#

v0.3.0 🚀🚗🚚🏃‍

- Added support for setting proxies: HTTP_PROXY, HTTPS_PROXY, http_proxy, https_proxy ✅

- Added a new Speech feature node, enabling the use of a voice assistant: SpeechRecognition & SpeechSynthesis 🎙️

- Added TextImage node, allowing conversion of text into image format 📷

- Added SvgImage node, enabling layout parsing and poster generation in conjunction with the Layer class node 🖼️

- Added an experimental 3DImage node for loading 3D models 🌟

README.md

@@ -1,11 +1,30 @@
 ## 
+v0.3.0 🚀🚗🚚🏃‍
+
+- Added support for setting proxies: HTTP_PROXY, HTTPS_PROXY, http_proxy, https_proxy ✅
+
+- Added a new Speech feature node, enabling the use of a voice assistant: SpeechRecognition & SpeechSynthesis 🎙️
+
+- Added TextImage node, allowing conversion of text into image format 📷
+
+- Added SvgImage node, enabling layout parsing and poster generation in conjunction with the Layer class node 🖼️
+
+- Added an experimental 3DImage node for loading 3D models 🌟
+
 
 ![screenshare](./assets/screenshare.png)
 
 
+### SpeechRecognition & SpeechSynthesis
+![f](./assets/audio-workflow.svg)
+
+[Voice + Real-time Face Swap Workflow](./workflow/语音+实时换脸workflow.json)
+
 ### 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! 💻🌐
 
+> 
+
 https://github.com/shadowcz007/comfyui-mixlab-nodes/assets/12645064/e7e77f90-e43e-410a-ab3a-1952b7b4e7da
 
 
@@ -16,7 +35,7 @@ https://github.com/shadowcz007/comfyui-mixlab-nodes/assets/12645064/e7e77f90-e43
 
 
 ### 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. Q: Translate into English
+> 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)
 
@@ -24,7 +43,7 @@ https://github.com/shadowcz007/comfyui-mixlab-nodes/assets/12645064/e7e77f90-e43
 
 
 ### GPT
-> 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
+> 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)
@@ -32,38 +51,14 @@ https://github.com/shadowcz007/comfyui-mixlab-nodes/assets/12645064/e7e77f90-e43
 [workflow-5](./workflow/5-gpt-workflow.json)
 
 
-## Installation
+### Layers
+> A new layer class node has been added, allowing you to separate the image into layers. After merging the images, you can input the controlnet for further processing.
 
-manually install, simply clone the repo into the custom_nodes directory with this command:
+![layers](./assets/layers-workflow.svg)
 
-```
-cd ComfyUI/custom_nodes
+![poster](./assets/poster-workflow.svg)
 
-git clone https://github.com/shadowcz007/comfyui-mixlab-nodes.git
-
-```
-
-Install the requirements:
-
-run directly:
-```
-cd ComfyUI_Mixlab
-install.bat
-```
-
-or install the requirements using:
-```
-../../../python_embeded/python.exe -s -m pip install -r requirements.txt
-```
-
-If you are using a venv, make sure you have it activated before installation and use:
-```
-pip3 install -r requirements.txt
-```
-
-
-
-## Nodes
+## Other Nodes
 
 ![main](./assets/all-workflow.svg)
 ![main2](./assets/detect-face-all.png)
@@ -79,9 +74,6 @@ pip3 install -r requirements.txt
 ![TransparentImage](./assets/TransparentImage.png)
 
 
-
-
-
 > Consistency Decoder
 
 [openai Consistency Decoder]( https://github.com/openai/consistencydecoder)
@@ -111,6 +103,42 @@ An improvement has been made to directly redirect to GitHub to search for missin
 <!-- ### Workflow
 [Workflow](./workflow.md) -->
 
+
+
+## Installation
+
+manually install, simply clone the repo into the custom_nodes directory with this command:
+
+```
+cd ComfyUI/custom_nodes
+
+git clone https://github.com/shadowcz007/comfyui-mixlab-nodes.git
+
+```
+
+Install the requirements:
+
+run directly:
+```
+cd ComfyUI/custom_nodes/comfyui-mixlab-nodes
+install.bat
+```
+
+or install the requirements using:
+```
+../../../python_embeded/python.exe -s -m pip install -r requirements.txt
+```
+
+If you are using a venv, make sure you have it activated before installation and use:
+```
+pip3 install -r requirements.txt
+```
+
+#### Chinese community
+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)
 
@@ -118,5 +146,26 @@ An improvement has been made to directly redirect to GitHub to search for missin
 [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>
+  <source
+    media="(prefers-color-scheme: dark)"
+    srcset="
+      https://api.star-history.com/svg?repos=shadowcz007/comfyui-mixlab-nodes&type=Date&theme=dark
+    "
+  />
+  <source
+    media="(prefers-color-scheme: light)"
+    srcset="
+      https://api.star-history.com/svg?repos=shadowcz007/comfyui-mixlab-nodes&type=Date
+    "
+  />
+  <img
+    alt="Star History Chart"
+    src="https://api.star-history.com/svg?repos=shadowcz007/comfyui-mixlab-nodes&type=Date"
+  />
+</picture>
+

__init__.py

@@ -64,6 +64,18 @@ except ImportError:
     sys.exit()
 
 
+
+def install_openai():
+    # Helper function to install the OpenAI module if not already installed
+    try:
+        importlib.import_module('openai')
+    except ImportError:
+        import pip
+        pip.main(['install', 'openai'])
+
+install_openai()
+
+
 current_path = os.path.abspath(os.path.dirname(__file__))
 
 
@@ -156,8 +168,44 @@ def save_workflow_json(data):
         json.dump(data, file)
     return workflow_path
 
+
+def get_nodes_map():
+    # print("#####path::", current_path)
+    data_path=os.path.join(current_path, "data")
+    print('data_path: ',data_path)
+    # if not os.path.exists(data_path):
+    #     # 使用mkdir()方法创建新目录
+    #     os.mkdir(data_path)
+    json_data={}
+    nodes_map=os.path.join(current_path, "data/extension-node-map.json")
+    if os.path.exists(nodes_map):
+        with open(nodes_map) as json_file:
+            json_data = json.load(json_file)
+
+    return json_data
+
+
+# 保存原始的 get 方法
+_original_request = aiohttp.ClientSession._request
+
+# 定义新的 get 方法
+async def new_request(self, method, url, *args, **kwargs):
+   # 检查环境变量以确定是否使用代理
+    proxy = os.environ.get('HTTP_PROXY') or os.environ.get('HTTPS_PROXY') or os.environ.get('http_proxy') or os.environ.get('https_proxy') 
+    # print('Proxy Config:',proxy)
+    if proxy and 'proxy' not in kwargs:
+        kwargs['proxy'] = proxy
+        print('Use Proxy:',proxy)
+    # 调用原始的 _request 方法
+    return await _original_request(self, method, url, *args, **kwargs)
+
+# 应用 Monkey Patch
+aiohttp.ClientSession._request = new_request
+
 # https
 async def new_start(self, address, port, verbose=True, call_on_start=None):
+        
+
         runner = web.AppRunner(self.app, access_log=None)
         await runner.setup()
         site = web.TCPSite(runner, address, port)
@@ -227,6 +275,20 @@ async def mixlab_workflow_hander(request):
 
     return web.json_response(result)
 
+@routes.post('/mixlab/nodes_map')
+async def nodes_map_hander(request):
+    data = await request.json()
+    result={}
+    try: 
+        result={
+            'data':get_nodes_map(),
+            'status':'success',
+                }
+    except Exception as e:
+            print(e)
+
+    return web.json_response(result)
+
 def new_add_routes(self):
         import nodes
         self.app.add_routes(routes)
@@ -256,11 +318,14 @@ PromptServer.add_routes=new_add_routes
 
 # 导入节点
 from .nodes.PromptNode import RandomPrompt
-from .nodes.ImageNode import TransparentImage,LoadImagesFromPath,AreaToMask,SmoothMask,FeatheredMask,SplitLongMask,ImageCropByAlpha,EnhanceImage,FaceToMask
+from .nodes.ImageNode import TransparentImage,LoadImagesFromPath,TextImage,SvgImage,Image3D,EmptyLayer,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 SpeechRecognition,SpeechSynthesis
+from .nodes.Utils import ColorInput,FontInput
+
 
 # 要导出的所有节点及其名称的字典
 # 注意：名称应全局唯一
@@ -268,7 +333,14 @@ NODE_CLASS_MAPPINGS = {
     "RandomPrompt":RandomPrompt,
     "TransparentImage":TransparentImage,
     "LoadImagesFromPath":LoadImagesFromPath,
+    "TextImage":TextImage,
     "EnhanceImage":EnhanceImage,
+    "SvgImage":SvgImage,
+    "3DImage":Image3D,
+    "EmptyLayer":EmptyLayer,
+    "ShowLayer":ShowLayer,
+    "NewLayer":NewLayer,
+    "MergeLayers":MergeLayers,
     "SplitLongMask":SplitLongMask,
     "FeatheredMask":FeatheredMask,
     "SmoothMask":SmoothMask,
@@ -281,21 +353,28 @@ NODE_CLASS_MAPPINGS = {
     "FloatingVideo":FloatingVideo,
     "CLIPSeg_":CLIPSeg,
     "CombineMasks_":CombineMasks,
-    "ChatGPT":ChatGPTNode,
+    "ChatGPTOpenAI":ChatGPTNode,
     "ShowTextForGPT":ShowTextForGPT,
-    "CharacterInText":CharacterInText
+    "CharacterInText":CharacterInText,
+    "SpeechRecognition":SpeechRecognition,
+    "SpeechSynthesis":SpeechSynthesis,
+    "Color":ColorInput,
+    "Font":FontInput
 }
 
 # 一个包含节点友好/可读的标题的字典
 NODE_DISPLAY_NAME_MAPPINGS = {
-    "RandomPrompt": "Random Prompt #Mixlab",
+    "RandomPrompt": "Random Prompt ♾️Mixlab",
     "SplitLongMask":"Splitting a long image into sections",
     "VAELoaderConsistencyDecoder":"Consistency Decoder Loader",
     "VAEDecodeConsistencyDecoder":"Consistency Decoder Decode",
-    "ScreenShare":"ScreenShare #Mixlab",
-    "FloatingVideo":"FloatingVideo #Mixlab",
-    "ChatGPT":"ChatGPT #Mixlab",
-    "ShowTextForGPT":"ShowTextForGPT #Mixlab"
+    "ScreenShare":"ScreenShare ♾️Mixlab",
+    "FloatingVideo":"FloatingVideo ♾️Mixlab",
+    "ChatGPTOpenAI":"ChatGPT ♾️Mixlab",
+    "ShowTextForGPT":"ShowTextForGPT ♾️Mixlab",
+    "MergeLayers":"MergeLayers ♾️Mixlab",
+    "SpeechSynthesis":"SpeechSynthesis ♾️Mixlab",
+    "SpeechRecognition":"SpeechRecognition ♾️Mixlab"
 }
 
 # web ui的节点功能

nodes/Audio.py

@@ -0,0 +1,46 @@
+
+
+
+
+class SpeechRecognition:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": { 
+                    "upload":("AUDIOINPUTMIX",),   },
+                }
+    
+    RETURN_TYPES = ("STRING",)
+    RETURN_NAMES = ("prompt",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/audio"
+
+    INPUT_IS_LIST = False
+    OUTPUT_IS_LIST = (False,)
+
+    def run(self,upload):
+        return (upload,)
+
+
+class SpeechSynthesis:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "text": ("STRING", {"forceInput": True}),
+            }
+        }
+
+    INPUT_IS_LIST = True
+    RETURN_TYPES = ("STRING",)
+    FUNCTION = "run"
+    OUTPUT_NODE = True
+    OUTPUT_IS_LIST = (True,)
+
+    CATEGORY = "♾️Mixlab/audio"
+
+    def run(self, text):
+        # print(session_history)
+        return {"ui": {"text": text}, "result": (text,)}
+    

nodes/ChatGPT.py

@@ -46,7 +46,7 @@ def chat(client, model_name,messages ):
             except (urllib.error.HTTPError, openai.OpenAIError) as ex:
                 if try_count >= 3:
                     raise ex
-                time.sleep(5)
+                time.sleep(3)
                 continue
 
         finish_reason = response.choices[0].finish_reason
@@ -75,17 +75,21 @@ class ChatGPTNode:
             "required": {
                 "api_key":("KEY", {"default": "", "multiline": True}),
                 "api_url":("URL", {"default": "", "multiline": True}),
-                "prompt": ("STRING", {"default": "", "multiline": True}),
+                "prompt": ("STRING", {"multiline": True}),
                 "system_content": ("STRING", 
                                    {
                                        "default": "You are ChatGPT, a large language model trained by OpenAI. Answer as concisely as possible.", 
                                        "multiline": True
                                        }),
-                "model": (["gpt-3.5-turbo", "gpt-3.5-turbo-16k-0613", "gpt-4-0613","gpt-4-1106-preview"], 
+                "model": (["gpt-3.5-turbo","gpt-35-turbo","gpt-3.5-turbo-16k", "gpt-3.5-turbo-16k-0613", "gpt-4-0613","gpt-4-1106-preview"], 
                           {"default": "gpt-3.5-turbo"}),
                 "seed": ("INT", {"default": 0, "min": 0, "max": 10000, "step": 1}),
                 "context_size":("INT", {"default": 1, "min": 0, "max":30, "step": 1}),
             },
+             "hidden": {
+                "unique_id": "UNIQUE_ID",
+                "extra_pnginfo": "EXTRA_PNGINFO",
+            },
         }
 
     RETURN_TYPES = ("STRING","STRING","STRING",)
@@ -102,7 +106,7 @@ class ChatGPTNode:
                                  prompt, 
                                  system_content,
                                    model, 
-                                   seed,context_size):
+                                   seed,context_size,unique_id = None, extra_pnginfo=None):
         # print(api_key!='',api_url,prompt,system_content,model,seed)
         # 可以选择保留会话历史以维持上下文记忆
         # 或者在此处清除会话历史 self.session_history.clear()
@@ -140,6 +144,19 @@ class ChatGPTNode:
         response_content = chat(client,model,messages)
         
         self.session_history=self.session_history+[{"role": "user", "content": prompt}]+[{'role':'assistant',"content":response_content}]
+
+
+        # if unique_id and extra_pnginfo and "workflow" in extra_pnginfo[0]:
+        #     workflow = extra_pnginfo[0]["workflow"]
+        #     node = next((x for x in workflow["nodes"] if str(x["id"]) == unique_id[0]), None)
+        #     if node:
+        #         node["widgets_values"] = ["",
+        #                          api_url, 
+        #                          prompt, 
+        #                          system_content,
+        #                            model,
+        #                            seed,
+        #                            context_size]
         
         return (response_content,json.dumps(messages, indent=4),json.dumps(self.session_history, indent=4),)
 

nodes/Clipseg.py

@@ -1,3 +1,6 @@
+#### Thanks:
+# [ComfyUI-CLIPSeg](https://github.com/biegert/ComfyUI-CLIPSeg/tree/main)
+
 from transformers import CLIPSegProcessor, CLIPSegForImageSegmentation
 
 from PIL import Image
@@ -252,7 +255,7 @@ class CombineMasks:
 
 # A dictionary that contains all nodes you want to export with their names
 # NOTE: names should be globally unique
-NODE_CLASS_MAPPINGS = {
-    "CLIPSeg": CLIPSeg,
-    "CombineSegMasks": CombineMasks,
-}
+# NODE_CLASS_MAPPINGS = {
+#     "CLIPSeg": CLIPSeg,
+#     "CombineSegMasks": CombineMasks,
+# }

nodes/ImageNode.py

@@ -1,17 +1,18 @@
 import numpy as np
 import torch
-from PIL import Image, ImageOps,ImageFilter,ImageEnhance,ImageDraw,ImageSequence
+from PIL import Image, ImageOps,ImageFilter,ImageEnhance,ImageDraw,ImageSequence, ImageFont
 from PIL.PngImagePlugin import PngInfo
 import base64,os
 from io import BytesIO
 import folder_paths
-import json
+import json,io
 from comfy.cli_args import args
 import cv2 
 
 from .Watcher import FolderWatcher
 
 
+FONT_PATH= os.path.abspath(os.path.join(os.path.dirname(__file__),'../assets/王汉宗颜楷体繁.ttf'))
 
 MAX_RESOLUTION=8192
 
@@ -322,6 +323,117 @@ def areaToMask(x,y,w,h,image):
     return mask
 
 
+# def merge_images(bg_image, layer_image,mask, x, y, width, height):
+#     # 打开底图
+#     # bg_image = Image.open(background)
+#     bg_image=bg_image.convert("RGBA")
+
+#     # 打开图层
+#     layer_image=layer_image.convert("RGBA")
+#     layer_image = layer_image.resize((width, height))
+#     # mask = Image.new("L", layer_image.size, 255)
+#     mask = mask.resize((width, height))
+#     # 在底图上粘贴图层
+#     bg_image.paste(layer_image, (x, y), mask=mask)
+
+#     # 输出合成后的图片
+#     # bg_image.save("output.jpg")
+#     return bg_image
+
+def merge_images(bg_image, layer_image, mask, x, y, width, height, scale_option):
+    # 打开底图
+    bg_image = bg_image.convert("RGBA")
+
+    # 打开图层
+    layer_image = layer_image.convert("RGBA")
+    # layer_image = layer_image.resize((width, height))
+
+    # 根据缩放选项调整图像大小
+    if scale_option == "height":
+        # 按照高度比例缩放
+        original_width, original_height = layer_image.size
+        scale = height / original_height
+        new_width = int(original_width * scale)
+        layer_image = layer_image.resize((new_width, height))
+    elif scale_option == "width":
+        # 按照宽度比例缩放
+        original_width, original_height = layer_image.size
+        scale = width / original_width
+        new_height = int(original_height * scale)
+        layer_image = layer_image.resize((width, new_height))
+    elif scale_option == "overall":
+        # 整体缩放
+        layer_image = layer_image.resize((width, height))
+
+    # 调整mask的大小
+    nw, nh = layer_image.size
+    mask = mask.resize((nw, nh))
+
+    # 在底图上粘贴图层
+    bg_image.paste(layer_image, (x, y), mask=mask)
+
+    # 输出合成后的图片
+    return bg_image
+
+
+
+def generate_text_image(text_list, font_path, font_size, text_color, vertical=True, spacing=0):
+    # Load Chinese font
+    font = ImageFont.truetype(font_path, font_size)
+
+    # Calculate image size based on the number of characters and orientation
+    if vertical:
+        width = font_size + 100
+        height = font_size * len(text_list) + (len(text_list) - 1) * spacing + 100
+    else:
+        width = font_size * len(text_list) + (len(text_list) - 1) * spacing + 100
+        height = font_size + 100
+
+    # Create a blank image
+    image = Image.new('RGBA', (width, height), (255, 255, 255,0))
+    draw = ImageDraw.Draw(image)
+
+    # Draw text
+    if vertical:
+        for i, char in enumerate(text_list):
+            char_position = (50, 50 + i * font_size)
+            draw.text(char_position, char, font=font, fill=text_color)
+    else:
+        for i, char in enumerate(text_list):
+            char_position = (50 + i * (font_size + spacing), 50)
+            draw.text(char_position, char, font=font, fill=text_color)
+
+    # Save the image
+    # image.save(output_image_path)
+
+    # 分离alpha通道
+    alpha_channel = image.split()[3]
+
+    # 创建一个只有alpha通道的新图像
+    alpha_image = Image.new('L', image.size)
+    alpha_image.putdata(alpha_channel.getdata())
+
+    image=image.convert('RGB')
+
+    return (image,alpha_image)
+
+
+def base64_to_image(base64_string):
+    # 去除前缀
+    prefix, base64_data = base64_string.split(",", 1)
+    
+    # 从base64字符串中解码图像数据
+    image_data = base64.b64decode(base64_data)
+    
+    # 创建一个内存流对象
+    image_stream = io.BytesIO(image_data)
+    
+    # 使用PIL的Image模块打开图像数据
+    image = Image.open(image_stream)
+    
+    return image
+
+
 
 class SmoothMask:
     @classmethod
@@ -494,6 +606,7 @@ class TransparentImage:
             }
     
     RETURN_TYPES = ('STRING','IMAGE','RGBA')
+    RETURN_NAMES = ("file_path","IMAGE","RGBA",)
 
     OUTPUT_NODE = True
 
@@ -671,7 +784,7 @@ class LoadImagesFromPath:
             imgs=[imgs[index_variable]] if index_variable < len(imgs) else None
             masks=[masks[index_variable]] if index_variable < len(masks) else None
 
-        print('#prompt::::',prompt)
+        # print('#prompt::::',prompt)
         return (imgs,masks,prompt,)
 
 
@@ -708,6 +821,117 @@ class ImageCropByAlpha:
         return (img,)
 
 
+
+class TextImage:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": { 
+            
+                    "text": ("STRING",{"multiline": False,"default": "龍馬精神迎新歲"}),
+                    "font_path": ("STRING",{"multiline": False,"default": FONT_PATH}),
+                    "font_size": ("INT",{
+                                "default":100, 
+                                "min": 100, #Minimum value
+                                "max": 1000, #Maximum value
+                                "step": 1, #Slider's step
+                                "display": "number" # Cosmetic only: display as "number" or "slider"
+                                }), 
+                    "spacing": ("INT",{
+                                "default":12, 
+                                "min": 1, #Minimum value
+                                "max": 200, #Maximum value
+                                "step": 1, #Slider's step
+                                "display": "number" # Cosmetic only: display as "number" or "slider"
+                                }), 
+                    "text_color":("STRING",{"multiline": False,"default": "#000000"}),
+                    "vertical":("BOOLEAN", {"default": True},),
+                             },
+                }
+    
+    RETURN_TYPES = ("IMAGE","MASK")
+    # RETURN_NAMES = ("WIDTH","HEIGHT","X","Y",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/image"
+
+    INPUT_IS_LIST = False
+    OUTPUT_IS_LIST = (False,False,)
+
+    def run(self,text,font_path,font_size,spacing,text_color,vertical):
+        
+        text_list=list(text)
+
+        img,mask=generate_text_image(text_list,font_path,font_size,text_color,vertical,spacing)
+        
+        img=pil2tensor(img)
+        mask=pil2tensor(mask)
+
+        return (img,mask,)
+
+
+
+class SvgImage:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": { 
+                    "upload":("SVG",),},
+                }
+    
+    RETURN_TYPES = ("IMAGE","LAYER")
+    RETURN_NAMES = ("IMAGE","layers",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/image"
+
+    INPUT_IS_LIST = False
+    OUTPUT_IS_LIST = (False,True,)
+
+    def run(self,upload):
+        layers=[]
+
+        image = base64_to_image(upload['image'])
+        image=image.convert('RGB')
+        image=pil2tensor(image)
+
+        for layer in upload['data']:
+            layers.append(layer)
+    
+        return (image,layers,)
+
+
+
+class Image3D:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": { 
+                    "upload":("THREED",),   },
+                }
+    
+    RETURN_TYPES = ("IMAGE","MASK",)
+    # RETURN_NAMES = ("IMAGE",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/image"
+
+    INPUT_IS_LIST = False
+    OUTPUT_IS_LIST = (False,False,)
+
+    def run(self,upload):
+        # print(upload['image'])
+        image = base64_to_image(upload['image'])
+        image=image.convert('RGB')
+        mask=image.convert('L')
+        
+        mask=pil2tensor(mask)
+        image=pil2tensor(image)
+
+        return (image,mask,)
+
+
+
 class AreaToMask:
     @classmethod
     def INPUT_TYPES(s):
@@ -770,3 +994,292 @@ class FaceToMask:
 
         return (mask,)
 
+
+class EmptyLayer:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": { 
+                "width": ("INT",{
+                    "default":512, 
+                    "min": 1, #Minimum value
+                    "max": 8192, #Maximum value
+                    "step": 1, #Slider's step
+                    "display": "number" # Cosmetic only: display as "number" or "slider"
+                }),
+               "height": ("INT",{
+                    "default": 512, 
+                    "min": 1, #Minimum value
+                    "max": 8192, #Maximum value
+                    "step": 1, #Slider's step
+                    "display": "number" # Cosmetic only: display as "number" or "slider"
+                }),
+            },
+        
+                }
+    
+    RETURN_TYPES = ("LAYER",)
+    RETURN_NAMES = ("layers",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/layer"
+
+    OUTPUT_IS_LIST = (True,)
+
+    def run(self, width,height):
+        blank_image = Image.new("RGB", (width, height))
+        
+        mask=blank_image.convert('L')
+
+        blank_image=pil2tensor(blank_image)
+        mask=pil2tensor(mask)
+
+        layer_n=[{
+            "x":0,
+            "y":0,
+            "width":width,
+            "height":height,
+            "z_index":0,
+            "scale_option":'width',
+            "image":blank_image,
+            "mask":mask
+        }]
+        return (layer_n,)
+
+
+class NewLayer:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            
+            "required": { 
+                "x": ("INT",{
+                    "default": 0, 
+                    "min": -100, #Minimum value
+                    "max": 8192, #Maximum value
+                    "step": 1, #Slider's step
+                    "display": "number" # Cosmetic only: display as "number" or "slider"
+                }),
+                "y": ("INT",{
+                    "default": 0, 
+                    "min": 0, #Minimum value
+                    "max": 8192, #Maximum value
+                    "step": 1, #Slider's step
+                    "display": "number" # Cosmetic only: display as "number" or "slider"
+                }),
+                "width": ("INT",{
+                    "default": 512, 
+                    "min": 1, #Minimum value
+                    "max": 8192, #Maximum value
+                    "step": 1, #Slider's step
+                    "display": "number" # Cosmetic only: display as "number" or "slider"
+                }),
+                "height": ("INT",{
+                    "default": 512, 
+                    "min": 1, #Minimum value
+                    "max": 8192, #Maximum value
+                    "step": 1, #Slider's step
+                    "display": "number" # Cosmetic only: display as "number" or "slider"
+                }),
+                "z_index": ("INT",{
+                    "default": 0, 
+                    "min":0, #Minimum value
+                    "max": 100, #Maximum value
+                    "step": 1, #Slider's step
+                    "display": "number" # Cosmetic only: display as "number" or "slider"
+                }),
+                "scale_option": (["width","height",'overall'],),
+                "image": ("IMAGE",),
+            },
+             "optional":{
+                    "mask": ("MASK",{"default": None}),
+                    "layers": ("LAYER",{"default": None}), 
+                }
+                }
+    
+    RETURN_TYPES = ("LAYER",)
+    RETURN_NAMES = ("layers",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/layer"
+
+    INPUT_IS_LIST = True
+    OUTPUT_IS_LIST = (True,)
+
+    def run(self,x,y,width,height,z_index,scale_option,image,mask,layers):
+        # print(x,y,width,height,z_index,image,mask)
+        
+        if mask==None:
+            im=tensor2pil(image)
+            mask=im.convert('L')
+            mask=pil2tensor(mask)
+        else:
+            mask=mask[0]
+
+        layer_n=[{
+            "x":x[0],
+            "y":y[0],
+            "width":width[0],
+            "height":height[0],
+            "z_index":z_index[0],
+            "scale_option":scale_option[0],
+            "image":image[0],
+            "mask":mask
+        }]
+
+        if layers!=None:
+            layer_n=layer_n+layers
+
+        return (layer_n,)
+
+
+class ShowLayer:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            
+            "required": { 
+                "edit": ("EDIT",),
+               
+                "x": ("INT",{
+                    "default": 0, 
+                    "min": -100, #Minimum value
+                    "max": 8192, #Maximum value
+                    "step": 1, #Slider's step
+                    "display": "number" # Cosmetic only: display as "number" or "slider"
+                }),
+                "y": ("INT",{
+                    "default": 0, 
+                    "min": 0, #Minimum value
+                    "max": 8192, #Maximum value
+                    "step": 1, #Slider's step
+                    "display": "number" # Cosmetic only: display as "number" or "slider"
+                }),
+                "width": ("INT",{
+                    "default": 512, 
+                    "min": 1, #Minimum value
+                    "max": 8192, #Maximum value
+                    "step": 1, #Slider's step
+                    "display": "number" # Cosmetic only: display as "number" or "slider"
+                }),
+                "height": ("INT",{
+                    "default": 512, 
+                    "min": 1, #Minimum value
+                    "max": 8192, #Maximum value
+                    "step": 1, #Slider's step
+                    "display": "number" # Cosmetic only: display as "number" or "slider"
+                }),
+                "z_index": ("INT",{
+                    "default": 0, 
+                    "min":0, #Minimum value
+                    "max": 100, #Maximum value
+                    "step": 1, #Slider's step
+                    "display": "number" # Cosmetic only: display as "number" or "slider"
+                }),
+                "scale_option": (["width","height",'overall'],),
+                # "image": ("IMAGE",),
+            },
+             "optional":{
+                    # "mask": ("MASK",{"default": None}),
+                    "layers": ("LAYER",{"default": None}), 
+                }
+                }
+    
+    RETURN_TYPES = ( )
+    RETURN_NAMES = ( )
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/layer"
+
+    INPUT_IS_LIST = True
+    # OUTPUT_IS_LIST = (True,)
+
+    def run(self,edit,x,y,width,height,z_index,scale_option,layers):
+        # print(x,y,width,height,z_index,image,mask)
+        
+        # if mask==None:
+        #     im=tensor2pil(image)
+        #     mask=im.convert('L')
+        #     mask=pil2tensor(mask)
+        # else:
+        #     mask=mask[0]
+
+        # layers[edit[0]]={
+        #     "x":x[0],
+        #     "y":y[0],
+        #     "width":width[0],
+        #     "height":height[0],
+        #     "z_index":z_index[0],
+        #     "scale_option":scale_option[0],
+        #     "image":image[0],
+        #     "mask":mask
+        # }
+
+        return ( )
+
+
+class MergeLayers:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": { 
+            "layers": ("LAYER",),
+            "image": ("IMAGE",),
+                             },
+                }
+    
+    RETURN_TYPES = ("IMAGE",)
+    # RETURN_NAMES = ("WIDTH","HEIGHT","X","Y",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/layer"
+
+    INPUT_IS_LIST = True
+    # OUTPUT_IS_LIST = (False,)
+
+    def run(self,layers,image):
+        # print(len(layers),len(image))
+        bg_image=image[0]
+        bg_image=tensor2pil(bg_image)
+        # 按z-index排序
+        layers_new = sorted(layers, key=lambda x: x["z_index"])
+     
+        for layer in layers_new:
+            image=layer['image']
+            mask=layer['mask']
+            if 'type' in layer and layer['type']=='base64' and type(image) == str:
+                im=base64_to_image(image)
+                im=im.convert('RGB')
+                image=pil2tensor(im)
+
+                mask=base64_to_image(mask)
+                mask=mask.convert('L')
+                mask=pil2tensor(mask)
+            
+            
+            layer_image=tensor2pil(image)
+            layer_mask=tensor2pil(mask)
+            bg_image=merge_images(bg_image,
+                                  layer_image,
+                                  layer_mask,
+                                  layer['x'],
+                                  layer['y'],
+                                  layer['width'],
+                                  layer['height'],
+                                  layer['scale_option']
+                                  )
+            
+        mask=bg_image.convert('RGBA')
+        mask=pil2tensor(mask)
+        
+        bg_image=bg_image.convert('RGB')
+        bg_image=pil2tensor(bg_image)
+
+        channels = ["red", "green", "blue", "alpha"]
+        # print(mask,mask.shape)
+        mask = mask[:, :, :, channels.index("green")]
+        
+        return (bg_image,mask,)

nodes/ScreenShareNode.py

@@ -82,23 +82,25 @@ class ScreenShareNode:
         },
           "optional":{
               "prompt": ("PROMPT",),
+              "slide": ("SLIDE",),
+              "seed": ("SEED",),
             #   "seed": ("INT", {"default": 1, "min": 0, "max": 0xffffffffffffffff}),
                 } }
     
-    RETURN_TYPES = ('IMAGE','STRING')
-
+    RETURN_TYPES = ('IMAGE','STRING','FLOAT',"INT")
+    RETURN_NAMES = ("IMAGE","PROMPT","FLOAT","INT")
     FUNCTION = "run"
 
     CATEGORY = "♾️Mixlab/image"
 
     # INPUT_IS_LIST = True
-    OUTPUT_IS_LIST = (False,False,False)
+    OUTPUT_IS_LIST = (False,False,False,False)
   
     # 运行的函数
-    def run(self,image_base64,prompt):
+    def run(self,image_base64,prompt,slide,seed):
         im,mask=base64_save(image_base64)
         # print('##########prompt',prompt)
-        return (im,prompt)
+        return (im,prompt,slide,seed)
     
 
 class FloatingVideo:
@@ -137,3 +139,15 @@ class FloatingVideo:
 
         return { "ui": { "images_": results } }
 
+
+
+# class SildeNode:
+#     CATEGORY = "quicknodes"
+#     @classmethod    
+#     def INPUT_TYPES(s):
+#         return { "required":{} }
+#     RETURN_TYPES = ()
+#     RETURN_NAMES = ()
+#     FUNCTION = "func"
+#     def func(self):
+#         return ()

nodes/Utils.py

@@ -0,0 +1,83 @@
+import os
+
+# FONT_PATH= os.path.abspath(os.path.join(os.path.dirname(__file__),'../assets/王汉宗颜楷体繁.ttf'))
+
+import matplotlib.font_manager as fm
+
+def get_font_files(directory):
+    font_files = {}
+
+    # 从指定目录加载字体
+    for file in os.listdir(directory):
+        if file.endswith('.ttf') or file.endswith('.otf'):
+            font_name = os.path.splitext(file)[0]
+            font_path = os.path.join(directory, file)
+            font_files[font_name] = os.path.abspath(font_path)
+
+    # 尝试获取系统字体
+    try:
+        font_paths = fm.findSystemFonts()
+        for path in font_paths:
+            try:
+                font_prop = fm.FontProperties(fname=path)
+                font_name = font_prop.get_name()
+                font_files[font_name] = path
+            except Exception as e:
+                print(f"Error processing font {path}: {e}")
+    except Exception as e:
+        print(f"Error finding system fonts: {e}")
+
+    return font_files
+
+r_directory = os.path.join(os.path.dirname(__file__), '../assets/')
+
+font_files = get_font_files(r_directory)
+# print(font_files)
+
+
+class ColorInput:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": { 
+             
+                    "color":("TCOLOR",), 
+                             },
+                }
+    
+    RETURN_TYPES = ("STRING",)
+    # RETURN_NAMES = ("WIDTH","HEIGHT","X","Y",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/utils"
+
+    INPUT_IS_LIST = False
+    OUTPUT_IS_LIST = (False,False,)
+
+    def run(self,color):
+        return (color,)
+
+
+
+class FontInput:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": { 
+             
+                    "font": (list(font_files.keys()),),
+                             },
+                }
+    
+    RETURN_TYPES = ("STRING",)
+    # RETURN_NAMES = ("WIDTH","HEIGHT","X","Y",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/utils"
+
+    INPUT_IS_LIST = False
+    OUTPUT_IS_LIST = (False,False,)
+
+    def run(self,font):
+
+        return (font_files[font],)

web/javascript/audio_mixlab.js

@@ -0,0 +1,311 @@
+import { app } from '../../../scripts/app.js'
+// import { api } from '../../../scripts/api.js'
+import { ComfyWidgets } from '../../../scripts/widgets.js'
+import { $el } from '../../../scripts/ui.js'
+
+function get_position_style (ctx, widget_width, y, node_height) {
+  const MARGIN = 4 // the margin around the html element
+
+  /* Create a transform that deals with all the scrolling and zooming */
+  const elRect = ctx.canvas.getBoundingClientRect()
+  const transform = new DOMMatrix()
+    .scaleSelf(
+      elRect.width / ctx.canvas.width,
+      elRect.height / ctx.canvas.height
+    )
+    .multiplySelf(ctx.getTransform())
+    .translateSelf(MARGIN, MARGIN + y)
+
+  return {
+    transformOrigin: '0 0',
+    transform: transform,
+    left: `0`,
+    top: `0`,
+    cursor: 'pointer',
+    position: 'absolute',
+    maxWidth: `${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}px`,
+    // height: `${node_height * 0.3 - MARGIN * 2}px`,
+    // background: '#EEEEEE',
+    display: 'flex',
+    flexDirection: 'column',
+    // alignItems: 'center',
+    justifyContent: 'space-around'
+  }
+}
+
+const getLocalData = key => {
+  let data = {}
+  try {
+    data = JSON.parse(localStorage.getItem(key)) || {}
+  } catch (error) {
+    return {}
+  }
+  return data
+}
+
+function speakText (text) {
+  const speechMsg = new SpeechSynthesisUtterance()
+  speechMsg.text = text
+
+  // 语音合成结束时触发的事件
+  speechMsg.onend = function (event) {
+    console.log('语音播放结束')
+    window._mixlab_speech_synthesis_onend = true
+  }
+
+  // 语音合成错误时触发的事件
+  speechMsg.onerror = function (event) {
+    console.error('语音播放错误:', event.error)
+  }
+
+  // 使用浏览器默认语音合成器进行语音播放
+  speechSynthesis.speak(speechMsg)
+}
+
+// 调用方法，将文字转换为语音播放
+// speakText('Hello, how are you?');
+//                      #MixCopilot
+
+const start = (element, id, startBtn) => {
+
+  startBtn.className='loading_mixlab'
+
+  window.recognition = new webkitSpeechRecognition()
+
+  window.recognition.continuous = true
+  window.recognition.interimResults = true
+  window.recognition.lang = navigator.language
+
+  let timeoutId, intervalId
+
+  window.recognition.onstart = () => {
+    console.log('开始语音输入', window._mixlab_speech_synthesis_onend)
+    window._mixlab_speech_synthesis_onend = false
+  }
+
+  window.recognition.onresult = function (event) {
+    const result = event.results[event.results.length - 1][0].transcript
+    console.log('识别结果：', result)
+    element.value = result
+
+    let data = getLocalData('_mixlab_speech_recognition')
+    data[id] = result.trim()
+    localStorage.setItem('_mixlab_speech_recognition', JSON.stringify(data))
+
+    if (timeoutId) clearTimeout(timeoutId)
+   
+    if (!window.recognition) return
+
+    timeoutId = setTimeout(function () {
+      console.log('结果传递：：', result)
+      app.queuePrompt(0, 1)
+      window.recognition?.stop()
+      window.recognition = null;
+      startBtn.className=''
+      startBtn.innerText = 'START'
+
+      timeoutId = null
+
+      intervalId = setInterval(() => {
+        if (
+          app.ui.lastQueueSize === 0 &&
+          !window.recognition &&
+          window._mixlab_speech_synthesis_onend
+        ) {
+          start(element, id, startBtn)
+          startBtn.innerText = 'STOP'
+          if (intervalId) {
+            clearInterval(intervalId)
+          }
+        }
+      }, 2200)
+    }, 2000)
+  }
+
+  window.recognition.onend = function () {
+    console.log('语音输入结束')
+  }
+
+  window.recognition.onspeechend = function () {
+    console.log('onspeechend')
+  }
+
+  window.recognition.onerror = function (event) {
+    console.log('Error occurred in recognition: ' + event.error)
+  }
+
+  window.recognition.start()
+}
+
+app.registerExtension({
+  name: 'Mixlab.audio.SpeechRecognition',
+  async getCustomWidgets (app) {
+    return {
+      AUDIOINPUTMIX (node, inputName, inputData, app) {
+        // console.log('##node', node)
+        const widget = {
+          type: inputData[0], // the type, CHEESE
+          name: inputName, // the name, slice
+          size: [128, 32], // a default size
+          draw (ctx, node, width, y) {},
+          computeSize (...args) {
+            return [128, 32] // a method to compute the current size of the widget
+          },
+          async serializeValue (nodeId, widgetIndex) {
+            let data = getLocalData('_mixlab_speech_recognition')
+            return data[node.id] || 'Hello Mixlab'
+          }
+        }
+        //  widget.something = something;          // maybe adds stuff to it
+        node.addCustomWidget(widget) // adds it to the node
+        return widget // and returns it.
+      }
+    }
+  },
+
+  async beforeRegisterNodeDef (nodeType, nodeData, app) {
+    if (nodeType.comfyClass == 'SpeechRecognition') {
+      const orig_nodeCreated = nodeType.prototype.onNodeCreated
+      nodeType.prototype.onNodeCreated = function () {
+        orig_nodeCreated?.apply(this, arguments)
+
+        const widget = {
+          type: 'div',
+          name: 'chatgptdiv',
+          draw (ctx, node, widget_width, y, widget_height) {
+            Object.assign(
+              this.div.style,
+              get_position_style(ctx, widget_width, 44, node.size[1])
+            )
+          }
+        }
+
+        widget.div = $el('div', {})
+
+        document.body.appendChild(widget.div)
+
+        const inputDiv = (key, placeholder) => {
+          let div = document.createElement('div')
+          const startBtn = document.createElement('button')
+          const textArea = document.createElement('textarea')
+
+          textArea.className = `${'comfy-multiline-input'} ${placeholder}`
+
+          textArea.style = `margin-top: 14px;
+          height: 44px;`
+
+          div.style = `flex-direction: column;
+          display: flex;
+          margin: 0px 8px 6px;`
+
+          startBtn.style = `
+            outline: none;
+            border: none;
+            padding: 4px; `
+
+          startBtn.innerText = 'START'
+
+          div.appendChild(startBtn)
+          div.appendChild(textArea)
+
+          startBtn.addEventListener('click', () => {
+            if (window.recognition) {
+              window.recognition.stop()
+              window.recognition = null
+              startBtn.innerText = 'START'
+              startBtn.className=''
+            } else {
+              start(textArea, this.id, startBtn)
+              startBtn.innerText = 'STOP'
+            }
+          })
+
+          return div
+        }
+
+        let inputAudio = inputDiv('_mixlab_speech_recognition', 'audio')
+        widget.div.appendChild(inputAudio)
+
+        this.addCustomWidget(widget)
+
+        const onRemoved = this.onRemoved
+        this.onRemoved = () => {
+          inputAudio.remove()
+          widget.div.remove()
+          return onRemoved?.()
+        }
+
+        this.serialize_widgets = true //需要保存参数
+      }
+    }
+  },
+  async loadedGraphNode (node, app) {
+    if (node.type === 'SpeechRecognition') {
+      let data = getLocalData('_mixlab_speech_recognition')
+      // console.log('_mixlab_speech_recognition', node.widgets)
+      let div = node.widgets.filter(f => f.type === 'div')[0]
+      if (div && data[node.id]) {
+        div.div.querySelector('textarea').value = data[node.id]
+      }
+    }
+  }
+})
+
+app.registerExtension({
+  name: 'Mixlab.audio.SpeechSynthesis',
+  async beforeRegisterNodeDef (nodeType, nodeData, app) {
+    if (nodeData.name === 'SpeechSynthesis') {
+      function populate (text) {
+        // console.log('SpeechSynthesis',this.widgets)
+
+        if (this.widgets) {
+          const pos = this.widgets.findIndex(w => w.name === 'text')
+          if (pos !== -1) {
+            for (let i = pos; i < this.widgets.length; i++) {
+              this.widgets[i].onRemove?.()
+            }
+            this.widgets.length = pos
+          }
+        }
+
+        for (let list of text) {
+          const w = ComfyWidgets['STRING'](
+            this,
+            'text',
+            ['STRING', { multiline: true }],
+            app
+          ).widget
+          w.inputEl.readOnly = true
+          w.inputEl.style.opacity = 0.6
+          w.value = list
+        }
+
+        speakText(text.join('\n'))
+
+        // console.log('ShowTextForGPT',this.widgets.length)
+        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)
+        populate.call(this, message.text)
+      }
+
+      this.serialize_widgets = true //需要保存参数
+    }
+  }
+})

web/javascript/checkVersion_mixlab.js

@@ -3,16 +3,20 @@ 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 = 'v0.2.5.2'
+const version = 'v0.3.1'
 
 fetch(`https://api.github.com/repos/${repoOwner}/${repoName}/releases/latest`)
   .then(response => response.json())
   .then(data => {
     const latestVersion = data.tag_name
     console.log('Latest release version:', latestVersion)
-    // if (latestVersion === localStorage.getItem('_mixlab_nodes_vesion')) return
-    if (latestVersion != version) {
-      // localStorage.setItem('_mixlab_nodes_vesion', latestVersion)
+    if (
+      latestVersion &&
+      latestVersion === localStorage.getItem('_mixlab_nodes_vesion')
+    )
+      return
+    if (latestVersion && latestVersion != version) {
+      localStorage.setItem('_mixlab_nodes_vesion', latestVersion)
       app.ui.dialog.show(`<h4 style="font-size: 18px;">${repoName} <br>
       Latest release version: ${latestVersion}</h4>
       <p>Please proceed to the official repository to download the latest version.</p>

web/javascript/gpt_mixlab.js

@@ -46,23 +46,33 @@ function get_position_style (ctx, widget_width, y, node_height) {
   }
 }
 
+const getLocalData = key => {
+  let data = {}
+  try {
+    data = JSON.parse(localStorage.getItem(key)) || {}
+  } catch (error) {
+    return {}
+  }
+  return data
+}
+
 app.registerExtension({
-  name: 'Mixlab.GPT.ChatGPT',
+  name: 'Mixlab.GPT.ChatGPTOpenAI',
   async getCustomWidgets (app) {
     return {
       KEY (node, inputName, inputData, app) {
-        // console.log('node', inputName, inputData[0])
+        // console.log('##node', node)
         const widget = {
           type: inputData[0], // the type, CHEESE
           name: inputName, // the name, slice
-          size: [128, 24], // a default size
+          size: [128, 32], // a default size
           draw (ctx, node, width, y) {},
           computeSize (...args) {
-            return [128, 24] // a method to compute the current size of the widget
+            return [128,32] // a method to compute the current size of the widget
           },
           async serializeValue (nodeId, widgetIndex) {
-            //localStorage.getItem('_mixlab_api_key') || ''
-            return 'by Mixlab'
+            let data = getLocalData('_mixlab_api_key')
+            return data[node.id] || 'by Mixlab'
           }
         }
         //  widget.something = something;          // maybe adds stuff to it
@@ -74,15 +84,16 @@ app.registerExtension({
         const widget = {
           type: inputData[0], // the type, CHEESE
           name: inputName, // the name, slice
-          size: [128, 24], // a default size
+          size: [128, 32], // a default size
           draw (ctx, node, width, y) {
             // a method to draw the widget (ctx is a CanvasRenderingContext2D)
           },
           computeSize (...args) {
-            return [128, 24] // a method to compute the current size of the widget
+            return [128, 32] // a method to compute the current size of the widget
           },
           async serializeValue (nodeId, widgetIndex) {
-            return localStorage.getItem('_mixlab_api_url') || 'https://api.openai.com/v1'
+            let data = getLocalData('_mixlab_api_url')
+            return data[node.id] || 'https://api.openai.com/v1'
           }
         }
         //  widget.something = something;          // maybe adds stuff to it
@@ -91,22 +102,21 @@ app.registerExtension({
       }
     }
   },
+
   async beforeRegisterNodeDef (nodeType, nodeData, app) {
-    // console.log(nodeType.comfyClass)
-    if (nodeType.comfyClass == 'ChatGPT') {
+    if (nodeType.comfyClass == 'ChatGPTOpenAI') {
       const orig_nodeCreated = nodeType.prototype.onNodeCreated
       nodeType.prototype.onNodeCreated = function () {
         orig_nodeCreated?.apply(this, arguments)
 
-        console.log('ChatGPT widtget', this.widgets)
-
         const api_key = this.widgets.filter(w => w.name == 'api_key')[0]
         const api_url = this.widgets.filter(w => w.name == 'api_url')[0]
-        // console.log('api_key', api_key, api_url)
+
+        console.log('ChatGPTOpenAI nodeData', this.widgets)
 
         const widget = {
           type: 'div',
-          name: 'chatgpt div',
+          name: 'chatgptdiv',
           draw (ctx, node, widget_width, y, widget_height) {
             Object.assign(
               this.div.style,
@@ -119,36 +129,43 @@ app.registerExtension({
 
         document.body.appendChild(widget.div)
 
-        const inputKey = document.createElement('input'),
-          inputUrl = document.createElement('input')
-        inputKey.type = 'text'
-        inputUrl.type = 'text'
+        const inputDiv = (key, placeholder) => {
+          let div = document.createElement('div')
+          const ip = document.createElement('input')
+          ip.type = placeholder === 'Key' ? 'password' : 'text'
+          ip.className = `${'comfy-multiline-input'} ${placeholder}`
+          div.style = `display: flex;
+          align-items: center; 
+          margin: 6px 8px;
+          margin-top: 0;`
+          ip.placeholder = placeholder
+          ip.value = placeholder
 
-        inputKey.placeholder = 'Key'
-        inputUrl.placeholder = 'URL'
+          ip.style = `margin-left: 24px;
+          outline: none;
+          border: none;
+          padding: 4px;width: 100%;`
+          const label = document.createElement('label')
+          label.style = 'font-size: 10px;min-width:32px'
+          label.innerText = placeholder
+          div.appendChild(label)
+          div.appendChild(ip)
 
-        inputKey.style = `margin:4px 48px;`
-        inputUrl.style = `margin:4px 48px`
+          ip.addEventListener('change', () => {
+            let data = getLocalData(key)
+            data[this.id] = ip.value.trim()
+            localStorage.setItem(key, JSON.stringify(data))
+            console.log(this.id, key)
+          })
+          return div
+        }
 
-        inputUrl.value = localStorage.getItem('_mixlab_api_url') || 'https://api.openai.com/v1'
-        inputKey.value = localStorage.getItem('_mixlab_api_key') || 'by Mixlab'
+        let inputKey = inputDiv('_mixlab_api_key', 'Key')
+        let inputUrl = inputDiv('_mixlab_api_url', 'URL')
 
         widget.div.appendChild(inputKey)
         widget.div.appendChild(inputUrl)
 
-        inputKey.addEventListener('change', () => {
-          api_key.serializeValue = () => inputKey.value || 'by Mixlab'
-          localStorage.setItem('_mixlab_api_key', inputKey.value)
-        })
-
-        inputUrl.addEventListener('change', () => {
-          api_url.serializeValue = () => inputUrl.value || 'https://api.openai.com/v1'
-          localStorage.setItem('_mixlab_api_url', inputUrl.value)
-        })
-
-        /*
-                Add the widget, make sure we clean up nicely, and we do not want to be serialized!
-                */
         this.addCustomWidget(widget)
 
         const onRemoved = this.onRemoved
@@ -159,82 +176,102 @@ app.registerExtension({
           return onRemoved?.()
         }
 
-        this.serialize_widgets = false
+        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 === 'ChatGPTOpenAI') {
+      let widget = node.widgets.filter(w => w.div)[0]
+
+      let apiKey = getLocalData('_mixlab_api_key'),
+        url = getLocalData('_mixlab_api_url')
+
+      let id = node.id
+
+      // console.log('ChatGPTOpenAI serialize_widgets', this)
+
+      widget.div.querySelector('.Key').value = apiKey[id] || 'by Mixlab'
+      widget.div.querySelector('.URL').value =
+        url[id] || 'https://api.openai.com/v1'
+    }
   }
 })
 
 app.registerExtension({
   name: 'Mixlab.GPT.ShowTextForGPT',
-  async beforeRegisterNodeDef (nodeType, nodeData, app) {
-    if (nodeData.name === 'ShowTextForGPT') {
-      function populate (text) {
-        if (this.widgets) {
-          // const pos = this.widgets.findIndex((w) => w.name === "text");
-          // if (pos !== -1) {
-          // 	for (let i = pos; i < this.widgets.length; i++) {
-          // 		this.widgets[i].onRemove?.();
-          // 	}
-          // 	this.widgets.length = pos;
-          // }
-
-          for (let i = 0; i < this.widgets.length; i++) {
-            this.widgets[i].onRemove?.()
-          }
-          this.widgets.length = 0
-        }
-
-        console.log('ShowTextForGPT', this.widgets, text)
-
-        for (const list of text) {
-          const w = ComfyWidgets['STRING'](
-            this,
-            'text',
-            ['STRING', { multiline: true }],
-            app
-          ).widget
-          w.inputEl.readOnly = true
-          w.inputEl.style.opacity = 0.6
-
-          let res = list
+  async beforeRegisterNodeDef(nodeType, nodeData, app) {
+		if (nodeData.name === "ShowTextForGPT") {
+			function populate(text) {
+				if (this.widgets) {
+          
+					const pos = this.widgets.findIndex((w) => w.name === "text");
+					if (pos !== -1) {
+						for (let i = pos; i < this.widgets.length; i++) {
+							this.widgets[i].onRemove?.();
+						}
+						this.widgets.length = pos;
+					}
+				}
+        // console.log('ShowTextForGPT',text)
+				for (let list of text) {
+					const w = ComfyWidgets["STRING"](this, "text", ["STRING", { multiline: true }], app).widget;
+					w.inputEl.readOnly = true;
+					w.inputEl.style.opacity = 0.6;
 
           try {
-            res = JSON.stringify(JSON.parse(list), null, 2)
+            let data=JSON.parse(list);
+            data=Array.from(data,d=>{
+              return {
+                ...d,
+                content:decodeURIComponent(d.content)
+              }
+            })
+            list=JSON.stringify(data,null,2)
           } catch (error) {
-            // console.log(list)
+            // console.log(error)
           }
 
-          w.value = res
-        }
+					w.value =list;
+        
+				}
+        // console.log('ShowTextForGPT',this.widgets.length)
+				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);
+				});
+			}
 
-        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);
+				populate.call(this, message.text);
+			};
 
-      // 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)
-        populate.call(this, message.text)
-      }
+			const onConfigure = nodeType.prototype.onConfigure;
+			nodeType.prototype.onConfigure = function () {
+				onConfigure?.apply(this, arguments);
+				if (this.widgets_values?.length) {
+          
+					populate.call(this, this.widgets_values);
+				}
+			};
 
-      const onConfigure = nodeType.prototype.onConfigure
-      nodeType.prototype.onConfigure = function () {
-        onConfigure?.apply(this, arguments)
-        if (this.widgets_values?.length) {
-          populate.call(this, this.widgets_values)
-        }
-      }
-    }
-  }
+      this.serialize_widgets = true //需要保存参数
+
+		}
+
+
+	},
 })

web/javascript/image_mixlab.js

@@ -0,0 +1,659 @@
+import { app } from '../../../scripts/app.js'
+import { api } from '../../../scripts/api.js'
+import { ComfyWidgets } from '../../../scripts/widgets.js'
+import { $el } from '../../../scripts/ui.js'
+
+async function uploadImage (blob, fileType = '.svg') {
+  // const blob = await (await fetch(src)).blob();
+  const body = new FormData()
+  body.append('image', new File([blob], new Date().getTime() + fileType))
+
+  const resp = await api.fetchApi('/upload/image', {
+    method: 'POST',
+    body
+  })
+
+  // console.log(resp)
+  let data = await resp.json()
+  let { name, subfolder } = data
+  let src = api.apiURL(
+    `/view?filename=${encodeURIComponent(
+      name
+    )}&type=input&subfolder=${subfolder}${app.getPreviewFormatParam()}${app.getRandParam()}`
+  )
+
+  return src
+}
+
+function base64ToBlobFromURL (base64URL, contentType) {
+  return fetch(base64URL).then(response => response.blob())
+}
+
+function getContentTypeFromBase64 (base64Data) {
+  const regex = /^data:(.+);base64,/
+  const matches = base64Data.match(regex)
+  if (matches && matches.length >= 2) {
+    return matches[1]
+  }
+  return null
+}
+
+// 示例用法
+// const base64Data = 'data:image/jpeg;base64,/9j/4AAQSkZJRgABAQEAAAAAAAD/...'; // 替换为实际的base64图片数据
+// const contentType = getContentTypeFromBase64(base64Data);
+// console.log(contentType);
+
+// // 示例用法
+// const base64Data = '...'; // 替换为实际的base64图片数据
+// const contentType = 'image/jpeg'; // 替换为实际的图片类型
+
+// const blob = base64ToBlob(base64Data, contentType);
+// console.log(blob);
+
+function get_position_style (ctx, widget_width, y, node_height) {
+  const MARGIN = 4 // the margin around the html element
+
+  /* Create a transform that deals with all the scrolling and zooming */
+  const elRect = ctx.canvas.getBoundingClientRect()
+  const transform = new DOMMatrix()
+    .scaleSelf(
+      elRect.width / ctx.canvas.width,
+      elRect.height / ctx.canvas.height
+    )
+    .multiplySelf(ctx.getTransform())
+    .translateSelf(MARGIN, MARGIN + y)
+
+  return {
+    transformOrigin: '0 0',
+    transform: transform,
+    left: `0`,
+    top: `0`,
+    cursor: 'pointer',
+    position: 'absolute',
+    maxWidth: `${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}px`,
+    // height: `${node_height * 0.3 - MARGIN * 2}px`,
+    // background: '#EEEEEE',
+    display: 'flex',
+    flexDirection: 'column',
+    // alignItems: 'center',
+    justifyContent: 'space-around'
+  }
+}
+
+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
+}
+
+function createImage (url) {
+  let im = new Image()
+  return new Promise((res, rej) => {
+    im.onload = () => res(im)
+    im.src = url
+  })
+}
+
+const parseImage = url => {
+  return new Promise((res, rej) => {
+    fetch(url)
+      .then(response => response.blob())
+      .then(blob => {
+        const reader = new FileReader()
+        reader.onloadend = () => {
+          const base64data = reader.result
+          res(base64data)
+          // 在这里可以将base64数据用于进一步处理或显示图片
+        }
+        reader.readAsDataURL(blob)
+      })
+      .catch(error => {
+        console.log('发生错误:', error)
+      })
+  })
+}
+
+const parseSvg = async svgContent => {
+  let scale = 2
+  // 创建一个临时的DOM元素来解析SVG
+  const tempContainer = document.createElement('div')
+  tempContainer.innerHTML = svgContent
+
+  // 提取SVG元素
+  const svgElement = tempContainer.querySelector('svg')
+  if (!svgElement) return
+  // 获取SVG中 rect元素
+  var rectElements = svgElement?.querySelectorAll('rect') || []
+  // console.log(rectElements,svgElement)
+  // 定义一个数组来存储处理后的数据
+  var data = []
+
+  Array.from(rectElements, (rectElement, i) => {
+    // 获取rect元素的属性值
+    var x = ~~(rectElement.getAttribute('x') || 0)
+    var y = ~~(rectElement.getAttribute('y') || 0)
+    var width = ~~rectElement.getAttribute('width')
+    var height = ~~rectElement.getAttribute('height')
+    // console.log('rectElements',rectElement,x,y,width,height)
+    if (x != undefined && y != undefined && width && height) {
+      // 创建一个新的canvas元素
+      var canvas = document.createElement('canvas')
+      canvas.width = width
+      canvas.height = height
+      var context = canvas.getContext('2d')
+
+      // 填充颜色到canvas
+      var fill = rectElement.getAttribute('fill')
+      context.fillStyle = fill
+      context.fillRect(0, 0, width, height)
+
+      // 将canvas转换为base64格式
+      var base64 = canvas.toDataURL()
+
+      // 将数据转化为指定的JSON格式
+
+      var rectData = {
+        x: parseInt(x),
+        y: parseInt(y),
+        width: parseInt(width),
+        height: parseInt(height),
+        z_index: i + 1,
+        scale_option: 'width',
+        image: base64,
+        mask: base64,
+        type: 'base64',
+        _t: 'rect'
+      }
+
+      // 将处理后的数据添加到数组中
+      data.push(rectData)
+    }
+  })
+
+  var svgWidth = svgElement.getAttribute('width')
+  var svgHeight = svgElement.getAttribute('height')
+
+  if (!(svgWidth && svgHeight)) {
+    // viewBox
+    let viewBox = svgElement.viewBox.baseVal
+
+    svgWidth = viewBox.width
+    svgHeight = viewBox.height
+  }
+
+  // 创建一个新的canvas元素
+  var canvas = document.createElement('canvas')
+  canvas.width = svgWidth
+  canvas.height = svgHeight
+  var context = canvas.getContext('2d')
+  // 绘制SVG到canvas
+  var svgString = new XMLSerializer().serializeToString(svgElement)
+  var DOMURL = window.URL || window.webkitURL || window
+
+  var svgBlob = new Blob([svgString], { type: 'image/svg+xml;charset=utf-8' })
+  var url = DOMURL.createObjectURL(svgBlob)
+
+  let img = await createImage(url)
+  context.drawImage(img, 0, 0)
+
+  let base64 = canvas.toDataURL()
+
+  var rectData = {
+    x: 0,
+    y: 0,
+    width: parseInt(svgWidth),
+    height: parseInt(svgHeight),
+    z_index: 0,
+    scale_option: 'width',
+    image: base64,
+    mask: base64,
+    type: 'base64',
+    _t: 'canvas'
+  }
+  data.push(rectData)
+
+  // 打印处理后的数据
+  console.log('layers', { data, image: base64, svgElement })
+  return { data, image: base64, svgElement }
+}
+
+app.registerExtension({
+  name: 'Mixlab.image.SvgImage',
+  async getCustomWidgets (app) {
+    return {
+      SVG (node, inputName, inputData, app) {
+        // console.log('##node', node, inputName, inputData)
+        const widget = {
+          type: inputData[0], // the type, CHEESE
+          name: inputName, // the name, slice
+          size: [128, 88], // a default size
+          draw (ctx, node, width, y) {},
+          computeSize (...args) {
+            return [128, 88] // a method to compute the current size of the widget
+          },
+          async serializeValue (nodeId, widgetIndex) {
+            let d = getLocalData('_mixlab_svg_image')
+            // console.log('serializeValue',d)
+            if (d) {
+              let url = d[node.id]
+              let dt = await fetch(url)
+              let svgStr = await dt.text()
+              const { data, image } = (await parseSvg(svgStr)) || {}
+              // console.log(data, image)
+              return JSON.parse(JSON.stringify({ data, image }))
+            } else {
+              return
+            }
+          }
+        }
+
+        // console.log('##node',node.serialize)
+        //  widget.something = something;          // maybe adds stuff to it
+        node.addCustomWidget(widget) // adds it to the node
+
+        return widget // and returns it.
+      }
+    }
+  },
+
+  async beforeRegisterNodeDef (nodeType, nodeData, app) {
+    if (nodeType.comfyClass == 'SvgImage') {
+      const orig_nodeCreated = nodeType.prototype.onNodeCreated
+      nodeType.prototype.onNodeCreated = async function () {
+        orig_nodeCreated?.apply(this, arguments)
+
+        const uploadWidget = this.widgets.filter(w => w.name == 'upload')[0]
+        // console.log('SvgImage nodeData',await uploadWidget.serializeValue())
+
+        const widget = {
+          type: 'div',
+          name: 'upload-preview',
+          draw (ctx, node, widget_width, y, widget_height) {
+            Object.assign(
+              this.div.style,
+              get_position_style(ctx, widget_width, 44, node.size[1])
+            )
+          }
+        }
+
+        widget.div = $el('div', {})
+
+        document.body.appendChild(widget.div)
+
+        const inputDiv = (key, placeholder, svgContainer) => {
+          let div = document.createElement('div')
+          const ip = document.createElement('input')
+          ip.type = 'file'
+          ip.className = `${'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: 60%;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)
+
+          let that = this
+
+          ip.addEventListener('change', event => {
+            const file = event.target.files[0]
+            const reader = new FileReader()
+
+            // 读取文件内容
+            reader.onload = async e => {
+              const svgContent = e.target.result
+
+              var blob = new Blob([svgContent], { type: 'image/svg+xml' })
+              let url = await uploadImage(blob)
+              // console.log(url)
+              const { svgElement, data, image } = await parseSvg(svgContent)
+              // 将提取的SVG元素显示在页面上
+              let dd = getLocalData(key)
+              dd[that.id] = url
+              setLocalDataOfWin(key, dd)
+              // console.log(this.id, ip.value.trim())
+
+              svgElement.style = `width: 90%;padding: 5%;`
+              // 将提取的SVG元素显示在页面上
+
+              svgContainer.innerHTML = ''
+              svgContainer.appendChild(svgElement)
+              let h = ~~getComputedStyle(svgElement).height.replace('px', '')
+              if (that.size && that.size[1] < h) {
+                that.setSize([that.size[0], that.size[1] + h])
+                app.canvas.draw(true, true)
+              }
+              // console.log(that.size,~~getComputedStyle(svgElement).height.replace('px',''))
+
+              uploadWidget.value = await uploadWidget.serializeValue()
+            }
+
+            // 以文本形式读取文件
+            reader.readAsText(file)
+          })
+          return div
+        }
+
+        let svg = document.createElement('div')
+        svg.className = 'preview'
+        svg.style = `background:#eee;margin-top: 12px;`
+
+        let upload = inputDiv('_mixlab_svg_image', 'Svg', svg)
+
+        widget.div.appendChild(upload)
+        widget.div.appendChild(svg)
+        this.addCustomWidget(widget)
+
+        const onRemoved = this.onRemoved
+        this.onRemoved = () => {
+          upload.remove()
+          svg.remove()
+          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) {
+    // Fires every time a node is constructed
+    // You can modify widgets/add handlers/etc here
+    const sleep = (t = 1000) => {
+      return new Promise((res, rej) => {
+        setTimeout(() => res(1), t)
+      })
+    }
+    if (node.type === 'SvgImage') {
+      // await sleep(0)
+      let widget = node.widgets.filter(w => w.name === 'upload-preview')[0]
+
+      let dd = getLocalData('_mixlab_svg_image')
+
+      let id = node.id
+      console.log('SvgImage load', node.widgets[0], node.widgets)
+      if (!dd[id]) return
+      let dt = await fetch(dd[id])
+      let svgStr = await dt.text()
+
+      const { svgElement, data, image } = await parseSvg(svgStr)
+      svgElement.style = `width: 90%;padding: 5%;`
+      // 将提取的SVG元素显示在页面上
+
+      widget.div.querySelector('.preview').innerHTML = ''
+      widget.div.querySelector('.preview').appendChild(svgElement)
+
+      const uploadWidget = node.widgets.filter(w => w.name == 'upload')[0]
+      uploadWidget.value = await uploadWidget.serializeValue()
+
+      // let h=~~getComputedStyle(widget.div).height.replace('px','');
+      // let w=~~getComputedStyle(widget.div).width.replace('px','');
+      // // console.log('svg', w,h,node.size)
+      // node.setSize([
+      //   w,h
+      // ])
+      // app.graph.setDirtyCanvas(true)
+
+      // console.log(node.widgets_values)
+    }
+  }
+})
+
+app.registerExtension({
+  name: 'Mixlab.image.3DImage',
+  async getCustomWidgets (app) {
+    return {
+      THREED (node, inputName, inputData, app) {
+        // console.log('##node', node, inputName, inputData)
+        const widget = {
+          type: inputData[0], // the type, CHEESE
+          name: inputName, // the name, slice
+          size: [128, 88], // a default size
+          draw (ctx, node, width, y) {},
+          computeSize (...args) {
+            return [128, 88] // a method to compute the current size of the widget
+          },
+          async serializeValue (nodeId, widgetIndex) {
+            let d = getLocalData('_mixlab_3d_image')
+            // console.log('serializeValue',d)
+            if (d) {
+              let url = d[node.id]
+              let base64 = await parseImage(url)
+
+              return JSON.parse(JSON.stringify({ image: base64 }))
+            } else {
+              return {}
+            }
+          }
+        }
+        node.addCustomWidget(widget)
+        return widget
+      }
+    }
+  },
+
+  async beforeRegisterNodeDef (nodeType, nodeData, app) {
+    if (nodeType.comfyClass == '3DImage') {
+      const orig_nodeCreated = nodeType.prototype.onNodeCreated
+      nodeType.prototype.onNodeCreated = async function () {
+        orig_nodeCreated?.apply(this, arguments)
+
+        const uploadWidget = this.widgets.filter(w => w.name == 'upload')[0]
+        console.log('3d nodeData', this.inputs)
+
+        const widget = {
+          type: 'div',
+          name: 'upload-preview',
+          draw (ctx, node, widget_width, y, widget_height) {
+            Object.assign(
+              this.div.style,
+              get_position_style(ctx, widget_width, 44, node.size[1])
+            )
+          }
+        }
+
+        widget.div = $el('div', {})
+
+        document.body.appendChild(widget.div)
+
+        const inputDiv = (key, placeholder, preview) => {
+          let div = document.createElement('div')
+          const ip = document.createElement('input')
+          ip.type = 'file'
+          ip.className = `${'comfy-multiline-input'} ${placeholder}`
+          div.style = `display: flex;
+          align-items: center; 
+          margin: 6px 8px;
+          margin-top: 0;`
+          ip.placeholder = placeholder
+          // ip.value = value
+
+          ip.style = `outline: none;
+          border: none;
+          padding: 4px;
+          width: 60%;cursor: pointer;
+          height: 32px;`
+          const label = document.createElement('label')
+          label.style = 'font-size: 10px;min-width:32px'
+          label.innerText = placeholder
+          div.appendChild(label)
+          div.appendChild(ip)
+
+          let that = this
+
+          ip.addEventListener('change', event => {
+            const file = event.target.files[0]
+            const reader = new FileReader()
+
+            // 读取文件内容
+            reader.onload = async e => {
+              const fileURL = URL.createObjectURL(file)
+              // console.log('文件URL: ', fileURL)
+              let html = `<model-viewer 
+              alt="Neil Armstrong's Spacesuit from the Smithsonian Digitization Programs Office and National Air and Space Museum"
+               src="${fileURL}" 
+               ar 
+               shadow-intensity="1" 
+               camera-controls 
+               touch-action="pan-y">
+               
+               <div class="controls">
+                <div>Variant: <select class="variant"></select></div>
+                <div><button class="capture">Capture</button></div>
+              </div></model-viewer>`
+
+              preview.innerHTML = html;
+              that.setSize([that.size[0],that.size[1]+300])
+              app.canvas.draw(true, true)
+
+              const modelViewerVariants = preview.querySelector('model-viewer')
+              const select = preview.querySelector('.variant')
+              const capture = preview.querySelector('.capture')
+
+              modelViewerVariants.addEventListener('load', () => {
+                const names = modelViewerVariants.availableVariants
+                for (const name of names) {
+                  const option = document.createElement('option')
+                  option.value = name
+                  option.textContent = name
+                  select.appendChild(option)
+                }
+                // Adds a default option.
+                const option = document.createElement('option')
+                option.value = 'default'
+                option.textContent = 'Default'
+                select.appendChild(option)
+              })
+
+              select.addEventListener('input', event => {
+                modelViewerVariants.variantName =
+                  event.target.value === 'default' ? null : event.target.value
+              })
+
+              capture.addEventListener('click', async () => {
+                let base64Data = modelViewerVariants.toDataURL()
+
+                const contentType = getContentTypeFromBase64(base64Data)
+
+                const blob = await base64ToBlobFromURL(base64Data, contentType)
+
+                //  const fileBlob = new Blob([e.target.result], { type: file.type });
+                let url = await uploadImage(blob, '.png')
+                console.log(url)
+
+                let dd = getLocalData(key)
+                dd[that.id] = url
+
+                setLocalDataOfWin(key, dd)
+              })
+
+              uploadWidget.value = await uploadWidget.serializeValue()
+            }
+
+            // 以文本形式读取文件
+            reader.readAsDataURL(file)
+          })
+          return div
+        }
+
+        let preview = document.createElement('div')
+        preview.className = 'preview'
+        preview.style = `margin-top: 12px;display: flex;
+        justify-content: center;
+        align-items: center;`
+
+        let upload = inputDiv('_mixlab_3d_image', '3D Model', preview)
+
+        widget.div.appendChild(upload)
+        widget.div.appendChild(preview)
+        this.addCustomWidget(widget);
+
+        const onResize = this.onResize;
+				this.onResize = function () {
+          let m=preview.querySelector('model-viewer')
+          m.style.width=`${this.size[0]-24}px`
+          m.style.height=`${this.size[1]-48}px`
+          // console.log(this.size,preview)
+					return onResize?.apply(this, arguments);
+				};
+
+
+        const onRemoved = this.onRemoved
+        this.onRemoved = () => {
+          upload.remove()
+          preview.remove()
+          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) {
+    // Fires every time a node is constructed
+    // You can modify widgets/add handlers/etc here
+    const sleep = (t = 1000) => {
+      return new Promise((res, rej) => {
+        setTimeout(() => res(1), t)
+      })
+    }
+    if (node.type === '3DImage') {
+      // await sleep(0)
+      let widget = node.widgets.filter(w => w.name === 'upload-preview')[0]
+
+      let dd = getLocalData('_mixlab_3d_image')
+
+      let id = node.id
+      console.log('3dImage load', node.widgets[0], node.widgets)
+      if (!dd[id]) return
+
+      let url = dd[id]
+      // let base64 = await parseImage(url)
+
+      widget.div.querySelector('.preview').innerHTML = `<img src="${url}"/>`
+
+      const uploadWidget = node.widgets.filter(w => w.name == 'upload')[0]
+      uploadWidget.value = await uploadWidget.serializeValue()
+
+      // let h=~~getComputedStyle(widget.div).height.replace('px','');
+      // let w=~~getComputedStyle(widget.div).width.replace('px','');
+      // // console.log('svg', w,h,node.size)
+      // node.setSize([
+      //   w,h
+      // ])
+      // app.graph.setDirtyCanvas(true)
+
+      // console.log(node.widgets_values)
+    }
+  }
+})

web/javascript/layer_mixlab.js

@@ -0,0 +1,352 @@
+import { app } from '../../../scripts/app.js'
+// import { api } from '../../../scripts/api.js'
+import { ComfyWidgets } from '../../../scripts/widgets.js'
+import { $el } from '../../../scripts/ui.js'
+
+function get_position_style (ctx, widget_width, y, node_height) {
+  const MARGIN = 4 // the margin around the html element
+
+  /* Create a transform that deals with all the scrolling and zooming */
+  const elRect = ctx.canvas.getBoundingClientRect()
+  const transform = new DOMMatrix()
+    .scaleSelf(
+      elRect.width / ctx.canvas.width,
+      elRect.height / ctx.canvas.height
+    )
+    .multiplySelf(ctx.getTransform())
+    .translateSelf(MARGIN, MARGIN + y)
+
+  return {
+    transformOrigin: '0 0',
+    transform: transform,
+    left: `0`,
+    top: `0`,
+    cursor: 'pointer',
+    position: 'absolute',
+    maxWidth: `${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}px`,
+    // height: `${node_height * 0.3 - MARGIN * 2}px`,
+    // background: '#EEEEEE',
+    display: 'flex',
+    // flexDirection: 'column',
+    // alignItems: 'center',
+    justifyContent: 'space-around'
+  }
+}
+
+const getLocalData = key => {
+  let data = {}
+  try {
+    data = JSON.parse(localStorage.getItem(key)) || {}
+  } catch (error) {
+    return {}
+  }
+  return data
+}
+
+function createImage (url) {
+  let im = new Image()
+  return new Promise((res, rej) => {
+    im.onload = () => res(im)
+    im.src = url
+  })
+}
+
+const parseSvg = async svgContent => {
+  // 创建一个临时的DOM元素来解析SVG
+  const tempContainer = document.createElement('div')
+  tempContainer.innerHTML = svgContent
+
+  // 提取SVG元素
+  const svgElement = tempContainer.querySelector('svg')
+  if (!svgElement) return
+  // 获取SVG中 rect元素
+  var rectElements = svgElement?.querySelectorAll('rect') || []
+  // console.log(rectElements,svgElement)
+  // 定义一个数组来存储处理后的数据
+  var data = []
+
+  Array.from(rectElements, (rectElement, i) => {
+    // 获取rect元素的属性值
+    var x = ~~(rectElement.getAttribute('x')||0);
+    var y = ~~(rectElement.getAttribute('y')||0);
+    var width = ~~rectElement.getAttribute('width')
+    var height = ~~rectElement.getAttribute('height')
+    // console.log('rectElements',rectElement,x,y,width,height)
+    if (x != undefined && y != undefined&&width&&height) {
+      // 创建一个新的canvas元素
+      var canvas = document.createElement('canvas')
+      canvas.width = width
+      canvas.height = height
+      var context = canvas.getContext('2d')
+
+      // 填充颜色到canvas
+      var fill = rectElement.getAttribute('fill')
+      context.fillStyle = fill
+      context.fillRect(0, 0, width, height)
+
+      // 将canvas转换为base64格式
+      var base64 = canvas.toDataURL()
+
+      // 将数据转化为指定的JSON格式
+
+      var rectData = {
+        x: parseInt(x),
+        y: parseInt(y),
+        width: parseInt(width),
+        height: parseInt(height),
+        z_index: i + 1,
+        scale_option: 'width',
+        image: base64,
+        mask: base64,
+        type: 'base64',
+        _t:'rect'
+      }
+
+      // 将处理后的数据添加到数组中
+      data.push(rectData)
+    }
+  })
+
+  var svgWidth = svgElement.getAttribute('width')
+  var svgHeight = svgElement.getAttribute('height')
+
+  if (!(svgWidth && svgHeight)) {
+    // viewBox
+    let viewBox = svgElement.viewBox.baseVal
+     
+    svgWidth =viewBox.width
+    svgHeight =viewBox.height
+  }
+
+  // 创建一个新的canvas元素
+  var canvas = document.createElement('canvas')
+  canvas.width = svgWidth
+  canvas.height = svgHeight
+  var context = canvas.getContext('2d')
+  // 绘制SVG到canvas
+  var svgString = new XMLSerializer().serializeToString(svgElement)
+  var DOMURL = window.URL || window.webkitURL || window
+
+  var svgBlob = new Blob([svgString], { type: 'image/svg+xml;charset=utf-8' })
+  var url = DOMURL.createObjectURL(svgBlob)
+
+  let img = await createImage(url)
+  context.drawImage(img, 0, 0)
+
+  let base64 = canvas.toDataURL()
+
+  var rectData = {
+    x: 0,
+    y: 0,
+    width: parseInt(svgWidth),
+    height: parseInt(svgHeight),
+    z_index: 0,
+    scale_option: 'width',
+    image: base64,
+    mask: base64,
+    type: 'base64',
+    _t:'canvas'
+  }
+  data.push(rectData)
+
+  // 打印处理后的数据
+  console.log('layers',{ data, image: base64, svgElement })
+  return { data, image: base64, svgElement }
+}
+
+app.registerExtension({
+  name: 'Mixlab.layer.ShowLayer',
+  async getCustomWidgets (app) {
+    return {
+      EDIT (node, inputName, inputData, app) {
+        //   console.log('EditLayer##node', node,inputName, inputData)
+        const widget = {
+          type: inputData[0], // the type, CHEESE
+          name: inputName, // the name, slice
+          size: [128, 44], // a default size
+          draw (ctx, node, widget_width, y, widget_height) {
+            // console.log('EditLayer', this)
+            if (this.input)
+              Object.assign(
+                this.input.style,
+                get_position_style(ctx, widget_width, 32, node.size[1])
+              )
+          },
+          computeSize (...args) {
+            return [128, 44] // a method to compute the current size of the widget
+          },
+          async serializeValue (nodeId, widgetIndex) {
+            let d = getLocalData('_mixlab_edit_layer')
+            // console.log('EditLayer',d[node.id])
+            return d[node.id]
+          }
+        }
+        //  widget.something = something;          // maybe adds stuff to it
+        node.addCustomWidget(widget) // adds it to the node
+        return widget // and returns it.
+      }
+    }
+  },
+
+  async beforeRegisterNodeDef (nodeType, nodeData, app) {
+    if (nodeType.comfyClass == 'ShowLayer') {
+      const orig_nodeCreated = nodeType.prototype.onNodeCreated
+      nodeType.prototype.onNodeCreated = async function () {
+        orig_nodeCreated?.apply(this, arguments)
+
+        const findNode = nodeId => {
+          let node = app.graph._nodes_by_id[nodeId]
+          if (node?.type == 'Reroute') {
+            
+            let linkId =node.inputs.filter(i=>i.type=='*')[0].link
+            nodeId = app.graph.links.filter(link => link.id == linkId)[0]
+              ?.origin_id
+            return findNode(nodeId)
+          } else {
+            return nodeId
+          }
+        }
+
+        // 获取layers数据
+        const getLayers = async () => {
+          console.log('getLayers1',this.inputs.filter(ip => ip.name === 'layers'))
+          let linkId = this.inputs.filter(ip => ip.name === 'layers')[0].link
+          let nodeId = app.graph.links?.filter(link => link.id == linkId)[0]
+            ?.origin_id;
+
+          if(nodeId){
+            nodeId = findNode(nodeId)
+          }
+          
+
+          //   let node = app.graph._nodes_by_id[nodeId]
+          //   if (node?.type == 'Reroute') {
+          //     linkId = node.inputs[0].link
+          //     nodeId = app.graph.links.filter(link => link.id == linkId)[0]
+          //       ?.origin_id
+          //   }
+         
+          let d = getLocalData('_mixlab_svg_image')
+          console.log('test',d[nodeId])
+
+          if (d[nodeId]) {
+            let url = d[nodeId]
+            let dt = await fetch(url)
+           
+            let svgStr = await dt.text()
+           
+            const { data } = (await parseSvg(svgStr)) || {}
+            console.log('fetch',data)
+            return data
+          } else {
+            return []
+          }
+        }
+
+        // 修改layers数据
+        const setLayer = async (editIndex, layers = null) => {
+          //   let editIndex = 0
+          let lys = layers || (await getLayers())
+          let layer = lys[editIndex]
+          //   console.log(layer)
+
+          const updateValue = name => {
+            const x = this.widgets.filter(w => w.name == name)[0]
+            x.value = layer[name]
+          }
+          if (layer) {
+            Array.from(['x', 'y', 'width', 'height', 'z_index'], n =>
+              updateValue(n)
+            )
+          }
+        }
+
+        let that = this
+        const save_edit_layer_index = i => {
+          let data = getLocalData('_mixlab_edit_layer')
+          data[that.id] = i
+          localStorage.setItem('_mixlab_edit_layer', JSON.stringify(data))
+        }
+
+        await setLayer(0)
+        save_edit_layer_index(0)
+
+        const edit = this.widgets.filter(w => w.name == 'edit')[0]
+
+        edit.input = $el('div', {})
+        edit.input.style = `
+        display: flex;
+        flex-direction:row;
+        align-items: center;
+        margin-top: 0;`
+
+        const ip = $el('input', {})
+        ip.className = 'comfy-multiline-input'
+        ip.type = 'number'
+        ip.min = 0
+        ip.step = 1
+        ip.max = Math.max(0, (await getLayers()).length - 1)
+        // ip.className = `${'comfy-multiline-input'} `
+
+        ip.value = 0
+
+        ip.style = `
+        background-color: var(--comfy-input-bg);
+        color: var(--input-text);
+        outline: none;
+          border: none;
+          padding: 4px;
+          width: 60%;
+          cursor: pointer;
+          height: 24px;`
+        const label = document.createElement('label')
+        label.style = 'font-size: 10px;min-width:32px'
+        label.innerText = 'Layer Index'
+        edit.input.appendChild(label)
+        edit.input.appendChild(ip)
+
+        document.body.appendChild(edit.input)
+
+        ip.addEventListener('click', async event => {
+          console.log(await getLayers())
+          ip.max = Math.max(0, (await getLayers()).length - 1)
+        })
+
+        ip.addEventListener('change', async event => {
+          let index = ~~ip.value
+          let lys = await getLayers()
+          await setLayer(index, lys)
+          app.graph.setDirtyCanvas(true, true)
+          save_edit_layer_index(index)
+        })
+
+        // console.log('EditLayer nodeData', edit)
+
+        const onRemoved = this.onRemoved
+        this.onRemoved = () => {
+          edit.input.remove()
+          return onRemoved?.()
+        }
+
+        if (this.onResize) {
+          this.onResize(this.size)
+        }
+
+        this.serialize_widgets = false //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 === 'SvgImage') {
+      let widget = node.widgets.filter(w => w.div)[0]
+      let data = getLocalData('_mixlab_svg_image')
+      let id = node.id
+
+      // widget.div.querySelector('.Svg').value = data[id] || '#000000'
+    }
+  }
+})

web/javascript/main_mixlab.js

@@ -106,24 +106,65 @@ async function uploadFile (file) {
 
 // alert(navigator.mediaDevices)
 
-async function shareScreen (webcamVideo, shareBtn, liveBtn, previewArea) {
+async function shareScreen (
+  isCamera = false,
+  webcamVideo,
+  shareBtn,
+  liveBtn,
+  previewArea
+) {
   try {
-    // let webcamVideo = document.createElement('video')
-    const mediaStream = await navigator.mediaDevices.getDisplayMedia({
-      video: true
-    })
+    let mediaStream
+
+    if (!isCamera) {
+      mediaStream = await navigator.mediaDevices.getDisplayMedia({
+        video: true
+      })
+    } else {
+      if (!localStorage.getItem('_mixlab_webcamera_select')) return
+      let constraints =
+        JSON.parse(localStorage.getItem('_mixlab_webcamera_select')) || {}
+      mediaStream = await navigator.mediaDevices.getUserMedia(constraints)
+    }
 
     webcamVideo.removeEventListener('timeupdate', videoTimeUpdateHandler)
     webcamVideo.srcObject = mediaStream
     webcamVideo.onloadedmetadata = () => {
+      let x = 0,
+        y = 0,
+        width = webcamVideo.videoWidth,
+        height = webcamVideo.videoHeight,
+        imgWidth = webcamVideo.videoWidth,
+        imgHeight = webcamVideo.videoHeight
+
+      let d = getSetAreaData()
+      if (
+        d &&
+        d.x >= 0 &&
+        d.imgWidth === imgWidth &&
+        d.imgHeight === imgHeight
+      ) {
+        x = d.x
+        y = d.y
+        width = d.width
+        height = d.height
+        imgWidth = d.imgWidth
+        imgHeight = d.imgHeight
+        console.log('#screen_share::使用上一次选区')
+      }
+      updateSetAreaData(x, y, width, height, imgWidth, imgHeight)
+
       webcamVideo.play()
+
+      createBlobFromVideo(webcamVideo, true)
+
       webcamVideo.addEventListener('timeupdate', videoTimeUpdateHandler)
 
-      window._mixlab_screen_x = 0
-      window._mixlab_screen_y = 0
-      // console.log(webcamVideo)
-      window._mixlab_screen_width = webcamVideo.videoWidth
-      window._mixlab_screen_height = webcamVideo.videoHeight
+      // window._mixlab_screen_x = 0
+      // window._mixlab_screen_y = 0
+      // // console.log(webcamVideo)
+      // window._mixlab_screen_width = webcamVideo.videoWidth
+      // window._mixlab_screen_height = webcamVideo.videoHeight
     }
 
     mediaStream.addEventListener('inactive', handleStopSharing)
@@ -278,7 +319,7 @@ async function startLive (btn) {
         previousImage,
         currentImage
       )
-      // console.log('#图片是否有变化:', imageChanged)
+      console.log('#图片是否有变化:', imageChanged)
 
       if (imageChanged) {
         window._mixlab_screen_imagePath = currentImage
@@ -328,26 +369,17 @@ async function createBlobFromVideoForArea (webcamVideo) {
   return blob
 }
 
-async function createBlobFromVideo (webcamVideo) {
+async function createBlobFromVideo (webcamVideo, updateImageBase64 = false) {
   const videoW = webcamVideo.videoWidth
   const videoH = webcamVideo.videoHeight
   const aspectRatio = videoW / videoH
-  const WIDTH = window._mixlab_screen_width,
-    HEIGHT = window._mixlab_screen_height
-  const canvas = new OffscreenCanvas(WIDTH, HEIGHT)
+
+  const { x, y, width, height } = window._mixlab_share_screen
+
+  const canvas = new OffscreenCanvas(width, height)
   const ctx = canvas.getContext('2d')
-  // console.log('#createBlobFromVideo', WIDTH, HEIGHT)
-  ctx.drawImage(
-    webcamVideo,
-    window._mixlab_screen_x,
-    window._mixlab_screen_y,
-    WIDTH,
-    HEIGHT,
-    0,
-    0,
-    WIDTH,
-    HEIGHT
-  )
+
+  ctx.drawImage(webcamVideo, x, y, width, height, 0, 0, width, height)
 
   const blob = await canvas.convertToBlob({
     type: 'image/jpeg',
@@ -356,12 +388,17 @@ async function createBlobFromVideo (webcamVideo) {
   // imgElement.src = await blobToBase64(blob)
   window._mixlab_screen_blob = blob
 
-  console.log('########')
-  // let currentImage = await blobToBase64(blob)
-  // // console.log(window._mixlab_screen_imagePath)
-  // if (!window._mixlab_screen_imagePath) {
-  //   window._mixlab_screen_imagePath = currentImage
-  // }
+  console.log(
+    '########updateImageBase64 ',
+    updateImageBase64,
+    x,
+    y,
+    width,
+    height
+  )
+  if (updateImageBase64) {
+    window._mixlab_screen_imagePath = await blobToBase64(blob)
+  }
 }
 
 async function blobToBase64 (blob) {
@@ -391,6 +428,36 @@ function base64ToBlob (base64) {
 
   return blob
 }
+
+async function requestCamera () {
+  // 请求授权
+  try {
+    let stream = await navigator.mediaDevices.getUserMedia({ video: true })
+    console.log('摄像头授权成功')
+    // 获取视频轨道
+    var videoTrack = stream.getVideoTracks()[0]
+
+    // 停止视频轨道
+    videoTrack.stop()
+
+    return true
+  } catch (error) {
+    // 用户拒绝授权或发生其他错误
+    console.error('摄像头授权失败：', error)
+
+    // 提示用户授权摄像头访问权限
+    if (error.name === 'NotAllowedError') {
+      alert('请授权摄像头访问权限 chrome://settings/content/camera')
+    } else {
+      alert('摄像头访问权限请求失败，请重试 chrome://settings/content/camera')
+    }
+
+    // // 跳转到浏览器的授权设置页面
+    // window.location.href = 'chrome://settings/content/camera'
+  }
+  return false
+}
+
 /* 
 A method that returns the required style for the html 
 */
@@ -432,7 +499,7 @@ const base64Df =
 app.registerExtension({
   name: 'Mixlab.image.ScreenShareNode',
   async getCustomWidgets (app) {
-    console.log('#Mixlab.image.ScreenShareNode', app)
+    // console.log('#Mixlab.image.ScreenShareNode', app)
     return {
       CHEESE (node, inputName, inputData, app) {
         // We return an object containing a field CHEESE which has a function (taking node, name, data, app)
@@ -473,6 +540,46 @@ app.registerExtension({
         // console.log('###widget', widget)
         node.addCustomWidget(widget) // adds it to the node
         return widget // and returns it.
+      },
+      SLIDE (node, inputName, inputData, app) {
+        // We return an object containing a field CHEESE which has a function (taking node, name, data, app)
+        const widget = {
+          type: inputData[0], // the type, CHEESE
+          name: inputName, // the name, slice
+          size: [128, 12], // a default size
+          draw (ctx, node, width, y) {
+            // a method to draw the widget (ctx is a CanvasRenderingContext2D)
+          },
+          computeSize (...args) {
+            return [128, 12] // a method to compute the current size of the widget
+          },
+          async serializeValue (nodeId, widgetIndex) {
+            return window._mixlab_screen_slide_input || 0.5
+          }
+        }
+        // console.log('###widget', widget)
+        node.addCustomWidget(widget) // adds it to the node
+        return widget // and returns it.
+      },
+      SEED (node, inputName, inputData, app) {
+        // We return an object containing a field CHEESE which has a function (taking node, name, data, app)
+        const widget = {
+          type: inputData[0], // the type, CHEESE
+          name: inputName, // the name, slice
+          size: [128, 12], // a default size
+          draw (ctx, node, width, y) {
+            // a method to draw the widget (ctx is a CanvasRenderingContext2D)
+          },
+          computeSize (...args) {
+            return [128, 12] // a method to compute the current size of the widget
+          },
+          async serializeValue (nodeId, widgetIndex) {
+            return window._mixlab_screen_seed_input || 0
+          }
+        }
+        // console.log('###widget', widget)
+        node.addCustomWidget(widget) // adds it to the node
+        return widget // and returns it.
       }
     }
   },
@@ -489,9 +596,15 @@ app.registerExtension({
           type: 'HTML', // whatever
           name: 'sreen_share', // whatever
           draw (ctx, node, widget_width, y, widget_height) {
+            console.log('ScreenSHare', y, widget_height)
             Object.assign(
               this.card.style,
-              get_position_style(ctx, widget_width, y, node.size[1])
+              get_position_style(
+                ctx,
+                widget_width,
+                widget_height * 5,
+                node.size[1]
+              )
             )
           }
         }
@@ -510,8 +623,15 @@ app.registerExtension({
         })
 
         widget.previewArea = $el('div', {
+          style: {}
+        })
+
+        widget.shareDiv = $el('div', {
+          // innerText: 'Share Screen',
           style: {
-            // position:'ab'
+            cursor: 'pointer',
+            fontWeight: '300',
+            display: 'flex'
           }
         })
 
@@ -521,7 +641,19 @@ app.registerExtension({
             cursor: 'pointer',
             padding: '8px 0',
             fontWeight: '300',
-            margin: '2px'
+            margin: '2px',
+            width: '100%'
+          }
+        })
+
+        widget.shareOfWebCamBtn = $el('button', {
+          innerText: 'Camera',
+          style: {
+            cursor: 'pointer',
+            padding: '8px 0',
+            fontWeight: '300',
+            margin: '2px',
+            width: '100%'
           }
         })
 
@@ -563,20 +695,30 @@ app.registerExtension({
         widget.previewCard.appendChild(widget.preview)
         widget.previewCard.appendChild(widget.previewArea)
 
-        widget.card.appendChild(widget.shareBtn)
+        widget.card.appendChild(widget.shareDiv)
+        widget.shareDiv.appendChild(widget.shareBtn)
+        widget.shareDiv.appendChild(widget.shareOfWebCamBtn)
         widget.card.appendChild(widget.openFloatingWinBtn)
         widget.card.appendChild(widget.refreshInput)
         widget.card.appendChild(widget.liveBtn)
 
-        widget.shareBtn.addEventListener('click', async () => {
+        const toggleShare = async (isCamera = false) => {
           if (widget.preview.paused) {
             window._mixlab_stopVideo = await shareScreen(
+              isCamera,
               widget.preview,
               widget.shareBtn,
               widget.liveBtn,
               widget.previewArea
             )
-            widget.shareBtn.innerText = 'Stop Share'
+
+            if (isCamera) {
+              widget.shareOfWebCamBtn.innerText = 'Stop Share'
+              widget.shareBtn.innerText = 'Stop'
+            } else {
+              widget.shareOfWebCamBtn.innerText = 'Stop'
+              widget.shareBtn.innerText = 'Stop Share'
+            }
 
             console.log('视频已暂停')
             if (window._mixlab_stopLive) {
@@ -584,12 +726,15 @@ app.registerExtension({
               window._mixlab_stopLive = null
               widget.liveBtn.innerText = 'Live Run'
             }
+
+            setTimeout(() => updateSetAreaDisplay(), 2000)
           } else {
             console.log('视频正在播放')
             if (window._mixlab_stopVideo) {
               window._mixlab_stopVideo()
               window._mixlab_stopVideo = null
               widget.shareBtn.innerText = 'Share Screen'
+              widget.shareOfWebCamBtn.innerText = 'Camera'
             }
             if (window._mixlab_stopLive) {
               window._mixlab_stopLive()
@@ -597,6 +742,121 @@ app.registerExtension({
               widget.liveBtn.innerText = 'Live Run'
             }
           }
+        }
+
+        // updateSetAreaDisplay(widget.previewArea, 200, 200)
+        widget.shareOfWebCamBtn.addEventListener('click', async () => {
+          if (!widget.preview.paused) {
+            if (window._mixlab_stopVideo) {
+              window._mixlab_stopVideo()
+              window._mixlab_stopVideo = null
+              widget.shareBtn.innerText = 'Share Screen'
+              widget.shareOfWebCamBtn.innerText = 'Camera'
+            }
+            if (window._mixlab_stopLive) {
+              window._mixlab_stopLive()
+              window._mixlab_stopLive = null
+              widget.liveBtn.innerText = 'Live Run'
+            }
+            return
+          }
+
+          let r = await requestCamera()
+          if (r === false) return
+          const devices = await navigator.mediaDevices.enumerateDevices()
+
+          // 查找摄像头设备
+          var cameras = devices.filter(function (device) {
+            // console.log(device)
+            return device.kind === 'videoinput'
+          })
+
+          // 创建 <select> 元素
+          var select = document.createElement('select')
+
+          // 创建默认选项
+          // var defaultOption = document.createElement('option')
+          // defaultOption.text = '请选择摄像头'
+          // defaultOption.disabled = true
+          // defaultOption.selected = true
+          // select.appendChild(defaultOption)
+
+          // 创建每个摄像头设备的选项
+          Array.from(cameras, (camera, i) => {
+            var option = document.createElement('option')
+            option.value = camera.deviceId
+            option.text = camera.label || 'Camera ' + (select.length - 1)
+            if (i === 0) option.selected = true
+            select.appendChild(option)
+          })
+
+          let modal = document.createElement('div')
+          modal.className = 'comfy-modal'
+          modal.style.display = 'flex'
+
+          let modalContent = document.createElement('div')
+          modalContent.className = 'comfy-modal-content'
+
+          let title = document.createElement('p')
+          title.innerText = 'Please select a camera'
+
+          modalContent.appendChild(title)
+          modalContent.appendChild(select)
+
+          let btns = document.createElement('div')
+          btns.style = `display: flex;
+          justify-content: space-between;
+          margin: 24px 0;`
+
+          let btn = document.createElement('button')
+          btn.innerText = 'OK'
+          btn.style = `width: 112px;`
+
+          let closeBtn = document.createElement('button')
+          closeBtn.innerText = 'Cancel'
+          closeBtn.style = `width: 112px;`
+
+          modalContent.appendChild(btns)
+          btns.appendChild(btn)
+          btns.appendChild(closeBtn)
+
+          modal.appendChild(modalContent)
+          document.body.appendChild(modal)
+
+          btn.addEventListener('click', () => {
+            // 获取所选择的选项的索引
+            var selectedIndex = select.selectedIndex
+
+            // 获取所选择的选项的值
+            var selectedValue = select.options[selectedIndex].value
+            if (selectedValue) {
+              const constraints = {
+                audio: false,
+                video: {
+                  width: { ideal: 1920, max: 1920 },
+                  height: { ideal: 1080, max: 1080 },
+                  deviceId: selectedValue
+                }
+              }
+
+              localStorage.setItem(
+                '_mixlab_webcamera_select',
+                JSON.stringify(constraints)
+              )
+
+              toggleShare(true)
+            }
+
+            modal.remove()
+          })
+
+          closeBtn.addEventListener('click', () => {
+            modal.remove()
+          })
+        })
+
+        widget.shareBtn.addEventListener('click', async () => {
+          toggleShare()
         })
 
         widget.refreshInput.addEventListener('change', async () => {
@@ -630,12 +890,17 @@ app.registerExtension({
         })
         // console.log('widget.inputEl',widget.inputEl)
 
+        this.setSize([this.size[0],this.size[1]+450])
+        app.canvas.draw(true, true)
+
         /*
               Add the widget, make sure we clean up nicely, and we do not want to be serialized!
               */
         this.addCustomWidget(widget)
         this.onRemoved = function () {
           widget.preview.remove()
+          widget.shareDiv.remove()
+          widget.shareOfWebCamBtn.remove()
           widget.shareBtn.remove()
           widget.liveBtn.remove()
           widget.card.remove()
@@ -643,22 +908,114 @@ app.registerExtension({
           widget.previewArea.remove()
           widget.previewCard.remove()
         }
-        this.serialize_widgets = false
+        this.serialize_widgets = true
       }
     }
   }
 })
 
-function setArea (src) {
+function updateSetAreaDisplay () {
+  try {
+    let canvas = document.createElement('canvas')
+    canvas.width = window._mixlab_screen_webcamVideo.videoWidth
+    canvas.height = window._mixlab_screen_webcamVideo.videoHeight
+    let ctx = canvas.getContext('2d')
+    const lineWidth = 2 // Width of the stroke line
+    const strokeColor = 'red' // Color of the stroke
+
+    // Draw the rectangle
+    ctx.strokeStyle = strokeColor // Set the stroke color
+    ctx.lineWidth = lineWidth // Set the stroke line width
+
+    ctx.fillStyle = 'rgba(255,0,0,0.35)'
+
+    let x = 0,
+      y = 0,
+      width = canvas.width,
+      height = canvas.height
+
+    if (!window._mixlab_share_screen) {
+      let d = getSetAreaData()
+      if (d) {
+        window._mixlab_share_screen = d
+      }
+    }
+
+    if (window._mixlab_share_screen) {
+      x = window._mixlab_share_screen.x
+      y = window._mixlab_share_screen.y
+      width = window._mixlab_share_screen.width
+      height = window._mixlab_share_screen.height
+    }
+
+    ctx.strokeRect(x, y, width, height) // Draw the stroked rectangle
+    ctx.fillRect(x, y, width, height)
+
+    canvas.style.width = '100%'
+
+    let area = graph._nodes
+      .filter(n => n.type === 'ScreenShare')[0]
+      .widgets.filter(w => w.name == 'sreen_share')[0].previewArea
+
+    area.innerHTML = ''
+    area.appendChild(canvas)
+    area.style = `
+    position: absolute;
+    width:100%%;
+    left:0;
+    top:0;
+    `
+  } catch (error) {
+    console.log(error)
+  }
+}
+
+function updateSetAreaData (left, top, width, height, imgWidth, imgHeight) {
+  window._mixlab_share_screen = {
+    x: left,
+    y: top,
+    width,
+    height,
+    imgWidth,
+    imgHeight
+  }
+  localStorage.setItem(
+    '_mixlab_share_screen',
+    JSON.stringify(window._mixlab_share_screen)
+  )
+}
+
+function getSetAreaData () {
+  try {
+    let data = JSON.parse(localStorage.getItem('_mixlab_share_screen')) || {}
+    if (data.width === 0 || data.height === 0 || data.width === undefined)
+      return
+    return data
+  } catch (error) {}
+  return
+}
+
+async function setArea (src) {
+  let displayHeight = Math.round(window.screen.availHeight * 0.6)
   let div = document.createElement('div')
   div.innerHTML = `
-    <div id='ml_overlay' style='position: absolute;top:0'>
-      <img id='ml_video' style='position: absolute; width: 500px;   user-select: none; -webkit-user-drag: none;' />
-      <div id='ml_selection' style='position: absolute; border: 2px dashed red; pointer-events: none;'></div>
+    <div id='ml_overlay' style='position: absolute;top:0;background: #251f1fc4;
+    height: 100vh;
+    width: 100%;'>
+      <img id='ml_video' style='position: absolute; 
+      height: ${displayHeight}px;user-select: none; 
+      -webkit-user-drag: none;
+      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>
     </div>`
   // document.body.querySelector('#ml_overlay')
   document.body.appendChild(div)
 
+  let im = await createImage(src)
+
   let img = div.querySelector('#ml_video')
   let overlay = div.querySelector('#ml_overlay')
   let selection = div.querySelector('#ml_selection')
@@ -667,10 +1024,56 @@ function setArea (src) {
   // Set video source
   img.src = src
 
+  // init area
+  const data = getSetAreaData()
+  let x = 0,
+    y = 0,
+    width = (im.naturalWidth * displayHeight) / im.naturalHeight,
+    height = displayHeight
+  let imgWidth = im.naturalWidth
+  let imgHeight = im.naturalHeight
+  // console.log(
+  //   '#screen_share::使用上一次选区 selection',
+  //   data,
+  //   imgWidth,
+  //   img.width
+  // )
+  if (
+    data &&
+    data.width > 0 &&
+    data.height > 0 &&
+    data.imgWidth === imgWidth &&
+    data.imgHeight === imgHeight &&
+    data.imgHeight > 0
+  ) {
+    // 相同尺寸窗口，恢复选区
+    x = (img.width * data.x) / data.imgWidth
+    y = (img.height * data.y) / data.imgHeight
+    width = (img.width * data.width) / data.imgWidth
+    height = (img.height * data.height) / data.imgHeight
+    // imgWidth = data.imgWidth
+    // imgHeight = data.imgHeight;
+    // console.log('#screen_share::使用上一次选区 selection', x, y, width, height)
+  }
+
+  selection.style.left = x + 'px'
+  selection.style.top = y + 'px'
+  selection.style.width = width + 'px'
+  selection.style.height = height + 'px'
+
   // Add mouse events
   img.addEventListener('mousedown', startSelection)
   img.addEventListener('mousemove', updateSelection)
   img.addEventListener('mouseup', endSelection)
+  overlay.addEventListener('click', remove)
+
+  function remove () {
+    overlay.removeEventListener('click', remove)
+    img.removeEventListener('mousedown', startSelection)
+    img.removeEventListener('mousemove', updateSelection)
+    img.removeEventListener('mouseup', endSelection)
+    div.remove()
+  }
 
   function startSelection (event) {
     if (start == false) {
@@ -732,49 +1135,27 @@ function setArea (src) {
     // console.log('宽度: ' + width)
     // console.log('高度: ' + height)
 
-    img.removeEventListener('mousedown', startSelection)
-    img.removeEventListener('mousemove', updateSelection)
-    img.removeEventListener('mouseup', endSelection)
+    // img.removeEventListener('mousedown', startSelection)
+    // img.removeEventListener('mousemove', updateSelection)
+    // img.removeEventListener('mouseup', endSelection)
 
-    window._mixlab_screen_x = left
-    window._mixlab_screen_y = top
-    window._mixlab_screen_width = width
-    window._mixlab_screen_height = height
+    // window._mixlab_screen_x = left
+    // window._mixlab_screen_y = top
+    // window._mixlab_screen_width = width
+    // window._mixlab_screen_height = height
 
-    try {
-      let canvas = document.createElement('canvas')
-      canvas.width = _mixlab_screen_webcamVideo.videoWidth
-      canvas.height = _mixlab_screen_webcamVideo.videoHeight
-      let ctx = canvas.getContext('2d')
-      const lineWidth = 1 // Width of the stroke line
-      const strokeColor = 'red' // Color of the stroke
+    if (width <= 0 && height <= 0) return remove()
 
-      // Draw the rectangle
-      ctx.strokeStyle = strokeColor // Set the stroke color
-      ctx.lineWidth = lineWidth // Set the stroke line width
-      ctx.strokeRect(
-        _mixlab_screen_x,
-        _mixlab_screen_y,
-        _mixlab_screen_width,
-        _mixlab_screen_height
-      ) // Draw the stroked rectangle
+    updateSetAreaData(left, top, width, height, imgWidth, imgHeight)
 
-      canvas.style.width = '100%'
+    updateSetAreaDisplay()
 
-      let area = graph._nodes
-        .filter(n => n.type === 'ScreenShare')[0]
-        .widgets.filter(w => w.name == 'sreen_share')[0].previewArea
-      area.innerHTML = ''
-      area.appendChild(canvas)
-      area.style = `
-      position: absolute;
-      width:100%%;
-  left:0;
-  top:0;
-      `
-    } catch (error) {}
+    createBlobFromVideo(
+      window._mixlab_screen_webcamVideo,
+      !window._mixlab_screen_live
+    )
 
-    div.remove()
+    remove()
   }
 }
 
@@ -941,7 +1322,7 @@ app.registerExtension({
           outline: none;background: black;`
 
           let div = document.createElement('div')
-          div.style = `display:flex;position: fixed;
+          div.style = `display:flex;position: fixed;flex-direction: column;
           bottom: 0px;
           z-index: 9999;
           left: 0px;
@@ -949,15 +1330,42 @@ app.registerExtension({
           margin: 12px;`
 
           let inputDiv = document.createElement('div')
+          inputDiv.style = `width: 100%;`
+
           // inputDiv.style = ``
           let infoDiv = document.createElement('div')
-          infoDiv.style = `    width: 100%;
+          infoDiv.style = `width: 100%;
+          display: flex;
+          justify-content: space-between;
           height: 16px;
           color: white;
           margin-bottom: 4px;
           font-size: 12px;
-          text-shadow: 1px 1px gray;`
-          infoDiv.id = 'info'
+          text-shadow: gray 1px 1px;
+          align-items: center;`
+
+          let infoText = document.createElement('div')
+          infoText.id = 'info'
+
+          let hideBtn = document.createElement('button')
+          hideBtn.innerText = '🤖'
+          hideBtn.style = `
+          border: none;
+          background: none;
+          cursor: pointer; height: 24px; margin: 4px; color: red;`
+
+          hideBtn.addEventListener('click', () => {
+            if (fnDiv.style.display == 'none') {
+              fnDiv.style.display = 'flex'
+            } else {
+              fnDiv.style.display = 'none'
+            }
+            try {
+              pipWindow.document.querySelector('#info').innerText = ''
+            } catch (error) {
+              console.log(error)
+            }
+          })
 
           // Move the player to the Picture-in-Picture window.
           let input = document.createElement('textarea')
@@ -1002,21 +1410,25 @@ app.registerExtension({
           font-size: 16px;
           margin-right: 6px;user-select: none;`
 
-          let btn = document.createElement('butotn')
-          btn.innerText = '❤'
-          btn.style = `cursor: pointer;height: 24px;margin:4px;
+          let seedBtn = document.createElement('butotn')
+          seedBtn.innerText = '🎲'
+          seedBtn.style = `cursor: pointer;height: 24px;margin:4px;
           color: red;`
-          btn.addEventListener('click', () => {
-            if (input.style.display == 'none') {
-              input.style.display = 'block'
-            } else {
-              input.style.display = 'none'
-            }
+
+          seedBtn.addEventListener('click', () => {
+            window._mixlab_screen_seed_input = Math.round(
+              Math.floor(Math.random() * 0xffffffffffffffff)
+            )
+
             try {
-              pipWindow.document.querySelector('#info').innerText = ''
+              pipWindow.document.querySelector('#info').innerText =window._mixlab_screen_seed_input
             } catch (error) {
               console.log(error)
             }
+
+            // console.log(window._mixlab_screen_seed_input)
+            if (window._mixlab_screen_imagePath)
+              document.querySelector('#queue-button').click()
           })
 
           // TODO 需要判断是否有screenshare节点，没有的话，不需要添加
@@ -1074,7 +1486,9 @@ app.registerExtension({
             console.log('##更新Prompt')
             window._mixlab_screen_prompt =
               window._mixlab_screen_prompt_input || window._mixlab_screen_prompt
-            document.querySelector('#queue-button').click()
+
+            if (window._mixlab_screen_imagePath)
+              document.querySelector('#queue-button').click()
 
             try {
               pipWindow.document.querySelector('#info').innerText =
@@ -1119,16 +1533,52 @@ app.registerExtension({
 
           pipWindow.document.body.append(widget.preview)
           pipWindow.document.body.append(div)
+
+          // 滑动条
+          const createSlide = () => {
+            let d = document.createElement('div')
+            d.style = `width: 100%;margin-bottom: 12px;`
+            let range = document.createElement('input')
+            range.type = 'range'
+            d.appendChild(range)
+            return range
+          }
+
+          let slideInp = createSlide()
+          slideInp.addEventListener('change', () => {
+            console.log(~~slideInp.value / 100)
+            window._mixlab_screen_slide_input = ~~slideInp.value / 100
+            try {
+              pipWindow.document.querySelector('#info').innerText =
+                window._mixlab_screen_slide_input
+              if (window._mixlab_screen_imagePath)
+                document.querySelector('#queue-button').click()
+            } catch (error) {
+              console.log(error)
+            }
+          })
+
           // console.log(pipWindow)
 
-          div.appendChild(btnDiv)
-          btnDiv.appendChild(btn)
+          let fnDiv = document.createElement('div')
+          fnDiv.style = `display: flex;`
+
+          div.appendChild(infoDiv)
+          div.appendChild(fnDiv)
+
+          infoDiv.appendChild(infoText)
+          infoDiv.appendChild(hideBtn)
+
+          fnDiv.appendChild(btnDiv)
+          // 按钮区域
+          btnDiv.appendChild(seedBtn)
           btnDiv.appendChild(pauseBtn)
           btnDiv.appendChild(promptFinishBtn)
 
           // 输入框
-          div.appendChild(inputDiv)
-          inputDiv.appendChild(infoDiv)
+          fnDiv.appendChild(inputDiv)
+          inputDiv.appendChild(slideInp)
+
           inputDiv.appendChild(input)
 
           input.addEventListener('input', () => {
@@ -1152,7 +1602,9 @@ app.registerExtension({
                 window._mixlab_screen_prompt =
                   window._mixlab_screen_prompt_input ||
                   window._mixlab_screen_prompt
-                document.querySelector('#queue-button').click()
+
+                if (window._mixlab_screen_imagePath)
+                  document.querySelector('#queue-button').click()
 
                 try {
                   pipWindow.document.querySelector('#info').innerText =
@@ -1179,7 +1631,7 @@ app.registerExtension({
           widget.card.remove()
           widget.PictureInPicture.remove()
         }
-        this.serialize_widgets = false
+        this.serialize_widgets = true
       }
 
       const onExecuted = nodeType.prototype.onExecuted
@@ -1628,7 +2080,7 @@ const node = {
   },
   async setup (a) {
     for (const node of app.graph._nodes) {
-      console.log('#setup', node)
+      // console.log('#setup', node)
       if (node.type === 'RandomPrompt') {
         updateUI(node)
       }

web/javascript/svg_icons.js

@@ -0,0 +1 @@
+export const closeIcon = '<svg xmlns="http://www.w3.org/2000/svg" height="24" viewBox="0 -960 960 960" width="24"><path d="m256-200-56-56 224-224-224-224 56-56 224 224 224-224 56 56-224 224 224 224-56 56-224-224-224 224Z"/></svg>'

web/javascript/ui_mixlab.js

@@ -1,4 +1,99 @@
 import { app } from '../../../scripts/app.js'
+import { api } from '../../../scripts/api.js'
+import { ComfyWidgets } from '../../../scripts/widgets.js'
+import { $el } from '../../../scripts/ui.js'
+import {closeIcon} from './svg_icons.js'
+
+function deepEqual (obj1, obj2) {
+  if (typeof obj1 !== typeof obj2) {
+    return false
+  }
+
+  if (typeof obj1 !== 'object' || obj1 === null || obj2 === null) {
+    return obj1 === obj2
+  }
+
+  const keys1 = Object.keys(obj1)
+  const keys2 = Object.keys(obj2)
+
+  if (keys1.length !== keys2.length) {
+    return false
+  }
+
+  for (let key of keys1) {
+    if (!deepEqual(obj1[key], obj2[key])) {
+      return false
+    }
+  }
+
+  return true
+}
+
+async function get_nodes_map () {
+  let api_host = `${window.location.hostname}:${window.location.port}`
+  let api_base = ''
+  let url = `${window.location.protocol}//${api_host}${api_base}`
+
+  const res = await fetch(`${url}/mixlab/nodes_map`, {
+    method: 'POST',
+    body: JSON.stringify({
+      data: 'json'
+    })
+  })
+  return await res.json()
+}
+
+function loadCSS(url) {
+  var link = document.createElement('link');
+  link.rel = 'stylesheet';
+  link.type = 'text/css';
+  link.href = url;
+  document.getElementsByTagName('head')[0].appendChild(link);
+}
+
+var cssURL = 'https://cdnjs.cloudflare.com/ajax/libs/github-markdown-css/5.5.0/github-markdown-light.min.css';
+loadCSS(cssURL);
+
+function injectCSS (css) {
+  // 检查页面中是否已经存在具有相同内容的style标签
+  const existingStyle = document.querySelector('style')
+  if (existingStyle && existingStyle.textContent === css) {
+    return // 如果已经存在相同的样式，则不进行注入
+  }
+
+  // 创建一个新的style标签，并将CSS内容注入其中
+  const style = document.createElement('style')
+  style.textContent = css
+
+  // 将style标签插入到页面的head元素中
+  const head = document.querySelector('head')
+  head.appendChild(style)
+}
+
+injectCSS(`::-webkit-scrollbar {
+  width: 2px;
+}
+
+@keyframes loading_mixlab {
+  0% {
+    background-color: green;
+  }
+
+  50% {
+    background-color: lightgreen;
+  }
+
+  100% {
+    background-color: green;
+  }
+}
+
+.loading_mixlab {
+  background-color: green;
+  animation-name: loading_mixlab;
+  animation-duration: 2s;
+  animation-iteration-count: infinite;
+}`)
 
 async function getCustomnodeMappings (mode = 'url') {
   // mode = "local";
@@ -6,18 +101,39 @@ async function getCustomnodeMappings (mode = 'url') {
   let api_base = ''
   let url = `${window.location.protocol}//${api_host}${api_base}`
 
-  const response = await fetch(`${url}/customnode/getmappings?mode=${mode}`)
-  const data = await response.json()
-
   let nodes = {}
-  try {
-    for (let url in data) {
-      let n = data[url]
-      for (let node of n[0]) {
-        nodes[node] = { url, title: n[1].title_aux }
-      }
+
+  const data = (await get_nodes_map()).data
+
+  for (let url in data) {
+    let n = data[url]
+    for (let node of n[0]) {
+      // if(node=='CLIPSeg')console.log('#CLIPSeg',n)
+      nodes[node] = { url, title: n[1].title_aux }
     }
-  } catch (error) {}
+  }
+  
+  // try {
+  //   const response = await fetch(`${url}/customnode/getmappings?mode=${mode}`)
+  //   const data = await response.json()
+  //   for (let url in data) {
+  //     let n = data[url]
+  //     for (let node of n[0]) {
+  //       // if(node=='CLIPSeg')console.log('#CLIPSeg',n)
+  //       nodes[node] = { url, title: n[1].title_aux }
+  //     }
+  //   }
+  // } catch (error) {
+  //   const data = (await get_nodes_map()).data
+
+  //   for (let url in data) {
+  //     let n = data[url]
+  //     for (let node of n[0]) {
+  //       // if(node=='CLIPSeg')console.log('#CLIPSeg',n)
+  //       nodes[node] = { url, title: n[1].title_aux }
+  //     }
+  //   }
+  // }
 
   return nodes
 }
@@ -55,13 +171,51 @@ const missingNodeGithub = (missingNodeTypes, nodesMap) => {
   })
 }
 
+let nodesMap
+
+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: `${widget_width - MARGIN * 2}px`,
+    // height: `${node_height * 0.3 - MARGIN * 2}px`,
+    // background: '#EEEEEE',
+    display: 'flex',
+    flexDirection: 'column',
+    // alignItems: 'center',
+    justifyContent: 'space-around'
+  }
+}
+
 app.showMissingNodesError = async function (
   missingNodeTypes,
   hasAddedNodes = true
 ) {
-  const nodesMap = await getCustomnodeMappings()
-  console.log('#nodesMap', nodesMap)
-  //   console.log('###MIXLAB', missingNodeTypes, hasAddedNodes)
+  nodesMap =
+    nodesMap && Object.keys(nodesMap).length > 0
+      ? nodesMap
+      : await getCustomnodeMappings('url')
+
+  // console.log('#nodesMap', nodesMap)
+  // console.log('###MIXLAB', missingNodeTypes, hasAddedNodes)
   this.ui.dialog.show(
     `When loading the graph, the following node types were not found: <ul>${missingNodeGithub(
       missingNodeTypes,
@@ -77,12 +231,507 @@ app.showMissingNodesError = async function (
   })
 }
 
-// app.ui.dialog.show = function (html) {
-//   console.log('###MIXLAB', html)
-//   if (typeof html === 'string') {
-//     this.textElement.innerHTML = html
-//   } else {
-//     this.textElement.replaceChildren(html)
-//   }
-//   this.element.style.display = 'flex'
-// }
+// app.registerExtension({
+//   name: 'Comfy.MDNote',
+//   registerCustomNodes () {
+//     class NoteNode {
+//       // color = LGraphCanvas.node_colors.yellow.color
+//       // bgcolor = LGraphCanvas.node_colors.yellow.bgcolor
+//       // groupcolor = LGraphCanvas.node_colors.yellow.groupcolor
+//       constructor () {
+//         if (!this.properties) {
+//           this.properties = {}
+//           this.properties.text = ''
+//         }
+//         console.log('NoteNode1', this)
+
+//         const widget = {
+//           type: 'div',
+//           name: 'input_color',
+//           draw (ctx, node, widget_width, y, widget_height) {
+//             Object.assign(
+//               this.div.style,
+//               get_position_style(
+//                 ctx,
+//                 widget_width,
+//                 44,
+//                 node.size[1]
+//               )
+//             )
+//           }
+//         }
+
+//         widget.div = $el('div', {});
+//         widget.div.innerText='1111'
+
+//         document.body.appendChild(widget.div)
+
+//         this.addCustomWidget(widget)
+
+//         this.serialize_widgets = true
+//         this.isVirtualNode = true
+//       }
+//     }
+
+//     // Load default visibility
+
+//     LiteGraph.registerNodeType(
+//       'MDNote',
+//       Object.assign(NoteNode, {
+//         title_mode: LiteGraph.NORMAL_TITLE,
+//         title: 'MDNote',
+//         collapsable: true
+//       })
+//     )
+
+//     NoteNode.category = '♾️Mixlab/utils'
+//   },
+
+// })
+
+async function fetchReadmeContent (url) {
+  try {
+    // var repo = 'owner/repo'; // 仓库的拥有者和名称
+    var match = url.match(/github.com\/([^/]+\/[^/]+)/)
+    var repo = match[1]
+    var url = `https://api.github.com/repos/${repo}/readme`
+    var response = await fetch(url)
+    var data = await response.json()
+    var readmeUrl = data.download_url
+
+    var readmeResponse = await fetch(readmeUrl)
+    var content = await readmeResponse.text()
+    // console.log(content) // 在控制台输出readme.md文件的内容
+
+    return content
+  } catch (error) {
+    console.log('获取readme.md文件信息失败:', error)
+  }
+}
+
+function createModal (url, markdown,title) {
+  
+  // Create modal element
+  var div =
+    document.querySelector('#mix-modal') || document.createElement('div')
+  div.id = 'mix-modal'
+  div.innerHTML = ''
+  div.style.cssText = `width: 100%;
+    z-index: 9990;
+    height: 100vh;
+    display: flex;
+    color: var(--descrip-text);
+    position: fixed;
+    top: 0;
+    left: 0;
+    `
+
+  var modal = document.createElement('div')
+
+  div.appendChild(modal)
+  modal.classList.add("modal-body")
+  // Set modal styles
+  modal.style.cssText = `
+    background: white;
+    height: 80vh;
+    position: fixed;
+    overflow:hidden;
+    top: 50%;
+    left: 50%;
+    transform: translate(-50%, -50%);
+    z-index: 9999;
+    border-radius: 4px;
+    box-shadow: 4px 4px 14px rgba(255,255,255,0.5);
+
+  `
+  // Create modal content area
+  var modalContent = document.createElement('div')
+  modalContent.classList.add('modal-content')
+  // Create modal header
+  const headerElement =  document.createElement('div')
+  headerElement.classList.add('modal-header')
+  headerElement.style.cssText = `
+    display: flex;
+    padding: 20px 24px 8px 24px;
+    justify-content: space-between;
+  `
+  
+  const headTitleElement = document.createElement('a')
+  headTitleElement.classList.add('header-title')
+  headTitleElement.style.cssText=`
+    color: var(--descrip-text);
+    font-size: 18px;
+    display: flex;
+    align-items: center;
+    flex: 1;
+    overflow: hidden;
+    text-decoration: none;
+    font-weight: bold;
+  `
+  headTitleElement.onmouseenter = function(){
+    headTitleElement.style.color = 'var(--comfy-menu-bg)'
+  }
+  headTitleElement.onmouseleave = function(){
+    headTitleElement.style.color = 'var(--descrip-text)'
+  }
+  headTitleElement.textContent= title ||'';
+  headTitleElement.href = url
+  headTitleElement.target='_blank'
+  const linkIcon = document.createElement('small')
+  linkIcon.textContent = '🔗'
+  headTitleElement.appendChild(linkIcon);
+  headerElement.appendChild(headTitleElement)
+
+  
+
+  // Create close button
+  const closeButton = document.createElement('span')
+  closeButton.classList.add('close')
+  closeButton.innerHTML = closeIcon
+  // Set close button styles
+  closeButton.style.cssText = `
+      padding: 4px;
+      cursor: pointer;
+      width: 32px;
+      height: 32px;
+      display: flex;
+      justify-content: center;
+      align-items: center;
+      user-select: none;
+      fill: var(--descrip-text);
+      `
+  closeButton.onmouseenter = function(){
+    closeButton.style.fill = 'var(--comfy-menu-bg)'; 
+  }
+  closeButton.onmouseleave = function(){
+    closeButton.style.fill = 'var(--descrip-text)';
+  }
+
+  headerElement.appendChild(closeButton)
+
+
+  // Click event to close the modal
+  function closeMixModal(){
+    div.style.display = 'none'
+    window.removeEventListener('keydown',MixModalEscKeyEvent)
+  }
+  closeButton.onclick = function () {
+    closeMixModal()
+  }
+
+  // Set modal content area styles
+  modalContent.style.cssText = `
+    position: relative;
+    padding: 0px;
+    overflow: hidden scroll;;
+    height: 100%;
+    min-width:300px
+    `
+
+  // Append close button to modal content area
+  modal.appendChild(headerElement)
+
+  // Create element for displaying Markdown content
+  var markdownContent = document.createElement('div')
+  markdownContent.classList.add('markdown-content','markdown-body')
+  markdownContent.style.cssText = `max-width: 50vw;padding: 0px 24px 100px 24px;`
+
+  showdown.setFlavor('github');
+  var converter = new showdown.Converter()
+
+  var html = converter.makeHtml(markdown)
+
+  // Hide images in the markdown when they fail to load
+  var regex = /<img[^>]+src="?([^"\s]+)"?[^>]*>/g
+  html = html.replace(regex, function (match, src) {
+    return `<img src="${src}" onerror="this.style.display='none'">`
+  })
+
+  // Open links in a new tab or window
+  html = html.replace(/<a/g, '<a target="_blank"')
+
+  // Fix href attribute to absolute path
+  html = html.replace(
+    /<a([^>]+href=["'])(?!https?:\/\/)([^"'>]+)/g,
+    function (match, prefix, path) {
+      var absolutePath = url + '/' + path
+      return '<a' + prefix + absolutePath
+    }
+  )
+
+  markdownContent.innerHTML = html
+
+  // Append Markdown content element to modal content area
+  modalContent.appendChild(markdownContent)
+
+  // Append modal content area to modal element
+  modal.appendChild(modalContent)
+
+  const footerElement = document.createElement('div')
+  footerElement.style.cssText=`
+      position: absolute;
+      left: 0;
+      right: 0;
+      text-align: right;
+      padding:10px;
+      font-size:12px
+  `
+
+  const footerText = document.createElement('a')
+  footerText.href ="https://github.com/shadowcz007/comfyui-mixlab-nodes"
+  footerText.innerText =  "Support by Mixlab"
+  footerText.style.cssText=`color:inherit`
+  footerText.target = "_blank"
+  footerText.onmouseenter=function(){
+    footerText.style.color = 'var(--input-text)'
+  }
+  footerText.onmouseleave=function(){
+    footerText.style.color = 'inherit'
+  }
+  
+  
+  footerText.onclick = function(e){
+    e.stopPropagation()
+  }
+  footerElement.appendChild(footerText)
+
+  div.appendChild(footerElement)
+
+
+  // Append modal element to the page
+  if (!document.querySelector('#mix-modal')) {
+    document.body.appendChild(div)
+  }
+  function MixModalEscKeyEvent(event){
+      if(event.key == "Escape"){
+        closeMixModal()
+      }
+  }
+  window.removeEventListener('keydown',MixModalEscKeyEvent)
+  window.addEventListener('keydown',MixModalEscKeyEvent)
+
+  const bgElement = document.createElement('div')
+  bgElement.classList.add('mix-modal-bg')
+  bgElement.style.cssText = `
+    width:100%;
+    height:100%;
+    background-color: rgba(0,0,0,0.8);
+  `
+  bgElement.onclick =  function( ){   
+    closeMixModal()
+  }
+  
+  div.appendChild(bgElement)
+
+
+}
+
+app.registerExtension({
+  name: 'Comfy.Mixlab.ui',
+  init () {
+    LGraphCanvas.prototype.helpAboutNode = async function (node) {
+      nodesMap =
+        nodesMap && Object.keys(nodesMap).length > 0
+          ? nodesMap
+          : await getCustomnodeMappings('url')
+
+      console.log('node & node map', node, nodesMap, nodesMap[node.type])
+      let repo = nodesMap[node.type]
+      if (repo) {
+        let markdown = await fetchReadmeContent(repo.url)
+        createModal(repo.url,markdown,repo.title)
+      }
+    }
+
+    const getNodeMenuOptions = LGraphCanvas.prototype.getNodeMenuOptions // store the existing method
+    LGraphCanvas.prototype.getNodeMenuOptions = function (node) {
+      // replace it
+      const options = getNodeMenuOptions.apply(this, arguments) // start by calling the stored one
+      node.setDirtyCanvas(true, true) // force a redraw of (foreground, background)
+      // options.splice(
+      //   options.length - 1,
+      //   0, // splice a new option in at the end
+      //   {
+      //     content: '♾️Mixlab', // with a name
+      //     callback: () => {
+      //       LGraphCanvas.prototype.helpAboutNode(node)
+      //     } // and the callback
+      //   },
+      //   null // a divider
+      // )
+      return [
+        {
+          content: 'Help ♾️Mixlab', // with a name
+          callback: () => {
+            LGraphCanvas.prototype.helpAboutNode(node)
+          } // and the callback
+        },
+        null,
+        ...options
+      ] // and return the options
+    }
+  },
+  async setup () {
+
+    // Add canvas menu options 
+			const orig = LGraphCanvas.prototype.getCanvasMenuOptions;
+			LGraphCanvas.prototype.getCanvasMenuOptions = function () {
+				const options = orig.apply(this, arguments);
+
+				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 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: 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)
+                  }
+                })
+  
+                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)
+          }
+        });
+				return options;
+			};
+
+
+    
+  }
+})

web/javascript/utils_mixlab.js

@@ -0,0 +1,168 @@
+
+import { app } from '../../../scripts/app.js'
+import { api } from '../../../scripts/api.js'
+import { ComfyWidgets } from '../../../scripts/widgets.js'
+import { $el } from '../../../scripts/ui.js'
+
+
+
+const getLocalData = key => {
+  let data = {}
+  try {
+    data = JSON.parse(localStorage.getItem(key)) || {}
+  } catch (error) {
+    return {}
+  }
+  return data
+}
+function get_position_style (ctx, widget_width, y, node_height) {
+  const MARGIN = 4 // the margin around the html element
+
+  /* Create a transform that deals with all the scrolling and zooming */
+  const elRect = ctx.canvas.getBoundingClientRect()
+  const transform = new DOMMatrix()
+    .scaleSelf(
+      elRect.width / ctx.canvas.width,
+      elRect.height / ctx.canvas.height
+    )
+    .multiplySelf(ctx.getTransform())
+    .translateSelf(MARGIN, MARGIN + y)
+
+  return {
+    transformOrigin: '0 0',
+    transform: transform,
+    left: `0`,
+    top: `0`,
+    cursor: 'pointer',
+    position: 'absolute',
+    maxWidth: `${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}px`,
+    // height: `${node_height * 0.3 - MARGIN * 2}px`,
+    // background: '#EEEEEE',
+    display: 'flex',
+    flexDirection: 'column',
+    // alignItems: 'center',
+    justifyContent: 'space-around'
+  }
+}
+
+
+app.registerExtension({
+    name: 'Mixlab.utils.Color',
+    async getCustomWidgets (app) {
+      return {
+        TCOLOR (node, inputName, inputData, app) {
+          // console.log('##node', node)
+          const widget = {
+            type: inputData[0], // the type, CHEESE
+            name: inputName, // the name, slice
+            size: [128, 32], // a default size
+            draw (ctx, node, width, y) {},
+            computeSize (...args) {
+              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'
+            }
+          }
+          //  widget.something = something;          // maybe adds stuff to it
+          node.addCustomWidget(widget) // adds it to the node
+          return widget // and returns it.
+        }
+      }
+    },
+  
+    async beforeRegisterNodeDef (nodeType, nodeData, app) {
+      if (nodeType.comfyClass == 'Color') {
+        const orig_nodeCreated = nodeType.prototype.onNodeCreated
+        nodeType.prototype.onNodeCreated = function () {
+          orig_nodeCreated?.apply(this, arguments)
+  
+          console.log('Color nodeData', this.widgets)
+   
+          const widget = {
+            type: 'div',
+            name: 'input_color',
+            draw (ctx, node, widget_width, y, widget_height) {
+              Object.assign(
+                this.div.style,
+                get_position_style(
+                  ctx,
+                  widget_width,
+                  44,
+                  node.size[1]
+                )
+              )
+            }
+          }
+  
+          widget.div = $el('div', {})
+  
+          document.body.appendChild(widget.div)
+  
+          const inputDiv = (key, placeholder, value) => {
+            let div = document.createElement('div')
+            const ip = document.createElement('input')
+            ip.type = 'color'
+            ip.className = `${'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())
+            })
+            return div
+          }
+  
+          let inputColor = inputDiv('_mixlab_utils_color', 'Color', '#000000')
+  
+          widget.div.appendChild(inputColor)
+  
+          this.addCustomWidget(widget)
+  
+          const onRemoved = this.onRemoved
+          this.onRemoved = () => {
+            inputColor.remove()
+            widget.div.remove()
+            return onRemoved?.()
+          }
+  
+          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 === 'Color') {
+        let widget = node.widgets.filter(w => w.div)[0]
+  
+        let data = getLocalData('_mixlab_utils_color')
+  
+        let id = node.id
+  
+        widget.div.querySelector('.Color').value = data[id] || '#000000'
+      }
+    }
+  })

web/javascript/watcher_mixlab.js

@@ -169,7 +169,7 @@ app.registerExtension({
         this.onRemoved = function () {
           // widget.card.remove()
         }
-        this.serialize_widgets = false
+        this.serialize_widgets = true
       }
     }
   }

web/main.css

@@ -1,3 +1,24 @@
 ::-webkit-scrollbar {
-    width: 2px;
-  }
+  width: 2px;
+}
+
+@keyframes loading_mixlab {
+  0% {
+    background-color: green;
+  }
+
+  50% {
+    background-color: lightgreen;
+  }
+
+  100% {
+    background-color: green;
+  }
+}
+
+.loading_mixlab {
+  background-color: green;
+  animation-name: loading_mixlab;
+  animation-duration: 2s;
+  animation-iteration-count: infinite;
+}

workflow/3-FloatVideo-workflow.json

@@ -1,6 +1,6 @@
 {
-  "last_node_id": 22,
-  "last_link_id": 48,
+  "last_node_id": 23,
+  "last_link_id": 51,
   "nodes": [
     {
       "id": 7,
@@ -105,7 +105,7 @@
         {
           "name": "text",
           "type": "STRING",
-          "link": 48,
+          "link": 51,
           "widget": {
             "name": "text"
           }
@@ -316,13 +316,13 @@
         "1": 246
       },
       "flags": {},
-      "order": 6,
+      "order": 7,
       "mode": 0,
       "inputs": [
         {
           "name": "images",
           "type": "IMAGE",
-          "link": 46
+          "link": 50
         }
       ],
       "properties": {
@@ -445,13 +445,13 @@
         "1": 58
       },
       "flags": {},
-      "order": 7,
+      "order": 6,
       "mode": 0,
       "inputs": [
         {
           "name": "image",
           "type": "IMAGE",
-          "link": 47
+          "link": 49
         }
       ],
       "outputs": [
@@ -472,45 +472,6 @@
         512
       ]
     },
-    {
-      "id": 22,
-      "type": "ScreenShare",
-      "pos": [
-        -63,
-        483
-      ],
-      "size": {
-        "0": 315,
-        "1": 98
-      },
-      "flags": {},
-      "order": 3,
-      "mode": 0,
-      "outputs": [
-        {
-          "name": "IMAGE",
-          "type": "IMAGE",
-          "links": [
-            46,
-            47
-          ],
-          "shape": 3,
-          "slot_index": 0
-        },
-        {
-          "name": "STRING",
-          "type": "STRING",
-          "links": [
-            48
-          ],
-          "shape": 3,
-          "slot_index": 1
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "ScreenShare"
-      }
-    },
     {
       "id": 20,
       "type": "FloatingVideo",
@@ -518,10 +479,10 @@
         1928,
         295
       ],
-      "size": [
-        315,
-        58
-      ],
+      "size": {
+        "0": 315,
+        "1": 58
+      },
       "flags": {},
       "order": 12,
       "mode": 0,
@@ -534,7 +495,68 @@
       ],
       "properties": {
         "Node name for S&R": "FloatingVideo"
-      }
+      },
+      "widgets_values": [
+        null
+      ]
+    },
+    {
+      "id": 23,
+      "type": "ScreenShare",
+      "pos": [
+        -65,
+        446
+      ],
+      "size": {
+        "0": 315,
+        "1": 170
+      },
+      "flags": {},
+      "order": 3,
+      "mode": 0,
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            49,
+            50
+          ],
+          "shape": 3,
+          "slot_index": 0
+        },
+        {
+          "name": "PROMPT",
+          "type": "STRING",
+          "links": [
+            51
+          ],
+          "shape": 3,
+          "slot_index": 1
+        },
+        {
+          "name": "FLOAT",
+          "type": "FLOAT",
+          "links": null,
+          "shape": 3
+        },
+        {
+          "name": "INT",
+          "type": "INT",
+          "links": null,
+          "shape": 3
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "ScreenShare"
+      },
+      "widgets_values": [
+        null,
+        null,
+        null,
+        null,
+        null
+      ]
     }
   ],
   "links": [
@@ -787,24 +809,24 @@
       "CLIP"
     ],
     [
-      46,
-      22,
-      0,
-      2,
-      0,
-      "IMAGE"
-    ],
-    [
-      47,
-      22,
+      49,
+      23,
       0,
       18,
       0,
       "IMAGE"
     ],
     [
-      48,
-      22,
+      50,
+      23,
+      0,
+      2,
+      0,
+      "IMAGE"
+    ],
+    [
+      51,
+      23,
       1,
       8,
       1,

workflow/5-gpt-workflow.json

@@ -1,6 +1,6 @@
 {
-  "last_node_id": 46,
-  "last_link_id": 42,
+  "last_node_id": 47,
+  "last_link_id": 46,
   "nodes": [
     {
       "id": 27,
@@ -25,7 +25,7 @@
         {
           "name": "text",
           "type": "STRING",
-          "link": 42,
+          "link": 46,
           "widget": {
             "name": "text"
           }
@@ -136,7 +136,7 @@
         "Node name for S&R": "KSampler"
       },
       "widgets_values": [
-        261818020972971,
+        971428736321335,
         "randomize",
         15,
         8,
@@ -300,10 +300,10 @@
         1171,
         425
       ],
-      "size": [
-        432.46002197265625,
-        264.40771484375
-      ],
+      "size": {
+        "0": 432.46002197265625,
+        "1": 264.40771484375
+      },
       "flags": {},
       "order": 6,
       "mode": 0,
@@ -311,7 +311,7 @@
         {
           "name": "text",
           "type": "STRING",
-          "link": 40,
+          "link": 44,
           "widget": {
             "name": "text"
           }
@@ -329,7 +329,7 @@
         "Node name for S&R": "ShowTextForGPT"
       },
       "widgets_values": [
-        "[\n  {\n    \"role\": \"system\",\n    \"content\": \"你现在充当stable diffsion 提示词专家，根据我输入的场景或需求描述，生成提示词，由stable diffsion根据你的提示词生成画面。stable diffusion是文本到图像的扩散模型。你的任务是在各种情况下产生适当的提示，引导人工智能创造出所需的图像。\\n\\n一个优秀的提示词需要遵循下面的规范：\\n\\n“““\\n\\n简洁明了：避免过于复杂或模糊的描述，以免造成模型的混乱或错误。\\n\\n具体细致：提供足够的细节，以便模型能够准确地捕捉想要生成的图片的特征。\\n\\n逻辑连贯：避免出现矛盾或不合理的描述，以免影响模型的理解和生成。\\n\\n创意独特：有创意，展示自己的想象力和个性，以便模型能够生成有趣和新颖的图片。\\n\\n我建议你可以参考以下几个步骤思考：\\n\\n• 确定主题：首先，你需要确定想要生成图片的主题，例如风景、动物、人物等。\\n\\n• 确定风格：其次，根据主题要求，确定合适的风格(如极简、现代)或根据主题(人物、风景等)调整提示词的语言风格、词汇和描述角度。\\n\\n• 选择关键词：再次，你需要选择一些能够描述主题的关键词，常用的关键词类别包括：主体、媒介、风格、画家、网站、分辨率、额外细节、色调和光影。 可以使用名人的名字作为关键词，来控制人物形象，因为他们在训练集中出现频次较大而训练充分。\\n\\n• 组合句子：然后，你需要将关键词组合成一个或多个简单句子，提示词的句式通常如：【图片的风格】,【内容主题 】,【 细节描述】,【 绘画风格或者艺术家风格】， 用逗号或分号隔开，例如a blue sky with white clouds, a green field with yellow flowers。\\n\\n• 调整细节：最后，根据告诉你的内容主题，尽可能细致刻画画面，譬如，要画“大海”，你需要给出类似这样的提示：梦幻的大海，白沙滩岸边铺满了粉色的玫瑰花，月光轻柔的人洒在海面上，绿色发光的海浪。对于细节描述，我们可以拆分【形容词】+【视角】+【时间】+【颜色】+【其他】，形容词可以是梦幻，神秘，浪漫或者写实 ……视角可以是：超广角，俯视和仰视 ……,时间：秋天，清晨，黄昏，夜晚 ……,颜色可以是 红黄绿蓝橙紫……,其他可以包含图片的尺寸，4k,8k ，HD,光效，高细节等。\\n\\n• 如果想让生成的图片更加的艺术化、风格化，可以考虑在 提示词中添加绘画风格和艺术家。艺术绘画风格可以是一些美术风格：梵高风格，油画，水彩，古风，CG感，动漫，少女，赛博朋克，卡通画，中国画，黄昏等等，艺术家风格包含：现实主义，印象派，野兽派，新艺术，表现主义，立体主义，未来主义等等\\n\\n• 以简洁的英语输出。输出完整提示词后，把它翻译成中文，然后保留英语版本备用。\\n\\n“““\\n\\n为了让你更好的理解提示词，我收集了一些表现效果较好的提示词案例，你可以对照上面的规则学习吸收：\\n\\n“““\\n\\nMaximalist chaotic buenos aires, birds eye view, illustrated by hergé, style of tin tin comics, pen and ink\\n\\nHyper -realistic girl in blue coat, left in the woods, weird, otherworldly, real, vintage photograph, film set, 85mm lens, f/2.8 aperture\\n\\ninstagram photo of a Japanese and Scandinavian design style living room with lots of golden light, hyperrealistic surrealism, award winning masterpiece with incredible details\\n\\nPortrait of an owl, steampunk, indigo blue, colorful, illustration, highly detailed, simple, smooth, and clean vector, no jagged lines, vector art, smooth, made all with grey colored gears inspired by future technology\\n\\n“““\\n\\n请通过回复 “确认 “来确认你是否理解了这项任务。然后我将向你发送第一条命令。\"\n  },\n  {\n    \"role\": \"user\",\n    \"content\": \"证件照，女生,请认真回答噢，很重要这个问题\"\n  }\n]"
+        "[\n    {\n        \"role\": \"system\",\n        \"content\": \"You are ChatGPT, a large language model trained by OpenAI. Answer as concisely as possible.\"\n    },\n    {\n        \"role\": \"user\",\n        \"content\": \"\"\n    }\n]"
       ]
     },
     {
@@ -339,10 +339,10 @@
         1166,
         740
       ],
-      "size": [
-        424.00797187258513,
-        430.6391176555039
-      ],
+      "size": {
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         {
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         "Node name for S&R": "ShowTextForGPT"
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-        "[\n  {\n    \"role\": \"user\",\n    \"content\": \"\"\n  },\n  {\n    \"role\": \"assistant\",\n    \"content\": \"ChatGPT is an artificial intelligence chatbot program launched by OpenAI in November 2022. The program is based on a large language model GPT-3.5, trained with Instruction Tuning and Reinforcement Learning with Human Feedback (RLHF).\"\n  },\n  {\n    \"role\": \"user\",\n    \"content\": \"\"\n  },\n  {\n    \"role\": \"assistant\",\n    \"content\": \"GPT-3.5 is a language model developed by OpenAI, based on the Transformer architecture. It is designed to perform a wide range of natural language processing tasks, including language translation, text summarization, and text generation.\"\n  },\n  {\n    \"role\": \"user\",\n    \"content\": \"\"\n  },\n  {\n    \"role\": \"assistant\",\n    \"content\": \"Is there anything specific you would like to know about GPT-3.5? I am here to help.\"\n  },\n  {\n    \"role\": \"user\",\n    \"content\": \"今天天气\"\n  },\n  {\n    \"role\": \"assistant\",\n    \"content\": \"I'm sorry, I am a text-based AI model and do not have the capability to access the current weather. However, I can tell you that it is likely to be a beautiful day, with the sun shining and a gentle breeze in the air. Enjoy your day!\"\n  },\n  {\n    \"role\": \"user\",\n    \"content\": \"今天天气不错噢，小明……\"\n  },\n  {\n    \"role\": \"assistant\",\n    \"content\": \"谢谢您的夸奖，不过我是一个人工智能模型，没有能力感知天气，只是通过语言理解回答问题。如果您需要查询当地的天气情况，建议您查询当地的天气预报。\"\n  },\n  {\n    \"role\": \"user\",\n    \"content\": \"今天天气不错噢，小明……\"\n  },\n  {\n    \"role\": \"assistant\",\n    \"content\": \"今天天气不错噢，小明……(这句话是重复的，之前已经回答过您的问题了。如果您需要查询当地的天气情况，建议您查询当地的天气预报。\"\n  },\n  {\n    \"role\": \"user\",\n    \"content\": \"证件照，女生\"\n  },\n  {\n    \"role\": \"assistant\",\n    \"content\": \"“女生分别为： Cut out of a colorful plaid skirt and white shirt, faced front, with a friendly smile, blonde-haired girl, age 22, blue eyes, naturalistic, clear, bright, young，以及人像，摄于户外，背景为美丽的自然风光，使用的相机是佳能5D Mark IV，镜头焦距为50mm，拍摄模式为肖像模式，使用的后期处理软件为Adobe Lightroom和Photoshop。\"\n  },\n  {\n    \"role\": \"user\",\n    \"content\": \"证件照，女生\"\n  },\n  {\n    \"role\": \"assistant\",\n    \"content\": \"• 拍摄证件照，要求提供女生的照片，背景可以是一片白色的天空，或者一片纯色的草地，不能有杂色。\\n• 视角应该从 above，即从上方俯视，让女生显得稳定自信。\\n• 时间应该选择在阳光明媚的早晨，这样可以让女生看起来更加青春活力。\\n• 颜色可以选择蓝色，这种颜色可以让人感到清新自然。\\n• 照片应该有高清清晰的效果，不能有模糊模糊的现象。\\n• 照片的尺寸可以选择2K或者4K，这样可以让照片更加清晰。\\n• 光效可以选择自然光，这样可以让照片看起来更加自然。\\n• 照片的风格可以选择日系或者韩系，这样可以让照片看起来更加时尚。\\n• 照片的背景可以选择浅色系，这样可以让照片看起来更加清新自然。\\n• 照片中不能有重大的人物或者动物，否则需要事先沟通好。\\n• 照片中不能有太强烈的光线或者阴影，需要调整好光线和阴影的平衡，使照片更加均匀。\\n• 照片中不能有太多的文字或者文字的内容，需要将文字或者文字的内容进行处理。\\n• 在拍摄证件照之前，需要让女生进行一些准备，比如保持好心态，调整好光线，保持好角度等等。\\n• 拍摄完证件照之后，需要将照片进行一些处理，比如进行美颜，磨皮，瘦脸等等。\"\n  },\n  {\n    \"role\": \"user\",\n    \"content\": \"证件照，女生,请认真回答噢，很重要这个问题\"\n  },\n  {\n    \"role\": \"assistant\",\n    \"content\": \"确认\"\n  }\n]"
+        "[\n    {\n        \"role\": \"user\",\n        \"content\": \"\"\n    },\n    {\n        \"role\": \"assistant\",\n        \"content\": \"I'm sorry, I'm ChatGLM3-6B, not ChatGPT. I am a language model jointly trained by Tsinghua University KEG Lab and Zhipu AI Company.\"\n    }\n]"
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workflow/6-gpt-all-workflow.json

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workflow/7-camera-workflow.json

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