device,text_pipe.model.device,torch.cuda.current_device() )
         en_texts=[]
+
         for t in texts:
-            en_text=translate(zh_en_tokenizer,zh_en_model,t)
-            en_texts.append(en_text)
+            # translated_text =  translated_word = translate(zh_en_tokenizer,zh_en_model,str(t))
+            parser = Lark(grammar, start="start", parser="lalr", transformer=ChinesePromptTranslate())
+            # print('t',t)
+            result = parser.parse(t).children
+            # print('en_result',result)        
+            # en_text=translate(zh_en_tokenizer,zh_en_model,text_without_syntax)
+            en_texts.append(result[0])
 
         zh_en_model.to('cpu')
         print("test en_text",en_texts)
@@ -232,7 +349,9 @@ class ChinesePrompt:
             pbar.update(1)
 
         text_pipe.model.to('cpu')
-        prompt_result = [correct_prompt_syntax(p) for p in prompt_result]
+
+        print('prompt_result',prompt_result,)
+        # prompt_result = [','.join(correct_prompt_syntax(p)) for p in prompt_result]
         
         return {
             "ui":{
@@ -241,6 +360,8 @@ class ChinesePrompt:
             "result": (prompt_result,)}
 
 
+
+
 class PromptGenerate:
 
     global _available

nodes/Utils.py

@@ -6,7 +6,7 @@ import numpy as np
 import folder_paths
 import matplotlib.font_manager as fm
 import torch
-
+import importlib.util
 
 
 def recursive_search(directory, excluded_dir_names=None):
@@ -347,7 +347,7 @@ class MultiplicationNode:
         return {"required": {
                     "numberA":(any_type,),
                     "multiply_by":("FLOAT", {
-                        "default": 0, 
+                        "default": 1, 
                         "min": -2, #Minimum value
                         "max": 0xffffffffffffffff,
                         "step": 0.01, #Slider's step
@@ -560,9 +560,11 @@ class SwitchByIndex:
     @classmethod
     def INPUT_TYPES(cls):
         return {
-            "required": {
-                "A":(any_type,),
-                "B":(any_type,),
+             "optional":{
+                  "A":(any_type,),
+                  "B":(any_type,),
+            },
+            "required": { 
                 "index":("INT", {
                         "default": -1, 
                         "min": -1, 
@@ -574,17 +576,17 @@ class SwitchByIndex:
             }
         }
 
-    RETURN_TYPES = (any_type,)
-    RETURN_NAMES = ("C",)
+    RETURN_TYPES = (any_type,"INT",)
+    RETURN_NAMES = ("C","count",)
 
     FUNCTION = "run"
 
     CATEGORY = "♾️Mixlab/Utils"
 
     INPUT_IS_LIST = True
-    OUTPUT_IS_LIST = (True,)
+    OUTPUT_IS_LIST = (True,False,)
 
-    def run(self, A,B,index,flat):
+    def run(self, A=[],B=[],index=-1,flat='on'):
 
         flat=flat[0]
 
@@ -604,8 +606,8 @@ class SwitchByIndex:
                 C=[C[index]]
             except Exception as e:
                 C=[]
-        
-        return (C,)
+
+        return (C,len(C),)
 
 
 
@@ -711,12 +713,26 @@ class TESTNODE_:
     OUTPUT_IS_LIST = (True,)
 
     def run(self,ANY):
-        print(ANY)
+        # print(ANY)
         # data=ANY
         list_stats = ListStatistics()
 
         # 调用count_types方法进行统计
         result = list_stats.count_types(ANY)
+ 
+
+        # 假设我们有一个模块文件名为 my_module.py，它位于 'importables' 目录下
+        module_path = os.path.join(os.path.dirname(__file__),'test.py')
+
+        # 使用 spec_from_file_location 获取模块的元数据（名称、定义等）
+        spec = importlib.util.spec_from_file_location('test', module_path)
+
+        module = importlib.util.module_from_spec(spec)
+        spec.loader.exec_module(module)
+
+        functions = getattr(module, 'run')  # 获取函数
+        
+        functions(ANY)
 
 
         return {"ui": {"data": result,"type":[str(type(ANY[0]))]}, "result": (ANY,)}

nodes/VisualStylePrompting/attention_functions.py

@@ -0,0 +1,45 @@
+from comfy.ldm.modules.attention import default, optimized_attention, optimized_attention_masked
+from .style_functions import adain, concat_first
+
+class VisualStyleProcessor(object):
+    def __init__(self, 
+        module_self, 
+        keys_scale: float = 1.0,
+        enabled: bool = True, 
+        adain_queries: bool = True,
+        adain_keys: bool = True,
+        adain_values: bool = False 
+    ):
+        self.module_self = module_self
+        self.keys_scale = keys_scale
+        self.enabled = enabled
+        self.adain_queries = adain_queries
+        self.adain_keys = adain_keys
+        self.adain_values = adain_values
+
+    def visual_style_forward(self, x, context, value, mask=None):
+        q = self.module_self.to_q(x)
+        context = default(context, x)
+        k = self.module_self.to_k(context)
+        if value is not None:
+            v = self.module_self.to_v(value)
+            del value
+        else:
+            v = self.module_self.to_v(context)
+
+        if self.enabled:
+            if self.adain_queries:
+                q = adain(q)
+            if self.adain_keys:
+                k = adain(k)
+            if self.adain_values:
+                v = adain(v)
+            
+            k = concat_first(k, -2, self.keys_scale)
+            v = concat_first(v, -2)
+
+        if mask is None:
+            out = optimized_attention(q, k, v, self.module_self.heads)
+        else:
+            out = optimized_attention_masked(q, k, v, self.module_self.heads, mask)
+        return self.module_self.to_out(out)

nodes/VisualStylePrompting/style_functions.py

@@ -0,0 +1,60 @@
+import torch
+
+from einops import rearrange
+from dataclasses import dataclass
+
+T = torch.Tensor
+
+@dataclass(frozen=True)
+class StyleAlignedArgs:
+    share_group_norm: bool = True
+    share_layer_norm: bool = True,
+    share_attention: bool = True
+    adain_queries: bool = True
+    adain_keys: bool = True
+    adain_values: bool = False
+    full_attention_share: bool = False
+    keys_scale: float = 1.
+    only_self_level: float = 0.
+
+def expand_first(feat: T, scale=1., ) -> T:
+    b = feat.shape[0]
+    feat_style = torch.stack((feat[0], feat[b // 2])).unsqueeze(1)
+    if scale == 1:
+        feat_style = feat_style.expand(2, b // 2, *feat.shape[1:])
+    else:
+        feat_style = feat_style.repeat(1, b // 2, 1, 1, 1)
+        feat_style = torch.cat([feat_style[:, :1], scale * feat_style[:, 1:]], dim=1)
+    return feat_style.reshape(*feat.shape)
+
+
+def concat_first(feat: T, dim=2, scale=1.) -> T:
+    feat_style = expand_first(feat, scale=scale)
+    return torch.cat((feat, feat_style), dim=dim)
+
+
+def calc_mean_std(feat, eps: float = 1e-5) -> tuple[T, T]:
+    feat_std = (feat.var(dim=-2, keepdims=True) + eps).sqrt()
+    feat_mean = feat.mean(dim=-2, keepdims=True)
+    return feat_mean, feat_std
+
+
+def adain(feat: T) -> T:
+    feat_mean, feat_std = calc_mean_std(feat)
+    feat_style_mean = expand_first(feat_mean)
+    feat_style_std = expand_first(feat_std)
+    feat = (feat - feat_mean) / feat_std
+    feat = feat * feat_style_std + feat_style_mean
+    return feat
+
+def swapping_attention(key, value, chunk_size=2):
+    chunk_length = key.size()[0] // chunk_size  # [text-condition, null-condition]
+    reference_image_index = [0] * chunk_length  # [0 0 0 0 0]
+    key = rearrange(key, "(b f) d c -> b f d c", f=chunk_length)
+    key = key[:, reference_image_index]  # ref to all
+    key = rearrange(key, "b f d c -> (b f) d c")
+    value = rearrange(value, "(b f) d c -> b f d c", f=chunk_length)
+    value = value[:, reference_image_index]  # ref to all
+    value = rearrange(value, "b f d c -> (b f) d c")
+
+    return key, value

nodes/test.py

@@ -0,0 +1,8 @@
+import folder_paths
+
+# 外挂一个文件，用来编写新的节点
+def run(v):
+
+    output_dir = folder_paths.get_temp_directory()
+
+    print('1323',v,output_dir)

requirements.txt

@@ -6,4 +6,6 @@ matplotlib
 openai
 simple-lama-inpainting
 clip-interrogator==0.6.0
-transformers>=4.36.0
+transformers>=4.36.0
+zhipuai
+lark-parser

web/index.html

@@ -11,12 +11,19 @@
             padding: 0;
         }
 
+        .header {
+            display: flex;
+            align-items: center;
+            justify-content: space-around;
+        }
+
         .app {
             display: flex;
             width: 90%;
             min-width: 400px;
             margin-left: 5%;
             user-select: none;
+            margin-top: 32px;
         }
 
         .apps {
@@ -35,6 +42,16 @@
 
 
         .apps .card {
+            width: 320px;
+            margin: 12px;
+            display: flex;
+            flex-direction: row;
+            background: #ffffff;
+            cursor: pointer;
+            user-select: none;
+        }
+
+        #history_container .card {
             width: 200px;
             margin: 12px;
             display: flex;
@@ -44,25 +61,25 @@
             user-select: none;
         }
 
-        .apps .selected {
+        .selected {
             box-shadow: 0px 0px 10px 10px #fbe9f0
         }
 
-        .apps .card:hover {
+        .card:hover {
             box-shadow: 0px 0px 10px 10px #e9fbfa
         }
 
-        .apps .card h5 {
+        .card h5 {
             font-size: 14px;
-            margin: 10px 0;
+            margin: 0 0 10px 0
         }
 
-        .apps .card p {
+        .card p {
             margin: 0;
             padding: 0;
-            max-height: 35px;
+            /* max-height: 35px; */
             overflow: hidden;
-            width: 98px;
+            /* width: 98px; */
         }
 
         .apps .card img {
@@ -71,14 +88,24 @@
             margin: 0px;
         }
 
-        .apps .card .item {
+        #history_container .card img {
+            width: auto;
+            height: 100%;
+            margin: 0px;
+        }
+
+        .toggle {
+            border: none;
+        }
+
+        .card .item {
             display: flex;
             flex-direction: column;
             justify-content: space-between;
             align-items: flex-start;
         }
 
-        .apps .card .icon {
+        .card .icon {
             width: 48px;
             height: 48px;
             overflow: hidden;
@@ -89,9 +116,8 @@
         }
 
 
-        .apps .card .version {
+        .card .version {
             font-size: 12px;
-
         }
 
         .card .toggle {
@@ -142,6 +168,10 @@
             word-wrap: break-word;
         }
 
+        .description img {
+            min-height: unset !important;
+        }
+
         .panel {
             display: flex;
             flex-direction: column;
@@ -172,6 +202,7 @@
             width: fit-content;
             max-width: 100%;
             margin-left: 12px;
+            min-height: 200px;
         }
 
         .input_card {
@@ -243,6 +274,7 @@
             border-radius: 100%;
             cursor: pointer;
             border: 3px solid;
+            z-index: 100;
         }
 
         button:hover {
@@ -374,13 +406,13 @@
     <link href="/extensions/comfyui-mixlab-nodes/lib/classic.min.css" rel="stylesheet">
     <script src="/extensions/comfyui-mixlab-nodes/lib/pickr.min.js"></script>
     <script src="/extensions/comfyui-mixlab-nodes/lib/filerobot-image-editor.min.js"></script>
+    <link rel="stylesheet" href="/extensions/comfyui-mixlab-nodes/lib/login.css">
 </head>
 
 <body>
+
     <div id="editor_container"></div>
-    <div style="display: flex;
-    align-items: center;
-    justify-content: space-around;">
+    <div class="header">
         <div style="margin: 0 24px;
             margin-bottom: 24px;
             padding: 8px;
@@ -391,18 +423,18 @@
             <a class="link" href="https://www.mixcomfy.com" target="_blank">ComfyUI中文爱好者社区推荐</a>
         </div>
 
-        <a target="_blank" href="https://www.mixcomfy.com/blog/" style="text-decoration: none;
+        <a target="_blank" id="login_btn" href="https://www.mixcomfy.com/blog/" style="text-decoration: none;
         color: black;font-size:12px">
             <svg height="32" aria-hidden="true" viewBox="0 0 16 16" version="1.1" width="32" data-view-component="true"
                 class="octicon octicon-mark-github v-align-middle color-fg-default">
                 <path
                     d="M8 0c4.42 0 8 3.58 8 8a8.013 8.013 0 0 1-5.45 7.59c-.4.08-.55-.17-.55-.38 0-.27.01-1.13.01-2.2 0-.75-.25-1.23-.54-1.48 1.78-.2 3.65-.88 3.65-3.95 0-.88-.31-1.59-.82-2.15.08-.2.36-1.02-.08-2.12 0 0-.67-.22-2.2.82-.64-.18-1.32-.27-2-.27-.68 0-1.36.09-2 .27-1.53-1.03-2.2-.82-2.2-.82-.44 1.1-.16 1.92-.08 2.12-.51.56-.82 1.28-.82 2.15 0 3.06 1.86 3.75 3.64 3.95-.23.2-.44.55-.51 1.07-.46.21-1.61.55-2.33-.66-.15-.24-.6-.83-1.23-.82-.67.01-.27.38.01.53.34.19.73.9.82 1.13.16.45.68 1.31 2.69.94 0 .67.01 1.3.01 1.49 0 .21-.15.45-.55.38A7.995 7.995 0 0 1 0 8c0-4.42 3.58-8 8-8Z">
                 </path>
-            </svg> Community
+            </svg> Community</a>
+
 
-        </a>
     </div>
-
+    <a id="author"></a>
     <!-- <script type="module" src="https://cdn.bootcdn.net/ajax/libs/photoswipe/5.4.0/photoswipe-lightbox.esm.min.js"></script> -->
     <script type="module">
         import PhotoSwipeLightbox from '/extensions/comfyui-mixlab-nodes/lib/photoswipe-lightbox.esm.min.js'
@@ -435,7 +467,6 @@
                 body
             })
 
-
             let data = await resp.json()
             // console.log(data)
             let { name, subfolder } = data
@@ -671,7 +702,7 @@
         }
 
 
-        function queuePrompt(promptWorkflow, seed, client_id) {
+        function queuePrompt(appInfo, promptWorkflow, seed, client_id) {
             // appinfo升级后 兼容，补丁
             for (const id in promptWorkflow) {
                 if (promptWorkflow[id].class_type == 'AppInfo') {
@@ -690,9 +721,14 @@
                 },
                 body: data,
             })
-                .then(response => {
+                .then(async response => {
                     // Handle response here
-                    console.log(response)
+                    // console.log(response)
+                    let res = await response.json();
+                    window.prompt_ids[res.prompt_id] = {
+                        appInfo,
+                        prompt_id: res.prompt_id
+                    }
                 })
                 .catch(error => {
                     // Handle error here
@@ -730,6 +766,31 @@
                 }
             } catch (error) {
             }
+
+            // 排序 
+            let appSelected = localStorage.getItem('app_selected')
+            if (appSelected) {
+                async function moveElementToFront(array, targetId) {
+
+                    for (let i = 0; i < array.length; i++) {
+                        if (array[i].id === targetId) {
+
+                            if (i !== 0) {
+                                const targetElement = array.splice(i, 1)[0];
+
+                                let nt = (await get_my_app(targetElement.category, targetElement.filename))[0];
+
+                                array.unshift(nt);
+                            }
+                            break;
+                        }
+                    }
+
+                    return array;
+                }
+                data = await moveElementToFront(data, appSelected)
+            }
+
             return data
         }
 
@@ -890,6 +951,7 @@
 
 
         function generateRainbowVideo() {
+
             // 创建一个canvas元素
             const canvas = document.createElement('canvas');
             canvas.width = 640; // 设置canvas宽度
@@ -908,30 +970,26 @@
             context.fillStyle = 'green';
             context.fillRect(canvas.width / 2, 0, canvas.width / 2, canvas.height);
 
-            // 创建一个新的video元素
-            const video = document.createElement('video');
-            video.setAttribute('controls', true)
-            // 将canvas绘制到video中
             const stream = canvas.captureStream();
-            video.srcObject = stream;
 
-            // 导出视频
-            const mediaRecorder = new MediaRecorder(stream);
-            const chunks = [];
-            mediaRecorder.ondataavailable = function (event) {
-                chunks.push(event.data);
-            };
-            mediaRecorder.onstop = function () {
-                const blob = new Blob(chunks, { type: 'video/mp4' });
-                const url = URL.createObjectURL(blob);
-                video.src = url;
-            };
-            mediaRecorder.start();
-            setTimeout(function () {
-                mediaRecorder.stop();
-            }, 1000); // 设置录制时长，这里设置为1秒
+            return new Promise((res, rej) => {
+                // 导出视频
+                const mediaRecorder = new MediaRecorder(stream);
+                const chunks = [];
+                mediaRecorder.ondataavailable = function (event) {
+                    chunks.push(event.data);
+                };
+                mediaRecorder.onstop = function () {
+                    const blob = new Blob(chunks, { type: 'video/mp4' });
+                    const url = URL.createObjectURL(blob);
+                    res(url)
+                };
+                mediaRecorder.start();
+                setTimeout(function () {
+                    mediaRecorder.stop();
+                }, 1000); // 设置录制时长，这里设置为1秒
+            })
 
-            return video;
         }
 
 
@@ -1127,9 +1185,10 @@
             // ];
             inputData = inputData.filter(inp => inp);
             // console.log('inputData',inputData)
-            inputData.forEach(data => {
+            inputData.forEach(async data => {
                 console.log(data)
-                // Check if the class_type is "LoadImage"
+
+                // 图片 or 视频输入
                 if (data.class_type === "LoadImage" || data.class_type === "VHS_LoadVideo") {
 
                     let isVideoUpload = data.class_type === "VHS_LoadVideo";
@@ -1145,6 +1204,7 @@
                     uploadContainer.appendChild(nameLabel);
 
                     let actionDiv = document.createElement('div');
+                    actionDiv.style = `padding: 0 8px;`
 
                     // Create an input field for the image name
                     const uploadImageInput = document.createElement("button");
@@ -1172,6 +1232,7 @@
                     // Create an image element to display the uploaded image
                     let imageElement = document.createElement("img");
                     if (isVideoUpload) {
+                        // 视频
                         imageElement = document.createElement('video');
                         imageElement.setAttribute('controls', true)
                         let [subfolder, name] = data.inputs.video.split('/');
@@ -1182,6 +1243,9 @@
                         }
                         let url = `${get_url()}/view?filename=${encodeURIComponent(name)}&type=input&subfolder=${subfolder}&rand=${Math.random()}`
                         imageElement.src = url;
+
+                        // imageElement.innerHTML=`<img src="${base64Df}"/>`
+
                     } else {
                         // 图片
                         let [subfolder, name] = data.inputs.image.split('/');
@@ -1191,7 +1255,10 @@
                         }
                         // imageElement.src = base64Df
                         let url = `${get_url()}/view?filename=${encodeURIComponent(name)}&type=input&subfolder=${subfolder}&rand=${Math.random()}`
-                        imageElement.src = url;
+                        // 如果有默认图                        
+                        imageElement.src = data.options?.defaultImage || url;
+                        imageElement.setAttribute('onerror', `this.src='${base64Df}'`)
+
                     }
 
                     imageElement.style.maxWidth = '200px';
@@ -1254,6 +1321,7 @@
                     container.appendChild(uploadContainer);
                 }
 
+                // 滑块输入
                 if (["PromptSlide"].includes(data.class_type)) {
                     // 滑块输入
                     let options = data.options || {
@@ -1283,6 +1351,7 @@
                 }
 
 
+                // 数字输入支持
                 if (['FloatSlider', 'IntNumber'].includes(data.class_type)) {
                     // console.log('data.options',data.options)
                     // 滑块输入
@@ -1305,8 +1374,8 @@
                     container.appendChild(silde);
                 }
 
-                // Check if the class_type is "CLIPTextEncode"
-                if (["TextInput_", "CLIPTextEncode", "PromptSimplification"].includes(data.class_type)) {
+                // 文本输入支持
+                if (["TextInput_", "CLIPTextEncode", "PromptSimplification", "ChinesePrompt_Mix"].includes(data.class_type)) {
                     // Create a container for the upload control
                     const uploadContainer = document.createElement("div");
                     uploadContainer.className = 'card';
@@ -1371,10 +1440,36 @@
                     container.appendChild(uploadContainer);
                 }
 
-
+                // lora的输入支持
                 if (["CheckpointLoaderSimple", "LoraLoader"].includes(data.class_type)) {
                     let value = data.inputs.ckpt_name || data.inputs.lora_name;
 
+
+                    try {
+                        let t = '';
+                        if (data.class_type == 'CheckpointLoaderSimple') {
+                            t = 'checkpoints'
+                        } else if (data.class_type == 'LoraLoader') {
+                            t = 'loras'
+                        }
+                        if (t) {
+                            const response = await fetch(`${get_url()}/mixlab/folder_paths`, {
+                                method: 'POST',
+                                headers: {
+                                    'Content-Type': 'application/json'
+                                },
+                                body: JSON.stringify({ type: t })
+                            });
+                            const data = await response.json();
+                            data.options = data.names;
+                            console.log(data.names);
+                        }
+
+                    } catch (error) {
+                        console.error(error);
+                    }
+
+
                     try {
                         let v = localStorage.getItem(`_model_${data.id}_${data.class_type}`)
                         if (v) {
@@ -1415,6 +1510,7 @@
                     container.appendChild(div);
                 }
 
+                // 色彩选择器
                 if (["Color"].includes(data.class_type)) {
                     let value = data.inputs.color.hex || '#000000';
                     let d = document.createElement('div');
@@ -1695,11 +1791,25 @@
 
         function createUI(data, share = true) {
             // appData.input, appData.output, appData.seed, share, appData.link
-            const { input: inputData, output: outputData, data: workflow, seed, link } = data;
+            const { input: inputData, output: outputData, data: workflow, seed, link, name } = data;
 
             let mainDiv = document.createElement('div');
+
+            if (document.body.querySelector('#app_container')) document.body.querySelector('#app_container').remove()
+            let appDetails = document.createElement('details');
+            appDetails.id = "app_container"
+            appDetails.setAttribute('open', true)
+            appDetails.innerHTML = `<summary>${name}</summary>`;
+            appDetails.style = `background: whitesmoke;
+            color: black;
+            padding: 12px;
+            cursor: pointer;
+            margin: 8px 44px;`
+
+
             let leftDetails = document.createElement('details');
             leftDetails.setAttribute('open', 'true')
+            leftDetails.id = 'app_input_pannel'
             leftDetails.innerHTML = `<summary>INPUT</summary>
                 <div class="content"></div>`
 
@@ -1845,7 +1955,13 @@
             mainDiv.appendChild(leftDetails);
             mainDiv.appendChild(rightDiv);
 
-            document.body.appendChild(mainDiv)
+            appDetails.appendChild(mainDiv);
+            document.body.appendChild(appDetails)
+
+            appDetails.addEventListener('toggle', e => {
+                e.preventDefault();
+                document.body.querySelector('#author').style.display = appDetails.open ? 'flex' : 'none'
+            })
 
             // 返回每个UI元素的引用和对应的更新方法
             return {
@@ -2058,6 +2174,71 @@
             return div
         }
 
+        function executed(detail, show) {
+            console.log('#executed', window.prompt_ids, detail)
+            if (detail?.node
+                && window.prompt_ids[detail.prompt_id]
+                && window._appData?.output.filter(f => f.id === detail.node)[0]) {
+                // 保存结果到记录里
+                window.prompt_ids[detail.prompt_id].data = detail
+                window.prompt_ids[detail.prompt_id].createTime = (new Date()).getTime()
+                savePromptResult({
+                    ...window.prompt_ids[detail.prompt_id],
+                    prompt_id: detail.prompt_id
+                })
+            }
+            // if (!enabled) return;
+            const images = detail?.output?.images;
+            const text = detail?.output?.text;
+            const gifs = detail?.output?.gifs;
+
+            const prompt = detail?.output?.prompt;
+            const analysis = detail?.output?.analysis;
+
+            const _images = detail?.output?._images;
+            const prompts = detail?.output?.prompts;
+
+            if (images) {
+                // if (!images) return;
+
+                let url = get_url();
+
+                show(Array.from(images, img => {
+                    return `${url}/view?filename=${encodeURIComponent(img.filename)}&type=${img.type}&subfolder=${encodeURIComponent(img.subfolder)}&t=${+new Date()}`;
+                }), detail.node, 'images');
+
+            } else if (_images && prompts) {
+                let url = get_url();
+
+                let items = [];
+                // 支持图片的batch
+                Array.from(_images, (imgs, i) => {
+
+                    for (const img of imgs) {
+                        items.push([`${url}/view?filename=${encodeURIComponent(img.filename)
+                            }&type=${img.type}&subfolder=${encodeURIComponent(img.subfolder)
+                            }&t=${+new Date()}`, prompts[i]])
+                    }
+
+                })
+
+                show(items, detail.node, 'images_prompts');
+
+            } else if (text) {
+                show(Array.isArray(text) ? text.join('\n\n') : text, detail.node, 'text')
+            } else if (gifs && gifs[0]) {
+                // if (!images) return; 
+                const src = `${get_url()}/view?filename=${encodeURIComponent(gifs[0].filename)}&type=${gifs[0].type}&subfolder=${encodeURIComponent(gifs[0].subfolder)
+                    }&&format=${gifs[0].format}&t=${+new Date()}`;
+
+                show(src, detail.node, gifs[0].format.match('video') ? 'video' : 'image');
+            } else if (prompt && analysis) {
+                // #ClipInterrogator: …… 
+                show(`${prompt.join('\n\n')}\n${JSON.stringify(analysis, null, 2)}`, detail.node, 'text')
+            }
+        }
+
+
 
         async function createApp(appData, share = true) {
             // console.log(appData)
@@ -2079,7 +2260,13 @@
             ui.submitButton.update(
                 () => {
                     // 在提交按钮点击时执行的逻辑
-                    queuePrompt(window._appData.data, window._appData.seed, api.clientId);
+                    queuePrompt({
+                        name: window._appData.name,
+                        id: window._appData.id,
+                        icon: window._appData.icon,
+                        category: window._appData.category,
+                        filename: window._appData.filename
+                    }, window._appData.data, window._appData.seed, api.clientId);
                 }, () => {
                     // 取消
                     if (api.runningCancel) {
@@ -2095,11 +2282,14 @@
                 // console.log(src)
                 ui.output.update(type, src, id)
             };
+            // 暴露给history使用
+            window._show = show;
 
             api.addEventListener("status", ({ detail }) => {
-                console.log("status", detail, detail.exec_info?.queue_remaining);
+                console.log("status", detail, detail?.exec_info?.queue_remaining);
                 try {
                     ui.status.update(`queue#${detail.exec_info?.queue_remaining}`);
+                    window.parent.postMessage({ cmd: 'status', data: `queue#${detail.exec_info?.queue_remaining}` }, '*');
                     if (detail.exec_info?.queue_remaining === 0) {
                         // 运行按钮重设
                         ui.submitButton.reset()
@@ -2107,6 +2297,7 @@
                     }
                 } catch (error) {
                     console.log(error)
+                    window.parent.postMessage({ cmd: 'status' }, '*');
                 }
 
             });
@@ -2124,57 +2315,7 @@
 
             api.addEventListener("executed", async ({ detail }) => {
                 console.log("executed", detail)
-                // if (!enabled) return;
-                const images = detail?.output?.images;
-                const text = detail?.output?.text;
-                const gifs = detail?.output?.gifs;
-
-                const prompt = detail?.output?.prompt;
-                const analysis = detail?.output?.analysis;
-
-                const _images = detail?.output?._images;
-                const prompts = detail?.output?.prompts;
-
-                if (images) {
-                    // if (!images) return;
-
-                    let url = get_url();
-
-                    show(Array.from(images, img => {
-                        return `${url}/view?filename=${encodeURIComponent(img.filename)}&type=${img.type}&subfolder=${encodeURIComponent(img.subfolder)}&t=${+new Date()}`;
-                    }), detail.node, 'images');
-
-                } else if (_images && prompts) {
-                    let url = get_url();
-
-                    let items = [];
-                    // 支持图片的batch
-                    Array.from(_images, (imgs, i) => {
-
-                        for (const img of imgs) {
-                            items.push([`${url}/view?filename=${encodeURIComponent(img.filename)
-                                }&type=${img.type}&subfolder=${encodeURIComponent(img.subfolder)
-                                }&t=${+new Date()}`, prompts[i]])
-                        }
-
-                    })
-
-                    show(items, detail.node, 'images_prompts');
-
-                } else if (text) {
-                    ui.output.update("text", Array.isArray(text) ? text.join('\n\n') : text, detail.node)
-                } else if (gifs && gifs[0]) {
-                    // if (!images) return; 
-                    const src = `${get_url()}/view?filename=${encodeURIComponent(gifs[0].filename)}&type=${gifs[0].type}&subfolder=${encodeURIComponent(gifs[0].subfolder)
-                        }&&format=${gifs[0].format}&t=${+new Date()}`;
-
-                    show(src, detail.node, gifs[0].format.match('video') ? 'video' : 'image');
-                } else if (prompt && analysis) {
-                    // #ClipInterrogator: …… 
-                    ui.output.update("text", `${prompt.join('\n\n')}\n${JSON.stringify(analysis, null, 2)}`, detail.node)
-                }
-
-
+                executed(detail, show);
 
                 try {
                     ui.status.update(`executed_#${window._appData.data[detail.node]?.class_type}`);
@@ -2206,6 +2347,7 @@
             api.addEventListener("execution_error", ({ detail }) => {
 
                 console.log("execution_error", detail)
+                window.parent.postMessage({ cmd: 'status', data: `execution_error:${JSON.stringify(detail)}` }, '*');
                 // show(URL.createObjectURL(detail));
             });
 
@@ -2235,7 +2377,6 @@
             api.init();
 
             // 外挂的UI
-
             createAllColorInput();
 
 
@@ -2283,14 +2424,26 @@
             //     return true;
             // });
 
+            // author信息
+            if (appData.author) {
+                let div = document.body.querySelector('#author');
+                if (appData.author.link) div.href = appData.author.link
+                div.style = `z-index:20;display: flex;flex-direction: column;position: fixed;bottom: 12px;right: 24px;cursor: pointer;text-decoration: none;color: black;`
+                div.innerHTML = `<p style="font-size:12px">Author:</p>
+                <div style="display: flex;"> <img style="width:32px;height:32px;border-radius: 100%;" 
+                src="${appData.author.avatar || base64Df}"/>
+                <p style="margin-left:8px;font-size:12px;font-weight:800">${appData.author.name || '-'}</p></div>`
+            }
+
         }
 
         // 创建app的选择菜单
-        function createAppList(apps = []) {
+        function createAppList(apps = [], innerApp = false) {
+            window.prompt_ids = {};
             let details = document.createElement('details');
             details.className = 'apps';
 
-            details.innerHTML = `<summary>ComfyUI APP Store / ${apps.length}</summary>
+            details.innerHTML = `<summary>APP Store / ${apps.length}</summary>
                 <div class="content"> </div>`
 
             let div = details.querySelector('div');
@@ -2311,52 +2464,273 @@
                                 <p>${app.description}</p>
                             </div>
                             <div >
-                                <p class="version">version: ${app.version}</p>
-                                
+                                <p class="version">Version: ${app.version}</p> 
                             </div>
+                            <br>
+                            ${app.author && app.author.name ? `<p class="version">Author:</p><div 
+                            style="display: flex;justify-content: center;align-items: center;margin-top: 8px;"> 
+                                <img style="width:28px;height:28px;border-radius: 100%;" 
+                                src="${app.author.avatar || base64Df}"/>
+                                <p class="version" style="margin-left: 12px;">${app.author.name}</p> 
+                            </div>`: ''}
                         </div>
                       `
 
+
                 div.appendChild(d);
                 dd.addEventListener('click', async e => {
                     e.preventDefault();
                     Array.from(div.querySelectorAll('.card'), c => c.classList.remove('selected'));
                     dd.className = 'card selected'
-                    // console.log(app.filename)
 
-                    window._appData = (await get_my_app(app.category, app.filename))[0];
-                    if (document.body.querySelector('.app')) document.body.querySelector('.app').remove()
-                    createApp(window._appData);
+                    details.removeAttribute('open');
+                    let res = (await get_my_app(app.category, app.filename)).filter(n => n.filename === app.filename)[0];
+
+                    if (res) {
+                        window._appData = res;
+                        if (document.body.querySelector('.app')) document.body.querySelector('.app').remove()
+                        createApp(window._appData);
+                        localStorage.setItem('app_selected', window._appData.id)
+                    }
 
                 })
                 // console.log(div)
             };
 
-            let uploadApp = createUploadJson(details);
-            div.appendChild(uploadApp);
+            if (!innerApp) {
+                let uploadApp = createUploadJson(details);
+                div.appendChild(uploadApp);
+            }
+
+            document.body.appendChild(details);
+            details.addEventListener('toggle', e => {
+                e.preventDefault();
+                if (document.body.querySelector('#app_container')) {
+                    document.body.querySelector('#app_container').removeAttribute('open');
+                    document.body.querySelector('#author').style.display = 'none'
+                }
+            })
+        }
+
+        // 请求历史数据
+        async function getPromptResult(category) {
+            let url = get_url()
+            try {
+                const response = await fetch(`${url}/mixlab/prompt_result`, {
+                    method: "POST",
+                    headers: {
+                        "Content-Type": "application/json",
+                    },
+                    body: JSON.stringify({
+                        action: "all",
+                    }),
+                });
+
+                if (response.ok) {
+                    const data = await response.json();
+                    console.log("#getPromptResult:", category, data);
+
+                    return data.result.filter(r => r.appInfo.category == category)
+                    // 处理返回的数据
+                } else {
+                    console.log("Error:", response.status);
+                    // 处理错误情况
+                }
+            } catch (error) {
+                console.log("Error:", error);
+                // 处理异常情况
+            }
+        }
+        // 保存历史数据
+        async function savePromptResult(data) {
+            let url = get_url()
+            try {
+                const response = await fetch(`${url}/mixlab/prompt_result`, {
+                    method: "POST",
+                    headers: {
+                        "Content-Type": "application/json",
+                    },
+                    body: JSON.stringify({
+                        action: "save",
+                        data
+                    }),
+                });
+
+                if (response.ok) {
+                    const res = await response.json();
+                    console.log("Response:", res);
+                    return res
+                    // 处理返回的数据
+                } else {
+                    console.log("Error:", response.status);
+                    // 处理错误情况
+                }
+            } catch (error) {
+                console.log("Error:", error);
+                // 处理异常情况
+            }
+        }
+
+
+
+        async function createHistoryList(category) {
+            if (document.body.querySelector('#history_container')) document.body.querySelector('#history_container').remove();
+
+            window._historyData = await getPromptResult(category);
+
+            if (!window._historyData || (window._historyData && window._historyData.length === 0)) return
+
+            let details = document.createElement('details');
+            details.id = "history_container"
+            details.innerHTML = `<summary>历史</summary>`;
+            details.style = `background: whitesmoke;
+            color: black;
+            padding: 12px;
+            cursor: pointer;
+            margin: 8px 44px;`;
+
+            details.addEventListener('toggle', function (event) {
+                if (details.open) {
+                    // console.log('details被展开了');
+                    // 在这里执行展开后的回调操作
+                    if (document.body.querySelector('#app_container')) {
+                        document.body.querySelector('#app_container').removeAttribute('open')
+                    }
+                    if (document.body.querySelector('.apps')) {
+                        document.body.querySelector('.apps').removeAttribute('open')
+                    }
+                } else {
+                    // console.log('details被收起了');
+                    // 在这里执行收起后的回调操作
+                    if (document.body.querySelector('#app_container')) {
+                        document.body.querySelector('#app_container').removeAttribute('open')
+                    }
+                    if (document.body.querySelector('.apps')) {
+                        document.body.querySelector('.apps').removeAttribute('open')
+                    }
+                }
+            });
+
+
+            let cards = document.createElement('div');
+            cards.style = `display: flex;flex-wrap: wrap;`
+
+            const addCard = (title, createTime, imgurl) => {
+                let card = document.createElement('div')
+                card.className = 'card';
+                card.innerHTML = `<div class="item icon">
+                            <img src="${imgurl || base64Df}"/>
+                            </div>
+                        <div class="item" style="margin-left: 24px;">
+                            <div>
+                                <h5>${title}</h5>
+                                <p></p>
+                            </div>
+                            <div>
+                                <p class="version">${new Date(createTime || (new Date()))}</p>
+                                
+                            </div>
+                        </div>`
+                return card
+            }
+
+            for (const c of window._historyData) {
+                let card = addCard(c.appInfo.name, c.createTime, c.appInfo.icon)
+                cards.appendChild(card)
+                card.addEventListener('click', async e => {
+                    e.preventDefault();
+                    // console.log(c)
+                    try {
+                        document.body.querySelector('#app_container').setAttribute('open', true)
+                        document.body.querySelector('#app_input_pannel').removeAttribute('open')
+                        document.body.querySelector('.apps').removeAttribute('open')
+                    } catch (error) {
+
+                    }
+
+                    const { category, filename } = c.appInfo;
+                    window._appData = (await get_my_app(category, filename))[0];
+
+                    createApp(window._appData);
+
+                    executed(c.data, window._show);
+                })
+            }
+
+            details.appendChild(cards);
 
             document.body.appendChild(details);
         }
 
         async function init_app() {
 
-            const { category, filename } = getFilenameAndCategoryFromUrl(location.href);
-            window._apps = await get_my_app(category, filename);
+            const innerApp = checkIsInnerApp();
 
-            window._appData = window._apps[0];
+            if (!innerApp) {
+                const { category, filename } = getFilenameAndCategoryFromUrl(location.href);
+                window._apps = await get_my_app(category, filename);
 
-            createAppList(window._apps);
+                window._appData = window._apps[0];
 
-            createApp(window._appData);
+                createAppList(window._apps);
+
+                if (window._apps.length > 0) await createHistoryList(category || '');
+
+                createApp(window._appData);
+            }
 
         };
 
         init_app();
 
+        // 支持内嵌app
+        function checkIsInnerApp() {
+            const url = new URL(window.location.href);
+            const params = new URLSearchParams(url.search);
+            const innerApp = params.get("innerApp");
+            // console.log(window.location.href, innerApp == 1, document.body);
+            if (innerApp == 1) {
+                document.body.querySelector('.header').style.display = 'none';
+                window.parent.postMessage({ innerApp, cmd: 'init' }, '*');
+
+                // 在iframe中监听来自父窗口的消息
+                window.addEventListener("message", async function (event) {
+                    console.log("Received message from parent:", event.data);
+                    const { init, url } = event.data;
+
+                    window._hostUrl = url;
+
+                    window._apps = init;
+
+                    window._appData = window._apps[0];
+
+                    if (window._appData) {
+                        createAppList(window._apps, innerApp);
+
+                        // await createHistoryList();
+
+                        createApp(window._appData);
+                    } else {
+                        // todo welcome页面
+                        document.body.innerHTML = `<h3 style="padding: 99px;">Welcome to Mixlab Nodes App!</h3>`
+                    }
+
+
+
+                });
+
+
+            }
+
+            return innerApp == 1
+
+        }
 
 
     </script>
 
+    <!-- <script src="/extensions/comfyui-mixlab-nodes/lib/login.js"></script> -->
+
 </body>
 
 </html>

web/javascript/app_mixlab.js

@@ -2,6 +2,9 @@ import { app } from '../../../scripts/app.js'
 import { $el } from '../../../scripts/ui.js'
 import { api } from '../../../scripts/api.js'
 
+const base64Df =
+  'data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAwAAAAMCAYAAABWdVznAAAAAXNSR0IArs4c6QAAALZJREFUKFOFkLERwjAQBPdbgBkInECGaMLUQDsE0AkRVRAYWqAByxldPPOWHwnw4OBGye1p50UDSoA+W2ABLPN7i+C5dyC6R/uiAUXRQCs0bXoNIu4QPQzAxDKxHoALOrZcqtiyR/T6CXw7+3IGHhkYcy6BOR2izwT8LptG8rbMiCRAUb+CQ6WzQVb0SNOi5Z2/nX35DRyb/ENazhpWKoGwrpD6nICp5c2qogc4of+c7QcrhgF4Aa/aoAFHiL+RAAAAAElFTkSuQmCC'
+
 function get_position_style (ctx, widget_width, y, node_height) {
   const MARGIN = 12 // the margin around the html element
 
@@ -28,20 +31,20 @@ function get_position_style (ctx, widget_width, y, node_height) {
     // height: `${node_height * 0.3 - MARGIN * 2}px`,
     // background: '#EEEEEE',
     display: 'flex',
-    flexDirection: 'row',
+    flexDirection: 'column',
     // alignItems: 'center',
     justifyContent: 'flex-start'
   }
 }
 
-async function drawImageToCanvas (imageUrl) {
+async function drawImageToCanvas (imageUrl, sFactor = 320) {
   var canvas = document.createElement('canvas')
   var ctx = canvas.getContext('2d')
   var img = new Image()
 
   await new Promise((resolve, reject) => {
     img.onload = function () {
-      var scaleFactor = 320 / img.width
+      var scaleFactor = sFactor / img.width
       var canvasWidth = img.width * scaleFactor
       var canvasHeight = img.height * scaleFactor
 
@@ -66,7 +69,11 @@ async function drawImageToCanvas (imageUrl) {
   // 可以在这里执行其他操作，比如将Base64数据保存到服务器或显示在页面上
 }
 
-function extractInputAndOutputData (jsonData, inputIds = [], outputIds = []) {
+async function extractInputAndOutputData (
+  jsonData,
+  inputIds = [],
+  outputIds = []
+) {
   // workflow
   // const workflow=jsonData.workflow;
   // const nodes=workflow.nodes;
@@ -117,13 +124,18 @@ function extractInputAndOutputData (jsonData, inputIds = [], outputIds = []) {
         if (node.type == 'Color') {
         }
 
-        // loadImage的mask支持
         if (node.type === 'LoadImage') {
+          // loadImage的mask支持
           let output = node.outputs.filter(ot => ot.type == 'MASK')[0]
           if (output.links) {
             // 有输出
             options.hasMask = true
           }
+          // loadImage的默认图，转为base64
+          let imgurl = app.graph.getNodeById(id).imgs[0].src
+          
+          options.defaultImage = await drawImageToCanvas(imgurl, 512)
+          console.log('#loadImage的默认图',options)
         }
 
         input[inputIds.indexOf(id)] = {
@@ -228,12 +240,19 @@ async function save (json, download = false, showInfo = true) {
   try {
     let data = await app.graphToPrompt()
 
-    let { input, output, seed } = extractInputAndOutputData(
+    let { input, output, seed } = await extractInputAndOutputData(
       data,
       inputIds,
       outputIds
     )
 
+    let authorAvatar =
+        localStorage.getItem('_mixlab_author_avatar') || base64Df,
+      authorName =
+        localStorage.getItem('_mixlab_author_name') ||
+        localStorage.getItem('Comfy.userName'),
+      authorLink = localStorage.getItem('_mixlab_author_link') || ''
+
     data.app = {
       name,
       description,
@@ -244,7 +263,12 @@ async function save (json, download = false, showInfo = true) {
       share_prefix,
       link,
       category,
-      filename: `${name}_${version}.json`
+      filename: `${name}_${version}.json`,
+      author: {
+        avatar: authorAvatar,
+        name: authorName,
+        link: authorLink
+      }
     }
 
     try {
@@ -377,10 +401,164 @@ app.registerExtension({
           }
         })
 
-        document.body.appendChild(widget.div)
-        widget.div.appendChild(btn)
-        widget.div.appendChild(download)
+        // author
+        let author = document.createElement('div')
+        // author.style=`display: flex`
 
+        let authorAvatar = document.createElement('img')
+        authorAvatar.className = `${'comfy-multiline-input'}`
+        authorAvatar.style = `outline: none;
+          border: none;
+          padding: 4px;
+          width: 32px;
+          cursor: pointer;
+          height: 32px;`
+
+        if (localStorage.getItem('_mixlab_author_avatar')) {
+          authorAvatar.src =
+            localStorage.getItem('_mixlab_author_avatar') || base64Df
+        }
+
+        let authorAvatarUpload = document.createElement('input')
+        authorAvatarUpload.type = 'file'
+        authorAvatarUpload.style = `display:none`
+
+        let authorAvatarInput = document.createElement('div')
+        authorAvatarInput.style = `display: flex;justify-content: flex-start;
+        align-items: center;`
+        let authorAvatarInputLabel = document.createElement('p')
+        authorAvatarInputLabel.innerText = 'Author Avatar'
+        authorAvatarInputLabel.className = `${'comfy-multiline-input'}`
+        authorAvatarInputLabel.style = `font-size:12px`
+
+        authorAvatar.addEventListener('click', e => {
+          authorAvatarUpload.click()
+        })
+
+        authorAvatarInputLabel.addEventListener('click', e => {
+          authorAvatarUpload.click()
+        })
+
+        authorAvatarUpload.addEventListener('change', event => {
+          const file = event.target.files[0]
+          const reader = new FileReader()
+
+          reader.onload = async e => {
+            let im = new Image()
+            im.src = e.target.result
+            authorAvatar.src = e.target.result
+            im.onload = () => {
+              let c = document.createElement('canvas')
+              let ctx = c.getContext('2d')
+              c.width = 72
+              c.height = 72
+              ctx.drawImage(
+                im,
+                0,
+                0,
+                im.naturalWidth,
+                im.naturalHeight,
+                0,
+                0,
+                c.width,
+                c.height
+              )
+              window._mixlab_author_avatar = c.toDataURL()
+              localStorage.setItem(
+                '_mixlab_author_avatar',
+                window._mixlab_author_avatar
+              )
+            }
+          }
+
+          // 以文本形式读取文件
+          reader.readAsDataURL(file)
+        })
+
+        author.appendChild(authorAvatarInput)
+        authorAvatarInput.appendChild(authorAvatarInputLabel)
+        authorAvatarInput.appendChild(authorAvatar)
+        authorAvatarInput.appendChild(authorAvatarUpload)
+
+        let authorName = document.createElement('input')
+        authorName.type = 'text'
+        authorName.value =
+          localStorage.getItem('_mixlab_author_name') ||
+          localStorage.getItem('Comfy.userName')
+        authorName.placeholder = 'author name'
+        authorName.className = `${'comfy-multiline-input'}`
+        authorName.style = `
+          outline: none;
+          border: none;
+          padding: 4px;
+          width: 100%;
+          cursor: pointer;
+          height: 32px;`
+
+        let authorNameInput = document.createElement('div')
+        authorNameInput.style = `display: flex;justify-content: flex-start;
+          align-items: center;`
+        let authorNameInputLabel = document.createElement('p')
+        authorNameInputLabel.innerText = 'Author Name'
+        authorNameInputLabel.className = `${'comfy-multiline-input'}`
+        authorNameInputLabel.style = `font-size:12px;width: 110px`
+
+        authorName.addEventListener('change', e => {
+          window._mixlab_author_name = authorName.value.trim()
+          localStorage.setItem(
+            '_mixlab_author_name',
+            window._mixlab_author_name
+          )
+        })
+
+        author.appendChild(authorNameInput)
+        authorNameInput.appendChild(authorNameInputLabel)
+        authorNameInput.appendChild(authorName)
+
+        // 社交链接
+        let authorLink = document.createElement('input')
+        authorLink.type = 'text'
+        authorLink.value = localStorage.getItem('_mixlab_author_link') || ''
+        authorLink.placeholder = 'author link'
+        authorLink.className = `${'comfy-multiline-input'}`
+        authorLink.style = `
+          outline: none;
+          border: none;
+          padding: 4px;
+          width: 100%;
+          cursor: pointer;
+          height: 32px;`
+
+        let authorLinkInput = document.createElement('div')
+        authorLinkInput.style = `display: flex;justify-content: flex-start;
+          align-items: center;`
+        let authorLinkInputLabel = document.createElement('p')
+        authorLinkInputLabel.innerText = 'Author Link'
+        authorLinkInputLabel.className = `${'comfy-multiline-input'}`
+        authorLinkInputLabel.style = `font-size:12px;width: 110px`
+
+        authorLink.addEventListener('change', e => {
+          window._mixlab_author_link = authorLink.value.trim()
+          localStorage.setItem(
+            '_mixlab_author_link',
+            window._mixlab_author_link
+          )
+        })
+
+        author.appendChild(authorLinkInput)
+        authorLinkInput.appendChild(authorLinkInputLabel)
+        authorLinkInput.appendChild(authorLink)
+
+        widget.div.appendChild(author)
+
+        let btns = document.createElement('div')
+
+        widget.div.appendChild(btns)
+
+        btns.appendChild(btn)
+        btns.appendChild(download)
+
+        document.body.appendChild(widget.div)
         this.addCustomWidget(widget)
 
         const onRemoved = this.onRemoved

web/javascript/checkVersion_mixlab.js

@@ -3,7 +3,7 @@ import { app } from '../../../scripts/app.js'
 const repoOwner = 'shadowcz007' // 替换为仓库的所有者
 const repoName = 'comfyui-mixlab-nodes' // 替换为仓库的名称
 
-const version = 'v0.17.0'
+const version = 'v0.18.0'
 
 fetch(`https://api.github.com/repos/${repoOwner}/${repoName}/releases/latest`)
   .then(response => response.json())

web/javascript/prompt_mixlab.js

@@ -408,7 +408,7 @@ const _createResult = async (node, widget, message) => {
   const width = node.size[0] * 0.5 - 12
 
   let height_add = 0
-
+  
   for (let index = 0; index < message._images.length; index++) {
     const imgs = message._images[index]
 
@@ -559,8 +559,7 @@ app.registerExtension({
 
       let cards = widget.div.querySelectorAll('.card')
       if (cards.length == 0) node.size = [280, 120]
-
-      _createResult(node, widget, widget.value)
+      if(widget.value) _createResult(node, widget, widget.value)
     }
   }
 })

web/javascript/ui_mixlab.js

@@ -282,18 +282,22 @@ function get_url () {
 
 async function get_my_app (filename = null, category = '') {
   let url = get_url()
-  const res = await fetch(`${url}/mixlab/workflow`, {
-    method: 'POST',
-    body: JSON.stringify({
-      task: 'my_app',
-      filename,
-      category,
-      admin: true
-    })
-  })
-  let result = await res.json()
-  let data = []
+  let data = null
+
   try {
+    const res = await fetch(`${url}/mixlab/workflow`, {
+      method: 'POST',
+      body: JSON.stringify({
+        task: 'my_app',
+        filename,
+        category,
+        admin: true
+      })
+    })
+    let result = await res.json()
+
+    data = []
+
     for (const res of result.data) {
       let { app, workflow } = res.data
       if (app.filename)
@@ -1126,6 +1130,7 @@ app.registerExtension({
       const orig = LGraphCanvas.prototype.getCanvasMenuOptions
 
       const apps = await get_my_app()
+      if (!apps) return
 
       let apps_map = { 0: [] }
 
@@ -1150,8 +1155,30 @@ app.registerExtension({
                 has_submenu: false,
                 callback: async () => {
                   try {
-                    let item = (await get_my_app(a.filename))[0]
+                    let ddd = await get_my_app(a.filename)
+                    if (!ddd) return
+                    let item = ddd[0]
                     if (item) {
+                      if (item.author) {
+                        // 有作者信息
+                        if (item.author.avatar)
+                          localStorage.setItem(
+                            '_mixlab_author_avatar',
+                            item.author.avatar
+                          )
+                        if (item.author.name)
+                          localStorage.setItem(
+                            '_mixlab_author_name',
+                            item.author.name
+                          )
+
+                        if (item.author.link)
+                          localStorage.setItem(
+                            '_mixlab_author_link',
+                            item.author.link
+                          )
+                      }
+
                       // console.log(item.data)
                       app.loadGraphData(item.data)
                       setTimeout(() => {
@@ -1179,8 +1206,31 @@ app.registerExtension({
                   content: `${a.name}_${a.version}`,
                   callback: async () => {
                     try {
-                      let item = (await get_my_app(a.filename, a.category))[0]
+                      let ddd = await get_my_app(a.filename, a.category)
+
+                      if (!ddd) return
+                      let item = ddd[0]
                       if (item) {
+                        console.log(item)
+                        if (item.author) {
+                          // 有作者信息
+                          if (item.author.avatar)
+                            localStorage.setItem(
+                              '_mixlab_author_avatar',
+                              item.author.avatar
+                            )
+                          if (item.author.name)
+                            localStorage.setItem(
+                              '_mixlab_author_name',
+                              item.author.name
+                            )
+                          if (item.author.link)
+                            localStorage.setItem(
+                              '_mixlab_author_link',
+                              item.author.link
+                            )
+                        }
+
                         // console.log(item.data)
                         app.loadGraphData(item.data)
                         setTimeout(() => {
@@ -1478,31 +1528,35 @@ app.registerExtension({
 
           widget.element.addEventListener('mouseover', e => {
             // console.log(node.widgets_values[index])
-            if (node.widgets_values[index])
+            if (node.widgets_values && node.widgets_values[index])
               widget.element.setAttribute('title', node.widgets_values[index])
           })
         }
       }
     }
 
-    // 右上角的badge是否已经绘制
-    if (!node.badge_enabled) {
-      if (!node.getNickname) {
-        node.getNickname = function () {
-          if (node.nickname) {
-            return node.nickname
+    fetch('manager/badge_mode').then(r => {
+      if (r.status === 404) {
+        // 右上角的badge是否已经绘制
+        if (!node.badge_enabled) {
+          if (!node.getNickname) {
+            node.getNickname = function () {
+              if (node.nickname) {
+                return node.nickname
+              }
+              return
+              // return getNickname(node, node.comfyClass.trim())
+            }
           }
-          return
-          // return getNickname(node, node.comfyClass.trim())
+
+          const orig = node.__proto__.onDrawForeground
+          node.onDrawForeground = function (ctx) {
+            drawBadge(node, orig, arguments)
+          }
+          node.badge_enabled = true
         }
       }
-
-      const orig = node.__proto__.onDrawForeground
-      node.onDrawForeground = function (ctx) {
-        drawBadge(node, orig, arguments)
-      }
-      node.badge_enabled = true
-    }
+    })
   },
   async loadedGraphNode (node, app) {
     // console.log(

web/lib/login.css

@@ -0,0 +1,277 @@
+* {
+    transition: all 0.6s cubic-bezier(0.77, 0, 0.175, 1);
+}
+
+#app-login {
+    width: 480px;
+    height: 90vh;
+    padding: 6vh;
+    background: white;
+    box-shadow: 0 0 2rem rgba(0, 0, 0, 0.1);
+    z-index: 999;
+    position: fixed;
+    top: 5vh;
+    left: calc(50vw - 240px);
+}
+
+.login-app-view {
+    position: absolute;
+    top: 0;
+    left: 0;
+    width: 100%;
+    height: 100%;
+    z-index: 999;
+}
+
+.login-background {
+    background-color: #202020e6;
+    position: fixed;
+    width: 100%;
+    height: 100vh;
+    left: 0;
+    top: 0;
+    z-index: 998;
+}
+
+.app-header {
+    padding: 6vh;
+}
+
+.app-header,
+.app-header>* {
+    font-size: 1.2em;
+    margin: 0;
+    font-weight: 300;
+}
+
+.app-header>h1 {
+    font-size: 4.8vh;
+    font-weight: 400;
+    margin-bottom: 4.8vh;
+}
+
+.app-header>h2 {
+    font-size: 3vh;
+}
+
+.app-subheading {
+    color: rgba(0, 0, 0, 0.45);
+}
+
+.app-register {
+    position: absolute;
+    bottom: 0;
+    height: 10vh;
+    line-height: 10vh;
+    padding: 0 6vh;
+    color: rgba(0, 0, 0, 0.45);
+}
+
+.app-register>a {
+    font-weight: 400;
+}
+
+
+#app-login input {
+    font-size: 2.5vh;
+    width: calc(100% - 13vh);
+    height: 7.5vh;
+    margin-bottom: 2vh;
+    background: transparent;
+    position: absolute;
+    top: 0;
+    left: 6.5vh;
+    z-index: 2;
+    border: none;
+    box-shadow: inset 0 -0.5vh rgba(0, 0, 0, 0.1);
+}
+
+#app-login input:focus {
+    outline: none;
+    box-shadow: inset 0 -0.5vh transparent;
+}
+
+#app-login input[type=email] {
+    top: 58%;
+}
+
+#app-login input[type=password] {
+    top: calc(58% + 7.5vh);
+}
+
+#app-login input[type=email]:valid~* .st1 {
+    transition-timing-function: ease-in-out;
+    stroke-dasharray: 50, 153;
+    stroke-dashoffset: 25;
+}
+
+#app-login input[type=password]:focus~* .st0,
+#app-login input[type=password]:valid~* .st0,
+#login_run:focus~* .st0 {
+    stroke-dasharray: 210, 900;
+    stroke-dashoffset: -305;
+}
+
+#app-login input[type=email]:focus~* .st0 {
+    stroke-dasharray: 210, 900;
+    stroke-dashoffset: 0;
+}
+
+#app-login input:not(:valid)~#login_run {
+    /* pointer-events: none; */
+    opacity: 0.6;
+}
+
+#login_run {
+    text-decoration: none;
+    color: #0f9ede;
+    font-size: 1.5em;
+    padding: 0 6vh;
+    position: absolute;
+    bottom: 10vh;
+    font-weight: 400;
+    z-index: 998;
+    cursor: pointer;
+}
+
+#login_run:focus {
+    outline: none;
+}
+
+.login-app-view:nth-child(2) {
+    display: flex;
+    flex-direction: column;
+    pointer-events: none;
+}
+
+.login-app-view:nth-child(2)>.app-header {
+    font-size: 1rem;
+    flex-basis: 25%;
+    display: flex;
+    flex-direction: column;
+    justify-content: space-between;
+    padding: 4vh;
+    padding-bottom: 1rem;
+}
+
+.login-app-view:nth-child(2)>.app-header>h2 {
+    transform: translateY(1rem);
+}
+
+.login-app-view:nth-child(2)>.app-header>h2>em {
+    color: #0f9ede;
+    font-style: normal;
+}
+
+.login-app-view:nth-child(2)>.app-header>h2,
+.login-app-view:nth-child(2) .app-item>*:not(.app-graphic) {
+    transition-duration: 0.9s;
+    opacity: 0;
+}
+
+
+.st0,
+.st1,
+.svg-loader-segment {
+    fill: none;
+    stroke: #0f9ede;
+    stroke-width: 0.5vh;
+    stroke-alignment: inside;
+    opacity: 1;
+    transition: all 0.6s cubic-bezier(0.77, 0, 0.175, 1);
+}
+
+.svg-loader {
+    opacity: 0;
+}
+
+.st0 {
+    stroke-dasharray: 0, 900;
+    stroke-dashoffset: 0;
+}
+
+.st1 {
+    transition-delay: 0.3s;
+    stroke-dasharray: 50, 153;
+    stroke-dashoffset: -153;
+}
+
+.svg-loader-segment {
+    transition: transform 1.2s cubic-bezier(0.77, 0, 0.175, 1), opacity 0.85s cubic-bezier(0.77, 0, 0.175, 1), stroke 0.85s cubic-bezier(0.77, 0, 0.175, 1);
+}
+
+#svg-lines {
+    position: absolute;
+    top: 45%;
+    left: 0;
+    width: 100%;
+    z-index: 0;
+    overflow: visible;
+    transform-origin: center 4vh;
+}
+
+.svg-data {
+    fill: none;
+    stroke-width: 0.5vh;
+}
+
+.svg-data.-temp {
+    stroke: #f4814b;
+    stroke-dasharray: 20, 118;
+}
+
+.svg-data.-cal {
+    stroke: #08b5cf;
+    stroke-dasharray: 20, 113;
+}
+
+.svg-data.-steps-bg {
+    stroke: #e0e1e0;
+    stroke-dasharray: 40, 100;
+    stroke-dashoffset: -60;
+}
+
+.svg-data.-steps {
+    stroke: #0f9ede;
+    stroke-dasharray: 20, 73;
+    stroke-dashoffset: -53;
+}
+
+.svg-data.-heart {
+    stroke: #9965aa;
+    stroke-dasharray: 50, 200;
+    stroke-dashoffset: -150;
+}
+
+.svg-activity-fill {
+    fill: #c4e4f8;
+}
+
+.svg-activity-line {
+    fill: none;
+    stroke: #65bcea;
+    stroke-miterlimit: 10;
+    stroke-width: 0.25vh;
+}
+
+.svg-activity-avg,
+.svg-activity-indicator {
+    fill: none;
+    stroke: #d0dff0;
+    stroke-width: 0.25vh;
+    mix-blend-mode: multiply;
+}
+
+.svg-activity-fill,
+.svg-activity-line {
+    transform: translateY(10vh);
+    opacity: 0;
+}
+
+
+*,
+*:before,
+*:after {
+    box-sizing: border-box;
+    position: relative;
+}

web/lib/login.js

@@ -0,0 +1,67 @@
+;(() => {
+  let div = document.createElement('div')
+
+  div.innerHTML = ` 
+    <div id="app-login">
+        <div class="login-app-view">
+            <header class="app-header">
+                <h1>Hi</h1>
+                Welcome back,<br />
+                <span class="app-subheading">
+                    sign in to continue<br />
+    
+                </span>
+            </header>
+            <input class="email" type="email" required pattern=".*\.\w{2,}" placeholder="Email Address" />
+            <input class="password" type="password" required placeholder="Password" />
+            <a class="app-button" id="login_run">登录</a>
+            <!-- <div class="app-register">
+                Don't have an account? <a>Sign Up</a>
+            </div> -->
+            <svg id="svg-lines" version="1.1" xmlns="http://www.w3.org/2000/svg"
+                xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px" viewBox="0 0 284.2 152.7"
+                xml:space="preserve">
+                <path class="st0"
+                    d="M37.7,107.3h222.6c12,0,21.8,9.7,21.8,21.7s-9.7,21.8-21.8,21.8c0,0-203.6,0-222.6,0S2.2,138.6,2.2,103.3   c0-52,113.5-101.5,141-101.5c13.5,0,21.8,9.7,21.8,21.8s-9.7,21.7-21.8,21.7s-21.8-9.7-21.8-21.7s9.7-21.8,21.8-21.8" />
+                <path class="st1"
+                    d="M260.2,76.3L250,87.8l-9-9c-6.2-6.2,2-24.7,17.2-24.7c15.2,0,23.9,17.7,23.9,29.7s-11.7,23.5-23.9,23.5h-10.2">
+                </path>
+                <g class="svg-loader" xmlns="http://www.w3.org/2000/svg">
+                    <path class="svg-loader-segment -cal" d="M164.7,23.5c0-12-9.7-21.8-21.8-21.8" />
+                    <path class="svg-loader-segment -heart" d="M143,45.2c12,0,21.8-9.7,21.8-21.7" />
+                    <path class="svg-loader-segment -steps" d="M121.2,23.5c0,12,9.7,21.7,21.8,21.7" />
+                    <path class="svg-loader-segment -temp" d="M143,1.7c-12,0-21.8,9.7-21.8,21.8" />
+                </g>
+            </svg>
+        </div>
+    </div>
+    <div class="login-background"></div>
+     `
+
+  document.body.appendChild(div)
+  let bg = div.querySelector('.login-background')
+  bg.addEventListener('click', e => {
+    div.style.display = 'none'
+  })
+  let login_btn = document.body.querySelector('#login_btn')
+  // login_btn.href="";
+  if (login_btn) {
+    login_btn.innerHTML =
+      '<svg stroke="currentColor" fill="none" stroke-width="0" viewBox="0 0 24 24" height="40px" width="40px" xmlns="http://www.w3.org/2000/svg"><path d="M12 17C14.2091 17 16 15.2091 16 13H8C8 15.2091 9.79086 17 12 17Z" fill="currentColor"></path><path d="M10 10C10 10.5523 9.55228 11 9 11C8.44772 11 8 10.5523 8 10C8 9.44772 8.44772 9 9 9C9.55228 9 10 9.44772 10 10Z" fill="currentColor"></path><path d="M15 11C15.5523 11 16 10.5523 16 10C16 9.44772 15.5523 9 15 9C14.4477 9 14 9.44772 14 10C14 10.5523 14.4477 11 15 11Z" fill="currentColor"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M22 12C22 17.5228 17.5228 22 12 22C6.47715 22 2 17.5228 2 12C2 6.47715 6.47715 2 12 2C17.5228 2 22 6.47715 22 12ZM20 12C20 16.4183 16.4183 20 12 20C7.58172 20 4 16.4183 4 12C4 7.58172 7.58172 4 12 4C16.4183 4 20 7.58172 20 12Z" fill="currentColor"></path></svg>LOGIN'
+    login_btn.addEventListener('click', e => {
+      e.preventDefault()
+      div.style.display = 'block'
+    })
+  }
+
+  let login_run = div.querySelector('#login_run')
+  if (login_run) {
+    login_run.addEventListener('click', e => {
+      e.preventDefault()
+      let ps = div.querySelector('.password')
+      let email = div.querySelector('.email')
+      div.style.display = 'none'
+      console.log(ps.value, email.value)
+    })
+  }
+})()

web/main.css

@@ -1,24 +0,0 @@
-::-webkit-scrollbar {
-  width: 2px;
-}
-
-@keyframes loading_mixlab {
-  0% {
-    background-color: green;
-  }
-
-  50% {
-    background-color: lightgreen;
-  }
-
-  100% {
-    background-color: green;
-  }
-}
-
-.loading_mixlab {
-  background-color: green;
-  animation-name: loading_mixlab;
-  animation-duration: 2s;
-  animation-iteration-count: infinite;
-}

workflow/Prompt-weight-workflow.json

@@ -1,6 +1,6 @@
 {
-  "last_node_id": 23,
-  "last_link_id": 25,
+  "last_node_id": 24,
+  "last_link_id": 26,
   "nodes": [
     {
       "id": 9,
@@ -203,6 +203,7 @@
         "Node name for S&R": "ShowTextForGPT"
       },
       "widgets_values": [
+        "a girl face,super,(Pop Art:1.26),(Black and White:1.26)",
         "a girl face,super,(Pop Art:1.26),(Black and White:1.26)"
       ]
     },
@@ -537,7 +538,7 @@
           "type": "IMAGE",
           "links": [
             24,
-            25
+            26
           ],
           "slot_index": 0
         }
@@ -547,7 +548,7 @@
       }
     },
     {
-      "id": 23,
+      "id": 24,
       "type": "AppInfo",
       "pos": [
         3363.0014990624995,
@@ -562,9 +563,9 @@
       "mode": 0,
       "inputs": [
         {
-          "name": "LOGO",
+          "name": "IMAGE",
           "type": "IMAGE",
-          "link": 25
+          "link": 26
         }
       ],
       "properties": {
@@ -580,7 +581,7 @@
         "https://",
         "",
         "enable",
-        1
+        2
       ]
     }
   ],
@@ -706,10 +707,10 @@
       "IMAGE"
     ],
     [
-      25,
+      26,
       10,
       0,
-      23,
+      24,
       0,
       "IMAGE"
     ]