correct Chinese text to prompt syntax

fix chinese prompt
修复SwitchByIndex的bug
2024-01-14 11:50:14 +08:00 · 2024-01-14 11:34:58 +08:00 · 2024-01-13 20:59:29 +08:00 · 2024-01-13 20:59:07 +08:00 · 2024-01-13 17:12:03 +08:00 · 2024-01-13 16:32:51 +08:00
68 changed files with 21988 additions and 1978 deletions
@@ -1,4 +1,6 @@
 __pycache__/
 https/
 nodes/config.json
-workflow/my_workflow.json
+workflow/my_workflow.json
+workflow/my_workflow_app.json
+app/*
@@ -1,30 +1,44 @@
-## 
-v0.5.0 🚀🚗🚚🏃‍
- Added video composition support to the MergeLayers.
- Enhanced visual selection support for the NewLayer node.
- Introduced the NoiseImage node and ResizeImage node.
- Improved compatibility for TextImage with line breaks.
- Optimized the 3DImage node to export textures for modification.
- [Added DynamicDelayByText, enabling delayed execution based on input text length.](./workflow/audio-chatgpt-workflow.json)
+> 适配了最新版comfyui的py3.11 ，torch 2.1.2+cu121
+
+## 🚀🚗🚚🏃 Workflow-to-APP 
+- 新增AppInfo节点，可以通过简单的配置，把workflow转变为一个Web APP。
+- 支持多个web app 切换
+- 发布为app的workflow，可以在右键里再次编辑了
+- web app可以设置分类，在comfyui右键菜单可以编辑更新web app


- 为MergeLayers添加了视频合成功能。
- NewLayer节点增加了视觉选择支持。
- 添加了NoiseImage节点和ResizeImage节点。
- 支持带有换行的文本图像。
- 对3D节点进行了优化，支持导出纹理以进行修改。
- [添加了DynamicDelayByText功能，可以根据输入文本的长度进行延迟执行。](./workflow/audio-chatgpt-workflow.json)
+- Support multiple web app switching.
+- Add the AppInfo node, which allows you to transform the workflow into a web app by simple configuration.
+- The workflow, which is now released as an app, can also be edited again by right-clicking.
+- The web app can be configured with categories, and the web app can be edited and updated in the right-click menu of ComfyUI.


-### 3D
-![](./assets/3dimage.png)
-[workflow](./workflow/3D-workflow.json)
+![](./assets/0-m-app.png)
+
+![](./assets/appinfo-readme.png)
+
+![](./assets/appinfo-2.png)
+
+Example:
+- workflow
+![APP info](./workflow/appinfo-workflow.svg)
+[text-to-image](./workflow/Text-to-Image-app.json)
+
+APP-JSON:
+- [text-to-image](./example/Text-to-Image_3.json)
+- [image-to-image](./example/Image-to-Image_2.json)
+- text-to-text
+
+> 暂时支持8种节点作为界面上的输入节点：Load Image、CLIPTextEncode、PromptSlide、TextInput_、Color、FloatSlider、IntNumber、CheckpointLoaderSimple、LoraLoader
+
+> 输出节点：PreviewImage 、SaveImage、ShowTextForGPT、VHS_VideoCombine、PromptImage
+
+> seed统一输入控件，支持：SamplerCustom、KSampler


-### ScreenShareNode & FloatingVideoNode
-> Now comfyui supports capturing screen pixel streams from any software and can be used for LCM-Lora integration. Let's get started with implementation and design! 💻🌐
+## 🏃🚗🚚🚀  Real-time Design
+> ScreenShareNode & FloatingVideoNode. Now comfyui supports capturing screen pixel streams from any software and can be used for LCM-Lora integration. Let's get started with implementation and design! 💻🌐

-> 
 ![screenshare](./assets/screenshare.png)

 https://github.com/shadowcz007/comfyui-mixlab-nodes/assets/12645064/e7e77f90-e43e-410a-ab3a-1952b7b4e7da
@@ -35,6 +49,7 @@ https://github.com/shadowcz007/comfyui-mixlab-nodes/assets/12645064/e7e77f90-e43

 !! Please use the address with HTTPS (https://127.0.0.1).

+
 ### SpeechRecognition & SpeechSynthesis
 ![f](./assets/audio-workflow.svg)

@@ -43,17 +58,30 @@ https://github.com/shadowcz007/comfyui-mixlab-nodes/assets/12645064/e7e77f90-e43
 ### 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 

-
 ![gpt-workflow.svg](./assets/gpt-workflow.svg)

 [workflow-5](./workflow/5-gpt-workflow.json)

-### LoadImagesFromLocal
-> Monitor changes to images in a local folder, and trigger real-time execution of workflows, supporting common image formats, especially PSD format, in conjunction with Photoshop. 

-![watch](./assets/4-loadfromlocal-watcher-workflow.svg)
+## Prompt
+> PromptSlide
+![](./assets/prompt_weight.png)

-[workflow-4](./workflow/4-loadfromlocal-watcher-workflow.json)
+<!-- ![](./workflow/promptslide-appinfo-workflow.svg) -->
+
+> randomPrompt
+
+![randomPrompt](./assets/randomPrompt.png)
+
+> ClipInterrogator
+
+[add clip-interrogator](https://github.com/pharmapsychotic/clip-interrogator)
+
+> PromptImage & PromptSimplification,Assist in simplifying prompt words, comparing images and prompt word nodes.
+
+> ChinesePrompt && PromptGenerate，中文prompt节点，直接用中文书写你的prompt
+
+![](./assets/ChinesePrompt_workflow.svg)


 ### Layers
@@ -63,9 +91,29 @@ https://github.com/shadowcz007/comfyui-mixlab-nodes/assets/12645064/e7e77f90-e43

 ![poster](./assets/poster-workflow.svg)

+
+### 3D
+![](./assets/3dimage.png)
+[workflow](./workflow/3D-workflow.json)
+
+
+### LoadImagesFromLocal
+> Monitor changes to images in a local folder, and trigger real-time execution of workflows, supporting common image formats, especially PSD format, in conjunction with Photoshop. 
+
+![watch](./assets/4-loadfromlocal-watcher-workflow.svg)
+
+[workflow-4](./workflow/4-loadfromlocal-watcher-workflow.json)
+
+### LoadImagesFromURL
+> Conveniently load images from a fixed address on the internet to ensure that default images in the workflow can be executed.
+
+
 ## 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.

+- [添加了DynamicDelayByText功能，可以根据输入文本的长度进行延迟执行。](./workflow/audio-chatgpt-workflow.json)
+
+- [Added DynamicDelayByText, enabling delayed execution based on input text length.](./workflow/audio-chatgpt-workflow.json)


 ## Other Nodes
@@ -75,9 +123,7 @@ https://github.com/shadowcz007/comfyui-mixlab-nodes/assets/12645064/e7e77f90-e43

 [workflow-1](./workflow/1-workflow.json)

-> randomPrompt

-![randomPrompt](./assets/randomPrompt.png)

 > TransparentImage

@@ -100,11 +146,15 @@ Add edges to an image.
 ![FeatheredMask](./assets/FlVou_Y6kaGWYoEj1Tn0aTd4AjMI.jpg)


+> LaMaInpainting
+
+from [simple-lama-inpainting](https://github.com/enesmsahin/simple-lama-inpainting)
+

 ### Improvement 

 - Add "help" option to the context menu for each node.
- Add "find the node" option to the global context menu.
+- Add "Nodes Map" option to the global context menu.

 An improvement has been made to directly redirect to GitHub to search for missing nodes when loading the graph.

@@ -114,12 +164,15 @@ An improvement has been made to directly redirect to GitHub to search for missin


 ### Models
-[Download CLIPSeg](https://huggingface.co/CIDAS/clipseg-rd64-refined/tree/main), move to : model/clipseg
+[Download CLIPSeg](https://huggingface.co/CIDAS/clipseg-rd64-refined/tree/main), move to : models/clipseg

-<!-- ### Workflow
-[Workflow](./workflow.md) -->
+[Download lama](https://github.com/enesmsahin/simple-lama-inpainting/releases/download/v0.1.0/big-lama.pt), move to : models/lama

+[Download Salesforce/blip-image-captioning-base](https://huggingface.co/Salesforce/blip-image-captioning-base), move to : models/clip_interrogator/Salesforce/blip-image-captioning-base

+[Download succinctly/text2image-prompt-generator](https://huggingface.co/succinctly/text2image-prompt-generator/tree/main),move to:text_generator/text2image-prompt-generator
+
+[Download Helsinki-NLP/opus-mt-zh-en](https://huggingface.co/Helsinki-NLP/opus-mt-zh-en/tree/main),move to:prompt_generator/opus-mt-zh-en

 ## Installation

@@ -154,16 +207,12 @@ 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


-
 #### Thanks:
 [ComfyUI-CLIPSeg](https://github.com/biegert/ComfyUI-CLIPSeg/tree/main)

 #### discussions:
 [discussions](https://github.com/shadowcz007/comfyui-mixlab-nodes/discussions)

-### TODO:
- 音频播放节点：带可视化、支持多音轨、可配置音轨音量
- vector https://github.com/GeorgLegato/stable-diffusion-webui-vectorstudio


 <picture>
@@ -4,7 +4,7 @@ import subprocess
 import importlib.util
 import sys,json
 import urllib
-
+import hashlib
 import datetime


@@ -79,6 +79,13 @@ install_openai()
 current_path = os.path.abspath(os.path.dirname(__file__))


+
+def calculate_md5(string):
+    encoded_string = string.encode()
+    md5_hash = hashlib.md5(encoded_string).hexdigest()
+    return md5_hash
+
+
 def create_key(key_p,crt_p):
    import OpenSSL
    # 生成自签名证书
@@ -126,8 +133,38 @@ def create_for_https():
    return (crt,key)


+
+# workflow  目录下的所有json
+def read_workflow_json_files_all(folder_path):
+    print('#read_workflow_json_files_all',folder_path)
+    json_files = []
+    for root, dirs, files in os.walk(folder_path):
+        for file in files:
+            if file.endswith('.json'):
+                json_files.append(os.path.join(root, file))
+
+    data = []
+    for file_path in json_files:
+        try:
+            with open(file_path) as json_file:
+                json_data = json.load(json_file)
+                creation_time = datetime.datetime.fromtimestamp(os.path.getctime(file_path))
+                numeric_timestamp = creation_time.timestamp()
+                file_info = {
+                    'filename': os.path.basename(file_path),
+                    'category': os.path.dirname(file_path),
+                    'data': json_data,
+                    'date': numeric_timestamp
+                }
+                data.append(file_info)
+        except Exception as e:
+            print(e)
+    
+    sorted_data = sorted(data, key=lambda x: x['date'], reverse=True)
+    return sorted_data
+
 # workflow  
-def read_workflow_json_files(folder_path):
+def read_workflow_json_files(folder_path ):
    json_files = []
    for filename in os.listdir(folder_path):
        if filename.endswith('.json'):
@@ -162,12 +199,125 @@ def get_workflows():
    workflows=read_workflow_json_files(workflow_path)
    return workflows

+def get_my_workflow_for_app(filename="my_workflow_app.json",category="",is_all=False):
+    app_path=os.path.join(current_path, "app")
+    if not os.path.exists(app_path):
+        os.mkdir(app_path)
+
+    category_path=os.path.join(app_path,category)
+    if not os.path.exists(category_path):
+        os.mkdir(category_path)
+
+    apps=[]
+    if filename==None:
+
+        #TODO 支持目录内遍历 
+        if is_all:
+            data=read_workflow_json_files_all(category_path)
+        else:
+            data=read_workflow_json_files(category_path)
+        
+        i=0
+        for item in data:
+            # print(item)
+            try:
+                x=item["data"]
+                if i==0:
+                    apps.append({
+                        "filename":item["filename"],
+                        # "category":item['category'],
+                        "data":x,
+                        "date":item["date"],
+                    })
+                else:
+                    category=''
+                    if 'category' in x['app']:
+                        category=x['app']['category']
+                    apps.append({
+                        "filename":item["filename"],
+                        "category":category,
+                        "data":{
+                            "app":{
+                                "category":category,
+                                "description":x['app']['description'],
+                                "filename":(x['app']['filename'] if 'filename' in x['app'] else "") ,
+                                "icon":(x['app']['icon'] if 'icon' in x['app'] else None),
+                                "name":x['app']['name'],
+                                "version":x['app']['version'],
+                            }
+                        },
+                        "date":item["date"]
+                    })
+                i+=1
+            except Exception as e:
+                print("发生异常：", str(e))
+    else:
+        app_workflow_path=os.path.join(category_path, filename)
+        # print('app_workflow_path: ',app_workflow_path)
+        try:
+            with open(app_workflow_path) as json_file:
+                apps = [{
+                    'filename':filename,
+                    'data':json.load(json_file)
+                }]
+        except Exception as e:
+            print("发生异常：", str(e))
+        
+        if len(apps)==1 and category!='' and category!=None:
+            data=read_workflow_json_files(category_path)
+            
+            for item in data:
+                x=item["data"]
+                # print(apps[0]['filename'] ,item["filename"])
+                if apps[0]['filename']!=item["filename"]:
+                    category=''
+                    if 'category' in x['app']:
+                        category=x['app']['category']
+                    apps.append({
+                        "filename":item["filename"],
+                        # "category":category,
+                        "data":{
+                            "app":{
+                                "category":category,
+                                "description":x['app']['description'],
+                                "filename":(x['app']['filename'] if 'filename' in x['app'] else "") ,
+                                "icon":(x['app']['icon'] if 'icon' in x['app'] else None),
+                                "name":x['app']['name'],
+                                "version":x['app']['version'],
+                            }
+                        },
+                        "date":item["date"]
+                    })
+
+    return apps
+
 def save_workflow_json(data):
    workflow_path=os.path.join(current_path, "workflow/my_workflow.json")
    with open(workflow_path, 'w') as file:
        json.dump(data, file)
    return workflow_path

+def save_workflow_for_app(data,filename="my_workflow_app.json",category=""):
+    app_path=os.path.join(current_path, "app")
+    if not os.path.exists(app_path):
+        os.mkdir(app_path)
+
+    category_path=os.path.join(app_path,category)
+    if not os.path.exists(category_path):
+        os.mkdir(category_path)
+    
+    app_workflow_path=os.path.join(category_path, filename)
+ 
+    try:
+        output_str = json.dumps(data['output'])
+        data['app']['id']=calculate_md5(output_str)
+        # id=data['app']['id']
+    except Exception as e:
+        print("发生异常：", str(e))
+    
+    with open(app_workflow_path, 'w') as file:
+        json.dump(data, file)
+    return filename

 def get_nodes_map():
    # print("#####path::", current_path)
@@ -201,33 +351,59 @@ async def new_request(self, method, url, *args, **kwargs):

 # 应用 Monkey Patch
 aiohttp.ClientSession._request = new_request
+import socket
+
+async def check_port_available(address, port):
+    #检查端口是否可用
+    with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as sock:
+        sock.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
+        try:
+            sock.bind((address, port))
+            return True
+        except socket.error:
+            return False

 # https
 async def new_start(self, address, port, verbose=True, call_on_start=None):
-        
-
+    try:
        runner = web.AppRunner(self.app, access_log=None)
        await runner.setup()
+
+        if not await check_port_available(address, port):
+            raise RuntimeError(f"Port {port} is already in use.")
+
        site = web.TCPSite(runner, address, port)
        await site.start()

        import ssl
-        crt,key=create_for_https()
+        crt, key = create_for_https()
        ssl_context = ssl.create_default_context(ssl.Purpose.CLIENT_AUTH)
-        ssl_context.load_cert_chain(crt,key)
-        site2 = web.TCPSite(runner, address, port+1,ssl_context=ssl_context)
-        await site2.start()
+        ssl_context.load_cert_chain(crt, key)
+
+        success = False
+        for i in range(10):  # 尝试最多10次
+            if await check_port_available(address, port + 1 + i):
+                https_port = port + 1 + i
+                site2 = web.TCPSite(runner, address, https_port, ssl_context=ssl_context)
+                await site2.start()
+                success = True
+                break
+
+        if not success:
+            raise RuntimeError(f"Ports {port + 1} to {port + 10} are all in use.")

        if address == '':
            address = '0.0.0.0'
        if verbose:
-            # print('\033[91mMixlab Nodes: \033[93mLoaded\033[0m')
            print("\033[93mStarting server\n")
            print("\033[93mTo see the GUI go to: http://{}:{}".format(address, port))
-            print("\033[93mTo see the GUI go to: https://{}:{}\033[0m".format(address, port+1))
+            print("\033[93mTo see the GUI go to: https://{}:{}\033[0m".format(address, https_port))
        if call_on_start is not None:
            call_on_start(address, port)

+    except Exception as e:
+        print(f"Error starting the server: {e}")
+
        # import webbrowser
        # if os.name == 'nt' and address == '0.0.0.0':
        #     address = '127.0.0.1'
@@ -253,6 +429,18 @@ async def mixlab_hander(request):
            print(e)
    return web.json_response(data)

+
+@routes.get('/mixlab/app')
+async def mixlab_app_handler(request):
+    html_file = os.path.join(current_path, "web/index.html")
+    if os.path.exists(html_file):
+        with open(html_file, 'r', encoding='utf-8', errors='ignore') as f:
+            html_data = f.read()
+            return web.Response(text=html_data, content_type='text/html')
+    else:
+        return web.Response(text="HTML file not found", status=404)
+    
+
@routes.post('/mixlab/workflow')
 async def mixlab_workflow_hander(request):
    data = await request.json()
@@ -265,6 +453,29 @@ async def mixlab_workflow_hander(request):
                    'status':'success',
                    'file_path':file_path
                }
+            elif data['task']=='save_app':
+                category=""
+                if "category" in data:
+                    category=data['category']
+                file_path=save_workflow_for_app(data['data'],data['filename'],category)
+                result={
+                    'status':'success',
+                    'file_path':file_path
+                }
+            elif data['task']=='my_app':
+                filename=None
+                category=""
+                admin=False
+                if 'filename' in data:
+                    filename=data['filename']
+                if 'category' in data:
+                    category=data['category']
+                if 'admin' in data:
+                    admin=data['admin']
+                result={
+                    'data':get_my_workflow_for_app(filename,category,admin),
+                    'status':'success',
+                }
            elif data['task']=='list':
                result={
                    'data':get_workflows(),
@@ -289,8 +500,14 @@ async def nodes_map_hander(request):

    return web.json_response(result)

+# 把插件自定义的路由添加到comfyui server里
 def new_add_routes(self):
        import nodes
+        try:
+            self.user_manager.add_routes(self.routes)
+        except:
+            print('pls update')
+        
        self.app.add_routes(routes)
        self.app.add_routes(self.routes)
        for name, dir in nodes.EXTENSION_WEB_DIRS.items():
@@ -317,28 +534,38 @@ PromptServer.add_routes=new_add_routes


 # 导入节点
-from .nodes.PromptNode import RandomPrompt
-from .nodes.ImageNode import NoiseImage,TransparentImage,LoadImagesFromPath,ResizeImage,TextImage,SvgImage,Image3D,EmptyLayer,ShowLayer,NewLayer,MergeLayers,AreaToMask,SmoothMask,FeatheredMask,SplitLongMask,ImageCropByAlpha,EnhanceImage,FaceToMask
+from .nodes.PromptNode import RandomPrompt,PromptSlide,PromptSimplification,PromptImage
+from .nodes.ImageNode import GetImageSize_,MirroredImage,ImageColorTransfer,NoiseImage,TransparentImage,GradientImage,LoadImagesFromPath,LoadImagesFromURL,ResizeImage,TextImage,SvgImage,Image3D,ShowLayer,NewLayer,MergeLayers,AreaToMask,SmoothMask,FeatheredMask,SplitLongMask,ImageCropByAlpha,EnhanceImage,FaceToMask
 from .nodes.Vae import VAELoader,VAEDecode
 from .nodes.ScreenShareNode import ScreenShareNode,FloatingVideo
 from .nodes.Clipseg import CLIPSeg,CombineMasks
 from .nodes.ChatGPT import ChatGPTNode,ShowTextForGPT,CharacterInText
 from .nodes.Audio import GamePal,SpeechRecognition,SpeechSynthesis
-from .nodes.Utils import ColorInput,FontInput,TextToNumber,DynamicDelayProcessor
+from .nodes.Utils import TESTNODE_,AppInfo,IntNumber,FloatSlider,TextInput,ColorInput,FontInput,TextToNumber,DynamicDelayProcessor,LimitNumber,SwitchByIndex,MultiplicationNode
+


 # 要导出的所有节点及其名称的字典
 # 注意：名称应全局唯一
 NODE_CLASS_MAPPINGS = {
+    "AppInfo":AppInfo,
+    "TESTNODE_":TESTNODE_,
    "RandomPrompt":RandomPrompt,
+    "PromptSlide":PromptSlide,
+    "PromptSimplification":PromptSimplification,
+    "PromptImage":PromptImage,
+    "MirroredImage":MirroredImage,
    "NoiseImage":NoiseImage,
+    "GradientImage":GradientImage,
    "TransparentImage":TransparentImage,
    "ResizeImageMixlab":ResizeImage,
    "LoadImagesFromPath":LoadImagesFromPath,
+    "LoadImagesFromURL":LoadImagesFromURL,
    "TextImage":TextImage,
    "EnhanceImage":EnhanceImage,
    "SvgImage":SvgImage,
    "3DImage":Image3D, 
+    "ImageColorTransfer":ImageColorTransfer,
    "ShowLayer":ShowLayer,
    "NewLayer":NewLayer,
    "MergeLayers":MergeLayers,
@@ -360,15 +587,24 @@ NODE_CLASS_MAPPINGS = {
    "SpeechRecognition":SpeechRecognition,
    "SpeechSynthesis":SpeechSynthesis,
    "Color":ColorInput,
+    "FloatSlider":FloatSlider,
+    "IntNumber":IntNumber,
+    "TextInput_":TextInput,
    "Font":FontInput,
    "TextToNumber":TextToNumber,
-    "DynamicDelayProcessor":DynamicDelayProcessor
+    "DynamicDelayProcessor":DynamicDelayProcessor,
+    "MultiplicationNode":MultiplicationNode,
+    "GetImageSize_":GetImageSize_,
+    "SwitchByIndex":SwitchByIndex,
+    "LimitNumber":LimitNumber, 
+    # "LaMaInpainting":LaMaInpainting
    # "GamePal":GamePal
 }

 # 一个包含节点友好/可读的标题的字典
 NODE_DISPLAY_NAME_MAPPINGS = {
-    "ResizeImageMixlab":"ResizeImage",
+    "AppInfo":"AppInfo ♾️Mixlab",
+    "ResizeImageMixlab":"ResizeImage ♾️Mixlab",
    "RandomPrompt": "Random Prompt ♾️Mixlab",
    "SplitLongMask":"Splitting a long image into sections",
    "VAELoaderConsistencyDecoder":"Consistency Decoder Loader",
@@ -381,14 +617,46 @@ NODE_DISPLAY_NAME_MAPPINGS = {
    "SpeechSynthesis":"SpeechSynthesis ♾️Mixlab",
    "SpeechRecognition":"SpeechRecognition ♾️Mixlab",
    "3DImage":"3DImage ♾️Mixlab",
-    "DynamicDelayProcessor":"DynamicDelayByText ♾️Mixlab"
-
-    # "GamePal":"GamePal ♾️Mixlab"
+    "DynamicDelayProcessor":"DynamicDelayByText ♾️Mixlab",
+    "LaMaInpainting":"LaMaInpainting ♾️Mixlab",
+    "PromptSlide":"PromptSlide ♾️Mixlab",
+    "PromptGenerate_Mix":"PromptGenerate ♾️Mixlab",
+    "ChinesePrompt_Mix":"ChinesePrompt ♾️Mixlab",
+    "GamePal":"GamePal ♾️Mixlab"
 }

 # web ui的节点功能
 WEB_DIRECTORY = "./web"

 print('--------------')
-print('\033[91mMixlab Nodes: \033[93mLoaded\033[0m')
-print('--------------')
+print('\033[91m ### Mixlab Nodes: \033[93mLoaded')
+
+try:
+    from .nodes.Lama import LaMaInpainting
+    print('LaMaInpainting.available',LaMaInpainting.available)
+    if LaMaInpainting.available:
+        NODE_CLASS_MAPPINGS['LaMaInpainting']=LaMaInpainting
+except:
+    print('LaMaInpainting.available',False)
+
+try:
+    from .nodes.ClipInterrogator import ClipInterrogator
+    print('ClipInterrogator.available',ClipInterrogator.available)
+    if ClipInterrogator.available:
+        NODE_CLASS_MAPPINGS['ClipInterrogator']=ClipInterrogator
+except:
+    print('ClipInterrogator.available',False)
+
+try:
+    from .nodes.TextGenerateNode import PromptGenerate,ChinesePrompt
+    print('PromptGenerate.available',PromptGenerate.available)
+    if PromptGenerate.available:
+        NODE_CLASS_MAPPINGS['PromptGenerate_Mix']=PromptGenerate
+    print('ChinesePrompt.available',ChinesePrompt.available)
+    if ChinesePrompt.available:
+        NODE_CLASS_MAPPINGS['ChinesePrompt_Mix']=ChinesePrompt
+except:
+    print('TextGenerateNode.available',False)
+ 
+
+print('\033[93m -------------- \033[0m')
@@ -0,0 +1,30 @@
+Jony Ive
+Dieter Rams
+Philippe Starck
+Karim Rashid
+Yves Béhar
+Marc Newson
+Naoto Fukasawa
+Jonathan Adler
+Patricia Urquiola
+Ross Lovegrove
+Tom Dixon
+Jasper Morrison
+Charles Eames
+Ray Eames
+Achille Castiglioni
+Ron Arad
+Konstantin Grcic
+Marcel Wanders
+Maarten Baas
+Stefan Sagmeister
+Ingo Maurer
+Hella Jongerius
+Sam Hecht
+Kim Colin
+Jaime Hayon
+Michael Anastassiades
+Nendo
+Oki Sato
+Matali Crasset
+Tokujin Yoshioka
@@ -0,0 +1,10 @@
+Chibi Anime Style
+Gakuen Anime Style
+Gekiga Anime Style
+Jidaimono Anime Style
+Kawaii Anime Style
+Mecha Anime Style
+Realistic Anime Style
+Semi-Realistic Anime Style
+Shoji Anime Style
+Kemonomimi Anime Style
@@ -0,0 +1,23 @@
+GoPro
+Drone
+polaroid
+black and white film
+Kodachrome
+shot on 8mm
+shot on 16mm
+shot on 35mm
+Microscopic
+Fisheye Lens
+Wide Angle
+Ultra-Wide Angle
+Panorama
+Short Exposure
+Long Exposure
+Double Exposure
+f2.8
+Depth of Field
+Soft Focus
+Deep Focus
+Shallow Focus
+Vanishing Point
+Vantage Point
@@ -0,0 +1,30 @@
+Elegant evening gown
+Casual jeans and t-shirt
+Formal black suit
+Stylish leather jacket
+Flowy bohemian dress
+Sporty tracksuit
+Chic little black dress
+Trendy ripped jeans
+Classic white button-down shirt
+Cozy oversized sweater
+Sophisticated tailored blazer
+Quirky patterned leggings
+Striped sailor top
+Polished knee-length skirt
+Vintage-inspired floral dress
+Edgy motorcycle jacket
+Preppy polo shirt
+Boho maxi skirt
+Professional pinstripe suit
+Relaxed denim shorts
+Glamorous sequined dress
+Athletic running shoes
+Formal bow tie
+Casual baseball cap
+Stylish fedora hat
+Warm woolen scarf
+Comfortable cotton socks
+Trendy ankle boots
+Cute summer sandals
+Cozy pajama set
@@ -0,0 +1,30 @@
+Happy
+Sad
+Angry
+Surprised
+Excited
+Worried
+Confused
+Disgusted
+Amused
+Bored
+Curious
+Embarrassed
+Frustrated
+Nervous
+Pleased
+Relieved
+Shy
+Tired
+Serious
+Silly
+Proud
+Grumpy
+Smug
+Sarcastic
+Flirty
+Skeptical
+Shocked
+Blissful
+Envious
+Mischievous
@@ -4761,26 +4761,36 @@
    ],
    "https://github.com/shadowcz007/comfyui-mixlab-nodes": [
        [
+            "PromptGenerate_Mix",
+            "ChinesePrompt_Mix",
            "3DImage",
+            "AppInfo",
+            "IntNumber",
+            "FloatSlider",
+            "ResizeImage",
+            "NoiseImage",
+            "PromptImage",
            "AreaToMask",
-            "CLIPSeg",
            "CLIPSeg_",
            "CharacterInText",
            "ChatGPTOpenAI",
            "Color",
            "CombineMasks_",
-            "CombineSegMasks",
-            "EmptyLayer",
            "EnhanceImage",
+            "GradientImage",
            "FaceToMask",
            "FeatheredMask",
            "FloatingVideo",
            "Font",
            "ImageCropByAlpha",
            "LoadImagesFromPath",
+            "LoadImagesFromURL",
            "MergeLayers",
            "NewLayer",
            "RandomPrompt",
+            "PromptSlide",
+            "PromptSimplification",
+            "ClipInterrogator",
            "ScreenShare",
            "ShowLayer",
            "ShowTextForGPT",
@@ -4790,12 +4800,17 @@
            "SplitLongMask",
            "SvgImage",
            "TextImage",
+            "ResizeImageMixlab",
            "TransparentImage",
            "VAEDecodeConsistencyDecoder",
-            "VAELoaderConsistencyDecoder"
+            "VAELoaderConsistencyDecoder",
+            "TextToNumber",
+            "TextInput_",
+            "DynamicDelayProcessor",
+            "LaMaInpainting"
        ],
        {
-            "title_aux": "comfyui-mixlab-nodes [WIP]"
+            "title_aux": "comfyui-mixlab-nodes"
        }
    ],
    "https://github.com/shiimizu/ComfyUI_smZNodes": [
@@ -0,0 +1,16 @@
+Mood Lighting
+Moody Lighting
+Studio Lighting
+Cove Lighting
+Soft Lighting
+Hard Lighting
+Volumetric Lighting
+Low-Key Lighting
+High-Key Lighting
+Epic Light
+Rembrandt Lighting
+Contre-Jour
+Veiling Flare
+Crepuscular Rays
+Rays of Shimmering Light
+Godrays
@@ -0,0 +1,132 @@
+Aaron Siskind
+Alessio Albi
+Alfred Eisenstaedt
+Alfred Stieglitz
+Alyssa Monks
+André Kertész
+Andreas Gursky
+Andrew Wyeth
+Anne Geddes
+Annie Leibovitz
+Ansel Adams
+Arnold Newman
+August Sander
+Balthus
+Berenice Abbott
+Bill Brandt
+Bill Henson
+Brassaï (Gyula Halász)
+Brooke Shaden
+Bruce Davidson
+Bruce Weber
+Bunny Yeager
+Carleton Watkins
+Carrie Mae Weems
+Chuck Close
+Cindy Sherman
+Clarence H. White
+Claude Cahun
+Danny Lyon
+David LaChapelle
+Dawoud Bey
+Diane Arbus
+Don McCullin
+Dora Maar
+Dorothea Lange
+Duane Michals
+Eadweard Muybridge
+Edward Burtynsky
+Edward Curtis
+Edward Ruscha
+Edward Steichen
+Edward Weston
+Elliott Erwitt
+Ernst Haas
+Eugene Atget
+Fan Ho
+Francesca Woodman
+Frans Lanting
+Garry Winogrand
+Georges Melies
+Gerda Taro
+Gertrude Käsebier
+Gordon Parks
+Graciela Iturbide
+Gregory Crewdson
+Harold Edgerton
+Helen Levitt
+Helmut Newton
+Hendrik Kerstens
+Henri Cartier-Bresson
+Hugh Kretschmer
+Irving Penn
+Jacques Henri Lartigue
+James Nachtwey
+James Van Der Zee
+Jay Maisel
+Jerry Uelsmann
+Joel Peter Witkin
+Joel Sartore
+John Frederick William Herschel
+Josef Sudek
+Julia Margaret Cameron
+Karl Blossfeldt
+Larry Burrows
+László Moholy-Nagy (photography)
+Lee Jeffries
+Lewis Hine
+Lorna Simpson
+Lynsey Addario
+Margaret Bourke-White
+Mario Testino
+Martin Parr
+Martin Schoeller
+Mary Ellen Mark
+Mathew B. Brady
+Méret Oppenheim
+Meryl McMaster
+Mick Rock
+Miles Aldridge
+Minor Martin White
+Nan Goldin
+Nathan Wirth
+Olive Cotton
+Olivier Rousteing
+Patrick Demarchelier
+Paul Nicklen
+Paul Outerbridge
+Paul Strand
+Pete Souza
+Peter Dombrovskis
+Peter Henry Emerson
+Peter Lik
+Peter Lindbergh
+Philip-Lorca diCorcia
+Philippe Halsman
+Ralph Gibson
+Richard Avedon
+Robert Adams
+Robert Bechtle
+Robert Capa
+Robert Frank
+Robert Mapplethorpe
+Roger Fenton
+Ruth Bernhard
+Sally Mann
+Sebastião Salgado
+Shirin Neshat
+Stefan Gesell
+Steven Meisel
+Susan Meiselas
+Vivian Maier
+Vivian Maier
+Viviane Sassen
+Walker Evans
+Wes Anderson
+William Eggleston
+William Eugene Smith
+William Henry Fox Talbot
+Yinka Shonibare
+Yousuf Karsh
+Man Ray
+Robert Mapplethorpe
@@ -0,0 +1,101 @@
+Doctor
+Teacher
+Engineer
+Lawyer
+Accountant
+Nurse
+Architect
+Chef
+Pilot
+Scientist
+Artist
+Writer
+Musician
+Actor
+Photographer
+Police officer
+Firefighter
+Dentist
+Pharmacist
+Veterinarian
+Electrician
+Plumber
+Carpenter
+Mechanic
+Farmer
+Astronaut
+Athlete
+Journalist
+Politician
+Economist
+Psychologist
+Social worker
+Librarian
+Translator
+Salesperson
+Entrepreneur
+Financial advisor
+Graphic designer
+Web developer
+Marketing manager
+Human resources manager
+Project manager
+Event planner
+Fashion designer
+Interior decorator
+Real estate agent
+Archaeologist
+Biologist
+Chemist
+Geologist
+Physicist
+Mathematician
+Historian
+Geographer
+Economist
+Sociologist
+Anthropologist
+Archaeologist
+Linguist
+Philosopher
+Economist
+Sociologist
+Anthropologist
+Archaeologist
+Linguist
+Philosopher
+Geographer
+Historian
+Economist
+Sociologist
+Anthropologist
+Archaeologist
+Linguist
+Philosopher
+Geographer
+Historian
+Economist
+Sociologist
+Anthropologist
+Archaeologist
+Linguist
+Philosopher
+Geographer
+Historian
+Economist
+Sociologist
+Anthropologist
+Archaeologist
+Linguist
+Philosopher
+Geographer
+Historian
+Economist
+Sociologist
+Anthropologist
+Archaeologist
+Linguist
+Philosopher
+Geographer
+Historian
+                     #MixCopilot
@@ -0,0 +1,135 @@
+Vintage
+Grain
+Sepia
+High Key
+Low Key
+High Dynamic Range
+Cross Process
+Radial Blur
+Infrared
+Lomo
+Photocopy
+Pencil Sketch
+Pop Art
+Orton
+Mosaic
+Selective Black and White
+Torn Paper
+Tilt-Shift
+Double Exposure
+Polaroid
+Liquid Ink
+Color Splash
+Sketch
+Water Drops
+Polarizer
+Chinese Painting
+Water Droplets
+Polarization
+Color Inversion
+Fish-eye
+Soft Focus
+Solarization
+Posterize
+Comic Book
+Duotone
+Gradient Map
+Edge Detection
+Oil Painting
+Reflection
+Mirror
+ASCII Art
+Glitch
+Time-Lapse
+Day to Night
+Surreal
+Black and White
+Sepia Tone
+Vintage Film
+Grainy Texture
+High Key Lighting
+Low Key Lighting
+Cross Processed Film
+Infrared Photography
+Photocopy
+Pencil Drawing
+Pop Art Filter
+Mosaic Filter
+Selective Desaturation
+Torn Paper
+Tilt-Shift Photography
+Double Exposure
+Polaroid Style Frame
+Water Drops Texture
+Polarizer
+Chinese Painting
+Water Droplets Texture
+Polarization
+Color Inversion
+Fish-eye Lens
+Soft Focus
+Solarize Filter
+Edge Detection
+Oil Painting
+Reflection
+Mirror Image
+Time-Lapse Photography
+Day to Night Transition
+Surreal Art Style
+Abstract Expressionism
+Acrylic Painting
+Anime
+Art Deco
+Biomorphic Abstraction
+Black and White Photograph
+Cartoon
+Charcoal Sketch
+Chibi Anime
+Chinese Painting
+Classicist Painting
+Collage
+Concept Art
+Cyberpunk
+Dada Art
+Digital Art
+Fantasy Art
+Fashion Art
+Fashion Sketch
+Fish-Eye lens Photograph
+Goth Art
+Graffiti
+Harlem Renaissance
+High Key Photograph
+Hyperrealist Pencil Sketch
+Impressionist Painting
+Josei Anime
+Long Exposure Photograph
+Low Key Photograph
+Macro Photograph
+Manga
+Metal Sculpture
+Mid Century Modern Illustration
+Mixed Media
+Modern Art
+Moe Anime
+Nihonga
+Origami
+Paper Mache
+Pen and Ink
+Pencil Sketch
+Photograph
+Photorealism
+Pinup Art
+Romanticist Painting
+Sci-Fi Art
+Semi Realistic Fantasy Art
+Semi Realistic Cyberpunk Art
+Shallow Depth of Field Photograph
+Steam Punk Art
+Stone Sculpture
+Superhero Comic
+Surrealist Art
+Tempura Painting
+Underground Comic
+Watercolor Painting
+Zulu Urban Art
@@ -24,7 +24,7 @@ class SpeechRecognition:

    FUNCTION = "run"

-    CATEGORY = "♾️Mixlab/audio"
+    CATEGORY = "♾️Mixlab/Audio"

    INPUT_IS_LIST = False
    OUTPUT_IS_LIST = (False,)
@@ -48,7 +48,7 @@ class SpeechSynthesis:
    OUTPUT_NODE = True
    OUTPUT_IS_LIST = (True,)

-    CATEGORY = "♾️Mixlab/audio"
+    CATEGORY = "♾️Mixlab/Audio"

    def run(self, text):
        # print(session_history)
@@ -82,7 +82,7 @@ class GamePal:
    OUTPUT_NODE = True
    OUTPUT_IS_LIST = (False,)

-    CATEGORY = "♾️Mixlab/audio"
+    CATEGORY = "♾️Mixlab/Audio"

    def run(self, input_text,input_num,python_code):
        exec(python_code)
@@ -75,15 +75,15 @@ class ChatGPTNode:
            "required": {
                "api_key":("KEY", {"default": "", "multiline": True}),
                "api_url":("URL", {"default": "", "multiline": True}),
-                "prompt": ("STRING", {"multiline": True}),
+                "prompt": ("STRING", {"multiline": True,"dynamicPrompts": False}),
                "system_content": ("STRING", 
                                   {
                                       "default": "You are ChatGPT, a large language model trained by OpenAI. Answer as concisely as possible.", 
-                                       "multiline": True
+                                       "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"], 
                          {"default": "gpt-3.5-turbo"}),
-                "seed": ("INT", {"default": 0, "min": 0, "max": 10000, "step": 1}),
+                "seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff, "step": 1}),
                "context_size":("INT", {"default": 1, "min": 0, "max":30, "step": 1}),
            },
             "hidden": {
@@ -167,7 +167,7 @@ class ShowTextForGPT:
    def INPUT_TYPES(s):
        return {
            "required": {
-                "text": ("STRING", {"forceInput": True}),
+                "text": ("STRING", {"forceInput": True,"dynamicPrompts": False}),
            }
        }

@@ -180,8 +180,9 @@ class ShowTextForGPT:
    CATEGORY = "♾️Mixlab/GPT"

    def run(self, text):
-        # print(session_history)
+        # print(text)
        return {"ui": {"text": text}, "result": (text,)}
+        


 class CharacterInText:
@@ -189,8 +190,8 @@ class CharacterInText:
    def INPUT_TYPES(s):
        return {
            "required": {
-                 "text": ("STRING", {"multiline": True}),
-                 "character": ("STRING", {"multiline": True}),
+                 "text": ("STRING", {"multiline": True,"dynamicPrompts": False}),
+                 "character": ("STRING", {"multiline": True,"dynamicPrompts": False}),
                 "start_index": ("INT", {
                    "default": 1,
                    "min": 0, #Minimum value
@@ -0,0 +1,271 @@
+import os,sys
+import folder_paths
+
+from PIL import Image
+import importlib.util
+
+import comfy.utils
+import numpy as np
+import json
+import torch
+import random
+
+
+# from clip_interrogator import Config, Interrogator
+
+
+global _available
+_available=False
+
+def is_installed(package):
+    try:
+        spec = importlib.util.find_spec(package)
+    except ModuleNotFoundError:
+        return False
+    return spec is not None
+
+try:
+    if is_installed('clip_interrogator')==False:
+        import subprocess
+
+        # 安装
+        print('#pip install clip-interrogator==0.6.0')
+
+        result = subprocess.run([sys.executable, '-s', '-m', 'pip', 'install', 'clip-interrogator==0.6.0'], capture_output=True, text=True)
+
+        #检查命令执行结果
+        if result.returncode == 0:
+            print("#install success")
+            from transformers import AutoProcessor, BlipForConditionalGeneration
+            from clip_interrogator import Config, Interrogator
+            _available=True
+        else:
+            print("#install error")
+        
+    else:
+        from transformers import AutoProcessor, BlipForConditionalGeneration
+        from clip_interrogator import Config, Interrogator
+        _available=True
+
+except:
+    _available=False
+
+
+def load_caption_model(model_path,config,t='blip-base'):
+    dtype=torch.float16 if config.device == 'cuda' else torch.float32
+    caption_model = BlipForConditionalGeneration.from_pretrained(model_path, torch_dtype=dtype)
+    
+    caption_processor = AutoProcessor.from_pretrained(model_path)
+
+    caption_model.eval()
+    if not config.caption_offload:
+        caption_model = caption_model.to(config.device)
+    
+    return (caption_model,caption_processor)
+    
+
+
+caption_model_path=os.path.join(folder_paths.models_dir, "clip_interrogator/Salesforce/blip-image-captioning-base")
+if not os.path.exists(caption_model_path):
+    print(f"## clip_interrogator_model not found: {caption_model_path}, pls download from https://huggingface.co/Salesforce/blip-image-captioning-base")
+    caption_model_path='Salesforce/blip-image-captioning-base'
+
+cache_path=os.path.join(folder_paths.models_dir, "clip_interrogator")
+
+
+# Tensor to PIL
+def tensor2pil(image):
+    return Image.fromarray(np.clip(255. * image.cpu().numpy().squeeze(), 0, 255).astype(np.uint8))
+
+# Convert PIL to Tensor
+def pil2tensor(image):
+    return torch.from_numpy(np.array(image).astype(np.float32) / 255.0).unsqueeze(0)
+
+
+def image_analysis_fn(ci,image):
+    image = image.convert('RGB')
+    image_features = ci.image_to_features(image)
+
+    top_mediums = ci.mediums.rank(image_features, 5)
+    top_artists = ci.artists.rank(image_features, 5)
+    top_movements = ci.movements.rank(image_features, 5)
+    top_trendings = ci.trendings.rank(image_features, 5)
+    top_flavors = ci.flavors.rank(image_features, 5)
+
+    medium_ranks = {medium: sim for medium, sim in zip(top_mediums, ci.similarities(image_features, top_mediums))}
+    artist_ranks = {artist: sim for artist, sim in zip(top_artists, ci.similarities(image_features, top_artists))}
+    movement_ranks = {movement: sim for movement, sim in zip(top_movements, ci.similarities(image_features, top_movements))}
+    trending_ranks = {trending: sim for trending, sim in zip(top_trendings, ci.similarities(image_features, top_trendings))}
+    flavor_ranks = {flavor: sim for flavor, sim in zip(top_flavors, ci.similarities(image_features, top_flavors))}
+    
+    return {
+        "medium_ranks":medium_ranks, 
+        "artist_ranks":artist_ranks, 
+        "movement_ranks":movement_ranks, 
+        "trending_ranks":trending_ranks, 
+        "flavor_ranks":flavor_ranks
+        }
+
+
+def generate_sentences(data):
+    sentences = []
+
+    # Get the length of data
+    data_length = len(data)
+
+    # Use a recursive function to handle variable-length data
+    def generate_recursive(index, current_sentence, current_score):
+        # Check if recursion is complete
+        if index == data_length:
+            sentences.append({"sentence": current_sentence, "score": current_score})
+            return
+
+        # Get the current level data
+        current_data = data[index]
+
+        # Iterate through the current level data
+        for phrase in current_data:
+            sentence = current_sentence + ("," if current_sentence.strip() else "") + phrase
+            score = current_score + current_data[phrase]
+            generate_recursive(index + 1, sentence, score)
+
+    # Start recursive generation of sentences
+    generate_recursive(0, "", 0)
+
+    # Sort the generated sentences by score in descending order
+    sentences.sort(key=lambda x: x["score"], reverse=True)
+
+    def get_random_elements(elements, num):
+        return random.sample(elements, num)
+
+    ps = get_random_elements(sentences, 5)
+    ps = [s["sentence"] for s in sorted(ps, key=lambda x: x["score"], reverse=True)]
+
+    return ps
+
+
+
+
+def image_to_prompt(ci,image, mode):
+    ci.config.chunk_size = 2048 if ci.config.clip_model_name == "ViT-L-14/openai" else 1024
+    ci.config.flavor_intermediate_count = 2048 if ci.config.clip_model_name == "ViT-L-14/openai" else 1024
+    image = image.convert('RGB')
+    if mode == 'best':
+        return ci.interrogate(image)
+    elif mode == 'classic':
+        return ci.interrogate_classic(image)
+    elif mode == 'fast':
+        return ci.interrogate_fast(image)
+    elif mode == 'negative':
+        return ci.interrogate_negative(image)
+
+# image = Image.open(image_path).convert('RGB')
+# ci = Interrogator(Config(clip_model_name="ViT-L-14/openai"))
+# print(ci.interrogate(image))
+
+
+class ClipInterrogator:
+
+    global _available
+    available=_available
+    
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": {
+            "image": ("IMAGE",),
+            "prompt_mode": (['fast','classic','best','negative'],),
+            "image_analysis": (["off","on"],), 
+                             },
+
+                # "optional":{
+                #     "output":("CLIPINTERROGATOR", {"multiline": True,"default": "", "dynamicPrompts": False})
+                # },
+
+                }
+    
+    RETURN_TYPES = ("STRING","STRING",)
+    RETURN_NAMES = ("prompt","random_samples",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/Prompt"
+    OUTPUT_NODE = True
+    INPUT_IS_LIST = True
+    OUTPUT_IS_LIST = (True,True,)
+    global ci
+    ci = None
+    def run(self,image,prompt_mode,image_analysis):
+        global ci
+
+        prompt_mode=prompt_mode[0]
+        analysis=image_analysis[0]
+
+        prompt_result=[]
+        analysis_result=[]
+
+        # 进度条
+        pbar = comfy.utils.ProgressBar(len(image)*(2 if analysis=='on' else 1))
+        
+        if ci==None:
+            config=Config(
+                clip_model_name="ViT-L-14/openai",
+                device="cuda" if torch.cuda.is_available() else "cpu",
+                download_cache=True,
+                clip_model_path=cache_path,
+                cache_path=cache_path
+                )
+            config.apply_low_vram_defaults()
+
+            caption_model,caption_processor=load_caption_model(caption_model_path,config)
+
+            config.caption_model= caption_model
+            config.caption_processor= caption_processor
+
+            ci = Interrogator(config)
+        # else:
+        #     simple_lama.model.to("cuda" if torch.cuda.is_available() else "cpu")
+
+        for i in range(len(image)):
+            im=image[i]
+
+            im=tensor2pil(im)
+            im=im.convert('RGB')
+
+            if analysis=='on':
+                analysis_res=image_analysis_fn(ci,im)
+                analysis_result.append( analysis_res )
+                pbar.update(1)
+
+            prompt=image_to_prompt(ci,im,prompt_mode)
+            pbar.update(1)
+            prompt_result.append(prompt)
+
+
+        # result.save("inpainted.png")
+        if ci.config.clip_offload and not ci.clip_offloaded:
+            ci.clip_model = ci.clip_model.to('cpu')
+            ci.clip_offloaded = True
+
+        if ci.config.caption_offload and not ci.caption_offloaded:
+            ci.caption_model = ci.caption_model.to('cpu')
+            ci.caption_offloaded = True
+
+        # analysis_result=[]
+        # items = app.graph.getNodeById(31).widgets[2].value["items"]
+        
+        random_samples=[]
+
+        for r in analysis_result:
+            random_sample = generate_sentences([r['medium_ranks'], r['artist_ranks'],r['movement_ranks'],r['trending_ranks'],r['flavor_ranks']])
+            for s in random_sample:
+                random_samples.append(s)
+        # print(len(random_samples))
+        # print('-----')
+        # print( random_samples)
+        return {
+            "ui":{
+                    "prompt": prompt_result,
+                    "analysis":analysis_result,
+                    "random_samples":random_samples
+                },
+            "result": (prompt_result,random_samples,)}
@@ -31,10 +31,20 @@ logger = logging.getLogger('CLIPSeg nodes')
 clipseg_model_dir = os.path.join(folder_paths.models_dir, "clipseg")

 if not os.path.exists(clipseg_model_dir):
+    print(f"## clipseg model not found: {clipseg_model_dir},pls download from https://huggingface.co/CIDAS/clipseg-rd64-refined/tree/main")
    clipseg_model_dir='CIDAS/clipseg-rd64-refined'

 """Helper methods for CLIPSeg nodes"""

+# Tensor to PIL
+def tensor2pil(image):
+    return Image.fromarray(np.clip(255. * image.cpu().numpy().squeeze(), 0, 255).astype(np.uint8))
+
+# Convert PIL to Tensor
+def pil2tensor(image):
+    return torch.from_numpy(np.array(image).astype(np.float32) / 255.0).unsqueeze(0)
+
+
 def tensor_to_numpy(tensor: torch.Tensor) -> np.ndarray:
    """Convert a tensor to a numpy array and scale its values to 0-255."""
    array = tensor.numpy().squeeze()
@@ -91,23 +101,23 @@ class CLIPSeg:
        return {"required":
                    {
                        "image": ("IMAGE",),
-                        "text": ("STRING", {"multiline": False}),
+                        "text": ("STRING", {"multiline": False,"dynamicPrompts": False}),
                        
                     },
                "optional":
                    {
-                        "blur": ("FLOAT", {"min": 0, "max": 15, "step": 0.1, "default": 7}),
-                        "threshold": ("FLOAT", {"min": 0, "max": 1, "step": 0.05, "default": 0.4}),
+                        "blur": ("FLOAT", {"min": 0, "max": 15, "step": 0.1, "default": 3}),
+                        "threshold": ("FLOAT", {"min": 0, "max": 1, "step": 0.05, "default": 0.3}),
                        "dilation_factor": ("INT", {"min": 0, "max": 10, "step": 1, "default": 4}),
                    }
                }

-    CATEGORY = "♾️Mixlab/mask"
+    CATEGORY = "♾️Mixlab/Mask"
    RETURN_TYPES = ("MASK", "IMAGE", "IMAGE",)
    RETURN_NAMES = ("Mask","Heatmap Mask", "BW Mask")

    # INPUT_IS_LIST = True
-    # OUTPUT_IS_LIST = (True,)
+    OUTPUT_IS_LIST = (False,False,False,)

    FUNCTION = "segment_image"
    def segment_image(self, image: torch.Tensor, text: str, blur: float, threshold: float, dilation_factor: int) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
@@ -180,12 +190,13 @@ class CLIPSeg:
        binary_mask_image = Image.fromarray(binary_mask_resized[..., 0])

        # convert PIL image to numpy array
-        tensor_bw = binary_mask_image.convert("RGB")
-        tensor_bw = np.array(tensor_bw).astype(np.float32) / 255.0
-        tensor_bw = torch.from_numpy(tensor_bw)[None,]
-        tensor_bw = tensor_bw.squeeze(0)[..., 0]
+        tensor_bw = binary_mask_image.convert("L")
+        tensor_bw=pil2tensor(tensor_bw)
+        # tensor_bw = np.array(tensor_bw).astype(np.float32) / 255.0
+        # tensor_bw = torch.from_numpy(tensor_bw)[None,]
+        # tensor_bw = tensor_bw.squeeze(0)[..., 0]

-        return tensor_bw, image_out_heatmap, image_out_binary
+        return (tensor_bw, image_out_heatmap, image_out_binary,)

    #OUTPUT_NODE = False

@@ -207,7 +218,7 @@ class CombineMasks:
                    },
                }
        
-    CATEGORY = "♾️Mixlab/mask"
+    CATEGORY = "♾️Mixlab/Mask"
    RETURN_TYPES = ("MASK", "IMAGE", "IMAGE",)
    RETURN_NAMES = ("Combined Mask","Heatmap Mask", "BW Mask")

@@ -235,7 +246,7 @@ class CombineMasks:
        
        # Resize heatmap and binary mask to match the original image dimensions
        dimensions = (image_np.shape[1], image_np.shape[0])
-        print('heatmap',heatmap)
+        # print('heatmap',heatmap)
        if dimensions is None or dimensions[0] == 0 or dimensions[1] == 0:
            raise ValueError("Invalid dimensions")
        
@@ -0,0 +1,120 @@
+import os,sys
+import folder_paths
+
+from PIL import Image
+import importlib.util
+import numpy as np
+
+import torch
+
+global _available
+_available=False
+
+def is_installed(package):
+    try:
+        spec = importlib.util.find_spec(package)
+    except ModuleNotFoundError:
+        return False
+    return spec is not None
+
+if is_installed('simple_lama_inpainting')==False:
+    import subprocess
+    from packaging import version
+    
+    if version.parse(torch.__version__)>=version.parse('2.1'):
+        # 安装
+        print('#pip install simple_lama_inpainting')
+
+        result = subprocess.run([sys.executable, '-s', '-m', 'pip', 'install', 'simple_lama_inpainting'], capture_output=True, text=True)
+
+        #检查命令执行结果
+        if result.returncode == 0:
+            print("#install success")
+            from simple_lama_inpainting import SimpleLama
+            _available=True
+        else:
+            print("#install error")
+    else:
+        print('#pls check your torch version >= 2.1')
+
+else:
+    from simple_lama_inpainting import SimpleLama
+    _available=True
+
+
+ 
+llma_model_path=os.path.join(folder_paths.models_dir, "lama/big-lama.pt")
+if not os.path.exists(llma_model_path):
+    os.environ['LAMA_MODEL']=''
+    print(f"## lama torchscript model not found: {llma_model_path},pls download from https://github.com/enesmsahin/simple-lama-inpainting/releases/download/v0.1.0/big-lama.pt")
+else:
+    os.environ['LAMA_MODEL'] = llma_model_path
+
+# Tensor to PIL
+def tensor2pil(image):
+    return Image.fromarray(np.clip(255. * image.cpu().numpy().squeeze(), 0, 255).astype(np.uint8))
+
+# Convert PIL to Tensor
+def pil2tensor(image):
+    return torch.from_numpy(np.array(image).astype(np.float32) / 255.0).unsqueeze(0)
+
+
+# simple_lama = SimpleLama()
+
+# img_path = "image.png"
+# mask_path = "mask.png"
+
+# image = Image.open(img_path)
+# mask = Image.open(mask_path).convert('L')
+
+# result = simple_lama(image, mask)
+# result.save("inpainted.png")
+
+
+class LaMaInpainting:
+    global _available
+    available=_available
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": {
+            "image": ("IMAGE",),
+            "mask": ("MASK",),
+                             },
+
+            
+                }
+    
+    RETURN_TYPES = ("IMAGE",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/Image"
+
+    INPUT_IS_LIST = True
+    OUTPUT_IS_LIST = (True,)
+    global simple_lama
+    simple_lama = None
+    def run(self,image,mask):
+        global simple_lama
+
+        result=[]
+        if simple_lama==None:
+            simple_lama = SimpleLama()
+        else:
+            simple_lama.model.to("cuda" if torch.cuda.is_available() else "cpu")
+
+        for i in range(len(image)):
+            im=image[i]
+            ma=mask[i]
+            im=tensor2pil(im)
+            ma=tensor2pil(ma)
+            ma =ma.convert('L')
+            
+            res = simple_lama(im, ma)
+            res=pil2tensor(res)
+            result.append(res)
+        # result.save("inpainted.png")
+        if simple_lama.device=='cuda':
+            simple_lama.model.to('cpu')
+
+        return (result,)
@@ -1,15 +1,16 @@
 import random
 import comfy.utils
-import json
+import os
+import numpy as np
 from urllib import request, parse
-
-
-
-def queue_prompt(prompt_workflow):
-    p = {"prompt": prompt_workflow}
-    data = json.dumps(p).encode('utf-8')
-    req =  request.Request("http://127.0.0.1:8188/prompt", data=data)
-    request.urlopen(req)    
+import folder_paths
+from PIL import Image, ImageOps,ImageFilter,ImageEnhance,ImageDraw,ImageSequence, ImageFont
+from PIL.PngImagePlugin import PngInfo
+# def queue_prompt(prompt_workflow):
+#     p = {"prompt": prompt_workflow}
+#     data = json.dumps(p).encode('utf-8')
+#     req =  request.Request("http://127.0.0.1:8188/prompt", data=data)
+#     request.urlopen(req)    


 default_prompt1='''Swing
@@ -45,6 +46,232 @@ default_prompt1='''Swing
                                                '''
 default_prompt1="\n".join([p.strip() for p in default_prompt1.split('\n') if p.strip()!=''])

+
+def tensor2pil(image):
+    return Image.fromarray(np.clip(255. * image.cpu().numpy().squeeze(), 0, 255).astype(np.uint8))
+
+def addWeight(text, weight=1):
+    if weight == 1:
+        return text
+    else:
+        return f"({text}:{round(weight,2)})"
+
+def prompt_delete_words(sentence, new_words_length):
+    # 使用逗号分割句子，并去除空格
+    words = [word.strip() for word in sentence.split(",")]
+    
+    # 计算需要删除的单词数量
+    num_to_delete = len(words) - new_words_length
+    
+    words_to=[w for w in words]
+
+    # 逐个删除单词并存储在新列表中
+    new_words = []
+    for i in range(len(words)):
+        if num_to_delete > 0:
+            num_to_delete -= 1
+        else:
+            words_to.pop()
+            if len(words_to)>0:
+                new_words.append(", ".join(words_to))
+         
+    return new_words
+
+# # 测试方法
+# sentence = "a computer, a glass tablet with a keyboard on a dark background, 3d illustration, reflection, cgi 8k, clear glass, archaic, cut-away, white outline"
+# new_words_length = 5
+# result = prompt_delete_words(sentence, new_words_length)
+# print(result)
+
+class PromptImage:
+    def __init__(self):
+        self.output_dir = folder_paths.get_output_directory()
+        self.type = "output"
+        self.prefix_append = "PromptImage"
+        self.compress_level = 4
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "prompts": ("STRING", 
+                         {
+                            "multiline": True, 
+                            "default": '',
+                            "dynamicPrompts": False
+                          }),
+
+                "images": ("IMAGE",{"default": None}), 
+                 "save_to_image": (["enable", "disable"],),
+                }
+            }
+    
+    RETURN_TYPES = ()
+   
+    OUTPUT_NODE = True
+
+    INPUT_IS_LIST = True
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/Prompt"
+
+    # 运行的函数
+    def run(self,prompts,images,save_to_image):
+        filename_prefix="mixlab_"
+        filename_prefix += self.prefix_append
+        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])
+        
+        results = list()
+
+        save_to_image=save_to_image[0]=='enable'
+
+        for index in range(len(images)):
+            res=[]
+            imgs=images[index]
+
+            for image in imgs:
+                img=tensor2pil(image)
+
+                metadata = None
+                if save_to_image:
+                    metadata = PngInfo()
+                    prompt_text=prompts[index]
+                    if prompt_text is not None:
+                        metadata.add_text("prompt_text", prompt_text)
+                    
+                file = f"{filename}_{index}_{counter:05}_.png"
+                img.save(os.path.join(full_output_folder, file), pnginfo=metadata, compress_level=self.compress_level)
+                res.append({
+                    "filename": file,
+                    "subfolder": subfolder,
+                    "type": self.type
+                })
+                counter += 1
+            results.append(res)
+        
+        return { "ui": { "_images": results,"prompts":prompts } }
+
+
+
+
+class PromptSimplification:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "prompt": ("STRING", 
+                         {
+                            "multiline": True, 
+                            "default": '',
+                            "dynamicPrompts": False
+                          }),
+
+                "length":("INT", {"default": 5, "min": 1,"max":100, "step": 1, "display": "number"}),
+
+                # "min_value":("FLOAT", {
+                #         "default": -2, 
+                #         "min": -10, 
+                #         "max": 0xffffffffffffffff,
+                #         "step": 0.01, 
+                #         "display": "number"  
+                #     }),
+                # "max_value":("FLOAT", {
+                #         "default": 2, 
+                #         "min": -10, 
+                #         "max": 0xffffffffffffffff,
+                #         "step": 0.01, 
+                #         "display": "number"  
+                #     }),
+              
+                }
+            }
+    
+    RETURN_TYPES = ("STRING",)
+    RETURN_NAMES = ("prompts",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/Prompt"
+
+    INPUT_IS_LIST = True
+    OUTPUT_IS_LIST = (True,)
+    OUTPUT_NODE = True
+
+    # 运行的函数
+    def run(self,prompt,length):
+        length=length[0]
+        result=[]
+        for p in prompt:
+            nps=prompt_delete_words(p,length)
+            for n in nps:
+                result.append(n)
+
+        result= [elem.strip() for elem in result if elem.strip()]
+
+        return {"ui": {"prompts": result}, "result": (result,)}
+
+
+
+class PromptSlide:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                
+                "prompt_keyword": ("STRING", 
+                         {
+                            "multiline": False, 
+                            "default": '',
+                            "dynamicPrompts": False
+                          }),
+
+                "weight":("FLOAT", {"default": 1, "min": -3,"max": 3,
+                                                                "step": 0.01,
+                                                                "display": "slider"}),
+
+                # "min_value":("FLOAT", {
+                #         "default": -2, 
+                #         "min": -10, 
+                #         "max": 0xffffffffffffffff,
+                #         "step": 0.01, 
+                #         "display": "number"  
+                #     }),
+                # "max_value":("FLOAT", {
+                #         "default": 2, 
+                #         "min": -10, 
+                #         "max": 0xffffffffffffffff,
+                #         "step": 0.01, 
+                #         "display": "number"  
+                #     }),
+              
+                }
+            }
+    
+    RETURN_TYPES = ("STRING",)
+    RETURN_NAMES = ("prompt",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/Prompt"
+
+    INPUT_IS_LIST = False
+    OUTPUT_IS_LIST = (False,)
+    OUTPUT_NODE = False
+
+    # 运行的函数
+    def run(self,prompt_keyword,weight):
+        # if weight < min_value:
+        #     weight= min_value
+        # elif weight > max_value:
+        #     weight= max_value
+        p=addWeight(prompt_keyword,weight)
+        return (p,)
+
+
+
+
 class RandomPrompt:

    '''
@@ -79,7 +306,7 @@ class RandomPrompt:

    FUNCTION = "run"

-    CATEGORY = "♾️Mixlab/prompt"
+    CATEGORY = "♾️Mixlab/Prompt"

    OUTPUT_IS_LIST = (True,)
    OUTPUT_NODE = True
@@ -87,7 +314,7 @@ class RandomPrompt:

    # 运行的函数
    def run(self,max_count,mutable_prompt,immutable_prompt,random_sample):
-        print('#运行的函数',mutable_prompt,immutable_prompt,max_count,random_sample)
+        # print('#运行的函数',mutable_prompt,immutable_prompt,max_count,random_sample)
        
        # Split the text into an array of words
        words1 = mutable_prompt.split("\n")
@@ -106,6 +333,8 @@ class RandomPrompt:
            w1=w1.strip()
            for w2 in words2:
                w2=w2.strip()
+                if '``' not in w2:
+                    w2=w2+',``'
                if w1!='' and w2!='':
                    prompts.append(w2.replace('``', w1))
                pbar.update(1)
@@ -119,6 +348,8 @@ class RandomPrompt:
        else:
            prompts = prompts[:min(max_count,len(prompts))]

+        prompts= [elem.strip() for elem in prompts if elem.strip()]
+
        # return (new_prompt)
        return {"ui": {"prompts": prompts}, "result": (prompts,)}

@@ -126,62 +357,62 @@ class RandomPrompt:



-class RunWorkflow:
-    @classmethod
-    def INPUT_TYPES(s):
-        return {
-            "required": {
-                "workflow": ("STRING", {
-                            "multiline": False, 
-                            "default": ''
-                          }),
-                "prompt": ("STRING", {
-                            "multiline": False, 
-                            "default": ''
-                          }),
-                 "image": ("IMAGE",),
-                 "input_node": ("STRING", {
-                            "multiline": False, 
-                            "default": ''
-                          }),
-                 "output_node": ("STRING", {
-                            "multiline": False, 
-                            "default": ''
-                          }),
-                },
+# class RunWorkflow:
+#     @classmethod
+#     def INPUT_TYPES(s):
+#         return {
+#             "required": {
+#                 "workflow": ("STRING", {
+#                             "multiline": False, 
+#                             "default": ''
+#                           }),
+#                 "prompt": ("STRING", {
+#                             "multiline": False, 
+#                             "default": ''
+#                           }),
+#                  "image": ("IMAGE",),
+#                  "input_node": ("STRING", {
+#                             "multiline": False, 
+#                             "default": ''
+#                           }),
+#                  "output_node": ("STRING", {
+#                             "multiline": False, 
+#                             "default": ''
+#                           }),
+#                 },
                
-            }
+#             }
    
    

-    RETURN_TYPES = ("IMAGE","STRING",)
+#     RETURN_TYPES = ("IMAGE","STRING",)

-    FUNCTION = "run"
+#     FUNCTION = "run"

-    CATEGORY = "♾️Mixlab/workflow"
+#     CATEGORY = "♾️Mixlab/workflow"

-    OUTPUT_IS_LIST = (True,)
-    OUTPUT_NODE = True
+#     OUTPUT_IS_LIST = (True,)
+#     OUTPUT_NODE = True


-    # 运行的函数
-    def run(self,workflow,prompt,image,input_node,output_node):
-        print('#运行的函数',prompt,image,input_node,output_node)
-        workflow=json.loads(workflow)
-        input_node=input_node.split(".")
-        workflow[input_node[0]][input_node[1]][input_node[2]]=prompt
+#     # 运行的函数
+#     def run(self,workflow,prompt,image,input_node,output_node):
+#         print('#运行的函数',prompt,image,input_node,output_node)
+#         workflow=json.loads(workflow)
+#         input_node=input_node.split(".")
+#         workflow[input_node[0]][input_node[1]][input_node[2]]=prompt

-        workflow_new={}
-        # 遍历，seed设为随机
-        for key, value in workflow.items():
-            if 'inputs' in value:
-                if 'seed' in value['inputs']:
-                    value['inputs']['seed']= random.randint(1, 18446744073709551614)
-            workflow_new[key]=value
+#         workflow_new={}
+#         # 遍历，seed设为随机
+#         for key, value in workflow.items():
+#             if 'inputs' in value:
+#                 if 'seed' in value['inputs']:
+#                     value['inputs']['seed']= random.randint(1, 18446744073709551614)
+#             workflow_new[key]=value

-        queue_prompt(workflow_new)
-        print('#运行的函数',workflow_new[input_node[0]])
+#         queue_prompt(workflow_new)
+#         print('#运行的函数',workflow_new[input_node[0]])

-        # return (new_prompt)
-        return  {"ui":{"images": []},"result": ([image],['text'],)}
+#         # return (new_prompt)
+#         return  {"ui":{"images": []},"result": ([image],['text'],)}

@@ -93,7 +93,7 @@ class ScreenShareNode:
    RETURN_NAMES = ("IMAGE","PROMPT","FLOAT","INT")
    FUNCTION = "run"

-    CATEGORY = "♾️Mixlab/image"
+    CATEGORY = "♾️Mixlab/Image"

    # INPUT_IS_LIST = True
    OUTPUT_IS_LIST = (False,False,False,False)
@@ -118,7 +118,7 @@ class FloatingVideo:
    OUTPUT_NODE = True
    FUNCTION = "run"

-    CATEGORY = "♾️Mixlab/image"
+    CATEGORY = "♾️Mixlab/Image"

    # INPUT_IS_LIST = True
    # OUTPUT_IS_LIST = (False,False,)
@@ -0,0 +1,271 @@
+from transformers import pipeline, set_seed,AutoTokenizer, AutoModelForSeq2SeqLM
+import random
+import re
+
+import os,sys
+import folder_paths
+
+# from PIL import Image
+# import importlib.util
+
+import comfy.utils
+# import numpy as np
+import torch
+import random
+
+global _available
+_available=True
+
+
+text_generator_model_path=os.path.join(folder_paths.models_dir, "prompt_generator/text2image-prompt-generator")
+if not os.path.exists(text_generator_model_path):
+    print(f"## text_generator_model not found: {text_generator_model_path}, pls download from https://huggingface.co/succinctly/text2image-prompt-generator/tree/main")
+    text_generator_model_path='succinctly/text2image-prompt-generator'
+
+zh_en_model_path=os.path.join(folder_paths.models_dir, "prompt_generator/opus-mt-zh-en")
+if not os.path.exists(zh_en_model_path):
+    print(f"## zh_en_model not found: {zh_en_model_path}, pls download from https://huggingface.co/Helsinki-NLP/opus-mt-zh-en/tree/main")
+    zh_en_model_path='Helsinki-NLP/opus-mt-zh-en'
+
+
+
+def translate(zh_en_tokenizer,zh_en_model,texts):
+    with torch.no_grad():
+        encoded = zh_en_tokenizer(texts, return_tensors="pt")
+        encoded.to(zh_en_model.device)
+        sequences = zh_en_model.generate(**encoded)
+        return zh_en_tokenizer.batch_decode(sequences, skip_special_tokens=True)
+
+input = "青春不能回头，所以青春没有终点。 ——《火影忍者》"
+# print(input, translate(input))
+
+
+def text_generate(text_pipe,input,seed=None):
+    
+    if seed==None:
+        seed = random.randint(100, 1000000)
+    
+    set_seed(seed)
+
+    for count in range(6):    
+        sequences = text_pipe(input, max_length=random.randint(60, 90), num_return_sequences=8)
+        list = []
+        for sequence in sequences:
+            line = sequence['generated_text'].strip()
+            if line != input and len(line) > (len(input) + 4) and line.endswith((":", "-", "—")) is False:
+                list.append(line)
+
+        result = "\n".join(list)
+        result = re.sub('[^ ]+\.[^ ]+','', result)
+        result = result.replace("<", "").replace(">", "")
+        if result != "":
+            return result
+        if count == 5:
+            return result
+
+# input = "Youth can't turn back, so there's no end to youth."
+# print(input, text_generate(input))
+
+    
+import re
+
+def correct_prompt_syntax(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()
+
+    # 分词
+    prompt_elements = prompt.split(',')
+
+    for element in prompt_elements:
+        element = element.strip()
+
+        # 处理空元素
+        if not element:
+            continue
+
+        # 检查并处理圆括号、方括号、尖括号
+        if element[0] in '([':
+            corrected_element = balance_brackets(element, '(', ')') if element[0] == '(' else balance_brackets(element, '[', ']')
+        elif element[0] == '<':
+            corrected_element = balance_brackets(element, '<', '>')
+        else:
+            # 删除开头的右括号或右方括号
+            corrected_element = element.lstrip(')]')
+
+        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
+
+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)
+
+        
+        
+class ChinesePrompt:
+
+    global _available
+    available=_available
+    
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": {
+               "text": ("STRING",{"multiline": True,"default": "", "dynamicPrompts": False}),
+               "generation": (["on","off"],{"default": "off"}), 
+                             },
+               
+                "optional":{
+                    "seed":("INT", {"default": 100, "min": 100, "max": 1000000}), 
+                    
+                },
+
+                }
+    
+    RETURN_TYPES = ("STRING",)
+    RETURN_NAMES = ("prompt",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/Prompt"
+    OUTPUT_NODE = True
+    INPUT_IS_LIST = True
+    OUTPUT_IS_LIST = (True,)
+
+    global text_pipe,zh_en_model,zh_en_tokenizer
+
+    text_pipe= None
+    zh_en_model=None
+    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)
+
+        text = correct_prompt_syntax(text[0])
+
+        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)
+        
+        zh_en_model.to("cuda" if torch.cuda.is_available() else "cpu")
+            # zh_en_tokenizer.to("cuda" if torch.cuda.is_available() else "cpu")
+        
+        text_pipe=pipeline('text-generation', model=text_generator_model_path,device="cuda" if torch.cuda.is_available() else "cpu")
+        
+        # text_pipe.model.to("cuda" if torch.cuda.is_available() else "cpu")
+
+        prompt_result=[]
+
+        # print('zh_en_model device',zh_en_model.device,text_pipe.model.device,torch.cuda.current_device() )
+        en_text=translate(zh_en_tokenizer,zh_en_model,text)
+        
+        zh_en_model.to('cpu')
+        print("test en_text",en_text)
+        # en_text.to("cuda" if torch.cuda.is_available() else "cpu")
+
+        pbar.update(1)
+        for t in en_text:
+            if generation=='on':
+                prompt =text_generate(text_pipe,t,seed)
+                # 多条，还是单条
+                lines = prompt.split("\n")
+                longest_line = max(lines, key=len)
+                # print(longest_line)
+                prompt_result.append(longest_line)
+            else:
+                prompt_result.append(t)
+            pbar.update(1)
+
+        text_pipe.model.to('cpu')
+        prompt_result = [correct_prompt_syntax(prompt_result[0])]
+        
+        return {
+            "ui":{
+                    "prompt": prompt_result
+                },
+            "result": (prompt_result,)}
+
+
+class PromptGenerate:
+
+    global _available
+    available=_available
+    
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": {
+            "text": ("STRING",{"multiline": True,"default": "", "dynamicPrompts": False}),
+                             },
+
+                "optional":{
+                    "multiple": (["off","on"],), 
+                    "seed":("INT", {"default": 100, "min": 100, "max": 1000000}), 
+                },
+
+                }
+    
+    RETURN_TYPES = ("STRING",)
+    RETURN_NAMES = ("prompt",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/Prompt"
+    OUTPUT_NODE = True
+    INPUT_IS_LIST = True
+    OUTPUT_IS_LIST = (True,)
+
+    global text_pipe
+
+    text_pipe= None
+    # 
+
+    def run(self,text,multiple,seed):
+        global text_pipe
+
+        seed=seed[0]
+
+        multiple=multiple[0]
+
+        # 进度条
+        pbar = comfy.utils.ProgressBar(len(text))
+        
+        text_pipe=pipeline('text-generation', model=text_generator_model_path,device="cuda" if torch.cuda.is_available() else "cpu")
+        
+        prompt_result=[]
+
+        for t in text:
+            prompt =text_generate(text_pipe,t,seed)
+            prompt = prompt.split("\n")
+            if multiple=='off':
+                prompt = [max(prompt, key=len)]
+            
+            for p in prompt:
+                prompt_result.append(p)
+            pbar.update(1)
+
+        text_pipe.model.to('cpu')
+
+        return {
+            "ui":{
+                    "prompt": prompt_result
+                },
+            "result": (prompt_result,)}
@@ -1,8 +1,98 @@
-import os
-import re,random
+import os,platform
+import re,random,json
+from PIL import Image
+import numpy as np
 # FONT_PATH= os.path.abspath(os.path.join(os.path.dirname(__file__),'../assets/王汉宗颜楷体繁.ttf'))
-
+import folder_paths
 import matplotlib.font_manager as fm
+import torch
+
+def recursive_search(directory, excluded_dir_names=None):
+    if not os.path.isdir(directory):
+        return [], {}
+
+    if excluded_dir_names is None:
+        excluded_dir_names = []
+
+    result = []
+    dirs = {directory: os.path.getmtime(directory)}
+    for dirpath, subdirs, filenames in os.walk(directory, followlinks=True, topdown=True):
+        subdirs[:] = [d for d in subdirs if d not in excluded_dir_names]
+        for file_name in filenames:
+            relative_path = os.path.relpath(os.path.join(dirpath, file_name), directory)
+            result.append(relative_path)
+        for d in subdirs:
+            path = os.path.join(dirpath, d)
+            dirs[path] = os.path.getmtime(path)
+    return result, dirs
+
+def filter_files_extensions(files, extensions):
+    return sorted(list(filter(lambda a: os.path.splitext(a)[-1].lower() in extensions or len(extensions) == 0, files)))
+
+
+def get_system_font_path():
+    ps=[]
+    system = platform.system()
+    if system == "Windows":
+        ps.append(os.path.join(os.environ["WINDIR"], "Fonts"))
+    elif system == "Darwin":
+        ps.append(os.path.join("/Library", "Fonts"))
+    elif system == "Linux":
+        ps.append(os.path.join("/usr", "share", "fonts"))
+        ps.append(os.path.join("/usr", "local", "share", "fonts"))
+    ps=[p for p in ps if os.path.exists(p)]
+    file_paths=[]
+    for f in ps:
+        result, dirs=recursive_search(f)
+        for r in result:
+            file_paths.append(r)
+    file_paths=filter_files_extensions(file_paths,[".otf", ".ttf"])
+
+    return file_paths
+
+
+
+# import json
+# import hashlib
+
+
+# def get_json_hash(json_content):
+#     json_string = json.dumps(json_content, sort_keys=True)
+#     hash_object = hashlib.sha256(json_string.encode())
+#     hash_value = hash_object.hexdigest()
+#     return hash_value
+    
+
+
+def tensor2pil(image):
+    return Image.fromarray(np.clip(255. * image.cpu().numpy().squeeze(), 0, 255).astype(np.uint8))
+
+
+def create_temp_file(image):
+    output_dir = folder_paths.get_temp_directory()
+
+    (
+            full_output_folder,
+            filename,
+            counter,
+            subfolder,
+            _,
+        ) = folder_paths.get_save_image_path('tmp', output_dir)
+
+    
+    im=tensor2pil(image)
+ 
+    image_file = f"{filename}_{counter:05}.png"
+     
+    image_path=os.path.join(full_output_folder, image_file)
+
+    im.save(image_path,compress_level=4)
+
+    return [{
+                "filename": image_file,
+                "subfolder": subfolder,
+                "type": "temp"
+                }]

 def get_font_files(directory):
    font_files = {}
@@ -16,14 +106,14 @@ def get_font_files(directory):

    # 尝试获取系统字体
    try:
-        font_paths = fm.findSystemFonts()
-        for path in font_paths:
+        font_paths = get_system_font_path()
+        for file in font_paths:
            try:
-                font_prop = fm.FontProperties(fname=path)
-                font_name = font_prop.get_name()
-                font_files[font_name] = path
+                font_name = os.path.splitext(file)[0]
+                font_path = file
+                font_files[font_name] = os.path.abspath(font_path)
            except Exception as e:
-                print(f"Error processing font {path}: {e}")
+                print(f"Error processing font {file}: {e}")
    except Exception as e:
        print(f"Error finding system fonts: {e}")

@@ -35,6 +125,21 @@ font_files = get_font_files(r_directory)
 # print(font_files)


+def flatten_list(nested_list):
+    flat_list = []
+    for item in nested_list:
+        if isinstance(item, list):
+            flat_list.extend(flatten_list(item))
+        else:
+            if torch.is_tensor(item):
+                print('item.shape',item.shape)
+                for i in range(item.shape[0]):
+                    flat_list.append(item[i:i + 1, ...])
+            else:
+                flat_list.append(item)
+    return flat_list
+
+
 class ColorInput:
    @classmethod
    def INPUT_TYPES(s):
@@ -44,18 +149,23 @@ class ColorInput:
                             },
                }
    
-    RETURN_TYPES = ("STRING",)
-    # RETURN_NAMES = ("WIDTH","HEIGHT","X","Y",)
+    RETURN_TYPES = ("STRING","INT","INT","INT","FLOAT",)
+    RETURN_NAMES = ("hex","r","g","b","a",)

    FUNCTION = "run"

-    CATEGORY = "♾️Mixlab/utils"
+    CATEGORY = "♾️Mixlab/Utils"

    INPUT_IS_LIST = False
-    OUTPUT_IS_LIST = (False,False,)
+    OUTPUT_IS_LIST = (False,False,False,False,False,)

    def run(self,color):
-        return (color,)
+        h=color['hex']
+        r=color['r']
+        g=color['g']
+        b=color['b']
+        a=color['a']
+        return (h,r,g,b,a,)



@@ -73,13 +183,13 @@ class FontInput:

    FUNCTION = "run"

-    CATEGORY = "♾️Mixlab/utils"
+    CATEGORY = "♾️Mixlab/Utils"

    INPUT_IS_LIST = False
-    OUTPUT_IS_LIST = (False,False,)
+    OUTPUT_IS_LIST = (False,)

    def run(self,font):
-
+        
        return (font_files[font],)
    
 class TextToNumber:
@@ -103,7 +213,7 @@ class TextToNumber:

    FUNCTION = "run"

-    CATEGORY = "♾️Mixlab/utils"
+    CATEGORY = "♾️Mixlab/Utils"

    INPUT_IS_LIST = False
    OUTPUT_IS_LIST = (False,)
@@ -120,6 +230,162 @@ class TextToNumber:
            result= random.randint(1, 10000000000)
        return {"ui": {"text": [text],"num":[result]}, "result": (result,)}
    
+
+   
+class FloatSlider:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": {
+                    "number":("FLOAT", {
+                        "default": 0, 
+                        "min": 0, #Minimum value
+                        "max": 0xffffffffffffffff, #Maximum value
+                        "step": 0.001, #Slider's step
+                        "display": "slider" # Cosmetic only: display as "number" or "slider"
+                    }),
+                    "min_value":("FLOAT", {
+                        "default": 0, 
+                        "min": -0xffffffffffffffff, 
+                        "max": 0xffffffffffffffff,
+                        "step": 0.001, 
+                        "display": "number"  
+                    }),
+                    "max_value":("FLOAT", {
+                            "default": 1, 
+                            "min": -0xffffffffffffffff,
+                            "max": 0xffffffffffffffff,
+                            "step": 0.001, 
+                            "display": "number"  
+                        }),
+                    "step":("FLOAT", {
+                            "default": 0.001, 
+                            "min": -0xffffffffffffffff,
+                            "max": 0xffffffffffffffff,
+                            "step": 0.001, 
+                            "display": "number"  
+                        }),
+                             },
+                }
+    
+    RETURN_TYPES = ("FLOAT",) 
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/Utils"
+
+    INPUT_IS_LIST = False
+    OUTPUT_IS_LIST = (False,)
+
+    def run(self, number, min_value, max_value, step):
+        if number < min_value:
+            number = min_value
+        elif number > max_value:
+            number = max_value
+        scaled_number = (number - min_value) / (max_value - min_value)
+        return (scaled_number,)
+    
+  
+class IntNumber:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": {
+                    "number":("INT", {
+                        "default": 0, 
+                        "min": -1, #Minimum value
+                        "max": 0xffffffffffffffff,
+                        "step": 1, 
+                        "display": "number"
+                    }),
+                    "min_value":("INT", {
+                        "default": 0, 
+                        "min": -0xffffffffffffffff, 
+                        "max": 0xffffffffffffffff,
+                        "step": 1, 
+                        "display": "number"  
+                    }),
+                    "max_value":("INT", {
+                            "default": 1, 
+                            "min": -0xffffffffffffffff,
+                            "max": 0xffffffffffffffff,
+                            "step": 1, 
+                            "display": "number"  
+                        }),
+                    "step":("INT", {
+                            "default": 1, 
+                            "min": -0xffffffffffffffff,
+                            "max": 0xffffffffffffffff,
+                            "step":1,
+                            "display": "number"  
+                        }),
+                             },
+                }
+    
+    RETURN_TYPES = ("INT",) 
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/Utils"
+
+    INPUT_IS_LIST = False
+    OUTPUT_IS_LIST = (False,)
+
+    def run(self,number,min_value,max_value,step):
+        if number < min_value:
+            number= min_value
+        elif number > max_value:
+            number= max_value
+        return (number,)
+
+class MultiplicationNode:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": {
+                    "numberA":(any_type,),
+                    "numberB":("FLOAT", {
+                        "default": 0, 
+                        "min": -1, #Minimum value
+                        "max": 0xffffffffffffffff,
+                        "step": 0.1, #Slider's step
+                        "display": "number" # Cosmetic only: display as "number" or "slider"
+                    })
+                             },
+                }
+    
+    RETURN_TYPES = ("FLOAT","INT",) 
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/Utils"
+
+    INPUT_IS_LIST = False
+    OUTPUT_IS_LIST = (False,False,)
+
+    def run(self,numberA,numberB):
+        b=int(numberA*numberB)
+        a=float(numberA*numberB)
+        return (a,b,) 
+
+class TextInput:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": {
+                    "text": ("STRING",{"multiline": True,"default": ""}),
+                             },
+                }
+    
+    RETURN_TYPES = ("STRING",) 
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/Utils"
+
+    INPUT_IS_LIST = False
+    OUTPUT_IS_LIST = (False,)
+
+    def run(self,text):
+       
+        return (text,)
+    
 # 接收一个值，然后根据字符串或数值长度计算延迟时间，用户可以自定义延迟"字/s"，延迟之后将转化

 import comfy.samplers
@@ -141,7 +407,7 @@ class DynamicDelayProcessor:

    @classmethod
    def INPUT_TYPES(cls):
-        print("print INPUT_TYPES",cls)
+        # print("print INPUT_TYPES",cls)
        return {
            "required":{
                    "delay_seconds":("INT",{
@@ -185,7 +451,7 @@ class DynamicDelayProcessor:
    RETURN_TYPES = (any_type,)
    RETURN_NAMES = ('output',)

-    CATEGORY = "♾️Mixlab/utils"
+    CATEGORY = "♾️Mixlab/Utils"
    def run(self,any_input,delay_seconds,delay_by_text,words_per_seconds,replace_output,replace_value):
        # print(f"Delay text:",delay_by_text )
        # 获取开始时间戳
@@ -210,3 +476,232 @@ class DynamicDelayProcessor:
        # 根据 replace_output 决定输出值
        return (max(0, replace_value),) if replace_output == "enable" else (any_input,)
        
+
+
+
+# app 配置节点
+class AppInfo:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": { 
+                    "name": ("STRING",{"multiline": False,"default": "Mixlab-App","dynamicPrompts": False}),
+                    "input_ids":("STRING",{"multiline": True,"default": "\n".join(["1","2","3"]),"dynamicPrompts": False}),
+                    "output_ids":("STRING",{"multiline": True,"default": "\n".join(["5","9"]),"dynamicPrompts": False}),
+                             },
+
+                "optional":{
+                    "IMAGE": ("IMAGE",),
+                    "description":("STRING",{"multiline": True,"default": "","dynamicPrompts": False}),
+                    "version":("INT", {
+                        "default": 1, 
+                        "min": 1, 
+                        "max": 10000, 
+                        "step": 1, 
+                        "display": "number"  
+                    }),
+                    "share_prefix":("STRING",{"multiline": False,"default": "","dynamicPrompts": False}),
+                    "link":("STRING",{"multiline": False,"default": "https://","dynamicPrompts": False}),
+                    "category":("STRING",{"multiline": False,"default": "","dynamicPrompts": False}),
+                    "auto_save": (["enable","disable"],),
+                }
+
+                }
+    
+    RETURN_TYPES = ()
+    # RETURN_NAMES = ("IMAGE",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab"
+
+    OUTPUT_NODE = True
+    INPUT_IS_LIST = True
+    # OUTPUT_IS_LIST = (True,)
+
+    def run(self,name,input_ids,output_ids,IMAGE,description,version,share_prefix,link,category,auto_save):
+        name=name[0]
+        
+        im=None
+        if IMAGE:
+            im=IMAGE[0][0]
+            #TODO batch 的方式需要处理
+            im=create_temp_file(im)
+        # image [img,] img[batch,w,h,a] 列表里面是batch，
+
+        input_ids=input_ids[0]
+        output_ids=output_ids[0]
+        description=description[0]
+        version=version[0]
+        share_prefix=share_prefix[0]
+        link=link[0]
+        category=category[0]
+        
+        # id=get_json_hash([name,im,input_ids,output_ids,description,version])
+
+        return {"ui": {"json": [name,im,input_ids,output_ids,description,version,share_prefix,link,category]}, "result": ()}
+    
+
+    
+
+
+class SwitchByIndex:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "A":(any_type,),
+                "B":(any_type,),
+                "index":("INT", {
+                        "default": -1, 
+                        "min": -1, 
+                        "max": 1000, 
+                        "step": 1, 
+                        "display": "number"  
+                    }),
+                 "flat": (['off',"on"],),
+            }
+        }
+
+    RETURN_TYPES = (any_type,)
+    RETURN_NAMES = ("C",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/Utils"
+
+    INPUT_IS_LIST = True
+    OUTPUT_IS_LIST = (True,)
+
+    def run(self, A,B,index,flat):
+
+        flat=flat[0]
+
+        C=[]
+        index=index[0]
+
+        for a in A:    
+            C.append(a)
+        for b in B:
+            C.append(b)
+
+        if flat=='on':
+            C=flatten_list(C)
+
+        if index>-1:
+            try:
+                C=[C[index]]
+            except Exception as e:
+                C=[]
+        
+        return (C,)
+
+
+
+class LimitNumber:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "number":(any_type,),
+                "min_value":("INT", {
+                        "default": 0, 
+                        "min": 0, 
+                        "max": 0xffffffffffffffff,
+                        "step": 1, 
+                        "display": "number"  
+                    }),
+                "max_value":("INT", {
+                        "default": 1, 
+                        "min": 1, 
+                        "max": 0xffffffffffffffff,
+                        "step": 1, 
+                        "display": "number"  
+                    }),
+            }
+        }
+
+    RETURN_TYPES = (any_type,)
+    RETURN_NAMES = ("number",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/Utils"
+
+    INPUT_IS_LIST = False
+    OUTPUT_IS_LIST = (False,)
+
+    def run(self, number, min_value, max_value):
+        nn=number
+
+        if isinstance(number, int):
+            min_value=int(min_value)
+            max_value=int(max_value)
+        if isinstance(number, float):
+            min_value=float(min_value)
+            max_value=float(max_value)
+
+        if number < min_value:
+            nn= min_value
+        elif number > max_value:
+            nn= max_value
+        
+        return (nn,)
+
+
+
+class ListStatistics:
+    @staticmethod
+    def count_types(lst):
+        type_count = {}
+
+        for item in lst:
+            item_type = type(item).__name__
+            if item_type not in type_count:
+                type_count[item_type] = []
+
+            if item_type in ['dict', 'str', 'int', 'float']:
+                type_count[item_type].append(item)
+
+        return type_count
+
+# # 示例列表
+# my_list = [1, 'hello', {'name': 'John'}, 3.14, {'age': 25}, 'world', 10]
+
+# # 创建ListStatistics对象
+# list_stats = ListStatistics()
+
+# # 调用count_types方法进行统计
+# result = list_stats.count_types(my_list)
+
+# # 输出结果
+# for item_type, values in result.items():
+#     print(item_type + ':')
+#     for value in values:
+#         print(value)
+#     print('---')
+
+class TESTNODE_:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": { "ANY":(any_type,), },
+                }
+    
+    RETURN_TYPES = (any_type,)
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/__TEST"
+
+    OUTPUT_NODE = True
+    INPUT_IS_LIST = True
+    OUTPUT_IS_LIST = (True,)
+
+    def run(self,ANY):
+        print(ANY)
+        # data=ANY
+        list_stats = ListStatistics()
+
+        # 调用count_types方法进行统计
+        result = list_stats.count_types(ANY)
+            
+        return {"ui": {"data": result,"type":[str(type(ANY[0]))]}, "result": (ANY,)}
@@ -145,7 +145,7 @@ class VAELoader:
    RETURN_TYPES = ("VAE",)
    FUNCTION = "load_vae"

-    CATEGORY = "♾️Mixlab/_test"
+    CATEGORY = "♾️Mixlab/__TEST"

    #TODO: scale factor?
    def load_vae(self, vae_name):
@@ -165,7 +165,7 @@ class VAEDecode:
    RETURN_TYPES = ("IMAGE",)
    FUNCTION = "decode"

-    CATEGORY = "♾️Mixlab/_test"
+    CATEGORY = "♾️Mixlab/__TEST"

    def decode(self, vae, samples):
        image = vae.decode(samples["samples"].to("cuda:0"))
@@ -3,4 +3,6 @@ pyOpenSSL
 watchdog
 opencv-python-headless
 matplotlib
-openai
+openai
+# simple-lama-inpainting
+# clip-interrogator==0.6.0
@@ -196,6 +196,9 @@ app.registerExtension({
              }
              if (bg) {
                data.bg_image = await parseImage(bg)
+                if (!data.bg_image.match('data:image/')) {
+                  delete data.bg_image
+                }
              }

              if (material) {
@@ -0,0 +1,435 @@
+import { app } from '../../../scripts/app.js'
+import { $el } from '../../../scripts/ui.js'
+import { api } from '../../../scripts/api.js'
+
+function get_position_style (ctx, widget_width, y, node_height) {
+  const MARGIN = 12 // the margin around the html element
+
+  /* Create a transform that deals with all the scrolling and zooming */
+  const elRect = ctx.canvas.getBoundingClientRect()
+  const transform = new DOMMatrix()
+    .scaleSelf(
+      elRect.width / ctx.canvas.width,
+      elRect.height / ctx.canvas.height
+    )
+    .multiplySelf(ctx.getTransform())
+    .translateSelf(MARGIN, MARGIN + y)
+
+  return {
+    transformOrigin: '0 0',
+    transform: transform,
+    left: `0`,
+    top: `0`,
+    cursor: 'pointer',
+    position: 'absolute',
+    maxWidth: `${widget_width - MARGIN * 2}px`,
+    // maxHeight: `${node_height - MARGIN * 2}px`, // we're assuming we have the whole height of the node
+    width: `${widget_width - MARGIN * 2}px`,
+    // height: `${node_height * 0.3 - MARGIN * 2}px`,
+    // background: '#EEEEEE',
+    display: 'flex',
+    flexDirection: 'row',
+    // alignItems: 'center',
+    justifyContent: 'flex-start'
+  }
+}
+
+async function drawImageToCanvas (imageUrl) {
+  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 canvasWidth = img.width * scaleFactor
+      var canvasHeight = img.height * scaleFactor
+
+      canvas.width = canvasWidth
+      canvas.height = canvasHeight
+
+      ctx.drawImage(img, 0, 0, canvasWidth, canvasHeight)
+
+      resolve()
+    }
+
+    img.onerror = function () {
+      reject(new Error('Failed to load image'))
+    }
+
+    img.src = imageUrl
+  })
+
+  var base64 = canvas.toDataURL('image/jpeg')
+  // console.log(base64); // 输出Base64数据
+  return base64
+  // 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 = []) {
+  const data = jsonData
+  const input = []
+  const output = []
+  const seed = {}
+
+  for (const id in data) {
+    if (data.hasOwnProperty(id)) {
+      let node = app.graph.getNodeById(id)
+      if (inputIds.includes(id)) {
+        // let node = app.graph.getNodeById(id)
+        let options = []
+        // 模型
+        try {
+          if (node.type === 'CheckpointLoaderSimple') {
+            options = node.widgets.filter(w => w.name === 'ckpt_name')[0]
+              .options.values
+          } else if (node.type === 'LoraLoader') {
+            options = node.widgets.filter(w => w.name === 'lora_name')[0]
+              .options.values
+          }
+        } catch (error) {}
+
+        if (node.type == 'IntNumber' || node.type == 'FloatSlider') {
+          // min max step
+          let [v, min, max, step] = Array.from(node.widgets, w => w.value)
+          options = { min, max, step }
+          // node.widgets.filter(w => w.type === 'number')[0].options
+        }
+
+        if (node.type == 'PromptSlide') {
+          // min max step
+          options = node.widgets.filter(w => w.type === 'slider')[0].options
+          // 备选的keywords清单
+          try {
+            let keywords = node.widgets.filter(w => w.name === 'upload')[0]
+              .value
+            keywords = JSON.parse(keywords)
+            options.keywords = keywords
+          } catch (error) {
+            console.log(error)
+          }
+        }
+
+        if (node.type == 'Color') {
+        }
+
+        input[inputIds.indexOf(id)] = {
+          ...data[id],
+          title: node.title,
+          id,
+          options
+        }
+        // input.push()
+      }
+      if (outputIds.includes(id)) {
+        // let node = app.graph.getNodeById(id)
+        // output.push()
+        output[outputIds.indexOf(id)] = { ...data[id], title: node.title, id }
+      }
+
+      if (node.type === 'KSampler' || node.type == 'SamplerCustom') {
+        // seed 的类型收集
+        try {
+          seed[id] = node.widgets.filter(
+            w => w.name === 'seed' || w.name == 'noise_seed'
+          )[0].linkedWidgets[0].value
+        } catch (error) {}
+      }
+    }
+  }
+
+  return { input, output, seed }
+}
+
+function getUrl () {
+  let api_host = `${window.location.hostname}:${window.location.port}`
+  let api_base = ''
+  let url = `${window.location.protocol}//${api_host}${api_base}`
+  return url
+}
+
+const getLocalData = key => {
+  let data = {}
+  try {
+    data = JSON.parse(localStorage.getItem(key)) || {}
+  } catch (error) {
+    return {}
+  }
+  return data
+}
+
+async function save_app (json) {
+  let url = getUrl()
+
+  const res = await fetch(`${url}/mixlab/workflow`, {
+    method: 'POST',
+    body: JSON.stringify({
+      data: json,
+      task: 'save_app',
+      filename: json.app.filename,
+      category: json.app.category
+    })
+  })
+  return await res.json()
+}
+
+function downloadJsonFile (jsonData, fileName = 'mix_app.json') {
+  const dataString = JSON.stringify(jsonData)
+  const blob = new Blob([dataString], { type: 'application/json' })
+  const url = URL.createObjectURL(blob)
+
+  const link = document.createElement('a')
+  link.href = url
+  link.download = fileName
+  link.click()
+
+  // 释放URL对象
+  setTimeout(() => {
+    URL.revokeObjectURL(url)
+  }, 0)
+}
+
+async function save (json, download = false, showInfo = true) {
+  console.log('####SAVE', json[0])
+  const name = json[0],
+    version = json[5],
+    share_prefix = json[6], //用于分享的功能扩展
+    link = json[7], //用于创建界面上的跳转链接
+    category = json[8] || '', //用于分类
+    description = json[4],
+    inputIds = json[2].split('\n').filter(f => f),
+    outputIds = json[3].split('\n').filter(f => f)
+
+  const iconData = json[1][0]
+  let { filename, subfolder, type } = iconData
+  let iconUrl = api.apiURL(
+    `/view?filename=${encodeURIComponent(
+      filename
+    )}&type=${type}&subfolder=${subfolder}${app.getPreviewFormatParam()}${app.getRandParam()}`
+  )
+
+  try {
+    let data = await app.graphToPrompt()
+
+    const { input, output, seed } = extractInputAndOutputData(
+      data.output,
+      inputIds,
+      outputIds
+    )
+
+    data.app = {
+      name,
+      description,
+      version,
+      input,
+      output,
+      seed, //控制是fixed 还是random
+      share_prefix,
+      link,
+      category,
+      filename: `${name}_${version}.json`
+    }
+
+    try {
+      data.app.icon = await drawImageToCanvas(iconUrl)
+    } catch (error) {}
+    // console.log(data.app)
+    // let http_workflow = app.graph.serialize()
+    await save_app(data)
+    if (download) {
+      await downloadJsonFile(data, data.app.filename)
+    }
+
+    if (showInfo) {
+      let open = window.confirm(
+        `You can now access the standalone application on a new page!\n${getUrl()}/mixlab/app?filename=${encodeURIComponent(
+          data.app.filename
+        )}&category=${encodeURIComponent(data.app.category)}`
+      )
+      if (open)
+        window.open(
+          `${getUrl()}/mixlab/app?filename=${encodeURIComponent(
+            data.app.filename
+          )}&category=${encodeURIComponent(data.app.category)}`
+        )
+    }
+  } catch (error) {
+    console.log('###error', error)
+  }
+}
+
+function getInputsAndOutputs () {
+  const inputs =
+      `LoadImage CLIPTextEncode PromptSlide TextInput_ Color FloatSlider IntNumber CheckpointLoaderSimple LoraLoader`.split(
+        ' '
+      ),
+    outputs = `PreviewImage SaveImage ShowTextForGPT VHS_VideoCombine`.split(
+      ' '
+    )
+
+  let inputsId = [],
+    outputsId = []
+
+  for (let node of app.graph._nodes) {
+    if (inputs.includes(node.type)) {
+      inputsId.push(node.id)
+    }
+
+    if (outputs.includes(node.type)) {
+      outputsId.push(node.id)
+    }
+  }
+
+  return {
+    input: inputsId,
+    output: outputsId
+  }
+}
+
+app.registerExtension({
+  name: 'Mixlab.utils.AppInfo',
+  async beforeRegisterNodeDef (nodeType, nodeData, app) {
+    if (nodeType.comfyClass == 'AppInfo') {
+      const orig_nodeCreated = nodeType.prototype.onNodeCreated
+      nodeType.prototype.onNodeCreated = function () {
+        orig_nodeCreated?.apply(this, arguments)
+        // console.log('#orig_nodeCreated', this)
+
+        // 自动计算workflow里哪些节点支持
+        let input_ids = this.widgets.filter(w => w.name == 'input_ids')[0],
+          output_ids = this.widgets.filter(w => w.name == 'output_ids')[0]
+
+        const { input, output } = getInputsAndOutputs()
+        input_ids.value = input.join('\n')
+        output_ids.value = output.join('\n')
+
+        const widget = {
+          type: 'div',
+          name: 'AppInfoRun',
+          draw (ctx, node, widget_width, y, widget_height) {
+            Object.assign(
+              this.div.style,
+              get_position_style(
+                ctx,
+                widget_width,
+                node.size[1] - widget_height,
+                node.size[1]
+              )
+            )
+          }
+        }
+
+        const style = `
+        flex-direction: row;
+        background-color: var(--comfy-input-bg);
+        border-radius: 8px;
+        border-color: var(--border-color);
+        border-style: solid;
+        color: var(--descrip-text);`
+
+        widget.div = $el('div', {})
+
+        const btn = document.createElement('button')
+        btn.innerText = 'Save & Open'
+        btn.style = style
+
+        btn.addEventListener('click', () => {
+          //   console.log('hahhah')
+          if (window._mixlab_app_json) {
+            save(window._mixlab_app_json)
+          } else {
+            alert('Please run the workflow before saving')
+            // app.queuePrompt(0, 1)
+            this.widgets.filter(w => w.name === 'version')[0].value += 1
+          }
+        })
+
+        const download = document.createElement('button')
+        download.innerText = 'Download For App'
+        download.style = style
+        download.style.marginLeft = '12px'
+
+        download.addEventListener('click', () => {
+          //   console.log('hahhah')
+          if (window._mixlab_app_json) {
+            save(window._mixlab_app_json, true)
+          } else {
+            alert('Please run the workflow before saving')
+            // app.queuePrompt(0, 1)
+            this.widgets.filter(w => w.name === 'version')[0].value += 1
+          }
+        })
+
+        document.body.appendChild(widget.div)
+        widget.div.appendChild(btn)
+        widget.div.appendChild(download)
+
+        this.addCustomWidget(widget)
+
+        const onRemoved = this.onRemoved
+        this.onRemoved = () => {
+          widget.div.remove()
+          return onRemoved?.()
+        }
+
+        this.serialize_widgets = true //需要保存参数
+
+        window._mixlab_app_json = null
+      }
+
+      const onExecuted = nodeType.prototype.onExecuted
+      nodeType.prototype.onExecuted = function (message) {
+        onExecuted?.apply(this, arguments)
+        console.log(message.json)
+        window._mixlab_app_json = message.json
+        try {
+          let a = this.widgets.filter(w => w.name === 'AppInfoRun')[0]
+          if (a) {
+            if (!a.value) a.value = 0
+            a.value += 1
+          }
+
+          const div = this.widgets.filter(w => w.div)[0].div
+          Array.from(
+            div.querySelectorAll('button'),
+            b => (b.style.background = 'yellow')
+          )
+        } catch (error) {}
+      }
+    }
+  },
+  async loadedGraphNode (node, app) {
+    console.log('#loadedGraphNode1111')
+    window._mixlab_app_json = null //切换workflow需要清空
+    if (node.type === 'AppInfo') {
+      let auto_save = node.widgets.filter(w => w.name == 'auto_save')[0]
+      if (auto_save) {
+        if (!['enable', 'disable'].includes(auto_save.value)) {
+          auto_save.value = 'enable'
+        }
+      }
+    }
+  }
+})
+
+api.addEventListener('execution_start', async ({ detail }) => {
+  console.log('#execution_start', detail)
+  window._mixlab_app_json = null
+})
+
+api.addEventListener('executed', async ({ detail }) => {
+  console.log('#executed', detail)
+  // window._mixlab_app_json=null;
+  const { output } = getInputsAndOutputs()
+  if (output.includes(parseInt(detail.node))) {
+    let appinfo = app.graph.findNodesByType('AppInfo')[0]
+    if (appinfo) {
+      let auto_save = appinfo.widgets.filter(w => w.name == 'auto_save')[0]
+      if (auto_save?.value === 'enable') {
+        // 自动保存
+        console.log('auto_save')
+        if (window._mixlab_app_json) save(window._mixlab_app_json, false, false)
+      }
+    }
+  }
+})
@@ -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 = 'v0.5.2'
+const version = 'v0.12.0'

 fetch(`https://api.github.com/repos/${repoOwner}/${repoName}/releases/latest`)
  .then(response => response.json())
@@ -0,0 +1,119 @@
+import { app } from '../../../scripts/app.js'
+// import { api } from '../../../scripts/api.js'
+import { ComfyWidgets } from '../../../scripts/widgets.js'
+import { $el } from '../../../scripts/ui.js'
+
+function getRandomElements (arr, num) {
+  var result = []
+  var len = arr.length
+
+  for (var i = 0; i < num; i++) {
+    var randomIndex = Math.floor(Math.random() * len)
+    result.push(arr[randomIndex])
+  }
+
+  return result
+}
+
+const createPrompt = (node, prompts, items, sample) => {
+  const w = ComfyWidgets['STRING'](
+    node,
+    'text',
+    ['STRING', { multiline: true }],
+    app
+  ).widget
+  w.inputEl.readOnly = true
+  w.inputEl.style.opacity = 0.6
+
+  w.value = typeof prompts === 'string' ? prompts : prompts.join('\n\n')
+
+  const w2 = ComfyWidgets['STRING'](
+    node,
+    'text',
+    ['STRING', { multiline: true }],
+    app
+  ).widget
+  w2.inputEl.readOnly = true
+  w2.inputEl.style.opacity = 0.6
+
+  w2.value = typeof items === 'string' ? items : JSON.stringify(items, null, 2)
+
+  const w3 = ComfyWidgets['STRING'](
+    node,
+    'text',
+    ['STRING', { multiline: true }],
+    app
+  ).widget
+  w3.inputEl.readOnly = true
+  w3.inputEl.style.opacity = 0.6
+  w3.value = typeof sample === 'string' ? sample : sample.join('\n\n')
+}
+
+app.registerExtension({
+  name: 'Mixlab.prompt.ClipInterrogator',
+  async beforeRegisterNodeDef (nodeType, nodeData, app) {
+    if (nodeData.name === 'ClipInterrogator') {
+      function populate (prompts, items, random_samples) {
+        if (this.widgets) {
+          for (let i = 0; i < this.widgets.length; i++) {
+            if (this.widgets[i].type !== 'combo') this.widgets[i].onRemove?.()
+          }
+          this.widgets.length = 2
+        }
+
+        createPrompt(this, prompts, items, random_samples)
+
+        // console.log('ClipInterrogator', w, w2)
+        requestAnimationFrame(() => {
+          const sz = this.computeSize()
+          if (sz[0] < this.size[0]) {
+            sz[0] = this.size[0]
+          }
+          if (sz[1] < this.size[1]) {
+            sz[1] = this.size[1]
+          }
+          this.onResize?.(sz)
+          app.graph.setDirtyCanvas(true, false)
+        })
+      }
+
+      // When the node is executed we will be sent the input text, display this in the widget
+      const onExecuted = nodeType.prototype.onExecuted
+      nodeType.prototype.onExecuted = function (message) {
+        onExecuted?.apply(this, arguments)
+        // console.log('##', message)
+        populate.call(
+          this,
+          message.prompt,
+          message.analysis,
+          message.random_samples
+        )
+      }
+
+      this.serialize_widgets = true //需要保存参数
+    }
+  },
+  async loadedGraphNode (node, app) {
+    // Fires every time a node is constructed
+    // You can modify widgets/add handlers/etc here
+
+    if (node.type === 'ClipInterrogator') {
+      try {
+        
+        let widgets_values = node.widgets_values
+        console.log(widgets_values )
+        try {
+          if (widgets_values[2] && widgets_values[3] && widgets_values[4])
+            createPrompt(
+              node,
+              widgets_values[2],
+              widgets_values[3],
+              widgets_values[4]
+            )
+        } catch (error) {
+          console.log(error)
+        }
+      } catch (error) {}
+    }
+  }
+})
@@ -256,6 +256,7 @@ app.registerExtension({
 			const onExecuted = nodeType.prototype.onExecuted;
 			nodeType.prototype.onExecuted = function (message) {
 				onExecuted?.apply(this, arguments);
+        console.log('##',message.text)
 				populate.call(this, message.text);
 			};

@@ -406,7 +406,9 @@ app.registerExtension({

        this.serialize_widgets = true //需要保存参数
      }
-    }
+    };
+
+ 
  },
  async loadedGraphNode (node, app) {
    // Fires every time a node is constructed
@@ -156,8 +156,8 @@ const parseSvg = async svgContent => {
  return { data, image: base64, svgElement }
 }

-async function setArea (cw, ch, base64, data, fn) {
-  let displayHeight = Math.round(window.screen.availHeight * 0.6)
+async function setArea (cw, ch, topBase64, base64, data, fn) {
+  let displayHeight = Math.round(window.screen.availHeight * 0.8)
  let div = document.createElement('div')
  div.innerHTML = `
    <div id='ml_overlay' style='position: absolute;top:0;background: #251f1fc4;
@@ -170,8 +170,13 @@ async function setArea (cw, ch, base64, data, fn) {
      outline: 2px solid #eaeaea;
      box-shadow: 8px 9px 17px #575757;' />
      <div id='ml_selection' style='position: absolute; 
-      border: 2px dashed red; 
-      pointer-events: none;'></div>
+      border: 2px dashed red;
+      pointer-events: none;
+      background-image: url("${topBase64}");
+            background-repeat: no-repeat;
+            background-size: cover;
+            '></div>
+      <div class="mx_close"> X </div>
    </div>`
  // document.body.querySelector('#ml_overlay')
  document.body.appendChild(div)
@@ -181,13 +186,25 @@ async function setArea (cw, ch, base64, data, fn) {
  // canvas.height = ch

  let img = div.querySelector('#ml_video')
-  let overlay = div.querySelector('#ml_overlay')
+  // let overlay = div.querySelector('#ml_overlay')
  let selection = div.querySelector('#ml_selection')
+  let close = div.querySelector('.mx_close')
  let startX, startY, endX, endY
  let start = false
+  let setDone = false
  // Set video source
  img.src = base64
  // canvas.toDataURL();
+  close.style = `cursor: pointer;
+  position: fixed;
+  left: 12px;
+  top: 12px;
+  z-index: 99999999;
+  background: black;
+  width: 44px;
+  height: 44px;
+  text-align: center;
+  line-height: 44px;`

  // init area
  // const data = getSetAreaData()
@@ -216,14 +233,37 @@ async function setArea (cw, ch, base64, data, fn) {
  img.addEventListener('mousedown', startSelection)
  img.addEventListener('mousemove', updateSelection)
  img.addEventListener('mouseup', endSelection)
-  overlay.addEventListener('click', remove)

-  function remove () {
-    overlay.removeEventListener('click', remove)
+  const removeDiv = () => {
+    div.remove()
+    close.removeEventListener('click', removeDiv)
    img.removeEventListener('mousedown', startSelection)
    img.removeEventListener('mousemove', updateSelection)
    img.removeEventListener('mouseup', endSelection)
-    div.remove()
+    img.removeEventListener('mousedown', setDoneCheck)
+  }
+  close.addEventListener('click', removeDiv)
+
+  const setDoneCheck = event => {
+    console.log(setDone)
+    if (setDone) {
+      img.addEventListener('mousedown', startSelection)
+      img.addEventListener('mousemove', updateSelection)
+      img.addEventListener('mouseup', endSelection)
+      setDone = false
+      start = false
+      startX = event.clientX
+      startY = event.clientY
+    }
+  }
+  img.addEventListener('mousedown', setDoneCheck)
+
+  function remove () {
+    img.removeEventListener('mousedown', startSelection)
+    img.removeEventListener('mousemove', updateSelection)
+    img.removeEventListener('mouseup', endSelection)
+    setDone = true
+    // div.remove()
  }

  function startSelection (event) {
@@ -531,12 +571,24 @@ app.registerExtension({
              }
            }
            try {
+              console.log('this.inputs', this.inputs)
+              let topLinkId = this.inputs[0].link
+              let topNodeId = app.graph.links[topLinkId].origin_id
+              let topIm = app.graph.getNodeById(topNodeId).imgs[0]
+
              let linkId = this.inputs[3].link
              let nodeId = app.graph.links[linkId].origin_id
              // console.log(linkId,this.inputs)
              let im = app.graph.getNodeById(nodeId).imgs[0]
-              let src = im.src
-              setArea(im.naturalWidth, im.naturalHeight, src, data, updateValue)
+              // let src = im.src
+              setArea(
+                im.naturalWidth,
+                im.naturalHeight,
+                topIm.src,
+                im.src,
+                data,
+                updateValue
+              )
            } catch (error) {}
          })
        }
@@ -1800,15 +1800,19 @@ const updateUI = node => {
    pw.inputEl.title = `Total of ${prompts.length} prompts`
  } else {
    // 动态添加
-    console.log('ComfyWidgets',ComfyWidgets.STRING(
-      node,
-      'prompts',
-      ['STRING', { multiline: true }]
-    ))
+    // console.log('ComfyWidgets',ComfyWidgets.STRING(
+    //   node,
+    //   'prompts',
+    //   ['STRING', { multiline: true }]
+    // ))
+
+    // ComfyWidgets.STRING(this, "", ["", {default:this.properties.text, multiline: true}], app)
+
    const w = ComfyWidgets.STRING(
      node,
      'prompts',
-      ['STRING', { multiline: true }]
+      ['STRING', { multiline: true }],
+      app
    ).widget
    w.inputEl.readOnly = true
    w.inputEl.style.opacity = 0.6
@@ -2089,13 +2093,13 @@ const node = {
  name: 'RandomPrompt',
  async init (app) {
    // Any initial setup to run as soon as the page loads
-    console.log('[logging]', 'extension init')
+    // console.log('[logging]', 'extension init')

    if (window.location.href.match('/?')) {
      const { workflow } = getURLParameters(window.location.href)
      if (workflow)
        get_my_workflow().then(data => {
-          console.log('#get_my_workflow', data)
+          // console.log('#get_my_workflow', data)
          let my_workflow = data.filter(
            d => d.filename == 'my_workflow.json'
          )[0]
@@ -2131,10 +2135,15 @@ const node = {
    // }
  },
  loadedGraphNode (node, app) {
-    // Fires for each node when loading/dragging/etc a workflow json or png
-    // If you break something in the backend and want to patch workflows in the frontend
-    // This is the place to do this
-    // console.log("[logging]", "loaded graph node: ", exportGraph(node.graph));
+    if (node.type === 'RandomPrompt') {
+      try {
+        let max_count = node.widgets.filter(w => w.name === "max_count")[0];
+        max_count.value= node.widgets_values[0]
+        // console.log('RandomPrompt',max_count,node.widgets_values[0])
+      } catch (error) {
+        console.log(error)
+      }
+    }
  },
  async nodeCreated (node) {
    if (node.type === 'RandomPrompt') {
@@ -2227,7 +2236,7 @@ const node = {
        const r = onExecuted?.apply?.(this, arguments)

        let prompts = message.prompts
-        console.log('executed', message)
+        // console.log('executed', message)
        // console.log('#RandomPrompt', this.widgets)
        const pw = this.widgets.filter(w => w.name === 'prompts')[0]

@@ -2238,7 +2247,7 @@ const node = {
        } else {
          // 动态添加
          const w = ComfyWidgets.STRING(
-            node,
+            this,
            'prompts',
            ['STRING', { multiline: true }],
            app
@@ -0,0 +1,576 @@
+import { app } from '../../../scripts/app.js'
+import { api } from '../../../scripts/api.js'
+import { ComfyWidgets } from '../../../scripts/widgets.js'
+import { $el } from '../../../scripts/ui.js'
+
+import PhotoSwipeLightbox from '/extensions/comfyui-mixlab-nodes/lib/photoswipe-lightbox.esm.min.js'
+function loadCSS (url) {
+  var link = document.createElement('link')
+  link.rel = 'stylesheet'
+  link.type = 'text/css'
+  link.href = url
+  document.getElementsByTagName('head')[0].appendChild(link)
+
+  // Create a style element
+  const style = document.createElement('style')
+  // Define the CSS rule for scrollbar width
+  const cssRule = `.pswp__custom-caption {
+    background: rgb(20 27 70);
+    font-size: 16px;
+    color: #fff;
+    width: calc(100% - 32px);
+    max-width: 980px;
+    padding: 2px 8px;
+    border-radius: 4px;
+    position: absolute;
+    left: 50%;
+    bottom: 16px;
+    transform: translateX(-50%);
+  }
+  .pswp__custom-caption a {
+    color: #fff;
+    text-decoration: underline;
+  }
+  .hidden-caption-content {
+    display: none;
+  }`
+  // Add the CSS rule to the style element
+  style.appendChild(document.createTextNode(cssRule))
+
+  // Append the style element to the document head
+  document.head.appendChild(style)
+}
+loadCSS('/extensions/comfyui-mixlab-nodes/lib/photoswipe.min.css')
+
+function initLightBox () {
+  const lightbox = new PhotoSwipeLightbox({
+    gallery: '.prompt_image_output',
+    children: 'a',
+    pswpModule: () =>
+      import('/extensions/comfyui-mixlab-nodes/lib/photoswipe.esm.min.js')
+  })
+
+  lightbox.on('uiRegister', function () {
+    lightbox.pswp.ui.registerElement({
+      name: 'custom-caption',
+      order: 9,
+      isButton: false,
+      appendTo: 'root',
+      html: 'Caption text',
+      onInit: (el, pswp) => {
+        lightbox.pswp.on('change', () => {
+          const currSlideElement = lightbox.pswp.currSlide.data.element
+          let captionHTML = ''
+          if (currSlideElement) {
+            const hiddenCaption = currSlideElement.querySelector(
+              '.hidden-caption-content'
+            )
+            if (hiddenCaption) {
+              // get caption from element with class hidden-caption-content
+              captionHTML = hiddenCaption.innerHTML
+            } else {
+              // get caption from alt attribute
+              captionHTML = currSlideElement
+                .querySelector('img')
+                .getAttribute('alt')
+            }
+          }
+          el.innerHTML = captionHTML || ''
+        })
+      }
+    })
+  })
+
+  lightbox.init()
+}
+
+function get_position_style (ctx, widget_width, y, node_height) {
+  const MARGIN = 4 // the margin around the html element
+
+  /* Create a transform that deals with all the scrolling and zooming */
+  const elRect = ctx.canvas.getBoundingClientRect()
+  const transform = new DOMMatrix()
+    .scaleSelf(
+      elRect.width / ctx.canvas.width,
+      elRect.height / ctx.canvas.height
+    )
+    .multiplySelf(ctx.getTransform())
+    .translateSelf(MARGIN, MARGIN + y)
+
+  return {
+    transformOrigin: '0 0',
+    transform: transform,
+    left: `0`,
+    top: `0`,
+    cursor: 'pointer',
+    position: 'absolute',
+    maxWidth: `${widget_width - MARGIN * 2}px`,
+    // maxHeight: `${node_height - MARGIN * 2}px`, // we're assuming we have the whole height of the node
+    width: `${widget_width - MARGIN * 2 - 24}px`,
+    // height: `${node_height * 0.3 - MARGIN * 2}px`,
+    // background: '#EEEEEE',
+    paddingLeft: '12px',
+    display: 'flex',
+    flexDirection: 'row',
+    // alignItems: 'center',
+    justifyContent: 'space-between'
+  }
+}
+function createImage (url) {
+  let im = new Image()
+  return new Promise((res, rej) => {
+    im.onload = () => res(im)
+    im.src = url
+  })
+}
+
+async function fetchImage (url) {
+  try {
+    const response = await fetch(url)
+    const blob = await response.blob()
+
+    return blob
+  } catch (error) {
+    console.error('出现错误:', error)
+  }
+}
+
+const getLocalData = key => {
+  let data = {}
+  try {
+    data = JSON.parse(localStorage.getItem(key)) || {}
+  } catch (error) {
+    return {}
+  }
+  return data
+}
+
+const setLocalDataOfWin = (key, value) => {
+  localStorage.setItem(key, JSON.stringify(value))
+  // window[key] = value
+}
+
+const createSelect = (select, opts, targetWidget) => {
+  select.style.display = 'block'
+  let html = ''
+  let isMatch = false
+  for (const opt of opts) {
+    html += `<option value='${opt}' ${
+      targetWidget.value === opt ? 'selected' : ''
+    }>${opt}</option>`
+    if (targetWidget.value === opt) isMatch = true
+  }
+  select.innerHTML = html
+  if (!isMatch) targetWidget.value = opts[0]
+  // 添加change事件监听器
+  select.addEventListener('change', function () {
+    // 获取选中的选项的值
+    var selectedOption = select.options[select.selectedIndex].value
+    targetWidget.value = selectedOption
+    // console.log(widget,selectedOption)
+  })
+}
+
+app.registerExtension({
+  name: 'Mixlab.prompt.RandomPrompt',
+  async beforeRegisterNodeDef (nodeType, nodeData, app) {
+    if (nodeType.comfyClass == 'RandomPrompt') {
+      const orig_nodeCreated = nodeType.prototype.onNodeCreated
+      nodeType.prototype.onNodeCreated = async function () {
+        orig_nodeCreated?.apply(this, arguments)
+        name
+
+        const mutable_prompt = this.widgets.filter(
+          w => w.name == 'mutable_prompt'
+        )[0]
+        // console.log('PromptSlide nodeData', prompt_keyword)
+
+        const widget = {
+          type: 'div',
+          name: 'upload',
+          draw (ctx, node, widget_width, y, widget_height) {
+            Object.assign(
+              this.div.style,
+              get_position_style(ctx, widget_width, y, node.size[1])
+            )
+          }
+        }
+
+        widget.div = $el('div', {})
+
+        const btn = document.createElement('button')
+        btn.innerText = 'Upload Keywords'
+
+        btn.style = `cursor: pointer;
+        font-weight: 300;
+        margin: 2px; 
+        color: var(--descrip-text);
+        background-color: var(--comfy-input-bg);
+        border-radius: 8px;
+        border-color: var(--border-color);
+        border-style: solid;    height: 30px;min-width: 122px;
+       `
+
+        // const btn=document.createElement('button');
+        // btn.innerText='Upload'
+        btn.addEventListener('click', () => {
+          let inp = document.createElement('input')
+          inp.type = 'file'
+          inp.accept = '.txt'
+          inp.click()
+          inp.addEventListener('change', event => {
+            // 获取选择的文件
+            const file = event.target.files[0]
+            this.title = file.name.split('.')[0]
+
+            // console.log(file.name.split('.')[0])
+            // 创建文件读取器
+            const reader = new FileReader()
+
+            // 定义读取完成事件的回调函数
+            reader.onload = event => {
+              // 读取完成后的文本内容
+              const fileContent = event.target.result.split('\n')
+              const keywords = Array.from(fileContent, f => f.trim()).filter(
+                f => f
+              )
+              // 打印文件内容
+              //   console.log(keywords)
+
+              mutable_prompt.value = keywords.join('\n')
+
+              inp.remove()
+            }
+
+            // 以文本方式读取文件
+            reader.readAsText(file)
+          })
+        })
+
+        widget.div.appendChild(btn)
+        document.body.appendChild(widget.div)
+        this.addCustomWidget(widget)
+
+        const onRemoved = this.onRemoved
+        this.onRemoved = () => {
+          widget.div.remove()
+          return onRemoved?.()
+        }
+
+        if (this.onResize) {
+          this.onResize(this.size)
+        }
+
+        this.serialize_widgets = true //需要保存参数
+      }
+    }
+  },
+  async loadedGraphNode (node, app) {
+    if (node.type === 'RandomPrompt') {
+      // try {
+      //   let mutable_prompt = node.widgets.filter(w => w.name === 'mutable_prompt')[0]
+      //   // let ks = getLocalData(`_mixlab_PromptSlide`)
+      //   let uploadWidget = node.widgets.filter(w => w.name == 'upload')[0]
+      //   // console.log('##widget', uploadWidget.value)
+      //   let keywords = JSON.parse(uploadWidget.value)
+      //   if (keywords && keywords[0]) {
+      //     mutable_prompt.value=keywords.join('\n')
+      //   }
+      // } catch (error) {}
+    }
+  }
+})
+
+app.registerExtension({
+  name: 'Mixlab.prompt.PromptSlide',
+  async beforeRegisterNodeDef (nodeType, nodeData, app) {
+    if (nodeType.comfyClass == 'PromptSlide') {
+      const orig_nodeCreated = nodeType.prototype.onNodeCreated
+      nodeType.prototype.onNodeCreated = async function () {
+        orig_nodeCreated?.apply(this, arguments)
+
+        const prompt_keyword = this.widgets.filter(
+          w => w.name == 'prompt_keyword'
+        )[0]
+        // console.log('PromptSlide nodeData', prompt_keyword)
+
+        const widget = {
+          type: 'div',
+          name: 'upload',
+          draw (ctx, node, widget_width, y, widget_height) {
+            Object.assign(
+              this.div.style,
+              get_position_style(ctx, widget_width, y, node.size[1])
+            )
+          }
+        }
+
+        widget.div = $el('div', {})
+
+        const btn = document.createElement('button')
+        btn.innerText = 'Upload Keywords'
+
+        btn.style = `cursor: pointer;
+        font-weight: 300;
+        margin: 2px; 
+        color: var(--descrip-text);
+        background-color: var(--comfy-input-bg);
+        border-radius: 8px;
+        border-color: var(--border-color);
+        border-style: solid;    height: 30px;min-width: 122px;
+       `
+
+        const select = document.createElement('select')
+        select.style = `display:none;cursor: pointer;
+        font-weight: 300;
+        margin: 2px; 
+        color: var(--descrip-text);
+        background-color: var(--comfy-input-bg);
+        border-radius: 8px;
+        border-color: var(--border-color);
+        border-style: solid;    height: 30px;min-width: 100px;
+       `
+        widget.select = select
+
+        // const btn=document.createElement('button');
+        // btn.innerText='Upload'
+        btn.addEventListener('click', () => {
+          let inp = document.createElement('input')
+          inp.type = 'file'
+          inp.accept = '.txt'
+          inp.click()
+          inp.addEventListener('change', event => {
+            // 获取选择的文件
+            const file = event.target.files[0]
+            this.title = file.name.split('.')[0]
+
+            // console.log(file.name.split('.')[0])
+            // 创建文件读取器
+            const reader = new FileReader()
+
+            // 定义读取完成事件的回调函数
+            reader.onload = event => {
+              // 读取完成后的文本内容
+              const fileContent = event.target.result.split('\n')
+              const keywords = Array.from(fileContent, f => f.trim()).filter(
+                f => f
+              )
+              // 打印文件内容
+              //   console.log(keywords)
+
+              widget.value = JSON.stringify(keywords)
+
+              // let ks = getLocalData(`_mixlab_PromptSlide`)
+              // ks[this.id] = keywords
+              // setLocalDataOfWin(`_mixlab_PromptSlide`, ks)
+
+              createSelect(select, keywords, prompt_keyword)
+
+              inp.remove()
+            }
+
+            // 以文本方式读取文件
+            reader.readAsText(file)
+          })
+        })
+
+        widget.div.appendChild(btn)
+        widget.div.appendChild(select)
+        document.body.appendChild(widget.div)
+        this.addCustomWidget(widget)
+
+        const onRemoved = this.onRemoved
+        this.onRemoved = () => {
+          widget.div.remove()
+          return onRemoved?.()
+        }
+
+        if (this.onResize) {
+          this.onResize(this.size)
+        }
+
+        this.serialize_widgets = true //需要保存参数
+      }
+    }
+  },
+  async loadedGraphNode (node, app) {
+    if (node.type === 'PromptSlide') {
+      try {
+        let prompt = node.widgets.filter(w => w.name === 'prompt_keyword')[0]
+        // let ks = getLocalData(`_mixlab_PromptSlide`)
+        let uploadWidget = node.widgets.filter(w => w.name == 'upload')[0]
+        // console.log('##widget', uploadWidget.value)
+        let keywords = JSON.parse(uploadWidget.value)
+        // console.log('keywords',keywords)
+        let widget = node.widgets.filter(w => w.select)[0]
+        if (keywords && keywords[0]) {
+          widget.select.style.display = 'block'
+          createSelect(widget.select, keywords, prompt)
+        }
+      } catch (error) {}
+    }
+  }
+})
+
+const _createResult = async (node, widget, message) => {
+  widget.div.innerHTML = ``
+
+  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]
+
+    for (const img of imgs) {
+      let url = api.apiURL(
+        `/view?filename=${encodeURIComponent(img.filename)}&type=${
+          img.type
+        }&subfolder=${
+          img.subfolder
+        }${app.getPreviewFormatParam()}${app.getRandParam()}`
+      )
+
+      let image = await createImage(url)
+
+      // 创建card
+      let div = document.createElement('div')
+      div.className = 'card'
+      div.draggable = true
+
+      div.ondragend = async event => {
+        console.log('拖动停止')
+        let url = div.querySelector('img').src
+
+        let blob = await fetchImage(url)
+
+        let imageNode = null
+        // No image node selected: add a new one
+        if (!imageNode) {
+          const newNode = LiteGraph.createNode('LoadImage')
+          newNode.pos = [...app.canvas.graph_mouse]
+          imageNode = app.graph.add(newNode)
+          app.graph.change()
+        }
+
+        // const blob = item.getAsFile();
+        imageNode.pasteFile(blob)
+      }
+
+      div.setAttribute('data-scale', image.naturalHeight / image.naturalWidth)
+
+      let h = (image.naturalHeight * width) / image.naturalWidth
+      if (index % 2 === 0) height_add += h
+      div.style = `width: ${width}px;height:${h}px;position: relative;margin: 4px;`
+
+      div.innerHTML = `<a href="${url}" 
+      data-pswp-width="${image.naturalWidth}" 
+      data-pswp-height="${image.naturalHeight}" 
+      target="_blank">
+      <img src="${url}" style='width: 100%' alt="${message.prompts[index]}"/>
+    </a>
+    <p style="position: absolute;
+            bottom: 0;
+            left: 0;
+            opacity: 0.6;
+            background-color: var(--comfy-input-bg); 
+            color: var(--descrip-text);
+            margin: 0;
+            font-size: 12px;
+            padding: 5px;
+            text-align: left;">${message.prompts[index]}</p>`
+      widget.div.appendChild(div)
+    }
+  }
+
+  node.size[1] = 98 + height_add
+}
+
+app.registerExtension({
+  name: 'Mixlab.prompt.PromptImage',
+
+  async beforeRegisterNodeDef (nodeType, nodeData, app) {
+    if (nodeType.comfyClass == 'PromptImage') {
+      const orig_nodeCreated = nodeType.prototype.onNodeCreated
+      nodeType.prototype.onNodeCreated = function () {
+        orig_nodeCreated?.apply(this, arguments)
+        console.log('#orig_nodeCreated', this)
+        const widget = {
+          type: 'div',
+          name: 'result',
+          draw (ctx, node, widget_width, y, widget_height) {
+            Object.assign(this.div.style, {
+              ...get_position_style(ctx, widget_width, y, node.size[1]),
+              flexWrap: 'wrap',
+              justifyContent: 'space-between',
+              // outline: '1px solid red',
+              paddingLeft: '0px',
+              width: widget_width + 'px'
+            })
+          }
+        }
+
+        widget.div = $el('div', {})
+        widget.div.className = 'prompt_image_output'
+
+        document.body.appendChild(widget.div)
+
+        this.addCustomWidget(widget)
+
+        initLightBox()
+
+        const onRemoved = this.onRemoved
+        this.onRemoved = () => {
+          widget.div.remove()
+          return onRemoved?.()
+        }
+
+        const onResize = this.onResize
+        this.onResize = function () {
+          // 缩放发生
+          // console.log('##缩放发生', this.size)
+          let w = this.size[0] * 0.5 - 12
+          Array.from(widget.div.querySelectorAll('.card'), card => {
+            card.style.width = `${w}px`
+            card.style.height = `${
+              w * parseFloat(card.getAttribute('data-scale'))
+            }px`
+          })
+          return onResize?.apply(this, arguments)
+        }
+
+        // this.serialize_widgets = true //需要保存参数
+      }
+
+      const onExecuted = nodeType.prototype.onExecuted
+      nodeType.prototype.onExecuted = async function (message) {
+        onExecuted?.apply(this, arguments)
+        console.log('#PromptImage', message.prompts, message._images)
+        // window._mixlab_app_json = message.json
+        try {
+          let widget = this.widgets.filter(w => w.name === 'result')[0]
+          widget.value = message
+          _createResult(this, widget, { ...message })
+        } catch (error) {
+          console.log(error)
+        }
+      }
+
+      this.serialize_widgets = true //需要保存参数
+    }
+  },
+  async loadedGraphNode (node, app) {
+    if (node.type === 'PromptImage') {
+      // await sleep(0)
+      let widget = node.widgets.filter(w => w.name === 'result')[0]
+      console.log('widget.value', widget.value)
+
+      initLightBox()
+
+      let cards = widget.div.querySelectorAll('.card')
+      if (cards.length == 0) node.size = [280, 120]
+
+      _createResult(node, widget, widget.value)
+    }
+  }
+})
@@ -48,6 +48,40 @@ async function get_nodes_map () {
  return await res.json()
 }

+function get_url () {
+  let api_host = `${window.location.hostname}:${window.location.port}`
+  let api_base = ''
+  let url = `${window.location.protocol}//${api_host}${api_base}`
+  return url
+}
+
+async function get_my_app (filename = null, category = '') {
+  let url = get_url()
+  const res = await fetch(`${url}/mixlab/workflow`, {
+    method: 'POST',
+    body: JSON.stringify({
+      task: 'my_app',
+      filename,
+      category,
+      admin: true
+    })
+  })
+  let result = await res.json()
+  let data = []
+  try {
+    for (const res of result.data) {
+      let { app, workflow } = res.data
+      if (app.filename)
+        data.push({
+          ...app,
+          data: workflow,
+          date: res.date
+        })
+    }
+  } catch (error) {}
+  return data
+}
+
 function loadCSS (url) {
  var link = document.createElement('link')
  link.rel = 'stylesheet'
@@ -633,7 +667,7 @@ app.registerExtension({
            }

            clipboardAction(() => {
-              let name = group.title+' ♾️Mixlab'
+              let name = group.title + ' ♾️Mixlab'
              let nodes = group._nodes

              app.canvas.copyToClipboard(nodes)
@@ -667,164 +701,357 @@ app.registerExtension({
        ...options
      ] // and return the options
    }
+    LGraphCanvas.prototype.centerOnNode = function (node) {
+      // console.log(node)
+      var dpr = window.devicePixelRatio || 1 // 获取设备像素比
+      this.ds.offset[0] =
+        -node.pos[0] -
+        node.size[0] * 0.5 +
+        (this.canvas.width * 0.5) / (this.ds.scale * dpr) // 考虑设备像素比
+      this.ds.offset[1] =
+        -node.pos[1] -
+        node.size[1] * 0.5 +
+        (this.canvas.height * 0.5) / (this.ds.scale * dpr) // 考虑设备像素比
+      this.setDirty(true, true)
+    }
  },
-  async setup () {
-    // Add canvas menu options
-    const orig = LGraphCanvas.prototype.getCanvasMenuOptions
-    LGraphCanvas.prototype.getCanvasMenuOptions = function () {
-      const options = orig.apply(this, arguments)
+  setup () {
+    setTimeout(async () => {
+      // Add canvas menu options
+      const orig = LGraphCanvas.prototype.getCanvasMenuOptions

-      options.push(null, {
-        content: `Find ♾️Mixlab`,
-        disabled: false, // or a function determining whether to disable
-        callback: async () => {
-          nodesMap =
-            nodesMap && Object.keys(nodesMap).length > 0
-              ? nodesMap
-              : await getCustomnodeMappings('url')
+      const apps = await get_my_app()

-          const nodesDiv = document.createDocumentFragment()
-          const nodes = (await app.graphToPrompt()).output
+      let apps_map = { '0': [] }

-          // console.log('[Mixlab]', 'loaded graph node: ', app)
-          let div =
-            document.querySelector('#mixlab_find_the_node') ||
-            document.createElement('div')
-          div.id = 'mixlab_find_the_node'
-          div.style = `
-              flex-direction: column;
-              align-items: end;
-              display:flex;position: absolute; 
-              top: 50px; left: 50px; width: 200px; 
-              color: var(--descrip-text);
-              background-color: var(--comfy-menu-bg);
-              padding: 10px; 
-              border: 1px solid black;z-index: 999999999;padding-top: 0;`
+      for (const app of apps) {
+        if (app.category) {
+          if (!apps_map[app.category]) apps_map[app.category] = []
+          apps_map[app.category].push(app)
+        } else {
+          apps_map['0'].push(app)
+        }
+      }

-          div.innerHTML = ''
-
-          let btn = document.createElement('div')
-          btn.style = `display: flex;
-            width: calc(100% - 24px);
-            justify-content: space-between;
-            align-items: center;
-            padding: 0 12px;
-            height: 32px;`
-          let btnB = document.createElement('button')
-          let textB = document.createElement('p')
-          btn.appendChild(textB)
-          btn.appendChild(btnB)
-          textB.innerText = `Find The Node`
-
-          btnB.style = `float: right; border: none; color: var(--input-text);
-            background-color: var(--comfy-input-bg); border-color: var(--border-color);cursor: pointer;`
-          btnB.addEventListener('click', () => {
-            div.style.display = 'none'
-          })
-          btnB.innerText = 'X'
-
-          // 悬浮框拖动事件
-          div.addEventListener('mousedown', function (e) {
-            var startX = e.clientX
-            var startY = e.clientY
-            var offsetX = div.offsetLeft
-            var offsetY = div.offsetTop
-
-            function moveBox (e) {
-              var newX = e.clientX
-              var newY = e.clientY
-              var deltaX = newX - startX
-              var deltaY = newY - startY
-              div.style.left = offsetX + deltaX + 'px'
-              div.style.top = offsetY + deltaY + 'px'
-            }
-
-            function stopMoving () {
-              document.removeEventListener('mousemove', moveBox)
-              document.removeEventListener('mouseup', stopMoving)
-            }
-
-            document.addEventListener('mousemove', moveBox)
-            document.addEventListener('mouseup', stopMoving)
-          })
-
-          div.appendChild(btn)
-
-          const updateNodes = (ns, nd) => {
-            for (let nodeId in ns) {
-              let n = ns[nodeId].class_type
-              const { url, title } = nodesMap[n]
-              let d = document.createElement('button')
-              d.style = `text-align: left;margin:6px;color: var(--input-text);
-                background-color: var(--comfy-input-bg); border-color: var(--border-color);cursor: pointer;`
-              d.addEventListener('click', () => {
-                const node = app.graph.getNodeById(nodeId)
-                if (!node) return
-                app.canvas.centerOnNode(node)
-                app.canvas.setZoom(1)
-              })
-              d.addEventListener('mouseover', async () => {
-                // console.log('mouseover')
-                let n = (await app.graphToPrompt()).output
-                if (!deepEqual(n, ns)) {
-                  nd.innerHTML = ''
-                  updateNodes(n, nd)
+      let apps_opts = []
+      for (const category in apps_map) {
+        console.log('category',typeof(category))
+        if (category === '0') {
+          apps_opts.push(
+            ...Array.from(apps_map[category], a => {
+              return {
+                content: a.name,
+                has_submenu: false,
+                callback: async () => {
+                  try {
+                    let item = (await get_my_app(a.filename))[0]
+                    if (item) {
+                      // console.log(item.data)
+                      app.loadGraphData(item.data)
+                      setTimeout(() => {
+                        const node = app.graph._nodes_in_order[0]
+                        if (!node) return
+                        app.canvas.centerOnNode(node)
+                        app.canvas.setZoom(0.5)
+                      }, 1000)
+                    }
+                  } catch (error) {}
                }
-              })
-
-              d.innerHTML = `
-                <span>${'#' + nodeId} ${n}</span>
-                <a href="${url}" target="_blank" style="text-decoration: none;">🔗</a>
-                `
-              d.title = title
-
-              nd.appendChild(d)
-            }
-          }
-
-          let nodesDivv = document.createElement('div')
-
-          for (let nodeId in nodes) {
-            let n = nodes[nodeId].class_type
-            const { url, title } = nodesMap[n]
-            let d = document.createElement('button')
-            d.style = `text-align: left;margin:6px;color: var(--input-text);
-              background-color: var(--comfy-input-bg); border-color: var(--border-color);cursor: pointer;`
-            d.addEventListener('click', () => {
-              const node = app.graph.getNodeById(nodeId)
-              if (!node) return
-              app.canvas.centerOnNode(node)
-              app.canvas.setZoom(1)
-            })
-            d.addEventListener('mouseover', async () => {
-              console.log('mouseover')
-              let n = (await app.graphToPrompt()).output
-              if (!deepEqual(n, nodes)) {
-                nodesDivv.innerHTML = ''
-                updateNodes(n, nodesDivv)
              }
            })
-
-            d.innerHTML = `
-              <span>${'#' + nodeId} ${n}</span>
-              <a href="${url}" target="_blank" style="text-decoration: none;">🔗</a>
-              `
-            d.title = title
-
-            nodesDiv.appendChild(d)
-          }
-
-          nodesDivv.appendChild(nodesDiv)
-          nodesDivv.style = `overflow: scroll;
-            height: 70vh;width: 100%;`
-
-          div.appendChild(nodesDivv)
-
-          if (!document.querySelector('#mixlab_find_the_node'))
-            document.body.appendChild(div)
+          )
+        } else {
+          // 二级
+          apps_opts.push({
+            content:  '🚀 '+category,
+            has_submenu: true,
+            disabled: false,
+            submenu: {
+              options: Array.from(apps_map[category], a => {
+                return {
+                  content: a.name,
+                  callback: async () => {
+                    try {
+                      let item = (await get_my_app(a.filename, a.category))[0]
+                      if (item) {
+                        // console.log(item.data)
+                        app.loadGraphData(item.data)
+                        setTimeout(() => {
+                          const node = app.graph._nodes_in_order[0]
+                          if (!node) return
+                          app.canvas.centerOnNode(node)
+                          app.canvas.setZoom(0.5)
+                        }, 1000)
+                      }
+                    } catch (error) {}
+                  }
+                }
+              })
+            }
+          })
        }
-      })
-      return options
-    }
+      }
+
+      // console.log('apps',apps_map, apps_opts,apps)
+      LGraphCanvas.prototype.getCanvasMenuOptions = function () {
+        const options = orig.apply(this, arguments)
+
+        options.push(
+          null,
+          {
+            content: `Nodes Map ♾️Mixlab`,
+            disabled: false,
+            callback: async () => {
+              nodesMap =
+                nodesMap && Object.keys(nodesMap).length > 0
+                  ? nodesMap
+                  : await getCustomnodeMappings('url')
+
+              const nodesDiv = document.createDocumentFragment()
+              const nodes = (await app.graphToPrompt()).output
+
+              // console.log('[Mixlab]', 'loaded graph node: ', app)
+              let div =
+                document.querySelector('#mixlab_find_the_node') ||
+                document.createElement('div')
+              div.id = 'mixlab_find_the_node'
+              div.style = `
+               flex-direction: column;
+               align-items: end;
+               display:flex;position: absolute; 
+               top: 50px; left: 50px; width: 200px; 
+               color: var(--descrip-text);
+               background-color: var(--comfy-menu-bg);
+               padding: 10px; 
+               border: 1px solid black;z-index: 999999999;padding-top: 0;`
+
+              div.innerHTML = ''
+
+              let btn = document.createElement('div')
+              btn.style = `display: flex;
+             width: calc(100% - 24px);
+             justify-content: space-between;
+             align-items: center;
+             padding: 0 12px;
+             height: 44px;`
+              let btnB = document.createElement('button')
+              let textB = document.createElement('p')
+              btn.appendChild(textB)
+              btn.appendChild(btnB)
+              textB.style.fontSize = '12px'
+              textB.innerText = `Locate and navigate nodes ♾️Mixlab`
+
+              btnB.style = `float: right; border: none; color: var(--input-text);
+             background-color: var(--comfy-input-bg); border-color: var(--border-color);cursor: pointer;`
+              btnB.addEventListener('click', () => {
+                div.style.display = 'none'
+              })
+              btnB.innerText = 'X'
+
+              // 悬浮框拖动事件
+              div.addEventListener('mousedown', function (e) {
+                var startX = e.clientX
+                var startY = e.clientY
+                var offsetX = div.offsetLeft
+                var offsetY = div.offsetTop
+
+                function moveBox (e) {
+                  var newX = e.clientX
+                  var newY = e.clientY
+                  var deltaX = newX - startX
+                  var deltaY = newY - startY
+                  div.style.left = offsetX + deltaX + 'px'
+                  div.style.top = offsetY + deltaY + 'px'
+                }
+
+                function stopMoving () {
+                  document.removeEventListener('mousemove', moveBox)
+                  document.removeEventListener('mouseup', stopMoving)
+                }
+
+                document.addEventListener('mousemove', moveBox)
+                document.addEventListener('mouseup', stopMoving)
+              })
+
+              div.appendChild(btn)
+
+              const updateNodes = (ns, nd) => {
+                let appInfoNodes = {}
+                try {
+                  let appInfo = app.graph._nodes.filter(
+                    n => n.type === 'AppInfo'
+                  )[0]
+                  if (appInfo) {
+                    appInfoNodes[appInfo.id] = 2
+                    for (const id of appInfo.widgets[1].value.split('\n')) {
+                      if (id && id.trim() && parseInt(id)) {
+                        appInfoNodes[id] = 0
+                      }
+                    }
+                    for (const id of app.graph._nodes
+                      .filter(n => n.type === 'AppInfo')[0]
+                      .widgets[2].value.split('\n')) {
+                      if (id && id.trim() && parseInt(id)) {
+                        appInfoNodes[id] = 1
+                      }
+                    }
+                  }
+                } catch (error) {
+                  console.log(error)
+                }
+
+                for (let nodeId in ns) {
+                  let n = ns[nodeId].title || ns[nodeId].class_type
+                  if (nodesMap[n]) {
+                    const { url, title } = nodesMap[n]
+                    let d = document.createElement('button')
+                    d.style = `text-align: left;
+                    margin:6px;
+                    color: var(--input-text);
+                   background-color: var(--comfy-input-bg); 
+                   border-color: ${
+                     appInfoNodes[nodeId] >= 0
+                       ? appInfoNodes[nodeId] === 1
+                         ? 'blue'
+                         : 'red'
+                       : 'var(--border-color)'
+                   };
+                   cursor: pointer;`
+
+                    if (appInfoNodes[nodeId] === 2) {
+                      // appinfo
+                      d.style.backgroundColor = '#326328'
+                      d.style.color = '#ffffff'
+                      d.style.borderColor = 'transparent'
+                    }
+
+                    d.addEventListener('click', () => {
+                      // console.log('node')
+                      const node = app.graph.getNodeById(nodeId)
+
+                      if (!node) return
+                      app.canvas.centerOnNode(node)
+                      app.canvas.setZoom(1)
+                    })
+                    d.addEventListener('mouseover', async () => {
+                      // console.log('mouseover')
+                      let n = (await app.graphToPrompt()).output
+                      if (!deepEqual(n, ns)) {
+                        nd.innerHTML = ''
+                        updateNodes(n, nd)
+                      }
+                    })
+
+                    d.innerHTML = `
+                   <span>${'#' + nodeId} ${n}</span>
+                   <a href="${url}" target="_blank" style="text-decoration: none;">🔗</a>
+                   `
+                    d.title = title
+
+                    nd.appendChild(d)
+                  }
+                }
+              }
+
+              let nodesDivv = document.createElement('div')
+              let appInfoNodes = {}
+              try {
+                let appInfo = app.graph._nodes.filter(
+                  n => n.type === 'AppInfo'
+                )[0]
+                if (appInfo) {
+                  appInfoNodes[appInfo.id] = 2
+                  for (const id of appInfo.widgets[1].value.split('\n')) {
+                    if (id && id.trim() && parseInt(id)) {
+                      appInfoNodes[id] = 0
+                    }
+                  }
+                  for (const id of app.graph._nodes
+                    .filter(n => n.type === 'AppInfo')[0]
+                    .widgets[2].value.split('\n')) {
+                    if (id && id.trim() && parseInt(id)) {
+                      appInfoNodes[id] = 1
+                    }
+                  }
+                }
+              } catch (error) {
+                console.log(error)
+              }
+
+              for (let nodeId in nodes) {
+                let n = nodes[nodeId].class_type
+                if (nodesMap[n]) {
+                  const { url, title: _title } = nodesMap[n]
+                  let title = app.graph.getNodeById(nodeId).title || _title
+                  let d = document.createElement('button')
+                  d.style = `text-align: left;
+                  margin:6px;
+                  color: var(--input-text);
+                 background-color: var(--comfy-input-bg); 
+                 border-color: ${
+                   appInfoNodes[nodeId] >= 0
+                     ? appInfoNodes[nodeId] === 1
+                       ? 'blue'
+                       : 'red'
+                     : 'var(--border-color)'
+                 };
+                 cursor: pointer;`
+
+                  if (appInfoNodes[nodeId] === 2) {
+                    // appinfo
+                    d.style.backgroundColor = '#326328'
+                    d.style.color = '#ffffff'
+                    d.style.borderColor = 'transparent'
+                  }
+
+                  d.addEventListener('click', () => {
+                    console.log('click')
+                    const node = app.graph.getNodeById(nodeId)
+                    if (!node) return
+                    app.canvas.centerOnNode(node)
+                    app.canvas.setZoom(1)
+                  })
+                  d.addEventListener('mouseover', async () => {
+                    // console.log('mouseover')
+                    let n = (await app.graphToPrompt()).output
+                    if (!deepEqual(n, nodes)) {
+                      nodesDivv.innerHTML = ''
+                      updateNodes(n, nodesDivv)
+                    }
+                  })
+
+                  d.innerHTML = `
+                 <span>${'#' + nodeId} ${title}</span>
+                 <a href="${url}" target="_blank" style="text-decoration: none;">🔗</a>
+                 `
+                  d.title = n
+
+                  nodesDiv.appendChild(d)
+                }
+              }
+
+              nodesDivv.appendChild(nodesDiv)
+              nodesDivv.style = `overflow: scroll;
+             height: 70vh;width: 100%;`
+
+              div.appendChild(nodesDivv)
+
+              if (!document.querySelector('#mixlab_find_the_node'))
+                document.body.appendChild(div)
+            }
+          },
+          {
+            content: 'Workflow App ♾️Mixlab',
+            has_submenu: true,
+            disabled: false,
+            submenu: {
+              options:apps_opts
+            }
+          }
+        )
+
+        return options
+      }
+    }, 1000)
  }
 })
@@ -2,7 +2,7 @@ import { app } from '../../../scripts/app.js'
 import { api } from '../../../scripts/api.js'
 import { ComfyWidgets } from '../../../scripts/widgets.js'
 import { $el } from '../../../scripts/ui.js'
-import { addValueControlWidget } from "../../../scripts/widgets.js";
+import { addValueControlWidget } from '../../../scripts/widgets.js'

 const getLocalData = key => {
  let data = {}
@@ -45,8 +45,47 @@ function get_position_style (ctx, widget_width, y, node_height) {
  }
 }

+function hexToRGBA (hexColor) {
+  var hex = hexColor.replace('#', '')
+  var r = parseInt(hex.substring(0, 2), 16)
+  var g = parseInt(hex.substring(2, 4), 16)
+  var b = parseInt(hex.substring(4, 6), 16)
+
+  // 获取透明度的十六进制值
+  var alphaHex = hex.substring(6)
+
+  // 将透明度的十六进制值转换为十进制值
+  var alpha = parseInt(alphaHex, 16) / 255
+
+  return [r, g, b, alpha]
+}
+
 app.registerExtension({
  name: 'Mixlab.utils.Color',
+  init () {
+    $el('link', {
+      rel: 'stylesheet',
+      href: '/extensions/comfyui-mixlab-nodes/lib/classic.min.css',
+      parent: document.head
+    })
+
+    $el('style', {
+      textContent: `
+      .pickr{
+        display: flex;
+        justify-content: center;
+        align-items: center;
+      }
+				.pickr .pcr-button {
+					width: 56px;
+          height: 56px;
+          outline: 1px solid white;
+				}
+				 
+			`,
+      parent: document.body
+    })
+  },
  async getCustomWidgets (app) {
    return {
      TCOLOR (node, inputName, inputData, app) {
@@ -60,8 +99,17 @@ app.registerExtension({
            return [128, 32] // a method to compute the current size of the widget
          },
          async serializeValue (nodeId, widgetIndex) {
-            let data = getLocalData('_mixlab_utils_color')
-            return data[node.id] || '#000000'
+            // let data = getLocalData('_mixlab_utils_color')
+            // let hex = data[node.id] || '#000000'
+            let hex = widget.value || '#000000'
+            let [r, g, b, a] = hexToRGBA(hex)
+            return {
+              hex,
+              r,
+              g,
+              b,
+              a
+            }
          }
        }
        //  widget.something = something;          // maybe adds stuff to it
@@ -77,7 +125,7 @@ app.registerExtension({
      nodeType.prototype.onNodeCreated = function () {
        orig_nodeCreated?.apply(this, arguments)

-        console.log('Color nodeData', this.widgets)
+        // console.log('Color nodeData', this.widgets)

        const widget = {
          type: 'div',
@@ -87,6 +135,7 @@ app.registerExtension({
              this.div.style,
              get_position_style(ctx, widget_width, 44, node.size[1])
            )
+            // console.log('draw',y,node.widgets[0].last_y)
          }
        }

@@ -94,35 +143,9 @@ app.registerExtension({

        document.body.appendChild(widget.div)

-        const inputDiv = (key, placeholder, value) => {
+        const inputDiv = () => {
          let div = document.createElement('div')
-          const ip = document.createElement('input')
-          ip.type = 'color'
-          ip.className = `${'comfy-multiline-input'} ${placeholder}`
-          div.style = `display: flex;
-            align-items: center; 
-            margin: 6px 8px;
-            margin-top: 0;`
-          ip.placeholder = placeholder
-          ip.value = value
-
-          ip.style = `outline: none;
-            border: none;
-            padding: 4px;
-            width: 100%;cursor: pointer;
-            height: 32px;`
-          const label = document.createElement('label')
-          label.style = 'font-size: 10px;min-width:32px'
-          label.innerText = placeholder
-          div.appendChild(label)
-          div.appendChild(ip)
-
-          ip.addEventListener('change', () => {
-            let data = getLocalData(key)
-            data[this.id] = ip.value.trim()
-            localStorage.setItem(key, JSON.stringify(data))
-            // console.log(this.id, ip.value.trim())
-          })
+          div.id = `color_picker_${this.id}`
          return div
        }

@@ -132,10 +155,85 @@ app.registerExtension({

        this.addCustomWidget(widget)

+        const pickr = Pickr.create({
+          el: `#${inputColor.id}`,
+          theme: 'classic', // or 'monolith', or 'nano'
+          // closeOnScroll: true,
+          default: '#000000',
+          swatches: [
+            'rgba(244, 67, 54, 1)',
+            'rgba(233, 30, 99, 0.95)',
+            'rgba(156, 39, 176, 0.9)',
+            'rgba(103, 58, 183, 0.85)',
+            'rgba(63, 81, 181, 0.8)',
+            'rgba(33, 150, 243, 0.75)',
+            'rgba(3, 169, 244, 0.7)',
+            'rgba(0, 188, 212, 0.7)',
+            'rgba(0, 150, 136, 0.75)',
+            'rgba(76, 175, 80, 0.8)',
+            'rgba(139, 195, 74, 0.85)',
+            'rgba(205, 220, 57, 0.9)',
+            'rgba(255, 235, 59, 0.95)',
+            'rgba(255, 193, 7, 1)'
+          ],
+
+          components: {
+            // Main components
+            preview: true,
+            opacity: true,
+            hue: true,
+            // Input / output Options
+            interaction: {
+              hex: true,
+              rgba: true,
+              hsla: true,
+              hsva: true,
+              cmyk: true,
+              input: true,
+              // clear: true,
+              save: true,
+              cancel: true
+            }
+          }
+        })
+
+        pickr
+          .on('save', (color, instance) => {
+            // console.log('Event: "save"', color.toHEXA().toString())
+            // let data = getLocalData('_mixlab_utils_color')
+            // data[this.id] = color.toHEXA().toString()
+            // localStorage.setItem('_mixlab_utils_color', JSON.stringify(data))
+
+            try {
+              let tc = this.widgets.filter(w => w.type == 'TCOLOR')[0]
+              tc.value = color.toHEXA().toString()
+            } catch (error) {}
+          })
+          .on('cancel', instance => {
+            pickr && pickr.hide()
+          })
+        this.pickr = pickr
+        const handleMouseWheel = () => {
+          try {
+            this.pickr && this.pickr.hide()
+          } catch (error) {}
+        }
+
+        document.addEventListener('wheel', handleMouseWheel)
+
        const onRemoved = this.onRemoved
        this.onRemoved = () => {
          inputColor.remove()
          widget.div.remove()
+
+          try {
+            this.pickr.destroyAndRemove()
+            this.pickr = null
+            document.removeEventListener('wheel', handleMouseWheel)
+          } catch (error) {
+            console.log(error)
+          }
+
          return onRemoved?.()
        }

@@ -148,34 +246,119 @@ app.registerExtension({
    // You can modify widgets/add handlers/etc here

    if (node.type === 'Color') {
-      let widget = node.widgets.filter(w => w.div)[0]
+      try {
+        let TCOLOR = node.widgets.filter(w => w.type == 'TCOLOR')[0]

-      let data = getLocalData('_mixlab_utils_color')
-
-      let id = node.id
-
-      widget.div.querySelector('.Color').value = data[id] || '#000000'
+        setTimeout(() => node.pickr.setColor(TCOLOR.value || '#000000'), 1000)
+      } catch (error) {}
    }
  }
 })

 app.registerExtension({
  name: 'Mixlab.utils.TextToNumber',
-
  async beforeRegisterNodeDef (nodeType, nodeData, app) {
    if (nodeType.comfyClass == 'TextToNumber') {
-
      const onExecuted = nodeType.prototype.onExecuted
      nodeType.prototype.onExecuted = function (message) {
        onExecuted?.apply(this, arguments)
-        const random_number=this.widgets.filter(w=>w.name==='random_number')[0]
-        if(random_number.value==='enable'){
-          const n=this.widgets.filter(w=>w.name==='number')[0]
-          n.value=message.num[0]
+        const random_number = this.widgets.filter(
+          w => w.name === 'random_number'
+        )[0]
+        if (random_number.value === 'enable') {
+          const n = this.widgets.filter(w => w.name === 'number')[0]
+          n.value = message.num[0]
        }
-        
        console.log('TextToNumber', random_number.value)
      }
    }
  }
 })
+
+const min_max = node => {
+  if(node.widgets){
+    const min_value = node.widgets.filter(w => w.name === 'min_value')[0]
+    const max_value = node.widgets.filter(w => w.name === 'max_value')[0]
+  
+    const number = node.widgets.filter(w => w.name === 'number')[0]
+    if (number) {
+      number.options.min = min_value.value
+      number.options.max = max_value.value
+  
+      number.value = Math.min(number.options.max, number.value)
+      number.value = Math.max(number.options.min, number.value)
+    }
+  
+    if (min_value)
+      min_value.callback = e => {
+        number.options.min = e
+        number.value = e
+      }
+    if (max_value)
+      max_value.callback = e => {
+        number.options.max = e
+        number.value = e
+      }
+  }
+  
+}
+
+app.registerExtension({
+  name: 'Mixlab.utils.FloatSlider',
+  async beforeRegisterNodeDef (nodeType, nodeData, app) {
+
+    if (nodeType.comfyClass == 'FloatSlider') {
+      const orig_nodeCreated = nodeType.prototype.onNodeCreated;
+      nodeType.prototype.onNodeCreated = function () {
+        orig_nodeCreated?.apply(this, arguments)
+        min_max(this)
+      }
+    }
+
+   
+  },
+  async loadedGraphNode (node, app) {
+    if (node.type === 'FloatSlider') {
+      min_max(node)
+    }
+  }
+})
+app.registerExtension({
+  name: 'Mixlab.utils.IntNumber',
+  async beforeRegisterNodeDef (nodeType, nodeData, app) {
+    
+    if (nodeType.comfyClass == 'IntNumber') {
+      const orig_nodeCreated = nodeType.prototype.onNodeCreated
+      nodeType.prototype.onNodeCreated = function () {
+        orig_nodeCreated?.apply(this, arguments)
+        min_max(this)
+      }
+    }
+   
+  },
+  async loadedGraphNode (node, app) {
+    if (node.type === 'IntNumber') {
+      min_max(node)
+    }
+  }
+})
+
+
+app.registerExtension({
+  name: 'Mixlab.utils.TESTNODE_',
+  async beforeRegisterNodeDef (nodeType, nodeData, app) {
+    
+    if (nodeType.comfyClass == 'TESTNODE_') {
+    
+      const onExecuted = nodeType.prototype.onExecuted;
+			nodeType.prototype.onExecuted = function (message) {
+				onExecuted?.apply(this, arguments);
+        console.log('##',message)
+				 
+			};
+
+
+    }
+   
+  }, 
+})
@@ -60,30 +60,7 @@ app.registerExtension({
          type: inputData[0], // the type, CHEESE
          name: inputName, // the name, slice
          size: [128, 24], // a default size
-          draw (ctx, node, width, y) {
-            // // 绘制文件图标的函数
-            // function drawFileIcon () {
-            //   // 清空画布
-            //   // ctx.clearRect(0, 0, canvas.width, canvas.height)
-
-            //   // 绘制文件外框
-            //   ctx.fillStyle = '#000'
-            //   ctx.fillRect(5, 5, 40, 40)
-
-            //   // 绘制文件夹图标
-            //   ctx.fillStyle = '#f00'
-            //   ctx.fillRect(10, 15, 30, 20)
-
-            //   // 绘制监听符号
-            //   ctx.beginPath()
-            //   ctx.arc(30, 35, 5, 0, 2 * Math.PI)
-            //   ctx.fillStyle = '#00f'
-            //   ctx.fill()
-            // }
-
-            // // 调用绘制函数
-            // drawFileIcon()
-          },
+          draw (ctx, node, width, y) {},
          computeSize (...args) {
            return [128, 24] // a method to compute the current size of the widget
          },
@@ -124,11 +101,19 @@ app.registerExtension({
      nodeType.prototype.onNodeCreated = function () {
        orig_nodeCreated?.apply(this, arguments)

-        console.log('watch widtget', this.widgets)
+        // 虚拟的widget，用于更新节点，让其每次都运行
+        const widget = {
+          type: 'div',
+          name: 'seed',
+          draw (ctx, node, widget_width, y, widget_height) {}
+        }
+
+        this.addCustomWidget(widget)

        const watcher = this.widgets.filter(w => w.name == 'watcher')[0]

        watcher.callback = () => {
+          console.log('watcher', watcher.value)
          if (watcher.value === 'enable') {
            if (window._mixlab_watcher_t)
              clearInterval(window._mixlab_watcher_t)
@@ -140,7 +125,7 @@ app.registerExtension({
                  window._mixlab_file_path_watcher = json.event_type
                  // widget.card.innerText = window._mixlab_file_path_watcher || ''
                  //运行
-                  document.querySelector('#queue-button').click()
+                  // document.querySelector('#queue-button').click()
                }
              })
            }, 1000)
@@ -162,15 +147,59 @@ app.registerExtension({
          window._mixlab_file_path_watcher = json.event_type
        })

-        /*
-                Add the widget, make sure we clean up nicely, and we do not want to be serialized!
-                */
-        // this.addCustomWidget(widget)
        this.onRemoved = function () {
          // widget.card.remove()
        }
        this.serialize_widgets = true
      }
+
+      const onExecuted = nodeType.prototype.onExecuted
+      nodeType.prototype.onExecuted = function (message) {
+        onExecuted?.apply(this, arguments)
+        console.log(message)
+        try {
+          let seed = this.widgets.filter(w => w.name === 'seed')[0]
+          if (seed) {
+            if (!seed.value) seed.value = 0
+            seed.value += 1
+          }
+        } catch (error) {}
+      }
+    }
+  },
+  async loadedGraphNode (node, app) {
+    if (node.type === 'LoadImagesFromPath') {
+      const watcher = node.widgets.filter(w => w.name == 'watcher')[0]
+      if (watcher) {
+        if (watcher.value === 'enable') {
+          if (window._mixlab_watcher_t) clearInterval(window._mixlab_watcher_t)
+          window._mixlab_watcher_t = setInterval(() => {
+            // 上次路径填充
+            getConfig().then(json => {
+              console.log(json.event_type)
+              if (json.event_type != window._mixlab_file_path_watcher) {
+                window._mixlab_file_path_watcher = json.event_type
+                // widget.card.innerText = window._mixlab_file_path_watcher || ''
+                //运行
+                document.querySelector('#queue-button').click()
+              }
+            })
+          }, 1000)
+        } else {
+          if (window._mixlab_watcher_t) {
+            clearInterval(window._mixlab_watcher_t)
+          }
+          window._mixlab_watcher_t = null
+        }
+      }
+
+      try {
+        let seed = node.widgets.filter(w => w.name === 'seed')[0]
+        if (seed) {
+          if (!seed.value) seed.value = 0
+          seed.value += 1
+        }
+      } catch (error) {}
    }
  }
 })
@@ -0,0 +1 @@
+/*! PhotoSwipe main CSS by Dmytro Semenov | photoswipe.com */.pswp{--pswp-bg:#000;--pswp-placeholder-bg:#222;--pswp-root-z-index:100000;--pswp-preloader-color:rgba(79, 79, 79, 0.4);--pswp-preloader-color-secondary:rgba(255, 255, 255, 0.9);--pswp-icon-color:#fff;--pswp-icon-color-secondary:#4f4f4f;--pswp-icon-stroke-color:#4f4f4f;--pswp-icon-stroke-width:2px;--pswp-error-text-color:var(--pswp-icon-color)}.pswp{position:fixed;top:0;left:0;width:100%;height:100%;z-index:var(--pswp-root-z-index);display:none;touch-action:none;outline:0;opacity:.003;contain:layout style size;-webkit-tap-highlight-color:transparent}.pswp:focus{outline:0}.pswp *{box-sizing:border-box}.pswp img{max-width:none}.pswp--open{display:block}.pswp,.pswp__bg{transform:translateZ(0);will-change:opacity}.pswp__bg{opacity:.005;background:var(--pswp-bg)}.pswp,.pswp__scroll-wrap{overflow:hidden}.pswp__bg,.pswp__container,.pswp__content,.pswp__img,.pswp__item,.pswp__scroll-wrap,.pswp__zoom-wrap{position:absolute;top:0;left:0;width:100%;height:100%}.pswp__img,.pswp__zoom-wrap{width:auto;height:auto}.pswp--click-to-zoom.pswp--zoom-allowed .pswp__img{cursor:-webkit-zoom-in;cursor:-moz-zoom-in;cursor:zoom-in}.pswp--click-to-zoom.pswp--zoomed-in .pswp__img{cursor:move;cursor:-webkit-grab;cursor:-moz-grab;cursor:grab}.pswp--click-to-zoom.pswp--zoomed-in .pswp__img:active{cursor:-webkit-grabbing;cursor:-moz-grabbing;cursor:grabbing}.pswp--no-mouse-drag.pswp--zoomed-in .pswp__img,.pswp--no-mouse-drag.pswp--zoomed-in .pswp__img:active,.pswp__img{cursor:-webkit-zoom-out;cursor:-moz-zoom-out;cursor:zoom-out}.pswp__button,.pswp__container,.pswp__counter,.pswp__img{-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none}.pswp__item{z-index:1;overflow:hidden}.pswp__hidden{display:none!important}.pswp__content{pointer-events:none}.pswp__content>*{pointer-events:auto}.pswp__error-msg-container{display:grid}.pswp__error-msg{margin:auto;font-size:1em;line-height:1;color:var(--pswp-error-text-color)}.pswp .pswp__hide-on-close{opacity:.005;will-change:opacity;transition:opacity var(--pswp-transition-duration) cubic-bezier(.4,0,.22,1);z-index:10;pointer-events:none}.pswp--ui-visible .pswp__hide-on-close{opacity:1;pointer-events:auto}.pswp__button{position:relative;display:block;width:50px;height:60px;padding:0;margin:0;overflow:hidden;cursor:pointer;background:0 0;border:0;box-shadow:none;opacity:.85;-webkit-appearance:none;-webkit-touch-callout:none}.pswp__button:active,.pswp__button:focus,.pswp__button:hover{transition:none;padding:0;background:0 0;border:0;box-shadow:none;opacity:1}.pswp__button:disabled{opacity:.3;cursor:auto}.pswp__icn{fill:var(--pswp-icon-color);color:var(--pswp-icon-color-secondary)}.pswp__icn{position:absolute;top:14px;left:9px;width:32px;height:32px;overflow:hidden;pointer-events:none}.pswp__icn-shadow{stroke:var(--pswp-icon-stroke-color);stroke-width:var(--pswp-icon-stroke-width);fill:none}.pswp__icn:focus{outline:0}.pswp__img--with-bg,div.pswp__img--placeholder{background:var(--pswp-placeholder-bg)}.pswp__top-bar{position:absolute;left:0;top:0;width:100%;height:60px;display:flex;flex-direction:row;justify-content:flex-end;z-index:10;pointer-events:none!important}.pswp__top-bar>*{pointer-events:auto;will-change:opacity}.pswp__button--close{margin-right:6px}.pswp__button--arrow{position:absolute;top:0;width:75px;height:100px;top:50%;margin-top:-50px}.pswp__button--arrow:disabled{display:none;cursor:default}.pswp__button--arrow .pswp__icn{top:50%;margin-top:-30px;width:60px;height:60px;background:0 0;border-radius:0}.pswp--one-slide .pswp__button--arrow{display:none}.pswp--touch .pswp__button--arrow{visibility:hidden}.pswp--has_mouse .pswp__button--arrow{visibility:visible}.pswp__button--arrow--prev{right:auto;left:0}.pswp__button--arrow--next{right:0}.pswp__button--arrow--next .pswp__icn{left:auto;right:14px;transform:scale(-1,1)}.pswp__button--zoom{display:none}.pswp--zoom-allowed .pswp__button--zoom{display:block}.pswp--zoomed-in .pswp__zoom-icn-bar-v{display:none}.pswp__preloader{position:relative;overflow:hidden;width:50px;height:60px;margin-right:auto}.pswp__preloader .pswp__icn{opacity:0;transition:opacity .2s linear;animation:pswp-clockwise .6s linear infinite}.pswp__preloader--active .pswp__icn{opacity:.85}@keyframes pswp-clockwise{0%{transform:rotate(0)}100%{transform:rotate(360deg)}}.pswp__counter{height:30px;margin-top:15px;margin-inline-start:20px;font-size:14px;line-height:30px;color:var(--pswp-icon-color);text-shadow:1px 1px 3px var(--pswp-icon-color-secondary);opacity:.85}.pswp--one-slide .pswp__counter{display:none}
@@ -0,0 +1,736 @@
+{
+  "last_node_id": 29,
+  "last_link_id": 32,
+  "nodes": [
+    {
+      "id": 7,
+      "type": "CLIPTextEncode",
+      "pos": [
+        108,
+        316
+      ],
+      "size": {
+        "0": 425.27801513671875,
+        "1": 180.6060791015625
+      },
+      "flags": {},
+      "order": 8,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "clip",
+          "type": "CLIP",
+          "link": 16
+        }
+      ],
+      "outputs": [
+        {
+          "name": "CONDITIONING",
+          "type": "CONDITIONING",
+          "links": [
+            6
+          ],
+          "slot_index": 0
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "CLIPTextEncode"
+      },
+      "widgets_values": [
+        "text, watermark"
+      ]
+    },
+    {
+      "id": 18,
+      "type": "ControlNetApply",
+      "pos": [
+        485,
+        792
+      ],
+      "size": {
+        "0": 317.4000244140625,
+        "1": 98
+      },
+      "flags": {},
+      "order": 10,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "conditioning",
+          "type": "CONDITIONING",
+          "link": 22,
+          "slot_index": 0
+        },
+        {
+          "name": "control_net",
+          "type": "CONTROL_NET",
+          "link": 18,
+          "slot_index": 1
+        },
+        {
+          "name": "image",
+          "type": "IMAGE",
+          "link": 26
+        }
+      ],
+      "outputs": [
+        {
+          "name": "CONDITIONING",
+          "type": "CONDITIONING",
+          "links": [
+            21
+          ],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "ControlNetApply"
+      },
+      "widgets_values": [
+        1
+      ]
+    },
+    {
+      "id": 6,
+      "type": "CLIPTextEncode",
+      "pos": [
+        117,
+        95
+      ],
+      "size": {
+        "0": 422.84503173828125,
+        "1": 164.31304931640625
+      },
+      "flags": {},
+      "order": 7,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "clip",
+          "type": "CLIP",
+          "link": 15
+        }
+      ],
+      "outputs": [
+        {
+          "name": "CONDITIONING",
+          "type": "CONDITIONING",
+          "links": [
+            22
+          ],
+          "slot_index": 0
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "CLIPTextEncode"
+      },
+      "widgets_values": [
+        "a future city,buiding,future,magic,under water"
+      ]
+    },
+    {
+      "id": 15,
+      "type": "LoraLoader",
+      "pos": [
+        116,
+        -113
+      ],
+      "size": {
+        "0": 315,
+        "1": 126
+      },
+      "flags": {},
+      "order": 3,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "model",
+          "type": "MODEL",
+          "link": 13
+        },
+        {
+          "name": "clip",
+          "type": "CLIP",
+          "link": 14
+        }
+      ],
+      "outputs": [
+        {
+          "name": "MODEL",
+          "type": "MODEL",
+          "links": [
+            12,
+            23
+          ],
+          "shape": 3,
+          "slot_index": 0
+        },
+        {
+          "name": "CLIP",
+          "type": "CLIP",
+          "links": [
+            15,
+            16
+          ],
+          "shape": 3,
+          "slot_index": 1
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "LoraLoader"
+      },
+      "widgets_values": [
+        "lcm-lora-sdv1-5.safetensors",
+        1,
+        1
+      ]
+    },
+    {
+      "id": 4,
+      "type": "CheckpointLoaderSimple",
+      "pos": [
+        -380,
+        185
+      ],
+      "size": {
+        "0": 315,
+        "1": 98
+      },
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "outputs": [
+        {
+          "name": "MODEL",
+          "type": "MODEL",
+          "links": [
+            13
+          ],
+          "slot_index": 0
+        },
+        {
+          "name": "CLIP",
+          "type": "CLIP",
+          "links": [
+            14
+          ],
+          "slot_index": 1
+        },
+        {
+          "name": "VAE",
+          "type": "VAE",
+          "links": [
+            8
+          ],
+          "slot_index": 2
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "CheckpointLoaderSimple"
+      },
+      "widgets_values": [
+        "deliberate_v2.safetensors"
+      ]
+    },
+    {
+      "id": 19,
+      "type": "DiffControlNetLoader",
+      "pos": [
+        40,
+        792
+      ],
+      "size": {
+        "0": 367.8165283203125,
+        "1": 58.083831787109375
+      },
+      "flags": {},
+      "order": 6,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "model",
+          "type": "MODEL",
+          "link": 23,
+          "slot_index": 0
+        }
+      ],
+      "outputs": [
+        {
+          "name": "CONTROL_NET",
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-![workflow](./assets/挖掘机_00076_1.png)
Author	SHA1	Message	Date
gold3bear	2918d4b07d	correct Chinese text to prompt syntax	2024-01-14 11:50:14 +08:00
gold3bear	c40e49be46	fix chinese prompt	2024-01-14 11:34:58 +08:00
shadowcz007	09957617d3	修复SwitchByIndex的bug	2024-01-13 20:59:29 +08:00
shadowcz007	c703aa7058	中文prompt增加选项，可控制是否添加更多	2024-01-13 20:59:07 +08:00
shadowcz007	64d366d323	Update prompt_mixlab.js	2024-01-13 17:12:03 +08:00
shadowcz007	333e0a2faa	Update ImageNode.py	2024-01-13 16:32:51 +08:00
shadowcz007	a677d95bc8	Update README.md	2024-01-13 16:02:24 +08:00
shadowcz007	aafd87e84b	v0.12.0 ChinesePrompt && PromptGenerate > ChinesePrompt && PromptGenerate，中文prompt节点，直接用中文书写你的prompt ![](./assets/ChinesePrompt_workflow.svg) > Web App增加图片编辑器	2024-01-13 15:59:52 +08:00
shadowcz007	efa3bae54b	Create profession.txt	2024-01-13 12:25:05 +08:00
shadowcz007	8e4362689d	Lama、ClipInterrogator安装移到节点内	2024-01-13 12:11:46 +08:00
shadowcz007	b86634284e	appinfo运行bug	2024-01-13 11:34:17 +08:00
shadowcz007	b3293ddccd	优化promptImage的预览	2024-01-12 17:16:47 +08:00
shadowcz007	4b40831b83	prompt keywords	2024-01-11 23:05:25 +08:00
shadowcz007	e426b0521c	添加图片编辑功能	2024-01-11 23:01:58 +08:00
shadowcz007	1777bf6e06	修复切换workflow，数据未清空的情况	2024-01-11 23:01:42 +08:00
shadowcz007	dafc892f0f	add image edit for web app	2024-01-11 15:41:05 +08:00
shadowcz007	fea0cfd5dd	更新workflow示例	2024-01-11 15:40:31 +08:00
shadowcz007	a7e158db6d	update workflow example	2024-01-11 15:32:20 +08:00
shadowcz007	455ac4abd3	Update promptslide-appinfo-workflow.svg	2024-01-11 15:27:11 +08:00
shadowcz007	778dfa2cf5	update workflow example	2024-01-11 15:24:31 +08:00
shadowcz007	329f2e6f81	系统字体的获取	2024-01-10 16:19:49 +08:00
shadowcz007	63ad6d97d7	Update ImageNode.py	2024-01-09 22:59:34 +08:00
shadowcz007	8db56db7cf	Update ImageNode.py	2024-01-09 22:34:13 +08:00
shadowcz007	bd542f1e0b	Update app_mixlab.js	2024-01-09 18:42:36 +08:00
shadowcz007	a162e53dea	Update ImageNode.py	2024-01-09 18:05:18 +08:00
shadowcz007	a8a4c848ed	Update __init__.py	2024-01-09 16:15:15 +08:00
shadowcz007	bddd38996a	Update ImageNode.py	2024-01-09 15:16:38 +08:00
shadowcz007	9f084eae94	修复LoadImagesFromPath的bug	2024-01-09 14:33:13 +08:00
shadowcz007	c54c635161	v0.11.4	2024-01-09 12:59:36 +08:00
shadowcz007	fa8b42e05e	增强ImageCrop功能	2024-01-09 12:48:20 +08:00
shadowcz007	9c3c323884	fixbug: user_manager	2024-01-09 12:41:29 +08:00
shadowcz007	c8a46439be	v0.11.3 - 修复appinfo的logo输入	2024-01-09 09:17:00 +08:00
shadowcz007	b7ec701259	Update Utils.py	2024-01-09 09:16:15 +08:00
shadowcz007	a2cd0e0a38	v0.11.2 - 优化appinfo - 自动保存 - 优化mergeLayer，可以输出合成的mask - 添加一个实验性的节点 ImageColorTransfer - random prompt ,增加上传关键词功能 - 修复LoadImageFromPath的bug	2024-01-08 23:03:37 +08:00
shadowcz007	7bccc0e236	优化appinfo-不需要输出，每次运行都会自动更新数据	2024-01-08 23:01:31 +08:00
shadowcz007	a3a649a79f	修复 LoadImagesFromPath 不更新的bug	2024-01-08 22:11:10 +08:00
shadowcz007	2a14d30552	添加一个实验性的节点 ImageColorTransfer	2024-01-08 16:40:00 +08:00
shadowcz007	313bef0609	ClipInterrogator优化	2024-01-07 22:55:24 +08:00
shadowcz007	960a80aeca	Merge branch 'main' of https://github.com/shadowcz007/comfyui-mixlab-nodes	2024-01-07 19:59:24 +08:00
shadowcz007	20e6d50a98	修复bug	2024-01-07 19:59:22 +08:00
shadow	507c3417d6	Merge pull request #114 from shadowcz007/fix_ssl_prot_occupied fix:ssl prot occupied	2024-01-07 17:08:08 +08:00
gold3bear	d1adb8d4ed	fix:ssl prot occupied	2024-01-07 15:56:23 +08:00
shadowcz007	915ff12747	支持图片的batch	2024-01-06 23:20:43 +08:00
shadowcz007	fbade79137	Update utils_mixlab.js	2024-01-06 20:15:17 +08:00
shadowcz007	a240a677d0	Update utils_mixlab.js	2024-01-06 20:14:17 +08:00
shadowcz007	ab64cf31f6	FloatSlider 优化	2024-01-06 20:13:00 +08:00
shadowcz007	67f2e32dae	floatSlider 优化	2024-01-06 20:00:58 +08:00
shadowcz007	0dc40fe052	修复bug	2024-01-06 17:55:26 +08:00
shadowcz007	b7225be552	Update ImageNode.py	2024-01-06 16:25:35 +08:00
shadowcz007	629e00ec94	fixbug	2024-01-06 12:14:02 +08:00
shadowcz007	6d033c9314	random prompt ,增加上传关键词功能	2024-01-06 08:40:27 +08:00
shadowcz007	4f8926ed00	promptslide 上传txt后写入workflow保留列表数据	2024-01-06 08:12:59 +08:00
shadow	1daa1a4603	Merge pull request #111 from shadowcz007/v.11.0-PromptImage-node-图片和prompt匹配 V0.11.0 PromptImage & PromptSimplification	2024-01-06 00:17:26 +08:00
shadowcz007	062773d929	v0.11.0 > PromptImage & PromptSimplification,Assist in simplifying prompt words, comparing images and prompt word nodes.	2024-01-06 00:16:33 +08:00
shadowcz007	57decadaef	Update index.html	2024-01-06 00:14:04 +08:00
shadowcz007	ec804ab7c9	优化	2024-01-05 23:09:08 +08:00
shadowcz007	3ee7533098	Update prompt_mixlab.js	2024-01-05 16:40:30 +08:00
shadowcz007	0d383ccc1f	add PromptImage	2024-01-05 15:27:13 +08:00
shadowcz007	e2f2257c34	Update index.html	2024-01-05 12:22:23 +08:00
shadowcz007	d62b9fc4c6	ClipInterrogator可以作为输出	2024-01-05 11:52:04 +08:00
shadowcz007	be7ad0c7fb	Update index.html	2024-01-04 23:35:56 +08:00
shadowcz007	156864cc8b	PromptSimplification	2024-01-04 23:33:24 +08:00
shadowcz007	7240e496cc	Update PromptNode.py	2024-01-04 23:02:48 +08:00
shadowcz007	8acdf4018d	test PromptSimplification	2024-01-04 20:32:43 +08:00
shadowcz007	1ea7c3e203	修复floatSlide最大值问题	2024-01-04 19:43:33 +08:00
shadowcz007	e54aeb6125	Update index.html	2024-01-04 18:35:54 +08:00
shadowcz007	d59f51fbcf	Update README.md	2024-01-04 18:20:52 +08:00
shadowcz007	a667eb6982	修复seed 为fixed 的运行按钮bug & 支持sd-xl 的SamplerCustom	2024-01-04 18:20:00 +08:00
shadowcz007	8d72732247	Update index.html	2024-01-04 17:19:46 +08:00
shadowcz007	f0f3b30a62	Update index.html	2024-01-04 17:03:36 +08:00
shadowcz007	d99fe24542	fixbug	2024-01-04 16:05:27 +08:00
shadowcz007	ea4c7381bd	Update index.html	2024-01-04 14:07:38 +08:00
shadow	e900d20641	Merge pull request #107 from shadowcz007/v0.10-add-clip-interrogator Update index.html	2024-01-04 14:02:42 +08:00
shadowcz007	8a46647d8c	Update index.html	2024-01-04 14:02:19 +08:00
shadow	968178bf57	Merge pull request #106 from shadowcz007/v0.10-add-clip-interrogator V0.10 add clip interrogator	2024-01-04 13:37:31 +08:00
shadowcz007	406a255db0	v0.10.0 增加 ClipInterrogator、优化APP功能	2024-01-04 13:37:07 +08:00
shadowcz007	574557810e	Update index.html	2024-01-04 13:24:50 +08:00
shadowcz007	998a02c3a4	上一次输入记录	2024-01-04 13:12:02 +08:00
shadowcz007	c6f964c921	textarea输入，增加上一次输入记录	2024-01-04 12:57:55 +08:00
shadowcz007	efb0e147c5	Update index.html	2024-01-04 12:45:00 +08:00
shadowcz007	9cf7356f98	Update index.html	2024-01-04 12:33:59 +08:00
shadowcz007	af05c43174	支持image的batch输出	2024-01-04 12:31:45 +08:00
shadowcz007	380c68ff2b	EnhanceImage节点支持batch多张输入和输出	2024-01-04 12:03:27 +08:00
shadowcz007	068b00b99f	update	2024-01-04 11:24:00 +08:00
shadowcz007	cd6a42ab64	clip-interrogator	2024-01-04 11:03:25 +08:00
shadowcz007	f115abec92	add clip interrogator	2024-01-04 11:01:08 +08:00
shadowcz007	f0e23cf878	AIPC大赛模板	2024-01-03 22:28:38 +08:00
shadowcz007	a94f11d809	Update index.html	2024-01-03 20:22:24 +08:00
shadowcz007	38972bea5f	更新AIPC大赛模板-直接合成，免去ps	2024-01-03 18:03:33 +08:00
shadowcz007	a761ff552a	Merge branch 'main' of https://github.com/shadowcz007/comfyui-mixlab-nodes	2024-01-03 17:54:25 +08:00
shadowcz007	dbeb84ea9a	resizeImage 缩放图像新增center模式，多余的背景可以设定填充颜色	2024-01-03 17:54:23 +08:00
shadow	0a4938f39a	Merge pull request #105 from shadowcz007/v0.9.2-中断生成修复3d image的bug，未上传bg图也可以运行了	2024-01-03 14:21:26 +08:00
shadowcz007	b2182c716d	修复3d image的bug，未上传bg图也可以运行了	2024-01-03 14:20:48 +08:00
shadow	8253be73f6	Merge pull request #104 from shadowcz007/v0.9.2-中断生成添加中断生成的功能	2024-01-03 09:35:12 +08:00
shadowcz007	20318e296e	添加中断生成的功能	2024-01-03 09:32:29 +08:00
shadow	cea1b69286	Merge pull request #103 from shadowcz007/v0.9.1-优化app模式 V0.9.1 优化app模式	2024-01-02 23:56:18 +08:00
shadowcz007	ab8aa69389	v0.9.1 web app可以设置分类，在comfyui右键菜单可以编辑更新web app The web app can be configured with categories, and the web app can be edited and updated in the right-click menu of ComfyUI. 暂时支持8种节点作为界面上的输入节点：Load Image、CLIPTextEncode、PromptSlide、TextInput_、Color、FloatSlider、IntNumber、CheckpointLoaderSimple、LoraLoader	2024-01-02 23:54:24 +08:00
shadowcz007	681491f1d0	v0.9.1	2024-01-02 23:51:19 +08:00
shadowcz007	c2fb815074	更新示例：TwinShot	2024-01-02 23:50:39 +08:00
shadowcz007	fffa14dc44	修复了randomprompt里的一个小bug	2024-01-02 17:48:41 +08:00
shadowcz007	df37166d42	Switch节点增加flat功能，可以把list里的某个元素取出来单独处理	2024-01-02 17:44:17 +08:00
shadowcz007	25fa3a8f6a	支持按照分类隔离应用	2024-01-02 16:19:01 +08:00
shadowcz007	b11507c5e6	样式	2024-01-02 15:11:29 +08:00
shadowcz007	f06d02489f	app支持color组件	2024-01-02 14:59:59 +08:00
shadowcz007	c203af2f71	优化	2024-01-02 13:42:39 +08:00
shadowcz007	c715155a70	渐变节点	2024-01-02 13:25:48 +08:00
shadowcz007	8163133294	优化颜色选择器	2024-01-02 12:17:41 +08:00
shadowcz007	765be5dab4	1	2024-01-02 11:03:22 +08:00
shadowcz007	7c1523389d	Update index.html	2024-01-02 09:53:25 +08:00
shadowcz007	7a2b1ba166	支持category	2024-01-02 09:32:46 +08:00
shadowcz007	45b4dcfcd0	Update index.html	2024-01-01 22:46:10 +08:00
shadowcz007	3b2e535566	add photoswipe	2024-01-01 22:34:58 +08:00
shadowcz007	db556d13a3	1	2024-01-01 21:33:54 +08:00
shadowcz007	a987063c68	nodes map - appinfo	2024-01-01 21:08:38 +08:00
shadowcz007	4ce30ef899	Update ui_mixlab.js	2024-01-01 20:33:00 +08:00
shadowcz007	d988282d98	增加种子生成模式切换	2024-01-01 20:24:12 +08:00
shadowcz007	695fdf7ceb	update	2024-01-01 20:08:39 +08:00
shadowcz007	0befe164cc	v0.9.0	2024-01-01 16:12:58 +08:00
shadowcz007	d506c68a80	promptslide-appinfo-workflow.svg	2024-01-01 16:10:46 +08:00
shadowcz007	c59c429b75	update	2024-01-01 16:05:19 +08:00
shadowcz007	c726b6e4a2	prompt weight 提供选项	2024-01-01 15:56:07 +08:00
shadowcz007	96075ad4e1	Update ImageNode.py	2024-01-01 14:17:58 +08:00
shadowcz007	7a8dc07a8a	Update ui_mixlab.js	2024-01-01 11:46:21 +08:00
shadowcz007	1fdac0bc09	Update index.html	2024-01-01 11:32:06 +08:00
shadowcz007	804b942a36	Update index.html	2024-01-01 11:16:56 +08:00
shadowcz007	6335d4378b	优化	2024-01-01 10:55:09 +08:00
shadowcz007	cfc2189616	v0.8.1	2023-12-31 23:58:16 +08:00
shadowcz007	e06e032701	fixbug	2023-12-31 23:56:30 +08:00
shadowcz007	c9499c2c79	update	2023-12-31 23:43:17 +08:00
shadowcz007	2bf43541bb	Update appinfo-workflow.svg	2023-12-31 23:42:23 +08:00
shadowcz007	0386c7266d	Update app_mixlab.js	2023-12-31 23:41:12 +08:00
shadowcz007	7aa6ed9a5d	fixbug	2023-12-31 23:36:57 +08:00
shadowcz007	b71325afa5	fixbug	2023-12-31 22:50:40 +08:00
shadowcz007	2cc29bdf77	适配了最新版comfyui的py3.11 ，torch 2.1.2+cu121	2023-12-31 22:48:11 +08:00
shadowcz007	b5d602abc4	Update index.html	2023-12-31 22:01:26 +08:00
shadowcz007	33c45637ac	app	2023-12-31 21:39:50 +08:00
shadowcz007	662d4478d0	Update ui_mixlab.js	2023-12-31 21:31:02 +08:00
shadowcz007	31d3809572	Update ui_mixlab.js	2023-12-31 21:28:45 +08:00
shadowcz007	024ff4a309	Update Lama.py	2023-12-31 21:24:40 +08:00
shadowcz007	9ae8d30b6b	llma	2023-12-31 21:23:26 +08:00
shadowcz007	44349c10b0	Update index.html	2023-12-31 20:09:34 +08:00
shadowcz007	506520a3c4	Create Prompt-weight-workflow.json	2023-12-31 17:58:06 +08:00
shadowcz007	50f7020977	prompt-weight	2023-12-31 17:50:47 +08:00
shadowcz007	02a27a03cc	Update PromptNode.py	2023-12-31 16:22:57 +08:00
shadowcz007	4ad6bacf7b	优化	2023-12-31 16:20:36 +08:00
shadowcz007	26ecc0fa44	新增 PromptSlide节点，实现滑块调节prompt的权重	2023-12-31 16:04:30 +08:00
shadowcz007	2619befca6	Update README.md	2023-12-31 13:14:29 +08:00
shadowcz007	ea24f52b13	Update checkVersion_mixlab.js	2023-12-31 13:12:34 +08:00
shadowcz007	4abfc47346	### Update 0.8.0 v0.8.0 🚀🚗🚚🏃‍ LaMaInpainting - 新增 LaMaInpainting - 优化color节点的输出 - 修复高清显示屏上定位节点不准的情况 - Add LaMaInpainting - Optimize the output of the color node - Fix the issue of inaccurate positioning node on high-definition display screens	2023-12-31 13:11:31 +08:00
shadowcz007	3b95010d06	新增LaMaInpainting & 优化color节点的输出	2023-12-31 13:04:28 +08:00
shadow	b3c1b96088	Merge pull request #97 from shadowcz007/fix_hidpi_node_move_center Fix:node can't move to center on HiDPI device	2023-12-31 10:07:07 +08:00
shadowcz007	a9f1326873	update	2023-12-30 23:52:50 +08:00
shadowcz007	75a696fb64	update	2023-12-30 23:39:36 +08:00
shadowcz007	24aaacba6d	update	2023-12-30 23:38:52 +08:00
shadowcz007	e3cd7d5f91	更新示例	2023-12-30 21:05:07 +08:00
shadow	2e228e8db5	Merge pull request #95 from shadowcz007/v0.7-apps V0.7 apps	2023-12-30 20:53:19 +08:00
shadowcz007	5c9dd80370	fixbug	2023-12-30 20:51:31 +08:00
shadowcz007	727f5f2e48	upate	2023-12-30 20:37:09 +08:00
shadowcz007	1c238f7697	sharebutton	2023-12-30 20:16:51 +08:00
shadowcz007	119d7cce15	0.7.0	2023-12-30 18:19:18 +08:00
shadowcz007	4afc8f6083	Support multiple web app switching. 支持多个web app 切换	2023-12-30 18:16:06 +08:00
shadowcz007	a9ec3af066	改进input range	2023-12-30 18:07:43 +08:00
shadowcz007	9edae81fee	update	2023-12-30 17:48:59 +08:00
shadowcz007	b941b12f12	update	2023-12-30 17:40:28 +08:00
shadowcz007	3069de188a	1	2023-12-30 17:02:44 +08:00
shadowcz007	a968f08abd	update	2023-12-30 14:16:44 +08:00
shadowcz007	4153d3e5ff	1	2023-12-30 12:37:03 +08:00
shadowcz007	9d9c1a6c84	update	2023-12-30 12:29:01 +08:00
shadowcz007	16ef10a4d9	优化node map	2023-12-30 10:10:21 +08:00
shadowcz007	b3766e440a	VHS_VideoCombine	2023-12-30 09:56:08 +08:00
gold3bear	6359c3f70f	Fix:node can't move to center on HiDPI device	2023-12-30 02:09:45 +08:00
shadowcz007	efe73fb965	Update README.md	2023-12-29 10:39:01 +08:00
shadowcz007	c45a962fcc	workflow-to-app支持checkpoints和lora	2023-12-29 10:38:22 +08:00
shadowcz007	f98a03e2e9	Update README.md	2023-12-29 00:00:16 +08:00
shadowcz007	5b6257814d	优化	2023-12-28 23:56:48 +08:00
shadowcz007	69a445d4ed	新增切换节点	2023-12-28 23:18:25 +08:00
shadowcz007	e82c786b8a	增加了从剪切板获取图片的控件	2023-12-28 18:36:34 +08:00
shadowcz007	eec2225c89	支持视频	2023-12-28 16:02:25 +08:00
shadowcz007	f7355e0b71	update	2023-12-28 14:33:59 +08:00
shadowcz007	6c6a99cfe4	优化LoadImagefromlocal ，新增LoadImageFromURL	2023-12-28 13:24:05 +08:00
shadowcz007	b4634e2e0d	修复clipseg的bug	2023-12-28 12:09:36 +08:00
shadowcz007	3f4cba0612	fixbug：textimage的高宽不对	2023-12-27 21:45:35 +08:00
shadowcz007	38db99cc75	支持showtext作为输出。GPT聊天也可以实现workflow-to-app了	2023-12-27 20:39:21 +08:00
shadowcz007	4d5906394b	优化newlayer的可视化效果	2023-12-27 20:12:55 +08:00
shadowcz007	2fc212b156	update	2023-12-27 19:38:39 +08:00
shadowcz007	53fbb5b027	fixbug	2023-12-27 17:48:49 +08:00
shadowcz007	4f24721450	Update README.md	2023-12-27 16:48:29 +08:00
shadow	83043727b5	Merge pull request #83 from shadowcz007/v0.6---simple-app V0.6 simple app	2023-12-27 16:29:27 +08:00
shadowcz007	2d336afb85	v0.6.0	2023-12-27 16:29:00 +08:00
shadowcz007	4d309435c8	Update index.html	2023-12-26 17:15:33 +08:00
shadowcz007	099ce9cdfd	1	2023-12-26 16:32:01 +08:00
shadowcz007	8914e60cb8	初步打通	2023-12-26 16:23:43 +08:00
shadowcz007	dbd30a40e9	init	2023-12-26 12:06:55 +08:00
shadowcz007	c9a598fd59	更新下workflow示例	2023-12-26 10:56:14 +08:00
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