#

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

@@ -1,15 +1,25 @@
 ## 
-v0.2.7 🚀🚗🚚🏃‍
+v0.3.0 🚀🚗🚚🏃‍
 
-- [Add getting camera video stream](./workflow/7-camera-workflow.json)
-- Add a slider to the floating window, which can be used as input for denoise
-- Add random seed control method to the floating window
-- OSupport for calling multiple GPTs
+- 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! 💻🌐
 
@@ -139,3 +149,23 @@ pip3 install -r requirements.txt
 - 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

@@ -169,6 +169,22 @@ def save_workflow_json(data):
     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
 
@@ -259,6 +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)
@@ -293,8 +323,10 @@ 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
 NODE_CLASS_MAPPINGS = {
@@ -324,6 +356,8 @@ NODE_CLASS_MAPPINGS = {
     "ChatGPTOpenAI":ChatGPTNode,
     "ShowTextForGPT":ShowTextForGPT,
     "CharacterInText":CharacterInText,
+    "SpeechRecognition":SpeechRecognition,
+    "SpeechSynthesis":SpeechSynthesis,
     "Color":ColorInput,
     "Font":FontInput
 }
@@ -338,7 +372,9 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "FloatingVideo":"FloatingVideo ♾️Mixlab",
     "ChatGPTOpenAI":"ChatGPT ♾️Mixlab",
     "ShowTextForGPT":"ShowTextForGPT ♾️Mixlab",
-    "MergeLayers":"MergeLayers ♾️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

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/Utils.py

@@ -1,30 +1,32 @@
 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:
-            font_prop = fm.FontProperties(fname=path)
-            font_name = font_prop.get_name()
-            font_files[font_name] = path
-    except ValueError:
-        print("findSystemFonts error")
+            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/')

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

@@ -3,7 +3,7 @@ import { app } from '../../../scripts/app.js'
 const repoOwner = 'shadowcz007' // 替换为仓库的所有者
 const repoName = 'comfyui-mixlab-nodes' // 替换为仓库的名称
 
-const version = 'v0.2.7'
+const version = 'v0.3.1'
 
 fetch(`https://api.github.com/repos/${repoOwner}/${repoName}/releases/latest`)
   .then(response => response.json())

web/javascript/gpt_mixlab.js

@@ -192,7 +192,7 @@ app.registerExtension({
 
       let id = node.id
 
-      console.log('ChatGPTOpenAI serialize_widgets', this)
+      // console.log('ChatGPTOpenAI serialize_widgets', this)
 
       widget.div.querySelector('.Key').value = apiKey[id] || 'by Mixlab'
       widget.div.querySelector('.URL').value =
@@ -216,12 +216,27 @@ app.registerExtension({
 						this.widgets.length = pos;
 					}
 				}
-        // console.log('ShowTextForGPT',this.widgets.length)
-				for (const list of text) {
+        // 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;
-					w.value = list;
+
+          try {
+            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(error)
+          }
+
+					w.value =list;
+        
 				}
         // console.log('ShowTextForGPT',this.widgets.length)
 				requestAnimationFrame(() => {

web/javascript/image_mixlab.js

@@ -3,7 +3,7 @@ import { api } from '../../../scripts/api.js'
 import { ComfyWidgets } from '../../../scripts/widgets.js'
 import { $el } from '../../../scripts/ui.js'
 
-async function uploadImage (blob,fileType='.svg') {
+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))
@@ -25,9 +25,8 @@ async function uploadImage (blob,fileType='.svg') {
   return src
 }
 
-function base64ToBlobFromURL(base64URL, contentType) {
-  return fetch(base64URL)
-    .then(response => response.blob());
+function base64ToBlobFromURL (base64URL, contentType) {
+  return fetch(base64URL).then(response => response.blob())
 }
 
 function getContentTypeFromBase64 (base64Data) {
@@ -126,6 +125,7 @@ const parseImage = url => {
 }
 
 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
@@ -135,17 +135,18 @@ const parseSvg = async svgContent => {
   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')
-    var y = rectElement.getAttribute('y')
-    var width = rectElement.getAttribute('width')
-    var height = rectElement.getAttribute('height')
-    if (x != undefined && y != undefined) {
+    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
@@ -171,7 +172,8 @@ const parseSvg = async svgContent => {
         scale_option: 'width',
         image: base64,
         mask: base64,
-        type: 'base64'
+        type: 'base64',
+        _t: 'rect'
       }
 
       // 将处理后的数据添加到数组中
@@ -181,6 +183,15 @@ const parseSvg = async svgContent => {
 
   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
@@ -207,12 +218,13 @@ const parseSvg = async svgContent => {
     scale_option: 'width',
     image: base64,
     mask: base64,
-    type: 'base64'
+    type: 'base64',
+    _t: 'canvas'
   }
   data.push(rectData)
 
   // 打印处理后的数据
-  // console.log({ data, image: base64, svgElement })
+  console.log('layers', { data, image: base64, svgElement })
   return { data, image: base64, svgElement }
 }
 
@@ -327,6 +339,12 @@ app.registerExtension({
 
               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()
             }
@@ -509,7 +527,9 @@ app.registerExtension({
                 <div><button class="capture">Capture</button></div>
               </div></model-viewer>`
 
-              preview.innerHTML = html
+              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')
@@ -540,10 +560,10 @@ app.registerExtension({
 
                 const contentType = getContentTypeFromBase64(base64Data)
 
-                const blob =await base64ToBlobFromURL(base64Data, contentType)
+                const blob = await base64ToBlobFromURL(base64Data, contentType)
 
                 //  const fileBlob = new Blob([e.target.result], { type: file.type });
-                let url = await uploadImage(blob,'.png')
+                let url = await uploadImage(blob, '.png')
                 console.log(url)
 
                 let dd = getLocalData(key)
@@ -563,13 +583,25 @@ app.registerExtension({
 
         let preview = document.createElement('div')
         preview.className = 'preview'
-        preview.style = `background:#eee;margin-top: 12px;`
+        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)
+        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 = () => {
@@ -608,7 +640,7 @@ app.registerExtension({
       let url = dd[id]
       // let base64 = await parseImage(url)
 
-      widget.div.querySelector('.preview').innerHTML = `<img src="${url}"/>` 
+      widget.div.querySelector('.preview').innerHTML = `<img src="${url}"/>`
 
       const uploadWidget = node.widgets.filter(w => w.name == 'upload')[0]
       uploadWidget.value = await uploadWidget.serializeValue()

web/javascript/layer_mixlab.js

@@ -63,17 +63,18 @@ const parseSvg = async svgContent => {
   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')
-    var y = rectElement.getAttribute('y')
-    var width = rectElement.getAttribute('width')
-    var height = rectElement.getAttribute('height')
-    if (x != undefined && y != undefined) {
+    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
@@ -99,7 +100,8 @@ const parseSvg = async svgContent => {
         scale_option: 'width',
         image: base64,
         mask: base64,
-        type: 'base64'
+        type: 'base64',
+        _t:'rect'
       }
 
       // 将处理后的数据添加到数组中
@@ -109,6 +111,15 @@ const parseSvg = async svgContent => {
 
   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
@@ -135,12 +146,13 @@ const parseSvg = async svgContent => {
     scale_option: 'width',
     image: base64,
     mask: base64,
-    type: 'base64'
+    type: 'base64',
+    _t:'canvas'
   }
   data.push(rectData)
 
   // 打印处理后的数据
-  console.log({ data, image: base64, svgElement })
+  console.log('layers',{ data, image: base64, svgElement })
   return { data, image: base64, svgElement }
 }
 
@@ -199,11 +211,15 @@ app.registerExtension({
 
         // 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
+          let nodeId = app.graph.links?.filter(link => link.id == linkId)[0]
+            ?.origin_id;
 
-          nodeId = findNode(nodeId)
+          if(nodeId){
+            nodeId = findNode(nodeId)
+          }
+          
 
           //   let node = app.graph._nodes_by_id[nodeId]
           //   if (node?.type == 'Reroute') {
@@ -218,8 +234,11 @@ app.registerExtension({
           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 []

web/javascript/main_mixlab.js

@@ -890,6 +890,9 @@ 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!
               */

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

@@ -5,6 +5,7 @@ import { ComfyWidgets } from '../../../scripts/widgets.js'
 import { $el } from '../../../scripts/ui.js'
 
 
+
 const getLocalData = key => {
   let data = {}
   try {
@@ -46,6 +47,7 @@ function get_position_style (ctx, widget_width, y, node_height) {
   }
 }
 
+
 app.registerExtension({
     name: 'Mixlab.utils.Color',
     async getCustomWidgets (app) {

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/语音+实时换脸workflow.json

@@ -0,0 +1,862 @@
+{
+  "last_node_id": 28,
+  "last_link_id": 64,
+  "nodes": [
+    {
+      "id": 7,
+      "type": "CLIPTextEncode",
+      "pos": [
+        515,
+        130
+      ],
+      "size": {
+        "0": 400,
+        "1": 200
+      },
+      "flags": {},
+      "order": 3,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "clip",
+          "type": "CLIP",
+          "link": 33
+        }
+      ],
+      "outputs": [
+        {
+          "name": "CONDITIONING",
+          "type": "CONDITIONING",
+          "links": [
+            29
+          ],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "CLIPTextEncode"
+      },
+      "widgets_values": [
+        ""
+      ]
+    },
+    {
+      "id": 6,
+      "type": "LoraLoader",
+      "pos": [
+        515,
+        460
+      ],
+      "size": {
+        "0": 315,
+        "1": 126
+      },
+      "flags": {},
+      "order": 4,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "model",
+          "type": "MODEL",
+          "link": 31
+        },
+        {
+          "name": "clip",
+          "type": "CLIP",
+          "link": 45
+        }
+      ],
+      "outputs": [
+        {
+          "name": "MODEL",
+          "type": "MODEL",
+          "links": [
+            44
+          ],
+          "shape": 3,
+          "slot_index": 0
+        },
+        {
+          "name": "CLIP",
+          "type": "CLIP",
+          "links": null,
+          "shape": 3
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "LoraLoader"
+      },
+      "widgets_values": [
+        "lcm-lora-sdv1-5.safetensors",
+        1,
+        1
+      ]
+    },
+    {
+      "id": 11,
+      "type": "VAEDecode",
+      "pos": [
+        1430,
+        130
+      ],
+      "size": {
+        "0": 210,
+        "1": 46
+      },
+      "flags": {},
+      "order": 11,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "samples",
+          "type": "LATENT",
+          "link": 35
+        },
+        {
+          "name": "vae",
+          "type": "VAE",
+          "link": 34
+        }
+      ],
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            41
+          ],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "VAEDecode"
+      }
+    },
+    {
+      "id": 23,
+      "type": "VAEEncode",
+      "pos": [
+        515,
+        1092
+      ],
+      "size": {
+        "0": 210,
+        "1": 46
+      },
+      "flags": {},
+      "order": 6,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "pixels",
+          "type": "IMAGE",
+          "link": 57
+        },
+        {
+          "name": "vae",
+          "type": "VAE",
+          "link": 58
+        }
+      ],
+      "outputs": [
+        {
+          "name": "LATENT",
+          "type": "LATENT",
+          "links": [
+            54
+          ],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "VAEEncode"
+      }
+    },
+    {
+      "id": 10,
+      "type": "CheckpointLoaderSimple",
+      "pos": [
+        100,
+        130
+      ],
+      "size": {
+        "0": 315,
+        "1": 98
+      },
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "outputs": [
+        {
+          "name": "MODEL",
+          "type": "MODEL",
+          "links": [
+            31
+          ],
+          "shape": 3,
+          "slot_index": 0
+        },
+        {
+          "name": "CLIP",
+          "type": "CLIP",
+          "links": [
+            32,
+            33,
+            45
+          ],
+          "shape": 3,
+          "slot_index": 1
+        },
+        {
+          "name": "VAE",
+          "type": "VAE",
+          "links": [
+            34,
+            58
+          ],
+          "shape": 3,
+          "slot_index": 2
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "CheckpointLoaderSimple"
+      },
+      "widgets_values": [
+        "deliberate_v2.safetensors"
+      ]
+    },
+    {
+      "id": 8,
+      "type": "CLIPTextEncode",
+      "pos": [
+        515,
+        1268
+      ],
+      "size": {
+        "0": 400,
+        "1": 200
+      },
+      "flags": {},
+      "order": 8,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "clip",
+          "type": "CLIP",
+          "link": 32
+        },
+        {
+          "name": "text",
+          "type": "STRING",
+          "link": 62,
+          "widget": {
+            "name": "text"
+          }
+        }
+      ],
+      "outputs": [
+        {
+          "name": "CONDITIONING",
+          "type": "CONDITIONING",
+          "links": [
+            51
+          ],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "CLIPTextEncode"
+      },
+      "widgets_values": [
+        ""
+      ]
+    },
+    {
+      "id": 20,
+      "type": "FloatingVideo",
+      "pos": [
+        1274,
+        536
+      ],
+      "size": [
+        315,
+        58
+      ],
+      "flags": {},
+      "order": 12,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "images",
+          "type": "IMAGE",
+          "link": 41
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "FloatingVideo"
+      },
+      "widgets_values": [
+        null
+      ]
+    },
+    {
+      "id": 5,
+      "type": "KSampler",
+      "pos": [
+        1004,
+        130
+      ],
+      "size": [
+        315,
+        262
+      ],
+      "flags": {},
+      "order": 10,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "model",
+          "type": "MODEL",
+          "link": 44
+        },
+        {
+          "name": "positive",
+          "type": "CONDITIONING",
+          "link": 51
+        },
+        {
+          "name": "negative",
+          "type": "CONDITIONING",
+          "link": 29
+        },
+        {
+          "name": "latent_image",
+          "type": "LATENT",
+          "link": 54
+        }
+      ],
+      "outputs": [
+        {
+          "name": "LATENT",
+          "type": "LATENT",
+          "links": [
+            35
+          ],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "KSampler"
+      },
+      "widgets_values": [
+        758428944049342,
+        "fixed",
+        4,
+        1.6,
+        "lcm",
+        "karras",
+        0.61
+      ]
+    },
+    {
+      "id": 24,
+      "type": "ScreenShare",
+      "pos": [
+        62,
+        543
+      ],
+      "size": {
+        "0": 315,
+        "1": 194
+      },
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            55,
+            57
+          ],
+          "shape": 3,
+          "slot_index": 0
+        },
+        {
+          "name": "PROMPT",
+          "type": "STRING",
+          "links": [],
+          "shape": 3,
+          "slot_index": 1
+        },
+        {
+          "name": "FLOAT",
+          "type": "FLOAT",
+          "links": [],
+          "shape": 3,
+          "slot_index": 2
+        },
+        {
+          "name": "INT",
+          "type": "INT",
+          "links": null,
+          "shape": 3
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "ScreenShare"
+      },
+      "widgets_values": [
+        null,
+        null,
+        null,
+        null,
+        null
+      ]
+    },
+    {
+      "id": 2,
+      "type": "PreviewImage",
+      "pos": [
+        -416,
+        516
+      ],
+      "size": {
+        "0": 210,
+        "1": 246
+      },
+      "flags": {},
+      "order": 5,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "images",
+          "type": "IMAGE",
+          "link": 55
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "PreviewImage"
+      }
+    },
+    {
+      "id": 26,
+      "type": "ChatGPTOpenAI",
+      "pos": [
+        5,
+        1325
+      ],
+      "size": [
+        400,
+        357.99993896484375
+      ],
+      "flags": {},
+      "order": 7,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "prompt",
+          "type": "STRING",
+          "link": 61,
+          "widget": {
+            "name": "prompt"
+          }
+        }
+      ],
+      "outputs": [
+        {
+          "name": "text",
+          "type": "STRING",
+          "links": [
+            62,
+            63
+          ],
+          "shape": 3,
+          "slot_index": 0
+        },
+        {
+          "name": "messages",
+          "type": "STRING",
+          "links": null,
+          "shape": 3
+        },
+        {
+          "name": "session_history",
+          "type": "STRING",
+          "links": null,
+          "shape": 3
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "ChatGPTOpenAI"
+      },
+      "widgets_values": [
+        null,
+        null,
+        "",
+        "你需要根据用户的输入，转化为英文单词的短句子组合，输出英文",
+        "gpt-35-turbo",
+        1249,
+        "randomize",
+        1,
+        null
+      ]
+    },
+    {
+      "id": 28,
+      "type": "SpeechSynthesis",
+      "pos": [
+        542,
+        1570
+      ],
+      "size": [
+        315,
+        76
+      ],
+      "flags": {},
+      "order": 9,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "text",
+          "type": "STRING",
+          "link": 63,
+          "widget": {
+            "name": "text"
+          }
+        }
+      ],
+      "outputs": [
+        {
+          "name": "STRING",
+          "type": "STRING",
+          "links": null,
+          "shape": 6
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "SpeechSynthesis"
+      },
+      "widgets_values": [
+        "A very handsome elderly gentleman."
+      ]
+    },
+    {
+      "id": 25,
+      "type": "SpeechRecognition",
+      "pos": [
+        -5,
+        1101
+      ],
+      "size": [
+        392.5606180664065,
+        166.64923671875022
+      ],
+      "flags": {},
+      "order": 2,
+      "mode": 0,
+      "outputs": [
+        {
+          "name": "prompt",
+          "type": "STRING",
+          "links": [
+            61
+          ],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "SpeechRecognition"
+      },
+      "widgets_values": [
+        null,
+        null
+      ]
+    }
+  ],
+  "links": [
+    [
+      1,
+      1,
+      0,
+      2,
+      0,
+      "IMAGE"
+    ],
+    [
+      3,
+      6,
+      0,
+      5,
+      0,
+      "MODEL"
+    ],
+    [
+      5,
+      8,
+      0,
+      5,
+      2,
+      "CONDITIONING"
+    ],
+    [
+      6,
+      9,
+      0,
+      5,
+      3,
+      "LATENT"
+    ],
+    [
+      7,
+      10,
+      0,
+      6,
+      0,
+      "MODEL"
+    ],
+    [
+      8,
+      10,
+      1,
+      6,
+      1,
+      "CLIP"
+    ],
+    [
+      9,
+      5,
+      0,
+      11,
+      0,
+      "LATENT"
+    ],
+    [
+      10,
+      10,
+      2,
+      11,
+      1,
+      "VAE"
+    ],
+    [
+      11,
+      6,
+      1,
+      7,
+      0,
+      "CLIP"
+    ],
+    [
+      12,
+      6,
+      1,
+      8,
+      0,
+      "CLIP"
+    ],
+    [
+      14,
+      11,
+      0,
+      3,
+      0,
+      "IMAGE"
+    ],
+    [
+      17,
+      1,
+      2,
+      7,
+      1,
+      "STRING"
+    ],
+    [
+      18,
+      7,
+      0,
+      15,
+      0,
+      "CONDITIONING"
+    ],
+    [
+      19,
+      15,
+      0,
+      5,
+      1,
+      "CONDITIONING"
+    ],
+    [
+      20,
+      16,
+      0,
+      15,
+      1,
+      "CONTROL_NET"
+    ],
+    [
+      24,
+      1,
+      0,
+      18,
+      0,
+      "IMAGE"
+    ],
+    [
+      25,
+      18,
+      0,
+      15,
+      2,
+      "IMAGE"
+    ],
+    [
+      29,
+      7,
+      0,
+      5,
+      2,
+      "CONDITIONING"
+    ],
+    [
+      31,
+      10,
+      0,
+      6,
+      0,
+      "MODEL"
+    ],
+    [
+      32,
+      10,
+      1,
+      8,
+      0,
+      "CLIP"
+    ],
+    [
+      33,
+      10,
+      1,
+      7,
+      0,
+      "CLIP"
+    ],
+    [
+      34,
+      10,
+      2,
+      11,
+      1,
+      "VAE"
+    ],
+    [
+      35,
+      5,
+      0,
+      11,
+      0,
+      "LATENT"
+    ],
+    [
+      41,
+      11,
+      0,
+      20,
+      0,
+      "IMAGE"
+    ],
+    [
+      44,
+      6,
+      0,
+      5,
+      0,
+      "MODEL"
+    ],
+    [
+      45,
+      10,
+      1,
+      6,
+      1,
+      "CLIP"
+    ],
+    [
+      51,
+      8,
+      0,
+      5,
+      1,
+      "CONDITIONING"
+    ],
+    [
+      54,
+      23,
+      0,
+      5,
+      3,
+      "LATENT"
+    ],
+    [
+      55,
+      24,
+      0,
+      2,
+      0,
+      "IMAGE"
+    ],
+    [
+      57,
+      24,
+      0,
+      23,
+      0,
+      "IMAGE"
+    ],
+    [
+      58,
+      10,
+      2,
+      23,
+      1,
+      "VAE"
+    ],
+    [
+      61,
+      25,
+      0,
+      26,
+      0,
+      "STRING"
+    ],
+    [
+      62,
+      26,
+      0,
+      8,
+      1,
+      "STRING"
+    ],
+    [
+      63,
+      26,
+      0,
+      28,
+      0,
+      "STRING"
+    ]
+  ],
+  "groups": [],
+  "config": {},
+  "extra": {},
+  "version": 0.4
+}