v0.34.0

Update PyProject Toml - License

.github/workflows/publish.yml

@@ -0,0 +1,21 @@
+name: Publish to Comfy registry
+on:
+  workflow_dispatch:
+  push:
+    branches:
+      - main
+    paths:
+      - "pyproject.toml"
+
+jobs:
+  publish-node:
+    name: Publish Custom Node to registry
+    runs-on: ubuntu-latest
+    steps:
+      - name: Check out code
+        uses: actions/checkout@v4
+      - name: Publish Custom Node
+        uses: Comfy-Org/publish-node-action@main
+        with:
+          ## Add your own personal access token to your Github Repository secrets and reference it here.
+          personal_access_token: ${{ secrets.REGISTRY_ACCESS_TOKEN }}

CNAME

@@ -0,0 +1 @@
+mixlabnodes.com

LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2024 shadow
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

@@ -6,21 +6,36 @@
 
 ##### `最新`：
 
-ChatGPT 节点支持 Local LLM（llama.cpp），Phi3、llama3 都可以直接一个节点运行了。模型下载后，放置到 `models/llamafile/`
+- App模式增加batch prompt，批量提示词，可以把动态提示词批量组成后运行
 
-- 右键菜单支持 text-to-text，方便对 prompt 词补全
+![alt text](./assets/1722517810720.png)
 
-强烈推荐：[Phi-3-mini-4k-instruct-GGUF](https://huggingface.co/lmstudio-community/Phi-3-mini-4k-instruct-GGUF/tree/main)，备选：[llama3_if_ai_sdpromptmkr_q2k](https://hf-mirror.com/impactframes/llama3_if_ai_sdpromptmkr_q2k/tree/main)
+- 增加 SiliconflowLLM，可以使用由Siliconflow提供的免费LLM
+
+- 增加 Edit Mask，方便在生成的时候手动绘制 mask [workflow](./workflow/edit-mask-workflow.json)
+
+<!-- - ChatGPT 节点支持 Local LLM（llama.cpp），Phi3、llama3 都可以直接一个节点运行了。模型下载后，放置到 `models/llamafile/` -->
+
+<!-- - 右键菜单支持 text-to-text，方便对 prompt 词补全 -->
+<!-- 
+强烈推荐：
+[Phi-3-mini-4k-instruct-function-calling-GGUF](https://huggingface.co/nold/Phi-3-mini-4k-instruct-function-calling-GGUF)
+
+[Phi-3-mini-4k-instruct-GGUF](https://huggingface.co/lmstudio-community/Phi-3-mini-4k-instruct-GGUF/tree/main)，备选：[llama3_if_ai_sdpromptmkr_q2k](https://hf-mirror.com/impactframes/llama3_if_ai_sdpromptmkr_q2k/tree/main)
 
 - 右键菜单支持 image-to-text，使用多模态模型，多模态使用 [llava-phi-3-mini-gguf](https://huggingface.co/xtuner/llava-phi-3-mini-gguf/tree/main)，注意需要把llava-phi-3-mini-mmproj-f16.gguf也下载
 
 ![](./assets/prompt_ai_setup.png)
-![](./assets/prompt-ai.png)
+![](./assets/prompt-ai.png) -->
 
 
 #### `相关插件推荐`
 
-<!-- [comfyui-sd-prompt-mixlab](https://github.com/shadowcz007/comfyui-sd-prompt-mixlab) -->
+[comfyui-liveportrait](https://github.com/shadowcz007/comfyui-liveportrait)
+
+[Comfyui-ChatTTS](https://github.com/shadowcz007/Comfyui-ChatTTS)
+
+[comfyui-sound-lab](https://github.com/shadowcz007/comfyui-sound-lab)
 
 [comfyui-Image-reward](https://github.com/shadowcz007/comfyui-Image-reward)
 
@@ -37,6 +52,8 @@ ChatGPT 节点支持 Local LLM（llama.cpp），Phi3、llama3 都可以直接一
 - 发布为 app 的 workflow，可以在右键里再次编辑了
 - web app 可以设置分类，在 comfyui 右键菜单可以编辑更新 web app
 - 支持动态提示
+- 支持把输出显示到comfyui背景（TouchDesigner 风格）
+- 如果转为web app打开是空白的，注意检查下插件目录的名字需要是：comfyui-mixlab-nodes(如果是zip包下载会多了个-main的后缀，需要去掉)
 
 ![](./assets/微信图片_20240421205440.png)
 
@@ -103,7 +120,7 @@ https://github.com/shadowcz007/comfyui-mixlab-nodes/assets/12645064/e7e77f90-e43
 
 [workflow-5](./workflow/5-gpt-workflow.json)
 
-最新：ChatGPT 节点支持 Local LLM（llama.cpp），Phi3、llama3 都可以直接一个节点运行了。
+<!-- 最新：ChatGPT 节点支持 Local LLM（llama.cpp），Phi3、llama3 都可以直接一个节点运行了。
 
 Model download,move to :`models/llamafile/`
 
@@ -131,7 +148,7 @@ pip install 'llama-cpp-python[server]'
 ```
 pip install llama-cpp-python \
   --extra-index-url https://abetlen.github.io/llama-cpp-python/whl/metal
-```
+``` -->
 
 ## Prompt
 
@@ -158,6 +175,9 @@ pip install llama-cpp-python \
 
 > 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.
 
+> The composite images node overlays a foreground image onto a background image at specified positions and scales, with optional blending modes and masking capabilities. position : 'overall',"center_center","left_bottom","center_bottom","right_bottom","left_top","center_top","right_top"
+
+
 ![layers](./assets/layers-workflow.svg)
 
 ![poster](./assets/poster-workflow.svg)
@@ -189,6 +209,12 @@ pip install llama-cpp-python \
 
 > Conveniently load images from a fixed address on the internet to ensure that default images in the workflow can be executed.
 
+#### TextImage
+
+> [下载字体](https://drxie.github.io/OSFCC/)放到 ```custom_nodes/comfyui-mixlab-nodes/assets/fonts```
+
+
+
 ### Style
 
 > Apply VisualStyle Prompting , Modified from [ComfyUI_VisualStylePrompting](https://github.com/ExponentialML/ComfyUI_VisualStylePrompting)

__init__.py

@@ -3,11 +3,15 @@ import os
 import subprocess
 import importlib.util
 import sys,json
-import urllib
+import execution
+import uuid
 import hashlib
 import datetime
 import folder_paths
 import logging
+import base64,io,re
+import random
+from PIL import Image
 from comfy.cli_args import args
 python = sys.executable
 
@@ -18,17 +22,18 @@ except:
     print('#fix sys.stdout.isatty')
     sys.stdout.isatty = lambda: False
 
-llama_port=None
-llama_model=""
-llama_chat_format=""
+_URL_=None
 
-try:
-    from .nodes.ChatGPT import get_llama_models,get_llama_model_path,llama_cpp_client
-    llama_cpp_client("")
 
-except:
-    print("##nodes.ChatGPT ImportError")
+# try:
+#     from .nodes.ChatGPT import get_llama_models,get_llama_model_path,llama_cpp_client
+#     llama_cpp_client("")
 
+# except:
+#     print("##nodes.ChatGPT ImportError")
+
+
+from .nodes.RembgNode import get_rembg_models,U2NET_HOME,run_briarmbg,run_rembg
 
 from server import PromptServer
 
@@ -98,6 +103,26 @@ install_openai()
 current_path = os.path.abspath(os.path.dirname(__file__))
 
 
+def remove_base64_prefix(base64_str):
+  """
+  去除 base64 字符串中的 data:image/*;base64, 前缀
+
+  Args:
+    base64_str: base64 编码的字符串
+
+  Returns:
+    去除前缀后的 base64 字符串
+  """
+
+  # 使用正则表达式匹配常见的前缀
+  pattern = r'^data:image\/(.*);base64,(.+)$'
+  match = re.match(pattern, base64_str)
+  if match:
+    # 如果匹配到常见的前缀，则去除前缀并返回
+    return match.group(2)
+  else:
+    # 如果不匹配到常见的前缀，则直接返回
+    return base64_str
 
 def calculate_md5(string):
     encoded_string = string.encode()
@@ -147,15 +172,14 @@ def create_for_https():
         os.mkdir(https_key_path)
     if not os.path.exists(crt):
         create_key(key,crt)
-
-    print('https_key OK: ', crt,key)
+    # print('https_key OK: ', crt,key)
     return (crt,key)
 
 
 
 # workflow  目录下的所有json
 def read_workflow_json_files_all(folder_path):
-    print('#read_workflow_json_files_all',folder_path)
+    # print('#read_workflow_json_files_all',folder_path)
     json_files = []
     for root, dirs, files in os.walk(folder_path):
         for file in files:
@@ -285,31 +309,32 @@ def get_my_workflow_for_app(filename="my_workflow_app.json",category="",is_all=F
         print('app_workflow_path: ',app_workflow_path)
         try:
             with open(app_workflow_path) as json_file:
+                json_data=json.load(json_file)
                 apps = [{
                     'filename':filename,
-                    'data':json.load(json_file)
+                    'data':json_data
                 }]
         except Exception as e:
             print("发生异常：", str(e))
         
         # 这个代码不需要
         # if len(apps)==1 and category!='' and category!=None:
-            data=read_workflow_json_files(category_path)
+        data=read_workflow_json_files(category_path)
             
-            for item in data:
-                x=item["data"]
-                # print(apps[0]['filename'] ,item["filename"])
-                if apps[0]['filename']!=item["filename"]:
-                    category=''
-                    input=None
-                    output=None
-                    if 'category' in x['app']:
-                        category=x['app']['category']
-                    if 'input' in x['app']:
-                        input=x['app']['input']
-                    if 'output' in x['app']:
-                        output=x['app']['output']
-                    apps.append({
+        for item in data:
+            x=item["data"]
+            # print(apps[0]['filename'] ,item["filename"])
+            if apps[0]['filename']!=item["filename"]:
+                category=''
+                input=None
+                output=None
+                if 'category' in x['app']:
+                    category=x['app']['category']
+                if 'input' in x['app']:
+                    input=x['app']['input']
+                if 'output' in x['app']:
+                    output=x['app']['output']
+                apps.append({
                         "filename":item["filename"],
                         # "category":category,
                         "data":{
@@ -429,6 +454,7 @@ async def check_port_available(address, port):
 
 # https
 async def new_start(self, address, port, verbose=True, call_on_start=None):
+    global _URL_
     try:
         runner = web.AppRunner(self.app, access_log=None)
         await runner.setup()
@@ -497,10 +523,19 @@ async def new_start(self, address, port, verbose=True, call_on_start=None):
             logging.info("\n")
             logging.info("\n\nStarting server")
 
+            import socket
+
+            hostname = socket.gethostname()
+            ip_address = socket.gethostbyname(hostname)
+
+            # print(f"本机的IP地址是: {ip_address}")
+
+
             # print("\033[93mStarting server\n")
-            logging.info("\033[93mTo see the GUI go to: http://{}:{}".format(address, http_port))
-            logging.info("\033[93mTo see the GUI go to: https://{}:{}\033[0m".format(address, https_port))
- 
+            logging.info("\033[93mTo see the GUI go to: http://{}:{} or http://{}:{}".format(ip_address, http_port,address,http_port))
+            logging.info("\033[93mTo see the GUI go to: https://{}:{} or https://{}:{}\033[0m".format(ip_address, https_port,address,https_port))
+
+            _URL_="http://{}:{}".format(address,http_port)
             # print("\033[93mTo see the GUI go to: http://{}:{}".format(address, http_port))
             # print("\033[93mTo see the GUI go to: https://{}:{}\033[0m".format(address, https_port))
 
@@ -584,13 +619,34 @@ async def mixlab_workflow_hander(request):
                     category=data['category']
                 if 'admin' in data:
                     admin=data['admin']
+
+                ds=get_my_workflow_for_app(filename,category,admin)
+                data=[]           
+                for json_data in ds:
+                    # 不传给前端
+                    if 'output' in json_data['data']:
+                        del json_data['data']['output']
+                    if 'workflow' in json_data['data']:
+                        del json_data['data']['workflow']
+                    data.append(json_data)
+
                 result={
-                    'data':get_my_workflow_for_app(filename,category,admin),
+                    'data':data,
                     'status':'success',
                 }
             elif data['task']=='list':
+                ds=get_workflows()
+                data=[]
+                for json_data in ds:
+                    # 不传给前端
+                    if 'output' in json_data['data']:
+                        del json_data['data']['output']
+                    if 'workflow' in json_data['data']:
+                        del json_data['data']['workflow']
+                    data.append(json_data)
+
                 result={
-                    'data':get_workflows(),
+                    'data':data,
                     'status':'success',
                 }
     except Exception as e:
@@ -624,142 +680,311 @@ async def get_checkpoints(request):
     except Exception as e:
         print('/mixlab/folder_paths',False,e)
 
+    # try:
+    #     if data['type']=='llamafile':
+    #         names=get_llama_models()
+    # except:
+    #     print("llamafile none")
+
     try:
-        if data['type']=='llamafile':
-            names=get_llama_models()
+        if data['type']=='rembg':
+            names=get_rembg_models(U2NET_HOME)
     except:
-        print("llamafile none")
+        print("rembg none")
     
     return web.json_response({"names":names,"types":list(folder_paths.folder_names_and_paths.keys())})
 
 
-@routes.post("/mixlab/prompt_result")
-async def post_prompt_result(request):
+@routes.post('/mixlab/rembg')
+async def rembg_hander(request):
     data = await request.json()
-    res=None
-    # print(data)
-    try:
-        action=data['action']
-        if action=='save':
-            result=data['data']
-            res=save_prompt_result(result['prompt_id'],result)
-        elif action=='all':
-            res=get_prompt_result()
-    except Exception as e:
-        print('/mixlab/prompt_result',False,e)
+    model=data['model']
+    result={}
+
+    data_base64=remove_base64_prefix(data['base64'])
+    image_data = base64.b64decode(data_base64)
     
-    return web.json_response({"result":res})
+    # 创建一个BytesIO对象
+    image_stream = io.BytesIO(image_data)
 
+    # 使用PIL Image模块读取图像
+    image = Image.open(image_stream)
 
-async def start_local_llm(data):
-    global llama_port,llama_model,llama_chat_format
-    if llama_port and llama_model and llama_chat_format:
-        return {"port":llama_port,"model":llama_model,"chat_format":llama_chat_format}
+    if model=='briarmbg':
+        _,rgba_images,_=run_briarmbg([image])
+    else:
+        _,rgba_images,_=run_rembg(model,[image])
 
-    import threading
-    import uvicorn
-    from llama_cpp.server.app import create_app
-    from llama_cpp.server.settings import (
-                Settings,
-                ServerSettings,
-                ModelSettings,
-                ConfigFileSettings,
-            )
+    with io.BytesIO() as buf:
+        rgba_images[0].save(buf, format='PNG')
+        img_bytes = buf.getvalue()
+    img_base64 = base64.b64encode(img_bytes).decode('utf-8')
     
-    if not "model" in data and "model_path" in data:
-        data['model']= os.path.basename(data["model_path"])
-        model=data["model_path"]
-
-    elif "model" in data:
-        model=get_llama_model_path(data['model'])
-
-    n_gpu_layers=-1
-
-    if "n_gpu_layers" in data:
-        n_gpu_layers=data['n_gpu_layers']
-
-
-    chat_format="chatml"
-
-    model_alias=os.path.basename(model)
-
-    # 多模态
-    clip_model_path=None
-    
-    prefix = "llava-phi-3-mini"
-    file_name = prefix+"-mmproj-"
-    if model_alias.startswith(prefix):
-        for file in os.listdir(os.path.dirname(model)):
-            if file.startswith(file_name):
-                clip_model_path=os.path.join(os.path.dirname(model),file)
-                chat_format='llava-1-5'
-    print('#clip_model_path',chat_format,clip_model_path)
-
-
-    address="127.0.0.1"
-    port=9090
-    success = False
-    for i in range(11):  # 尝试最多11次
-        if await check_port_available(address, port + i):
-            port = port + i
-            success = True
-            break
-
-    if success == False:
-        return {"port":None,"model":""}
-    
-    
-    server_settings=ServerSettings(host=address,port=port)
-
-    app = create_app(
-                server_settings=server_settings,
-                model_settings=[
-                    ModelSettings(
-                    model=model,
-                    model_alias=os.path.basename(model),
-                    n_gpu_layers=n_gpu_layers,
-                    n_ctx=4098,
-                    chat_format=chat_format,
-                    embedding=False,
-                    clip_model_path=clip_model_path
-                    )])
-
-    def run_uvicorn():
-        uvicorn.run(
-                app,
-                host=os.getenv("HOST", server_settings.host),
-                port=int(os.getenv("PORT", server_settings.port)),
-                ssl_keyfile=server_settings.ssl_keyfile,
-                ssl_certfile=server_settings.ssl_certfile,
-            )
-
-    # 创建一个子线程
-    thread = threading.Thread(target=run_uvicorn)
-
-    # 启动子线程
-    thread.start()
-
-    llama_port=port
-    llama_model=data['model']
-    llama_chat_format=chat_format
-
-    return  {"port":llama_port,"model":llama_model,"chat_format":llama_chat_format}
-
-# llam服务的开启
-@routes.post('/mixlab/start_llama')
-async def my_hander_method(request):
-    data =await request.json()
-    # print(data)
-    try:
-        result=await start_local_llm(data)
-    except:
+    try: 
         result={
-            {"port":None,"model":"","llama_cpp_error":True}
-        }
-        print('start_local_llm error')
+            'data':img_base64,
+            'model':model,
+            'status':'success',
+            }
+    except Exception as e:
+            print(e)
 
     return web.json_response(result)
 
+# 保存运行结果？暂时去掉
+# @routes.post("/mixlab/prompt_result")
+# async def post_prompt_result(request):
+#     data = await request.json()
+#     res=None
+#     # print(data)
+#     try:
+#         action=data['action']
+#         if action=='save':
+#             result=data['data']
+#             res=save_prompt_result(result['prompt_id'],result)
+#         elif action=='all':
+#             res=get_prompt_result()
+#     except Exception as e:
+#         print('/mixlab/prompt_result',False,e)
+    
+#     return web.json_response({"result":res})
+
+# 种子设置
+def random_seed(seed, data):
+    max_seed = 4294967295
+
+    for id, value in data.items():
+        # print(seed,id)
+        if id in seed:
+            if 'seed' in value['inputs'] and not isinstance(value['inputs']['seed'], list) and seed[id] in ['increment', 'decrement', 'randomize']:
+                value['inputs']['seed'] = round(random.random() * max_seed)
+            
+            if 'noise_seed' in value['inputs'] and not isinstance(value['inputs']['noise_seed'], list) and seed[id] in ['increment', 'decrement', 'randomize']:
+                value['inputs']['noise_seed'] = round(random.random() * max_seed)
+            
+            if value.get('class_type') == "Seed_" and seed[id] in ['increment', 'decrement', 'randomize']:
+                value['inputs']['seed'] = round(random.random() * max_seed)
+            
+        print('new Seed', value)
+    
+    return data
+
+
+# 运行工作流，代替官方的prompt接口
+@routes.post("/mixlab/prompt")
+async def mixlab_post_prompt(request):
+    p_intance=PromptServer.instance
+    logging.info("got prompt")
+    resp_code = 200
+    out_string = ""
+    json_data =  await request.json()
+    # json_data = p_intance.trigger_on_prompt(json_data)
+    # filename,category, client_id ,input
+    # workflow 的 filename,category
+
+    # 输入的参数
+    input_data=json_data['input'] if "input" in json_data else []
+    # 种子
+    seed=json_data['seed'] if "seed" in json_data else {}
+
+    apps=get_my_workflow_for_app(json_data['filename'],json_data['category'],False)
+    
+    prompt=json_data['prompt'] if 'prompt' in json_data else None
+
+    if len(apps)==1:
+        # 取到prompt
+        prompt=apps[0]['data']['output']
+        # 更新input_data到prompt里
+        '''
+          {
+                "inputs": {
+                    "number": 512,
+                    "min_value": 512,
+                    "max_value": 2048,
+                    "step": 1
+                },
+                "class_type": "IntNumber",
+                "id": "22"
+            },
+        '''
+
+        for inp in input_data:
+            id=inp['id']
+            if prompt[id]['class_type']==inp['class_type']:
+                prompt[id]['inputs'].update(inp['inputs']) 
+
+
+    if prompt==None:
+        return web.json_response({"error": "no prompt", "node_errors": []}, status=400)
+    else:
+        # 种子更新 
+        '''
+            "seed": {
+                    "45": "randomize",
+                    "46": "randomize"
+                }
+            '''
+        json_data["prompt"]=random_seed(seed,prompt)
+
+    # print("#json_data",prompt)
+    # 需要把apps处理成 prompt
+    # 注意seed的处理
+    
+    if "number" in json_data:
+        number = float(json_data['number'])
+    else:
+        number = p_intance.number
+        if "front" in json_data:
+            if json_data['front']:
+                number = -number
+
+        p_intance.number += 1
+
+    if "prompt" in json_data:
+        prompt = json_data["prompt"]
+        valid = execution.validate_prompt(prompt)
+        extra_data = {}
+        if "extra_data" in json_data:
+            extra_data = json_data["extra_data"]
+
+        if "client_id" in json_data:
+            extra_data["client_id"] = json_data["client_id"]
+        if valid[0]:
+            prompt_id = str(uuid.uuid4())
+            outputs_to_execute = valid[2]
+            p_intance.prompt_queue.put((number, prompt_id, prompt, extra_data, outputs_to_execute))
+            response = {"prompt_id": prompt_id, "number": number, "node_errors": valid[3]}
+            return web.json_response(response)
+        else:
+            logging.warning("invalid prompt: {}".format(valid[1]))
+            return web.json_response({"error": valid[1], "node_errors": valid[3]}, status=400)
+    else:
+        return web.json_response({"error": "no prompt", "node_errors": []}, status=400)
+
+
+# AR页面
+# @routes.get('/mixlab/AR')
+async def handle_ar_page(request):
+    html_file = os.path.join(current_path, "web/ar.html")
+    if os.path.exists(html_file):
+        with open(html_file, 'r', encoding='utf-8', errors='ignore') as f:
+            html_data = f.read()
+            return web.Response(text=html_data, content_type='text/html')
+    else:
+        return web.Response(text="HTML file not found", status=404)
+
+
+# async def start_local_llm(data):
+#     global llama_port,llama_model,llama_chat_format
+#     if llama_port and llama_model and llama_chat_format:
+#         return {"port":llama_port,"model":llama_model,"chat_format":llama_chat_format}
+
+#     import threading
+#     import uvicorn
+#     from llama_cpp.server.app import create_app
+#     from llama_cpp.server.settings import (
+#                 Settings,
+#                 ServerSettings,
+#                 ModelSettings,
+#                 ConfigFileSettings,
+#             )
+    
+#     if not "model" in data and "model_path" in data:
+#         data['model']= os.path.basename(data["model_path"])
+#         model=data["model_path"]
+
+#     elif "model" in data:
+#         model=get_llama_model_path(data['model'])
+
+#     n_gpu_layers=-1
+
+#     if "n_gpu_layers" in data:
+#         n_gpu_layers=data['n_gpu_layers']
+
+
+#     chat_format="chatml"
+
+#     model_alias=os.path.basename(model)
+
+#     # 多模态
+#     clip_model_path=None
+    
+#     prefix = "llava-phi-3-mini"
+#     file_name = prefix+"-mmproj-"
+#     if model_alias.startswith(prefix):
+#         for file in os.listdir(os.path.dirname(model)):
+#             if file.startswith(file_name):
+#                 clip_model_path=os.path.join(os.path.dirname(model),file)
+#                 chat_format='llava-1-5'
+#     # print('#clip_model_path',chat_format,clip_model_path,model)
+
+#     address="127.0.0.1"
+#     port=9090
+#     success = False
+#     for i in range(11):  # 尝试最多11次
+#         if await check_port_available(address, port + i):
+#             port = port + i
+#             success = True
+#             break
+
+#     if success == False:
+#         return {"port":None,"model":""}
+    
+    
+#     server_settings=ServerSettings(host=address,port=port)
+
+#     name, ext = os.path.splitext(os.path.basename(model))
+#     if name:
+#         # print('#model',name)
+#         app = create_app(
+#                     server_settings=server_settings,
+#                     model_settings=[
+#                         ModelSettings(
+#                         model=model,
+#                         model_alias=name,
+#                         n_gpu_layers=n_gpu_layers,
+#                         n_ctx=4098,
+#                         chat_format=chat_format,
+#                         embedding=False,
+#                         clip_model_path=clip_model_path
+#                         )])
+
+#         def run_uvicorn():
+#             uvicorn.run(
+#                     app,
+#                     host=os.getenv("HOST", server_settings.host),
+#                     port=int(os.getenv("PORT", server_settings.port)),
+#                     ssl_keyfile=server_settings.ssl_keyfile,
+#                     ssl_certfile=server_settings.ssl_certfile,
+#                 )
+
+#         # 创建一个子线程
+#         thread = threading.Thread(target=run_uvicorn)
+
+#         # 启动子线程
+#         thread.start()
+
+#         llama_port=port
+#         llama_model=data['model']
+#         llama_chat_format=chat_format
+
+#     return  {"port":llama_port,"model":llama_model,"chat_format":llama_chat_format}
+
+# llam服务的开启
+# @routes.post('/mixlab/start_llama')
+# async def my_hander_method(request):
+#     data =await request.json()
+#     # print(data)
+#     if llama_port and llama_model and llama_chat_format:
+#         return web.json_response({"port":llama_port,"model":llama_model,"chat_format":llama_chat_format} )
+#     try:
+#         result=await start_local_llm(data)
+#     except:
+#         result= {"port":None,"model":"","llama_cpp_error":True}
+#         print('start_local_llm error')
+
+#     return web.json_response(result)
+
 # 重启服务
 @routes.post('/mixlab/re_start')
 def re_start(request):
@@ -769,24 +994,23 @@ def re_start(request):
         pass
     return os.execv(sys.executable, [sys.executable] + sys.argv)
 
-
+# 状态
+@routes.get('/mixlab/status')
+def mix_status(request):
+    return web.Response(text="running#"+_URL_)
 
 # 导入节点
 from .nodes.PromptNode import GLIGENTextBoxApply_Advanced,EmbeddingPrompt,RandomPrompt,PromptSlide,PromptSimplification,PromptImage,JoinWithDelimiter
-from .nodes.ImageNode import ComparingTwoFrames,LoadImages_,CompositeImages,GridDisplayAndSave,GridInput,ImagesPrompt,SaveImageAndMetadata,SaveImageToLocal,SplitImage,GridOutput,GetImageSize_,MirroredImage,ImageColorTransfer,NoiseImage,TransparentImage,GradientImage,LoadImagesFromPath,LoadImagesFromURL,ResizeImage,TextImage,SvgImage,Image3D,ShowLayer,NewLayer,MergeLayers,CenterImage,AreaToMask,SmoothMask,SplitLongMask,ImageCropByAlpha,EnhanceImage,FaceToMask
+from .nodes.ImageNode import ImageBatchToList_,ImageListToBatch_,ComparingTwoFrames,LoadImages_,CompositeImages,GridDisplayAndSave,GridInput,ImagesPrompt,SaveImageAndMetadata,SaveImageToLocal,SplitImage,GridOutput,GetImageSize_,MirroredImage,ImageColorTransfer,NoiseImage,TransparentImage,GradientImage,LoadImagesFromPath,LoadImagesFromURL,ResizeImage,TextImage,SvgImage,Image3D,ShowLayer,NewLayer,MergeLayers,CenterImage,AreaToMask,SmoothMask,SplitLongMask,ImageCropByAlpha,EnhanceImage,FaceToMask
 # from .nodes.Vae import VAELoader,VAEDecode
 from .nodes.ScreenShareNode import ScreenShareNode,FloatingVideo
 
-from .nodes.ChatGPT import ChatGPTNode,ShowTextForGPT,CharacterInText,TextSplitByDelimiter
-from .nodes.Audio import GamePal,SpeechRecognition,SpeechSynthesis
-from .nodes.Utils import IncrementingListNode,ListSplit,CreateLoraNames,CreateSampler_names,CreateCkptNames,CreateSeedNode,TESTNODE_,TESTNODE_TOKEN,AppInfo,IntNumber,FloatSlider,TextInput,ColorInput,FontInput,TextToNumber,DynamicDelayProcessor,LimitNumber,SwitchByIndex,MultiplicationNode
+from .nodes.Audio import AudioPlayNode,SpeechRecognition,SpeechSynthesis
+from .nodes.Utils import KeyInput,IncrementingListNode,ListSplit,CreateLoraNames,CreateSampler_names,CreateCkptNames,CreateSeedNode,TESTNODE_,TESTNODE_TOKEN,AppInfo,IntNumber,FloatSlider,TextInput,ColorInput,FontInput,TextToNumber,DynamicDelayProcessor,LimitNumber,SwitchByIndex,MultiplicationNode
 from .nodes.Mask import PreviewMask_,MaskListReplace,MaskListMerge,OutlineMask,FeatheredMask
 
 from .nodes.Style import ApplyVisualStylePrompting,StyleAlignedReferenceSampler,StyleAlignedBatchAlign,StyleAlignedSampleReferenceLatents
 
-from .nodes.Video import VideoCombine_Adv,LoadVideoAndSegment,ImageListReplace,VAEEncodeForInpaint_Frames
-
-from .nodes.TripoSR import LoadTripoSRModel,TripoSRSampler,SaveTripoSRMesh
 
 
 # 要导出的所有节点及其名称的字典
@@ -817,6 +1041,8 @@ NODE_CLASS_MAPPINGS = {
     "ImageColorTransfer":ImageColorTransfer,
     "ShowLayer":ShowLayer,
     "NewLayer":NewLayer,
+    "ImageListToBatch_":ImageListToBatch_,
+    "ImageBatchToList_":ImageBatchToList_,
     "CompositeImages_":CompositeImages,
     "SplitImage":SplitImage,
     "CenterImage":CenterImage,
@@ -838,12 +1064,10 @@ NODE_CLASS_MAPPINGS = {
     # "VAEDecodeConsistencyDecoder":VAEDecode,
     "ScreenShare":ScreenShareNode,
     "FloatingVideo":FloatingVideo,
-    "ChatGPTOpenAI":ChatGPTNode,
-    "ShowTextForGPT":ShowTextForGPT,
-    "CharacterInText":CharacterInText,
-    "TextSplitByDelimiter":TextSplitByDelimiter,
+   
     "SpeechRecognition":SpeechRecognition,
     "SpeechSynthesis":SpeechSynthesis,
+    "KeyInput":KeyInput,
     "Color":ColorInput,
     "FloatSlider":FloatSlider,
     "IntNumber":IntNumber,
@@ -865,24 +1089,21 @@ NODE_CLASS_MAPPINGS = {
     "ApplyVisualStylePrompting_":ApplyVisualStylePrompting,
     "StyleAlignedReferenceSampler_": StyleAlignedReferenceSampler,
     "StyleAlignedSampleReferenceLatents_": StyleAlignedSampleReferenceLatents,
-    "StyleAlignedBatchAlign_": StyleAlignedBatchAlign,
-    "LoadVideoAndSegment_":LoadVideoAndSegment,
-    "VideoCombine_Adv":VideoCombine_Adv,
+    "StyleAlignedBatchAlign_": StyleAlignedBatchAlign, 
     "ListSplit_":ListSplit,
-    "MaskListReplace_":MaskListReplace,
-    "ImageListReplace_":ImageListReplace,
-    "VAEEncodeForInpaint_Frames":VAEEncodeForInpaint_Frames,
+    "MaskListReplace_":MaskListReplace, 
     "IncrementingListNode_":IncrementingListNode,
     "PreviewMask_":PreviewMask_,
-     "LoadTripoSRModel_": LoadTripoSRModel,
-    "TripoSRSampler_": TripoSRSampler,
-    "SaveTripoSRMesh": SaveTripoSRMesh
-    # "GamePal":GamePal
+    "AudioPlay":AudioPlayNode
 }
 
 # 一个包含节点友好/可读的标题的字典
 NODE_DISPLAY_NAME_MAPPINGS = {
     "AppInfo":"App Info ♾️MixlabApp",
+    "ScreenShare":"Screen Share ♾️Mixlab",
+    "FloatingVideo":"Floating Video ♾️Mixlab",
+    "TextImage":"Text Image ♾️Mixlab",
+    
     "Color":"Color Input ♾️MixlabApp",
     "TextInput_":"Text Input ♾️MixlabApp",
     "FloatSlider":"Float Slider Input ♾️MixlabApp",
@@ -896,14 +1117,14 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "SplitLongMask":"Splitting a long image into sections",
     "VAELoaderConsistencyDecoder":"Consistency Decoder Loader",
     "VAEDecodeConsistencyDecoder":"Consistency Decoder Decode",
-    "ScreenShare":"Screen Share ♾️Mixlab",
-    "FloatingVideo":"FloatingVideo ♾️Mixlab",
-    "ChatGPTOpenAI":"ChatGPT & Local LLM ♾️Mixlab",
-    "ShowTextForGPT":"Show Text ♾️MixlabApp",
+    
+    
     "MergeLayers":"Merge Layers ♾️Mixlab",
     "SpeechSynthesis":"SpeechSynthesis ♾️Mixlab",
     "SpeechRecognition":"SpeechRecognition ♾️Mixlab",
     "3DImage":"3DImage ♾️Mixlab",
+    "ImageListToBatch_":"Image List To Batch",
+    "ImageBatchToList_":"Image Batch To List",
     "CompositeImages_":"Composite Images ♾️Mixlab",
     "DynamicDelayProcessor":"DynamicDelayByText ♾️Mixlab",
     "LaMaInpainting":"LaMaInpainting ♾️Mixlab",
@@ -929,23 +1150,58 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "GridInput":"Grid Input ♾️Mixlab",
     "GridOutput":"Grid Output ♾️Mixlab",
     "GetImageSize_":"Get Image Size ♾️Mixlab",
-    "VAEEncodeForInpaint_Frames":"VAE Encode For Inpaint Frames ♾️Mixlab",
     "IncrementingListNode_":"Create Incrementing Number List ♾️Mixlab",
     "LoadImagesToBatch":"Load Images(base64) ♾️Mixlab",
     "PreviewMask_":"Preview Mask",
-    "LoadTripoSRModel_": "Load TripoSR Model",
-    "TripoSRSampler_": "TripoSR Sampler",
-    "SaveTripoSRMesh": "Save TripoSR Mesh"
+    "AudioPlay":"Preview Audio ♾️Mixlab",
+
+     "MultiplicationNode":"Math Operation ♾️Mixlab",
 }
 
 # web ui的节点功能
 WEB_DIRECTORY = "./web"
 
-
 logging.info('--------------')
 logging.info('\033[91m ### Mixlab Nodes: \033[93mLoaded')
 # print('\033[91m ### Mixlab Nodes: \033[93mLoaded')
 
+try:
+    from .nodes.ChatGPT import ChatGPTNode,ShowTextForGPT,CharacterInText,TextSplitByDelimiter,SiliconflowFreeNode
+    logging.info('ChatGPT.available True')
+
+    NODE_CLASS_MAPPINGS_V = { 
+       "ChatGPTOpenAI":ChatGPTNode,
+       "SiliconflowLLM":SiliconflowFreeNode,
+        "ShowTextForGPT":ShowTextForGPT,
+        "CharacterInText":CharacterInText,
+        "TextSplitByDelimiter":TextSplitByDelimiter,
+    }
+
+    # 一个包含节点友好/可读的标题的字典
+    NODE_DISPLAY_NAME_MAPPINGS_V = { 
+        "ChatGPTOpenAI":"ChatGPT & Local LLM ♾️Mixlab",
+        "SiliconflowLLM":"LLM Siliconflow ♾️Mixlab",
+        "ShowTextForGPT":"Show Text ♾️MixlabApp",
+        "CharacterInText":"Character In Text",
+        "TextSplitByDelimiter":"Text Split By Delimiter",
+    }
+
+
+    NODE_CLASS_MAPPINGS.update(NODE_CLASS_MAPPINGS_V)
+    NODE_DISPLAY_NAME_MAPPINGS.update(NODE_DISPLAY_NAME_MAPPINGS_V)
+
+except Exception as e:
+    logging.info('ChatGPT.available False')
+
+
+try:
+    from .nodes.edit_mask import EditMask
+    logging.info('edit_mask.available True')
+    NODE_CLASS_MAPPINGS['EditMask']=EditMask
+    NODE_DISPLAY_NAME_MAPPINGS['EditMask']="Edit Mask ♾️Mixlab"
+except Exception as e:
+    logging.info('edit_mask.available False')
+
 try:
     from .nodes.Lama import LaMaInpainting
     logging.info('LaMaInpainting.available {}'.format(LaMaInpainting.available))
@@ -981,4 +1237,57 @@ try:
 except Exception as e:
     logging.info('RembgNode_.available False' )
 
+
+try:
+    from .nodes.Video import GenerateFramesByCount,scenesNode_,CombineAudioVideo,VideoCombine_Adv,LoadVideoAndSegment,ImageListReplace,VAEEncodeForInpaint_Frames,LoadAndCombinedAudio_
+    
+    NODE_CLASS_MAPPINGS_V = {
+        "VAEEncodeForInpaint_Frames":VAEEncodeForInpaint_Frames,
+        "ImageListReplace_":ImageListReplace,
+        "LoadVideoAndSegment_":LoadVideoAndSegment,
+        "VideoCombine_Adv":VideoCombine_Adv,
+        "LoadAndCombinedAudio_":LoadAndCombinedAudio_,
+        "CombineAudioVideo":CombineAudioVideo,
+        "ScenesNode_":scenesNode_,
+        "GenerateFramesByCount":GenerateFramesByCount 
+    }
+
+    # 一个包含节点友好/可读的标题的字典
+    NODE_DISPLAY_NAME_MAPPINGS_V = {
+        "VAEEncodeForInpaint_Frames":"VAE Encode For Inpaint Frames ♾️Mixlab",
+        "ImageListReplace_":"Image List Replace",
+        "LoadVideoAndSegment_":"Load Video And Segment",
+        "VideoCombine_Adv":"Video Combine",
+        "LoadAndCombinedAudio_":"Load And Combined Audio",
+        "CombineAudioVideo":"Combine Audio Video",
+        "ScenesNode_":"Select Scene", 
+        "GenerateFramesByCount":"Generate Frames By Count"
+    }
+
+
+    NODE_CLASS_MAPPINGS.update(NODE_CLASS_MAPPINGS_V)
+    NODE_DISPLAY_NAME_MAPPINGS.update(NODE_DISPLAY_NAME_MAPPINGS_V)
+
+except:
+    logging.info('Video.available False')
+
+
+try:
+    from .nodes.TripoSR import LoadTripoSRModel,TripoSRSampler,SaveTripoSRMesh
+    logging.info('TripoSR.available')
+    # logging.info( folder_paths.get_temp_directory())
+    NODE_CLASS_MAPPINGS['LoadTripoSRModel_']=LoadTripoSRModel
+    NODE_DISPLAY_NAME_MAPPINGS["LoadTripoSRModel_"]= "Load TripoSR Model"
+    
+    NODE_CLASS_MAPPINGS['TripoSRSampler_']=TripoSRSampler
+    NODE_DISPLAY_NAME_MAPPINGS["TripoSRSampler_"]= "TripoSR Sampler"
+
+    NODE_CLASS_MAPPINGS['SaveTripoSRMesh']=SaveTripoSRMesh
+    NODE_DISPLAY_NAME_MAPPINGS["SaveTripoSRMesh"]= "Save TripoSR Mesh"
+    
+
+except Exception as e:
+    logging.info('TripoSR.available False' )
+
+
 logging.info('\033[93m -------------- \033[0m')

install.bat

@@ -11,9 +11,9 @@ if exist "%python_exec%" (
         %python_exec% -s -m pip install "%%i" -i https://pypi.tuna.tsinghua.edu.cn/simple
     )
 
-    %python_exec% -s -m pip install --upgrade --force llama-cpp-python --extra-index-url https://abetlen.github.io/llama-cpp-python/whl/cu121
+    @REM %python_exec% -s -m pip install --upgrade --force llama-cpp-python --extra-index-url https://abetlen.github.io/llama-cpp-python/whl/cu121
 
-    %python_exec% -s -m pip install --upgrade --force llama-cpp-python[server]
+    @REM %python_exec% -s -m pip install --upgrade --force llama-cpp-python[server]
     
 
 ) else (

nodes/Audio.py

@@ -1,6 +1,7 @@
 
-
-
+import os
+import folder_paths
+import torchaudio
 
 class SpeechRecognition:
     @classmethod
@@ -55,46 +56,65 @@ class SpeechSynthesis:
         return {"ui": {"text": text}, "result": (text,)}
     
 
-#
-class GamePal:
+
+class AudioPlayNode:
+    def __init__(self):
+        self.output_dir = folder_paths.get_temp_directory()
+        self.type = "temp"
+        self.prefix_append = ""
+        self.compress_level = 4
     @classmethod
     def INPUT_TYPES(s):
-        return {
-            "required": {
-                "input_text": ("STRING",{"multiline": True,"default": ""}),
-            },
-            "optional": {
-                 
-                "input_num": ("INT",{
-                                "default":100, 
-                                "min": -1, #Minimum value
-                                "max": 0xffffffffffffffff, #Maximum value
-                                "step": 1, #Slider's step
-                                "display": "slider" # Cosmetic only: display as "number" or "slider"
-                                }), 
-                "python_code": ("STRING",{"multiline": True,"default": "result= 1 if 'Mixlab' in input_text else 0"}),
-            }
-        }
-
-    INPUT_IS_LIST = False
-    RETURN_TYPES = ("INT",)
+        return {"required": {
+            "audio": ("AUDIO",),
+              }, 
+                }
+    
+    RETURN_TYPES = ()
+  
     FUNCTION = "run"
-    OUTPUT_NODE = True
-    OUTPUT_IS_LIST = (False,)
 
     CATEGORY = "♾️Mixlab/Audio"
 
-    def run(self, input_text,input_num,python_code):
-        exec(python_code)
-        res=None
-        try:
-            # 可能会引发异常的代码
-            res=result
-        except:
-            # 处理异常的代码
-            print('')
+    INPUT_IS_LIST = False
+    OUTPUT_IS_LIST = ()
 
-        print(res)
+    OUTPUT_NODE = True
+  
+    def run(self,audio):
 
-        # print(session_history)
-        return {"ui": {"text": [input_text],"num":[input_num]}, "result": (res,)}
+        # 判断是否是 Tensor 类型
+        is_tensor = not isinstance(audio, dict)
+        # print('#判断是否是 Tensor 类型',is_tensor,audio)
+        if not is_tensor and 'waveform' in audio and 'sample_rate' in audio:
+            # {'waveform': tensor([], size=(1, 1, 0)), 'sample_rate': 44100}
+            is_tensor=True
+
+        if is_tensor and (not 'audio_path' in audio):
+            filename_prefix=""
+            # 保存
+            filename_prefix += self.prefix_append
+            full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(filename_prefix, self.output_dir)
+            results = list()
+            
+            filename_with_batch_num = filename.replace("%batch_num%", str(1))
+            file = f"{filename_with_batch_num}_{counter:05}_.wav"
+            
+            torchaudio.save(os.path.join(full_output_folder, file), audio['waveform'].squeeze(0), audio["sample_rate"])
+            results.append({
+                    "filename": file,
+                    "subfolder": subfolder,
+                    "type": self.type
+                })
+            
+        else:
+            results=[{
+                    "filename": audio['filename'],
+                    "subfolder":audio['subfolder'],
+                    "type": audio['type'],
+                    "audio_path":audio['audio_path']
+                }]
+                
+
+        # print(audio)
+        return {"ui": {"audio":results}}

nodes/ChatGPT.py

@@ -53,8 +53,8 @@ def azure_client(key,url):
 
 def openai_client(key,url):
     client = openai.OpenAI(
-    api_key=key,
-    base_url=url
+        api_key=key,
+        base_url=url
     )
     return client
 
@@ -97,73 +97,74 @@ def get_llama_path():
     except:
         return os.path.join(folder_paths.models_dir, "llamafile")
 
-def get_llama_models():
-    res=[]
+# def get_llama_models():
+#     res=[]
 
-    model_path=get_llama_path()
-    if os.path.exists(model_path):
-        files = os.listdir(model_path)
-        for file in files:
-            if os.path.isfile(os.path.join(model_path, file)):
-                res.append(file)
-        res=phi_sort(res)
-    return res
+#     model_path=get_llama_path()
+#     if os.path.exists(model_path):
+#         files = os.listdir(model_path)
+#         for file in files:
+#             if os.path.isfile(os.path.join(model_path, file)):
+#                 res.append(file)
+#         res=phi_sort(res)
+#     return res
 
-llama_modes_list=get_llama_models()
+# llama_modes_list=get_llama_models()
+# llama_modes_list=[]
 
-def get_llama_model_path(file_name):
-    model_path=get_llama_path()
-    mp=os.path.join(model_path,file_name)
-    return mp
+# def get_llama_model_path(file_name):
+#     model_path=get_llama_path()
+#     mp=os.path.join(model_path,file_name)
+#     return mp
 
-def llama_cpp_client(file_name):
-    try:
-        if is_installed('llama_cpp')==False:
-            import subprocess
+# def llama_cpp_client(file_name):
+#     try:
+#         if is_installed('llama_cpp')==False:
+#             import subprocess
 
-            # 安装
-            print('#pip install llama-cpp-python')
+#             # 安装
+#             print('#pip install llama-cpp-python')
  
-            result = subprocess.run([sys.executable, '-s', '-m', 'pip', 
-                                     'install', 
-                                     'llama-cpp-python',
-                                     '--extra-index-url',
-                                     'https://abetlen.github.io/llama-cpp-python/whl/cu121'
-                                     ], capture_output=True, text=True)
+#             result = subprocess.run([sys.executable, '-s', '-m', 'pip', 
+#                                      'install', 
+#                                      'llama-cpp-python',
+#                                      '--extra-index-url',
+#                                      'https://abetlen.github.io/llama-cpp-python/whl/cu121'
+#                                      ], capture_output=True, text=True)
 
-            #检查命令执行结果
-            if result.returncode == 0:
-                print("#install success")
-                from llama_cpp import Llama
+#             #检查命令执行结果
+#             if result.returncode == 0:
+#                 print("#install success")
+#                 from llama_cpp import Llama
 
-                subprocess.run([sys.executable, '-s', '-m', 'pip', 
-                                     'install', 
-                                     'llama-cpp-python[server]'
-                                     ], capture_output=True, text=True)
+#                 subprocess.run([sys.executable, '-s', '-m', 'pip', 
+#                                      'install', 
+#                                      'llama-cpp-python[server]'
+#                                      ], capture_output=True, text=True)
 
-            else:
-                print("#install error")
+#             else:
+#                 print("#install error")
             
-        else:
-            from llama_cpp import Llama
-    except:
-        print("#install llama-cpp-python error")
+#         else:
+#             from llama_cpp import Llama
+#     except:
+#         print("#install llama-cpp-python error")
 
-    if file_name:
-        mp=get_llama_model_path(file_name)
-        # file_name=get_llama_models()[0]
-        # model_path=os.path.join(folder_paths.models_dir, "llamafile")
-        # mp=os.path.join(model_path,file_name)
+#     if file_name:
+#         mp=get_llama_model_path(file_name)
+#         # file_name=get_llama_models()[0]
+#         # model_path=os.path.join(folder_paths.models_dir, "llamafile")
+#         # mp=os.path.join(model_path,file_name)
 
-        llm = Llama(model_path=mp, chat_format="chatml",n_gpu_layers=-1,n_ctx=512)
+#         llm = Llama(model_path=mp, chat_format="chatml",n_gpu_layers=-1,n_ctx=512)
 
-        return llm
+#         return llm
 
     
 
 
 def chat(client, model_name,messages ):
-
+        print('#chat',model_name,messages)
         try_count = 0
         while True:
             try_count += 1
@@ -215,15 +216,32 @@ class ChatGPTNode:
 
     @classmethod
     def INPUT_TYPES(cls):
-        model_list=llama_modes_list+[
+        model_list=[ 
                     "gpt-3.5-turbo",
-                    "gpt-3.5-turbo-0125",
-                    "gpt-35-turbo",
-                    "gpt-3.5-turbo-16k", 
-                    "gpt-3.5-turbo-16k-0613", 
-                    "gpt-4-0613",
-                    "gpt-4-1106-preview",
-                    "glm-4"
+            "gpt-3.5-turbo-16k",
+            "gpt-4o",
+            "gpt-4o-2024-05-13",
+            "gpt-4",
+            "gpt-4-0314",
+            "gpt-4-0613",
+            "gpt-3.5-turbo-0301",
+            "gpt-3.5-turbo-0613",
+            "gpt-3.5-turbo-16k-0613",
+            "qwen-turbo",
+            "qwen-plus",
+            "qwen-long",
+            "qwen-max",
+            "qwen-max-longcontext",
+            "glm-4",
+            "glm-3-turbo",
+            "moonshot-v1-8k",
+            "moonshot-v1-32k",
+            "moonshot-v1-128k",
+            "deepseek-chat",
+            "Qwen/Qwen2-7B-Instruct",
+            "THUDM/glm-4-9b-chat",
+            "01-ai/Yi-1.5-9B-Chat-16K",
+            "meta-llama/Meta-Llama-3.1-8B-Instruct"
                     ]
         return {
             "required": {
@@ -282,12 +300,12 @@ class ChatGPTNode:
             if model == "glm-4" :
                 client = ZhipuAI_client(api_key)  # 使用 Zhipuai 的接口
                 print('using Zhipuai interface')
-            elif model in llama_modes_list:
-                #
-                client=llama_cpp_client(model)
+            # elif model in llama_modes_list:
+            #     #
+            #     client=llama_cpp_client(model)
             else :
                 client = openai_client(api_key,api_url)  # 使用 ChatGPT  的接口
-                print('using ChatGPT interface')
+                # print('using ChatGPT interface',api_key,api_url)
 
         # 把用户的提示添加到会话历史中
         # 调用API时传递整个会话历史
@@ -303,6 +321,7 @@ class ChatGPTNode:
         session_history=crop_list_tail(self.session_history,context_size)
 
         messages=[{"role": "system", "content": self.system_content}]+session_history+[{"role": "user", "content": prompt}]
+
         response_content = chat(client,model,messages)
         
         self.session_history=self.session_history+[{"role": "user", "content": prompt}]+[{'role':'assistant',"content":response_content}]
@@ -323,6 +342,91 @@ class ChatGPTNode:
         return (response_content,json.dumps(messages, indent=4),json.dumps(self.session_history, indent=4),)
 
 
+class SiliconflowFreeNode:
+    def __init__(self):
+        # self.__client = OpenAI()
+        self.session_history = []  # 用于存储会话历史的列表
+        # self.seed=0
+        self.system_content="You are ChatGPT, a large language model trained by OpenAI. Answer as concisely as possible."
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        model_list= [ 
+            "Qwen/Qwen2-7B-Instruct",
+            "THUDM/glm-4-9b-chat",
+            "01-ai/Yi-1.5-9B-Chat-16K",
+            "meta-llama/Meta-Llama-3.1-8B-Instruct"
+            ]
+        return {
+            "required": {
+                "api_key":("KEY", {"default": "", "multiline": True,"dynamicPrompts": False}),
+                "prompt": ("STRING", {"multiline": True,"dynamicPrompts": False}),
+                "system_content": ("STRING", 
+                                   {
+                                       "default": "You are ChatGPT, a large language model trained by OpenAI. Answer as concisely as possible.", 
+                                       "multiline": True,"dynamicPrompts": False
+                                       }),
+                "model": ( model_list, 
+                    {"default": model_list[0]}),
+                "seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff, "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",)
+    RETURN_NAMES = ("text","messages","session_history",)
+    FUNCTION = "generate_contextual_text"
+    CATEGORY = "♾️Mixlab/GPT"
+    INPUT_IS_LIST = False
+    OUTPUT_IS_LIST = (False,False,False,)
+
+    
+    def generate_contextual_text(self,
+                                 api_key,
+                                 prompt, 
+                                 system_content,
+                                model, 
+                                seed,context_size,unique_id = None, extra_pnginfo=None):
+    
+        api_url="https://api.siliconflow.cn/v1"
+        
+        # 把系统信息和初始信息添加到会话历史中
+        if system_content:
+            self.system_content=system_content
+            # self.session_history=[]
+            # self.session_history.append({"role": "system", "content": system_content})
+        
+        # 
+        client = openai_client(api_key,api_url)  # 使用 ChatGPT  的接口
+        # print('using ChatGPT interface',api_key,api_url)
+
+        # 把用户的提示添加到会话历史中
+        # 调用API时传递整个会话历史
+
+        def crop_list_tail(lst, size):
+            if size >= len(lst):
+                return lst
+            elif size==0:
+                return []
+            else:
+                return lst[-size:]
+            
+        session_history=crop_list_tail(self.session_history,context_size)
+
+        messages=[{"role": "system", "content": self.system_content}]+session_history+[{"role": "user", "content": prompt}]
+
+        response_content = chat(client,model,messages)
+        
+        self.session_history=self.session_history+[{"role": "user", "content": prompt}]+[{'role':'assistant',"content":response_content}]
+
+        return (response_content,json.dumps(messages, indent=4),json.dumps(self.session_history, indent=4),)
+
+
+
 
 class ShowTextForGPT:
     @classmethod

nodes/ClipInterrogator.py

@@ -79,7 +79,7 @@ def get_clip_interrogator_path():
 
 cache_path=get_clip_interrogator_path()
 
-caption_model_path=os.path.join(cache_path, "Salesforce/blip-image-captioning-base")
+caption_model_path=os.path.join(cache_path, "Salesforce","blip-image-captioning-base")
 if not os.path.exists(caption_model_path):
     print(f"## clip_interrogator_model not found: {caption_model_path}, pls download from https://huggingface.co/Salesforce/blip-image-captioning-base")
     caption_model_path='Salesforce/blip-image-captioning-base'

nodes/ImageNode.py

@@ -1,6 +1,7 @@
 import numpy as np
 import requests
 import torch
+import torchvision.transforms.v2 as T
 # from PIL import Image, ImageDraw
 from PIL import Image, ImageOps,ImageFilter,ImageEnhance,ImageDraw,ImageSequence, ImageFont
 from PIL.PngImagePlugin import PngInfo
@@ -14,8 +15,8 @@ import cv2
 import string
 import math,glob
 from .Watcher import FolderWatcher
-import hashlib
 
+from itertools import product
 
 
 # 将PIL图片转换为OpenCV格式
@@ -28,142 +29,105 @@ def opencv_to_pil(image):
     pil_image = Image.fromarray(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
     return pil_image
 
+# 列出目录下面的所有文件
+def get_files_with_extension(directory, extensions):
+    file_list = []
+    # 确保extensions参数是一个list，即使只有一个元素
+    if not isinstance(extensions, (tuple, list)):
+        extensions = [extensions]
+    for root, dirs, files in os.walk(directory):
+        # print(f"Files at {root}: {files}")  # 确认files是一个字符串列表
+        for file in files:
+            # 检查文件是否以任何一个提供的扩展名结尾
+            if any(file.endswith(ext) for ext in extensions):
+                # 直接将文件名添加到列表中
+                file_list.append(file)
+    return file_list
+	
+def composite_images(foreground, background, mask, is_multiply_blend=False, position="overall", scale=0.25):
+    width, height = foreground.size
+    bg_image = background
+    bwidth, bheight = bg_image.size
 
-def composite_images(foreground, background, mask,is_multiply_blend=False,position="overall"):
-    width,height=foreground.size
- 
-    bg_image=background
+    scale=max(scale,1/bwidth)
+    scale=max(scale,1/bheight)
 
-    bwidth,bheight=bg_image.size
+    def determine_scale_option(width, height):
+        return 'height' if height > width else 'width'
 
-    # 按z-index排序
-    if position=="overall":
+    if position == "overall":
         layer = {
-                "x":0,
-                "y":0,
-                "width":bwidth,
-                "height":bheight,
-                "z_index":88,
-                "scale_option":'overall',
-                "image":foreground,
-                "mask":mask
+            "x": 0,
+            "y": 0,
+            "width": bwidth,
+            "height": bheight,
+            "z_index": 88,
+            "scale_option": 'overall',
+            "image": foreground,
+            "mask": mask
         }
+    else:
+        scale_option = determine_scale_option(width, height)
+        if scale_option == 'height':
+            scale = int(bheight * scale) / height
+        else:
+            scale = int(bwidth * scale) / width
 
-    elif position=='center_bottom':
-        
-        scale = int(bwidth*0.25) / width
+        new_width = int(width * scale)
         new_height = int(height * scale)
 
-        layer = {
-                "x":int(bwidth*0.75*0.5),
-                "y":bheight-new_height-24,
-                "width":int(bwidth*0.25),
-                "height":int(bheight*0.25),
-                "z_index":88,
-                "scale_option":'width',
-                "image":foreground,
-                "mask":mask
-        }
-
-    elif position=='right_bottom':
-        
-        scale = int(bwidth*0.25) / width
-        new_height = int(height * scale)
+        if position == 'center_bottom':
+            x_position = int((bwidth - new_width) * 0.5)
+            y_position = bheight - new_height - 24
+        elif position == 'right_bottom':
+            x_position = bwidth - new_width - 24
+            y_position = bheight - new_height - 24
+        elif position == 'center_top':
+            x_position = int((bwidth - new_width) * 0.5)
+            y_position = 24
+        elif position == 'right_top':
+            x_position = bwidth - new_width - 24
+            y_position = 24
+        elif position == 'left_top':
+            x_position = 24
+            y_position = 24
+        elif position == 'left_bottom':
+            x_position = 24
+            y_position = bheight - new_height - 24
+        elif position == 'center_center':
+            x_position = int((bwidth - new_width) * 0.5)
+            y_position = int((bheight - new_height) * 0.5)
 
         layer = {
-                "x":bwidth-int(bwidth*0.25)-24,
-                "y":bheight-new_height-24,
-                "width":int(bwidth*0.25),
-                "height":int(bheight*0.25),
-                "z_index":88,
-                "scale_option":'width',
-                "image":foreground,
-                "mask":mask
+            "x": x_position,
+            "y": y_position,
+            "width": new_width,
+            "height": new_height,
+            "z_index": 88,
+            "scale_option": scale_option,
+            "image": foreground,
+            "mask": mask
         }
 
+    layer_image = layer['image']
+    layer_mask = layer['mask']
 
-    elif position=='center_top':
-        
-        scale = int(bwidth*0.25) / width
-        new_height = int(height * scale)
+    bg_image = merge_images(bg_image,
+                            layer_image,
+                            layer_mask,
+                            layer['x'],
+                            layer['y'],
+                            layer['width'],
+                            layer['height'],
+                            layer['scale_option'],
+                            is_multiply_blend)
 
-        layer = {
-                "x":int( bwidth*0.75*0.5),
-                "y":24,
-                "width":int(bwidth*0.25),
-                "height":int(bheight*0.25),
-                "z_index":88,
-                "scale_option":'width',
-                "image":foreground,
-                "mask":mask
-        }
+    bg_image = bg_image.convert('RGB')
 
-    elif position=='right_top':
-        
-        scale = int(bwidth*0.25) / width
-        new_height = int(height * scale)
-
-        layer = {
-                "x":bwidth-int(bwidth*0.25)-24,
-                "y":24,
-                "width":int(bwidth*0.25),
-                "height":int(bheight*0.25),
-                "z_index":88,
-                "scale_option":'width',
-                "image":foreground,
-                "mask":mask
-        }
-    elif position=='left_top':
-        
-        scale = int(bwidth*0.25) / width
-        new_height = int(height * scale)
-
-        layer = {
-                "x":24,
-                "y":24,
-                "width":int(bwidth*0.25),
-                "height":int(bheight*0.25),
-                "z_index":88,
-                "scale_option":'width',
-                "image":foreground,
-                "mask":mask
-        }
-    elif position=='left_bottom':
-        
-        scale = int(bwidth*0.25) / width
-        new_height = int(height * scale)
-
-        layer = {
-                "x":24,
-                "y":bheight-new_height-24,
-                "width":int(bwidth*0.25),
-                "height":int(bheight*0.25),
-                "z_index":88,
-                "scale_option":'width',
-                "image":foreground,
-                "mask":mask
-        }
-                
-    # width, height = bg_image.size
-
-    layer_image=layer['image']
-    layer_mask=layer['mask']
-    
-    bg_image=merge_images(bg_image,
-                        layer_image,
-                        layer_mask,
-                        layer['x'],
-                        layer['y'],
-                        layer['width'],
-                        layer['height'],
-                        layer['scale_option'],
-                        is_multiply_blend )
-                   
-    bg_image=bg_image.convert('RGB')
-    
     return bg_image
 
 
+
 def count_files_in_directory(directory):
     file_count = 0
     for _, _, files in os.walk(directory):
@@ -200,7 +164,8 @@ class AnyType(str):
 any_type = AnyType("*")
 
 
-FONT_PATH= os.path.abspath(os.path.join(os.path.dirname(__file__),'../assets/王汉宗颜楷体繁.ttf'))
+FONT_PATH= os.path.abspath(os.path.join(os.path.dirname(__file__),"..","assets","fonts"))
+
 
 MAX_RESOLUTION=8192
 
@@ -802,85 +767,78 @@ def multiply_blend(image1, image2):
 
 # cv2.imwrite('result.jpg', result)
 
+# 使用gpt4o优化代码
+# 为了消除图像合并时出现的灰色描边，可以使用以下方法：
+# 调整透明度：确保透明像素不会引入不需要的颜色。
+# 预处理图像：在缩放图像之前，可以先将图像的边缘进行预处理，例如扩展边缘颜色，减少抗锯齿带来的过渡效果。
 
-def merge_images(bg_image, layer_image, mask, x, y, width, height, scale_option,is_multiply_blend=False):
+def merge_images(bg_image, layer_image, mask, x, y, width, height, scale_option, is_multiply_blend=False):
     # 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))
+        layer_image = layer_image.resize((new_width, height), Image.NEAREST)
     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))
+        layer_image = layer_image.resize((width, new_height), Image.NEAREST)
     elif scale_option == "overall":
         # 整体缩放
-        layer_image = layer_image.resize((width, height))
-
+        layer_image = layer_image.resize((width, height), Image.NEAREST)
     elif scale_option == "longest":
         original_width, original_height = layer_image.size
         if original_width > original_height:
-            new_width=width
+            new_width = width
             scale = width / original_width
             new_height = int(original_height * scale)
-            x=0
-            y=int((height-new_height)*0.5)
+            x = 0
+            y = int((height - new_height) * 0.5)
         else:
-            new_height=height
+            new_height = height
             scale = height / original_height
             new_width = int(original_height * scale)
-            x=int((width-new_width)*0.5)
-            y=0
-    # elif side == "shortest":
-    #         if width < height:
-    #              
-    #         else:
-    #              
-    
+            x = int((width - new_width) * 0.5)
+            y = 0
 
     # 调整mask的大小
     nw, nh = layer_image.size
-    mask = mask.resize((nw, nh))
+    mask = mask.resize((nw, nh), Image.NEAREST)
 
-    # # 分离出a通道
-    # r, g, b, alpha = layer_image.split()
-    # alpha = ImageOps.invert(alpha)
-    # # 创建一个新的RGB图像
-    # new_rgb_image = Image.new("RGB", layer_image.size)
-    # # 将透明通道粘贴到新的RGB图像上
-    # new_rgb_image.paste(layer_image, (0, 0), mask=alpha)
-   
-    # new_rgb_image.paste(layer_image, (x, y), mask=mask)
-    # mask=new_rgb_image.convert('L')
-    # mask = ImageOps.invert(mask)
+    # 预处理图像边缘以减少灰色描边
+    layer_image = layer_image.filter(ImageFilter.SMOOTH)
 
     if is_multiply_blend:
-        bg_image_white=Image.new("RGB", bg_image.size,(255, 255, 255))
+        bg_image_white = Image.new("RGB", bg_image.size, (255, 255, 255))
 
         bg_image_white.paste(layer_image, (x, y), mask=mask)
-        bg_image=multiply_blend(bg_image_white,bg_image)
-        bg_image=bg_image.convert("RGBA")
+        bg_image = multiply_blend(bg_image_white, bg_image)
+        bg_image = bg_image.convert("RGBA")
     else:
-        transparent_img = Image.new("RGBA",layer_image.size, (255, 255, 255, 0))
-        transparent_img.paste(layer_image,(0, 0), mask)
-        # transparent_img.save('test.png')
-        bg_image.paste(transparent_img, (x, y), transparent_img)
+        transparent_img = Image.new("RGBA", layer_image.size, (255, 255, 255, 0))
+        # 调整透明度处理
+        for i in range(transparent_img.size[0]):
+            for j in range(transparent_img.size[1]):
+                r, g, b, a = transparent_img.getpixel((i, j))
+                if a > 0:
+                    transparent_img.putpixel((i, j), (r, g, b, 255))
 
+        transparent_img.paste(layer_image, (0, 0), mask)
+        bg_image.paste(transparent_img, (x, y), transparent_img)
 
     # 输出合成后的图片
     return bg_image
 
+#MixCopilot
 
 def resize_2(img):
     # 检查图像的高度是否是2的倍数，如果不是，则调整高度
@@ -954,53 +912,13 @@ def resize_image(layer_image, scale_option, width, height,color="white"):
     return layer_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 generate_text_image(text, font_path, font_size, text_color, vertical=True, stroke=False, stroke_color=(0, 0, 0), stroke_width=1, spacing=0):
+def generate_text_image(text, font_path, font_size, text_color, vertical=True, stroke=False, stroke_color=(0, 0, 0), stroke_width=1, spacing=0, line_spacing=0,padding=4):
     # Split text into lines based on line breaks
     lines = text.split("\n")
 
+    # Load font
+    font = ImageFont.truetype(font_path, font_size)
+
     # 1. Determine layout direction
     if vertical:
         layout = "vertical"
@@ -1009,49 +927,54 @@ def generate_text_image(text, font_path, font_size, text_color, vertical=True, s
 
     # 2. Calculate absolute coordinates for each character
     char_coordinates = []
-    if layout == "vertical":
-        x = 0
-        y = 0
-        for i in range(len(lines)):
-            line = lines[i]
-            for char in line:
-                char_coordinates.append((x, y))
-                y += font_size + spacing
-            x += font_size + spacing
-            y = 0
-    else:
-        x = 0
-        y = 0
-        for line in lines:
-            for char in line:
-                char_coordinates.append((x, y))
-                x += font_size + spacing
-            y += font_size + spacing
-            x = 0
+    x, y = padding, padding
+    max_width, max_height = 0, 0
 
-    # 3. Calculate image width and height
     if layout == "vertical":
-        width = (len(lines) * (font_size + spacing)) - spacing
-        height = ((len(max(lines, key=len)) + 1) * (font_size + spacing)) + spacing
+        for line in lines:
+            max_char_width = max(font.getsize(char)[0] for char in line)
+            for char in line:
+                char_width, char_height = font.getsize(char)
+                char_coordinates.append((x, y))
+                y += char_height + spacing
+                max_height = max(max_height, y + padding)
+            x += max_char_width + line_spacing
+            y = padding
+        max_width = x
+        total_line_width = sum(font.getsize(line)[1] for line in lines)
+        total_spacing = line_spacing * (len(lines) - 1)
+        # 确保左边和右边的padding都被计入max_width
+        max_width = total_line_width + total_spacing + padding * 2
     else:
-        width = (len(max(lines, key=len)) * (font_size + spacing)) - spacing
-        height = ((len(lines) - 1) * (font_size + spacing)) + font_size
+        for line in lines:
+            line_width, line_height = font.getsize(line)
+            for char in line:
+                char_width, char_height = font.getsize(char)
+                char_coordinates.append((x, y))
+                x += char_width + spacing
+                max_width = max(max_width, x + padding)
+            y += line_height + line_spacing
+            x = padding
+        # max_height = y
+        total_line_heights = sum(font.getsize(line)[1] for line in lines)
+        total_spacing = line_spacing * (len(lines) - 1)
+        # 确保顶部和底部的padding都被计入max_height
+        max_height = total_line_heights + total_spacing + padding * 2
+
+    # 3. Create image with calculated width and height
+    image = Image.new('RGBA', (max_width, max_height), (255, 255, 255, 0))
+    draw = ImageDraw.Draw(image)
 
     # 4. Draw each character on the image
-    image = Image.new('RGBA', (width, height), (255, 255, 255, 0))
-    draw = ImageDraw.Draw(image)
-    font = ImageFont.truetype(font_path, font_size)
-
     index = 0
-    for i, line in enumerate(lines):
-        for j, char in enumerate(line):
+    for line in lines:
+        for char in line:
             x, y = char_coordinates[index]
-            
             if stroke:
-                draw.text((x-stroke_width, y), char, font=font, fill=stroke_color)
-                draw.text((x+stroke_width, y), char, font=font, fill=stroke_color)
-                draw.text((x, y-stroke_width), char, font=font, fill=stroke_color)
-                draw.text((x, y+stroke_width), char, font=font, fill=stroke_color)
+                draw.text((x-stroke_width, y), char, font=font, fill=text_color)
+                draw.text((x+stroke_width, y), char, font=font, fill=text_color)
+                draw.text((x, y-stroke_width), char, font=font, fill=text_color)
+                draw.text((x, y+stroke_width), char, font=font, fill=text_color)
             
             draw.text((x, y), char, font=font, fill=text_color)
             index += 1
@@ -1376,6 +1299,9 @@ class LoadImages_:
             image=pil2tensor(image)
             ims.append(image)
 
+        if len(ims)==0:
+            image1 = Image.new('RGB', (512, 512), color='black')
+            return (pil2tensor(image1),)
         image1 = ims[0]
         for image2 in ims[1:]:
             if image1.shape[1:] != image2.shape[1:]:
@@ -1578,7 +1504,7 @@ class ImageCropByAlpha:
 
 
 
-
+# get_files_with_extension(FONT_PATH,'.ttf')
 
 class TextImage:
     @classmethod
@@ -1586,7 +1512,7 @@ class TextImage:
         return {"required": { 
             
                     "text": ("STRING",{"multiline": True,"default": "龍馬精神迎新歲","dynamicPrompts": False}),
-                    "font_path": ("STRING",{"multiline": False,"default": FONT_PATH,"dynamicPrompts": False}),
+                    "font": (get_files_with_extension(FONT_PATH,['.ttf','.otf']),),#后缀为 ttf
                     "font_size": ("INT",{
                                 "default":100, 
                                 "min": 100, #Minimum value
@@ -1601,6 +1527,20 @@ class TextImage:
                                 "step": 1, #Slider's step
                                 "display": "number" # Cosmetic only: display as "number" or "slider"
                                 }), 
+                    "line_spacing": ("INT",{
+                                "default":12, 
+                                "min": -200, #Minimum value
+                                "max": 200, #Maximum value
+                                "step": 1, #Slider's step
+                                "display": "number" # Cosmetic only: display as "number" or "slider"
+                                }), 
+                    "padding": ("INT",{
+                                "default":8, 
+                                "min": 0, #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","dynamicPrompts": False}),
                     "vertical":("BOOLEAN", {"default": True},),
                     "stroke":("BOOLEAN", {"default": False},),
@@ -1608,7 +1548,7 @@ class TextImage:
                 }
     
     RETURN_TYPES = ("IMAGE","MASK",)
-    # RETURN_NAMES = ("WIDTH","HEIGHT","X","Y",)
+    RETURN_NAMES = ("image","mask",)
 
     FUNCTION = "run"
 
@@ -1617,11 +1557,14 @@ class TextImage:
     INPUT_IS_LIST = False
     OUTPUT_IS_LIST = (False,False,)
 
-    def run(self,text,font_path,font_size,spacing,text_color,vertical,stroke):
+    def run(self,text,font,font_size,spacing,line_spacing,padding,text_color,vertical,stroke):
         
-        # text_list=list(text)
+        font_path=os.path.join(FONT_PATH,font)
+
+        if text=="":
+            text=" "
         # stroke=False, stroke_color=(0, 0, 0), stroke_width=1, spacing=0
-        img,mask=generate_text_image(text,font_path,font_size,text_color,vertical,stroke,(0, 0, 0),1,spacing)
+        img,mask=generate_text_image(text,font_path,font_size,text_color,vertical,stroke,(0, 0, 0),1,spacing,line_spacing,padding)
         
         img=pil2tensor(img)
         mask=pil2tensor(mask)
@@ -1854,10 +1797,16 @@ class CompositeImages:
                     "mask":("MASK",),
                     "background": ("IMAGE",),
                     },
-             "optional":{
-                           
+             "optional":{ 
                   "is_multiply_blend":  ("BOOLEAN", {"default": False}),
-                  "position":  (['overall',"center_bottom","center_top","right_bottom","left_bottom","right_top","left_top"],),    
+                  "position":  (['overall',"center_center","left_bottom","center_bottom","right_bottom","left_top","center_top","right_top"],),
+                   "scale": ("FLOAT",{
+                                "default":0.35, 
+                                "min": 0.01, #Minimum value
+                                "max": 1, #Maximum value
+                                "step": 0.01, #Slider's step
+                                "display": "number" # Cosmetic only: display as "number" or "slider"
+                            }), 
                     }
                 }
     
@@ -1870,15 +1819,30 @@ class CompositeImages:
 
     # OUTPUT_IS_LIST = (True,)
 
-    def run(self, foreground,mask,background,is_multiply_blend,position):
-        foreground= tensor2pil(foreground)
-        mask= tensor2pil(mask)
-        background= tensor2pil(background)
-        res=composite_images(foreground,background,mask,is_multiply_blend,position)
+    # def run(self, foreground,mask,background,is_multiply_blend,position,scale):
+    #     foreground= tensor2pil(foreground)
+    #     mask= tensor2pil(mask)
+    #     background= tensor2pil(background)
+    #     res=composite_images(foreground,background,mask,is_multiply_blend,position,scale)
         
-        return (pil2tensor(res),)
+    #     return (pil2tensor(res),)
 
+    def run(self, foreground,mask,background, is_multiply_blend, position, scale):
+        results = []
+        f1=[]
+        for fg, mask in zip(foreground, mask ):
+            f1.append([fg,mask])
+        for f, bg in product(f1, background):
+            [fg,mask]=f
+            fg_pil = tensor2pil(fg)
+            mask_pil = tensor2pil(mask)
+            bg_pil = tensor2pil(bg)
+            res = composite_images(fg_pil, bg_pil, mask_pil, is_multiply_blend, position, scale)
+            results.append(pil2tensor(res))
+        
+        output_image = torch.cat(results, dim=0)
 
+        return (output_image,)
 
 
 class EmptyLayer:
@@ -3207,3 +3171,52 @@ class SaveImageToLocal:
             counter += 1
 
         return ()
+
+
+class ImageBatchToList_:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": {"image_batch": ("IMAGE",), }}
+
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("image_list",)
+    OUTPUT_IS_LIST = (True,)
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/Image"
+
+    def run(self, image_batch):
+        images = [image_batch[i:i + 1, ...] for i in range(image_batch.shape[0])]
+        return (images, )
+
+class ImageListToBatch_:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "images": ("IMAGE",),
+            }
+        }
+
+    RETURN_TYPES = ("IMAGE",)
+    FUNCTION = "run"
+    INPUT_IS_LIST = True
+    CATEGORY = "♾️Mixlab/Image"
+
+    def run(self, images):
+        shape = images[0].shape[1:3]
+        out = []
+
+        for i in range(len(images)):
+            img = images[i].permute([0,3,1,2])
+            if images[i].shape[1:3] != shape:
+                transforms = T.Compose([
+                    T.CenterCrop(min(img.shape[2], img.shape[3])),
+                    T.Resize((shape[0], shape[1]), interpolation=T.InterpolationMode.BICUBIC),
+                ])
+                img = transforms(img)
+            out.append(img.permute([0,2,3,1]))
+
+        out = torch.cat(out, dim=0)
+
+        return (out,)

nodes/Lama.py

@@ -85,8 +85,6 @@ class LaMaInpainting:
             "image": ("IMAGE",),
             "mask": ("MASK",),
                              },
-
-            
                 }
     
     RETURN_TYPES = ("IMAGE",)

nodes/RembgNode.py

@@ -467,15 +467,37 @@ class BriaRMBG(nn.Module):
 
 
 
+def get_U2NET_model_path():
+    try:
+        return folder_paths.get_folder_paths('rembg')[0]
+    except:
+        return os.path.join(folder_paths.models_dir, "rembg")
+    
 
-
-
-U2NET_HOME=os.path.join(folder_paths.models_dir, "rembg")
+U2NET_HOME=get_U2NET_model_path()
 os.environ["U2NET_HOME"] = U2NET_HOME
 
 global _available
 _available=False
 
+
+def get_rembg_models(path):
+    """从目录中获取文件并提取文件名
+    Args:
+        path: 目录路径
+    Returns:
+        文件名列表
+    """
+    filenames = []
+    for root, _, files in os.walk(path):
+        for filename in files:
+        # 过滤隐藏文件
+            if not filename.startswith('.'):
+                name, ext = os.path.splitext(os.path.basename(filename))
+                filenames.append(name)
+    return filenames
+
+
 def is_installed(package):
     try:
         spec = importlib.util.find_spec(package)
@@ -509,8 +531,8 @@ except:
     _available=False
 
 
-def briarmbg_run(images=[]):
-    mroot=os.path.join(folder_paths.models_dir, "rembg")
+def run_briarmbg(images=[]):
+    mroot=U2NET_HOME
     m=os.path.join(mroot,'briarmbg.pth')
     if os.path.exists(m)==False:
         # 下载
@@ -573,14 +595,15 @@ def briarmbg_run(images=[]):
     return (masks,rgba_images,rgb_images)   
 
 
-def run_bg(model_name= "unet",images=[]):
+def run_rembg(model_name= "unet",images=[],callback=None):
     # model_name = "unet" # "isnet-general-use"
+    # print('#run_rembg',model_name)
     rembg_session = new_session(model_name)
     masks=[]
     rgba_images=[]
     rgb_images=[]
     # 进度条
-    pbar = comfy.utils.ProgressBar(len(images) )
+    pbar=callback 
     for img in images:
         # use the post_process_mask argument to post process the mask to get better results.
         mask = remove(img, session=rembg_session,only_mask=True,post_process_mask=True)
@@ -620,8 +643,9 @@ def run_bg(model_name= "unet",images=[]):
             rgb_image = Image.new("RGB", image_rgba.size, (0, 0, 0))
             rgb_image.paste(image_rgba, mask=image_rgba.split()[3])
             rgb_images.append(rgb_image)
-            
-        pbar.update(1)
+
+        if pbar:
+            pbar.update(1)
     return (masks,rgba_images,rgb_images)
 
 
@@ -643,17 +667,7 @@ class RembgNode_:
     def INPUT_TYPES(s):
         return {"required": {
             "image": ("IMAGE",),
-            "model_name": ([
-                            "briarmbg",
-                            "u2net",
-                            "u2netp",
-                            "u2net_human_seg",
-                            "u2net_cloth_seg",
-                            "silueta",
-                            "isnet-general-use",
-                            "isnet-anime",
-                            
-                            ],),
+            "model_name": (get_rembg_models(U2NET_HOME),),
             
                              },
                 }
@@ -681,9 +695,9 @@ class RembgNode_:
                 images.append(im)
 
         if model_name=='briarmbg':
-            masks,rgba_images,rgb_images=briarmbg_run(images)
+            masks,rgba_images,rgb_images=run_briarmbg(images)
         else:
-            masks,rgba_images,rgb_images=run_bg(model_name,images)
+            masks,rgba_images,rgb_images=run_rembg(model_name,images, comfy.utils.ProgressBar(len(images) ))
 
         masks=[pil2tensor(m) for m in masks]
 

nodes/ScreenShareNode.py

@@ -90,7 +90,7 @@ class ScreenShareNode:
                 } }
     
     RETURN_TYPES = ('IMAGE','STRING','FLOAT',"INT")
-    RETURN_NAMES = ("IMAGE","PROMPT","FLOAT","INT")
+    RETURN_NAMES = ("current frame (image)","prompt","denoise (float)","seed (int)")
     FUNCTION = "run"
 
     CATEGORY = "♾️Mixlab/Screen"
@@ -109,7 +109,7 @@ class FloatingVideo:
     @classmethod
     def INPUT_TYPES(s):
         return { "required":{
-            "images": ("IMAGE",)
+            "image": ("IMAGE",)
         }, }
     
     # RETURN_TYPES = ('IMAGE','MASK')
@@ -124,16 +124,16 @@ class FloatingVideo:
     # OUTPUT_IS_LIST = (False,False,)
   
     # 运行的函数
-    def run(self,images):
+    def run(self,image):
        
         results = list()
     
-        for image in images:
-            image=tensor2pil(image)
+        for im in image:
+            im=tensor2pil(im)
             # image_base64 = base64.b64encode(image.tobytes())
 
             buffered = BytesIO()
-            image.save(buffered, format="JPEG")
+            im.save(buffered, format="JPEG")
             image_base64 = base64.b64encode(buffered.getvalue()).decode("utf-8")
 
             results.append(image_base64)

nodes/TripoSR.py

@@ -5,13 +5,20 @@ from PIL import Image
 import numpy as np
 import torch
 
-from folder_paths import get_filename_list, get_full_path, get_save_image_path, get_output_directory,models_dir
+from folder_paths import get_folder_paths, get_full_path, get_save_image_path, get_output_directory,models_dir
 from comfy.model_management import get_torch_device
 from .tsr.system import TSR
 
 import comfy.utils
 
-triposr_model_path=path.join(models_dir,'triposr/model.ckpt')
+
+def get_triposr_model_path():
+    try:
+        return path.join(get_folder_paths('triposr')[0],'model.ckpt')
+    except:
+        return path.join(path.join(models_dir, "triposr"),'model.ckpt')
+    
+triposr_model_path=get_triposr_model_path()
 
 
 # Tensor to PIL

nodes/Utils.py

@@ -133,7 +133,7 @@ def get_font_files(directory):
 
     return font_files
 
-r_directory = os.path.join(os.path.dirname(__file__), '../assets/')
+r_directory = os.path.join(os.path.dirname(__file__), '..','assets','/')
 
 font_files = get_font_files(r_directory)
 # print(font_files)
@@ -181,6 +181,28 @@ class ColorInput:
         return (h,r,g,b,a,)
 
 
+class KeyInput:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": { 
+                    "key":("KEY",), 
+                             },
+                }
+    
+    RETURN_TYPES = ("STRING",)
+    RETURN_NAMES = ("key",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/Input"
+
+    INPUT_IS_LIST = False
+    OUTPUT_IS_LIST = (False,)
+
+    def run(self,key):
+        return (key,)
+
+
 
 class FontInput:
     @classmethod
@@ -284,7 +306,7 @@ class FloatSlider:
                 }
     
     RETURN_TYPES = ("FLOAT",) 
-    RETURN_NAMES = ('weight(0-1)',)
+    RETURN_NAMES = ('FLOAT',)
     FUNCTION = "run"
 
     CATEGORY = "♾️Mixlab/Input"
@@ -297,9 +319,7 @@ class FloatSlider:
             number = min_value
         elif number > max_value:
             number = max_value
-        scaled_number = (number - min_value) / (max_value - min_value)
-        return (scaled_number,)
-    
+        return (number,)    
   
 class IntNumber:
     @classmethod
@@ -568,7 +588,7 @@ class AppInfo:
                              },
 
                 "optional":{
-                    "IMAGE": ("IMAGE",),
+                    "image": ("IMAGE",),
                     "description":("STRING",{"multiline": True,"default": "","dynamicPrompts": False}),
                     "version":("INT", {
                         "default": 1, 
@@ -596,12 +616,12 @@ class AppInfo:
     INPUT_IS_LIST = True
     # OUTPUT_IS_LIST = (True,)
 
-    def run(self,name,input_ids,output_ids,IMAGE,description,version,share_prefix,link,category,auto_save):
+    def run(self,name,input_ids,output_ids,image,description,version,share_prefix,link,category,auto_save):
         name=name[0]
         
         im=None
-        if IMAGE:
-            im=IMAGE[0][0]
+        if image:
+            im=image[0][0]
             #TODO batch 的方式需要处理
             im=create_temp_file(im)
         # image [img,] img[batch,w,h,a] 列表里面是batch，

nodes/Video.py

@@ -17,9 +17,128 @@ import folder_paths
 from comfy.k_diffusion.utils import FolderOfImages
 from comfy.utils import common_upscale
 
+import torchaudio
+import base64
+
+import mimetypes
 
 
 
+def get_frames(frame_count, frames, revert=False):
+    if not revert:
+        if frame_count <= len(frames):
+            return frames[:frame_count]
+        else:
+            return [frames[i % len(frames)] for i in range(frame_count)]
+    else:
+        extended_frames = frames + frames[-2:0:-1]  # 正向加反向中间部分
+        if frame_count <= len(extended_frames):
+            return extended_frames[:frame_count]
+        else:
+            return [extended_frames[i % len(extended_frames)] for i in range(frame_count)]
+
+# # 示例用法
+# frames = ["frame1", "frame2", "frame3"]
+# frame_count = 2
+
+# result = get_frames(frame_count, frames, revert=False)
+# print(result)  # 输出: ['frame1', 'frame2', 'frame3', 'frame1', 'frame2', 'frame3', 'frame1']
+
+# result = get_frames(frame_count, frames, revert=True)
+# print(result)  # 输出: ['frame1', 'frame2', 'frame3', 'frame2', 'frame1', 'frame2', 'frame3']
+
+
+
+
+def get_mime_type(file_path):
+    # 获取文件的 MIME 类型
+    mime_type, _ = mimetypes.guess_type(file_path)
+    
+    # 如果无法猜测类型，返回默认类型
+    if mime_type is None:
+        return 'application/octet-stream'
+    
+    return mime_type
+# import subprocess
+# from imageio_ffmpeg import get_ffmpeg_exe
+
+
+def save_audio_base64s_to_file(base64_audios, output_folder, file_name):
+    # Ensure the output folder exists
+    if not os.path.exists(output_folder):
+        os.makedirs(output_folder)
+
+    decoded_audios=[]
+    for a in base64_audios:
+    
+        # If the base64 string contains a header, remove it
+        if ',' in a:
+            a = a.split(',')[1]
+        
+        # 解码 base64 数据
+        a=base64.b64decode(a)
+        decoded_audios.append(a)
+
+    # 拼接音频数据
+    combined_audio = b''.join(decoded_audios)
+    
+    # Create the full file path
+    file_path = os.path.join(output_folder, file_name)
+    
+    # Write the decoded audio to the file
+    with open(file_path, 'wb') as audio_file:
+        audio_file.write(combined_audio)
+    
+    return file_path
+
+# Example usage
+# base64_audio = "data:audio/wav;base64,UklGRiQAAABXQVZFZm10IBAAAAABAAEAIlYAAESsAAACABAAZGF0YQAAAAA="
+# output_folder = "audio_files"
+# file_name = "output.wav"
+
+# file_path = save_audio_base64_to_file(base64_audio, output_folder, file_name)
+# print(f"Audio saved to: {file_path}")
+
+# 写一个python文件，用来 判断文件夹内命名为 所有chat_tts开头的文件数量（chat_tts_00001），并输出新的编号
+def get_new_counter(full_output_folder, filename_prefix):
+    # 获取目录中的所有文件
+    files = os.listdir(full_output_folder)
+    
+    # 过滤出以 filename_prefix 开头并且后续部分为数字的文件
+    filtered_files = []
+    for f in files:
+        if f.startswith(filename_prefix):
+            # 去掉文件名中的前缀和后缀，只保留中间的数字部分
+            base_name = f[len(filename_prefix)+1:]
+            number_part = base_name.split('.')[0]  # 假设文件名中只有一个点，即扩展名
+            if number_part.isdigit():
+                filtered_files.append(int(number_part))
+
+    if not filtered_files:
+        return 1
+
+    # 获取最大的编号
+    max_number = max(filtered_files)
+    
+    # 新的编号
+    return max_number + 1
+
+def crop_audio(input_file, start_time, duration):
+    # Load the audio file
+    audio_tensor, sample_rate = torchaudio.load(input_file)
+    
+    # Convert start_time and duration from seconds to sample indices
+    start_sample = int(start_time * sample_rate)
+    end_sample = start_sample + int(duration * sample_rate)
+    
+    # Perform the slicing
+    cropped_audio_tensor = audio_tensor[:, start_sample:end_sample]
+    
+    # Save the cropped audio to a new file
+    torchaudio.save(input_file, cropped_audio_tensor, sample_rate)
+    
+    return input_file
+
 def generate_folder_name(directory,video_path):
     # Get the directory and filename from the video path
     _, filename = os.path.split(video_path)
@@ -60,6 +179,9 @@ def split_video(video_path, video_segment_frames, transition_frames, output_dir)
         
         # 打印当前片段的起始帧和结束帧
         print(f"Segment {i+1}: Start Frame {start_frame}, End Frame {end_frame}")
+
+        if end_frame<start_frame:
+            break
         
         # 保存当前片段为一个视频文件
         segment_video_path = f"{output_dir}/segment_{i+1}.avi"
@@ -68,6 +190,7 @@ def split_video(video_path, video_segment_frames, transition_frames, output_dir)
         segment_video = cv2.VideoWriter(segment_video_path, fourcc, fps, (int(video_capture.get(cv2.CAP_PROP_FRAME_WIDTH)),
                                                               int(video_capture.get(cv2.CAP_PROP_FRAME_HEIGHT))))
         
+
         for frame_num in range(start_frame, end_frame):
             ret, frame = video_capture.read()
             if ret:
@@ -87,7 +210,7 @@ def split_video(video_path, video_segment_frames, transition_frames, output_dir)
 
 folder_paths.folder_names_and_paths["video_formats"] = (
     [
-        os.path.join(os.path.dirname(os.path.abspath(__file__)), "..", "video_formats"),
+        os.path.join(os.path.dirname(os.path.abspath(__file__)), ".", "video_formats"),
     ],
     [".json"]
 )
@@ -101,6 +224,25 @@ if ffmpeg_path is None:
     except:
         print("ffmpeg could not be found. Outputs that require it have been disabled")
 
+
+def combine_audio_video(audio_path, video_path, output_path):
+   
+    command = [
+        ffmpeg_path,
+        '-i', video_path,
+        '-i', audio_path,
+        '-c:v', 'copy',
+        '-c:a', 'aac',
+        '-shortest',
+        output_path
+    ]
+    
+    subprocess.run(command, check=True)
+    return output_path
+
+
+
+
 # Tensor to PIL
 def tensor2pil(image):
     return Image.fromarray(np.clip(255. * image.cpu().numpy().squeeze(), 0, 255).astype(np.uint8))
@@ -262,7 +404,7 @@ class LoadVideoAndSegment:
                     files.append(f)
         return {"required": {
                     "video": (sorted(files), {"video_upload": True}),
-                     "video_segment_frames": ("INT", {"default": 10, "min": 1, "step": 1}),
+                     "video_segment_frames": ("INT", {"default": 10, "min": -1, "step": 1}),
                      "transition_frames": ("INT", {"default": 0, "min": 0, "step": 1}), 
                      },}
 
@@ -332,63 +474,6 @@ class LoadVideoAndSegment:
         
         video_path = folder_paths.get_annotated_filepath(video)
         
-        # check if video is a gif - will need to use cv fallback to read frames
-        # use cv fallback if ffmpeg not installed or gif
-        # if ffmpeg_path is None:
-        #     return self.load_video_cv_fallback(video, frame_load_cap, skip_first_frames)
-        # otherwise, continue with ffmpeg
-        
-        # args_dummy = [ffmpeg_path, "-i", video_path, "-f", "null", "-"]
-        # try:
-        #     with subprocess.Popen(args_dummy, stdout=subprocess.DEVNULL, stderr=subprocess.PIPE) as proc:
-        #         for line in proc.stderr.readlines():
-        #             match = re.search(", ([1-9]|\\d{2,})x(\\d+)",line.decode('utf-8'))
-        #             if match is not None:
-        #                 size = [int(match.group(1)), int(match.group(2))]
-        #                 break
-        # except Exception as e:
-        #     print(f"Retrying with opencv due to ffmpeg error: {e}")
-        #     return self.load_video_cv_fallback(video, frame_load_cap, skip_first_frames)
-        # args_all_frames = [ffmpeg_path, "-i", video_path, "-v", "error",
-        #                      "-pix_fmt", "rgb24"]
-
-        # vfilters = []
-       
-        # if skip_first_frames > 0:
-        #     vfilters.append(f"select=gt(n\\,{skip_first_frames-1})")
-        # if frame_load_cap > 0:
-        #     vfilters.append(f"select=gt({frame_load_cap}\\,n)")
-        # #manually calculate aspect ratio to ensure reads remain aligned
-        
-        # if len(vfilters) > 0:
-        #     args_all_frames += ["-vf", ",".join(vfilters)]
-
-        # args_all_frames += ["-f", "rawvideo", "-"]
-        # images = []
-        # try:
-        #     with subprocess.Popen(args_all_frames, stdout=subprocess.PIPE) as proc:
-        #         #Manually buffer enough bytes for an image
-        #         bpi = size[0]*size[1]*3
-        #         current_bytes = bytearray(bpi)
-        #         current_offset=0
-        #         while True:
-        #             bytes_read = proc.stdout.read(bpi - current_offset)
-        #             if bytes_read is None:#sleep to wait for more data
-        #                 time.sleep(.2)
-        #                 continue
-        #             if len(bytes_read) == 0:#EOF
-        #                 break
-        #             current_bytes[current_offset:len(bytes_read)] = bytes_read
-        #             current_offset+=len(bytes_read)
-        #             if current_offset == bpi:
-        #                 images.append(np.array(current_bytes, dtype=np.float32).reshape(size[1], size[0], 3) / 255.0)
-        #                 current_offset = 0
-        # except Exception as e:
-        #     print(f"Retrying with opencv due to ffmpeg error: {e}")
-        #     return self.load_video_cv_fallback(video, frame_load_cap, skip_first_frames)
-
-        # imgs=split_list(images,video_segment_frames,transition_frames)
-
         # temp path 
         tp=folder_paths.get_temp_directory()
         basename = os.path.basename(video_path)  # 获取文件名
@@ -396,15 +481,22 @@ class LoadVideoAndSegment:
 
         folder_path = create_folder(tp,name_without_extension)
         
- 
-        # 导出的数据
-        scenes_video,total_frames,fps=split_video(video_path,video_segment_frames,
-                                 transition_frames,folder_path)
+        if video_segment_frames==-1:
+            # 不切割视频
+            scenes_video=[video_path]
+            # 读取视频文件
+            video_capture = cv2.VideoCapture(video_path)
+            
+            # 获取视频的总帧数和帧率
+            total_frames = int(video_capture.get(cv2.CAP_PROP_FRAME_COUNT))
+            fps = video_capture.get(cv2.CAP_PROP_FPS)
+
+        else:
+            # 导出的数据
+            scenes_video,total_frames,fps=split_video(video_path,video_segment_frames,
+                                    transition_frames,folder_path)
       
 
-        # imgs=[torch.from_numpy(np.stack(im)) for im in imgs]
-
-        # images = torch.from_numpy(np.stack(images))
 
         return (scenes_video,len(scenes_video), total_frames,fps,)
 
@@ -422,7 +514,113 @@ class LoadVideoAndSegment:
             return "Invalid image file: {}".format(video)
 
         return True
-    
+
+
+
+class LoadAndCombinedAudio_:
+    @classmethod
+    def INPUT_TYPES(s):
+       
+        return {"required": {
+                    "audios": ("AUDIOBASE64",),
+                    "start_time": ("FLOAT" , {"default": 0, "min": 0, "max": 10000000, "step": 0.01}),
+                    "duration": ("FLOAT" , {"default": 10, "min": -1, "max": 10000000, "step": 0.01}),
+                     },
+                }
+
+    CATEGORY = "♾️Mixlab/Audio"
+
+    RETURN_TYPES = ("STRING","AUDIO",)
+    RETURN_NAMES = ("audio_file_path","audio",)
+    FUNCTION = "run"
+
+    def run(self,audios, start_time, duration):
+        output_dir = folder_paths.get_output_directory()
+        counter=get_new_counter(output_dir,'audio_')
+
+        audio_file_name = f"audio_{counter:05}.wav"
+
+        audio_file=save_audio_base64s_to_file(audios['base64'],output_dir,audio_file_name)
+        # duration == -1 则不裁切
+        if duration > -1:
+            crop_audio(audio_file, start_time, duration)
+
+        waveform, sample_rate = torchaudio.load(audio_file)
+        audio = {
+            "filename": audio_file_name,
+            "subfolder": "",
+            "type": "output",
+            "audio_path":audio_file,
+            "waveform": waveform.unsqueeze(0), 
+            "sample_rate": sample_rate}
+
+        return (audio_file,audio ,)
+
+class CombineAudioVideo:
+    @classmethod
+    def INPUT_TYPES(s):
+       
+        return {"required": {
+                     "video": ("SCENE_VIDEO",),
+                     "audio": ("AUDIO", ), 
+                     },
+                }
+
+    CATEGORY = "♾️Mixlab/Video"
+
+    OUTPUT_NODE = True
+    FUNCTION = "run" 
+    RETURN_TYPES = ("SCENE_VIDEO",)
+    RETURN_NAMES = ("SCENE_VIDEO",)
+
+    def run(self,video, audio):
+
+        output_dir = folder_paths.get_output_directory()
+
+        # 判断是否是 Tensor 类型
+        is_tensor = not isinstance(audio, dict)
+        # print('#判断是否是 Tensor 类型',is_tensor,audio)
+        if not is_tensor and 'waveform' in audio and 'sample_rate' in audio:
+            # {'waveform': tensor([], size=(1, 1, 0)), 'sample_rate': 44100}
+            is_tensor=True
+
+        if "audio_path" in audio:
+            is_tensor=False
+            audio_file_path=audio["audio_path"]
+
+        if is_tensor:
+            filename_prefix="audio_tmp"
+            full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(
+                filename_prefix, 
+                folder_paths.get_temp_directory())
+            
+            filename_with_batch_num = filename.replace("%batch_num%", str(1))
+            file = f"{filename_with_batch_num}_{counter:05}_.wav"
+            
+            audio_file_path=os.path.join(full_output_folder, file)
+
+            torchaudio.save(audio_file_path, audio['waveform'].squeeze(0), audio["sample_rate"])
+            
+        # 获取文件名和扩展名
+        base, ext = os.path.splitext(video)
+        counter=get_new_counter(output_dir,'video_final_')
+
+        v_file = f"video_final_{counter:05}{ext}"
+        
+        v_file_path=os.path.join(output_dir, v_file)
+
+        combine_audio_video(audio_file_path,video,v_file_path)
+
+        previews = [
+            {
+                "filename": v_file,
+                "subfolder": "",
+                "type": "output",
+                "format": get_mime_type(v_file),
+            }
+        ]
+
+        return {"ui": {"gifs": previews},"result":(v_file_path,)}
 
 # The code is based on ComfyUI-VideoHelperSuite modification.
 class VideoCombine_Adv:
@@ -433,6 +631,7 @@ class VideoCombine_Adv:
             ffmpeg_formats = ["video/"+x[:-5] for x in folder_paths.get_filename_list("video_formats")]
         else:
             ffmpeg_formats = []
+        # ffmpeg_formats =["video/"+x for x in  ['webm', 'mp4', 'mkv']]
         return {
             "required": {
                 "image_batch": ("IMAGE",),
@@ -453,7 +652,8 @@ class VideoCombine_Adv:
             },
         }
 
-    RETURN_TYPES = ()
+    RETURN_TYPES = ("SCENE_VIDEO",)
+    RETURN_NAMES = ("scenes_video",)
     OUTPUT_NODE = True
     CATEGORY = "♾️Mixlab/Video"
     FUNCTION = "run"
@@ -622,7 +822,7 @@ class VideoCombine_Adv:
                 "format": format,
             }
         ]
-        return {"ui": {"gifs": previews}}
+        return {"ui": {"gifs": previews},"result":(file_path,)}
 
 
 class VAEEncodeForInpaint_Frames:
@@ -689,4 +889,113 @@ class VAEEncodeForInpaint_Frames:
             result.append({"samples":t, "noise_mask": (mask_erosion[:,:,:x,:y].round())})
 
 
-        return (result, )
+        return (result, )
+    
+
+
+class GenerateFramesByCount:
+    @classmethod
+    def INPUT_TYPES(cls):
+        
+        return {"required": {
+                    "frames": ('IMAGE',),
+                    "frame_count": ("INT", {"default": 72, "min": 1, "step": 1}), 
+                    "revert" :("BOOLEAN", {"default": True},),
+                     },}
+
+    RETURN_TYPES = ('IMAGE',)
+    RETURN_NAMES = ("frames",)
+
+    FUNCTION = "r"
+    CATEGORY = "♾️Mixlab/Video"
+    # INPUT_IS_LIST = True
+
+    def r(self, frames, frame_count, revert):
+        
+        image_list = [frames[i:i + 1, ...] for i in range(frames.shape[0])]
+
+        image_list=get_frames(frame_count,image_list,revert)
+
+        images = torch.cat(image_list, dim=0)
+
+        return (images,)
+
+
+class scenesNode_:
+    @classmethod
+    def INPUT_TYPES(cls):
+        
+        return {"required": {
+                    "scenes_video": ('SCENE_VIDEO',),
+                    "index": ("INT", {"default": 0, "min": 0, "step": 1}),
+                     
+                     },}
+
+    RETURN_TYPES = ('IMAGE','INT',)
+    RETURN_NAMES = ("video frames (batch)","count",)
+    # OUTPUT_IS_LIST = (False,)
+
+    FUNCTION = "run"
+    CATEGORY = "♾️Mixlab/Video"
+    INPUT_IS_LIST = True
+
+    def load_video_cv_fallback(self, video, frame_load_cap, skip_first_frames):
+        # print('#video',video)
+        try:
+            video_cap = cv2.VideoCapture(video)
+            if not video_cap.isOpened():
+                raise ValueError(f"{video} could not be loaded with cv fallback.")
+            # set video_cap to look at start_index frame
+            images = []
+            total_frame_count = 0
+            frames_added = 0
+            base_frame_time = 1/video_cap.get(cv2.CAP_PROP_FPS)
+            
+            target_frame_time = base_frame_time
+
+            time_offset=0.0
+            while video_cap.isOpened():
+                if time_offset < target_frame_time:
+                    is_returned, frame = video_cap.read()
+                    # if didn't return frame, video has ended
+                    if not is_returned:
+                        break
+                    time_offset += base_frame_time
+                if time_offset < target_frame_time:
+                    continue
+                time_offset -= target_frame_time
+                # if not at start_index, skip doing anything with frame
+                total_frame_count += 1
+                if total_frame_count <= skip_first_frames:
+                    continue
+                # TODO: do whatever operations need to happen, like force_size, etc
+
+                # opencv loads images in BGR format (yuck), so need to convert to RGB for ComfyUI use
+                # follow up: can videos ever have an alpha channel?
+                frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+                # convert frame to comfyui's expected format (taken from comfy's load image code)
+                image = Image.fromarray(frame)
+                image = ImageOps.exif_transpose(image)
+                image = np.array(image, dtype=np.float32) / 255.0
+                image = torch.from_numpy(image)[None,]
+                images.append(image)
+                frames_added += 1
+                # if cap exists and we've reached it, stop processing frames
+                if frame_load_cap > 0 and frames_added >= frame_load_cap:
+                    break
+        finally:
+            video_cap.release()
+        
+        images = torch.cat(images, dim=0)
+       
+        return (images, frames_added,)
+
+    def run(self, scenes_video,index):
+        print('#scenes_video',index,scenes_video)
+        index=index[0]
+        if len(scenes_video) > index:
+            vp=scenes_video[index]
+        else:
+            vp=scenes_video[-1]
+        
+        return self.load_video_cv_fallback(vp,0,0)

nodes/edit_mask.py

@@ -0,0 +1,172 @@
+import torch
+from PIL import Image, ImageOps, ImageSequence, ImageFile
+from PIL.PngImagePlugin import PngInfo
+
+import numpy as np
+import os
+import folder_paths 
+import node_helpers
+import hashlib
+
+# Tensor to PIL
+def tensor2pil(image):
+    return Image.fromarray(np.clip(255. * image.cpu().numpy().squeeze(), 0, 255).astype(np.uint8))
+
+# tensor 取hash值
+def tensor_to_hash(tensor):
+    # 将 Tensor 转换为 NumPy 数组
+    np_array = tensor.cpu().numpy()
+    
+    # 将 NumPy 数组转换为字节数据
+    byte_data = np_array.tobytes()
+    
+    # 计算哈希值
+    hash_value = hashlib.md5(byte_data).hexdigest()
+    
+    return hash_value
+
+
+def create_temp_file(image):
+    output_dir = folder_paths.get_temp_directory()
+
+    (
+            full_output_folder,
+            filename,
+            counter,
+            subfolder,
+            _,
+        ) = folder_paths.get_save_image_path('material', output_dir)
+
+    
+    image=tensor2pil(image)
+ 
+    image_file = f"{filename}_{counter:05}.png"
+     
+    image_path=os.path.join(full_output_folder, image_file)
+
+    image.save(image_path,compress_level=4)
+
+    return (image_path,[{
+    "filename": image_file,
+    "subfolder": subfolder,
+    "type": "temp"
+    }])
+
+
+# image - tensor - 文件路径
+# loadImage的方法（ 文件路径 - image-mask ）
+class EditMask:
+
+    def __init__(self):
+        self.image_id = None
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required":
+                    {"image": ("IMAGE",), # 表示一个张量
+                     
+                     },
+
+                    "optional":{
+                            "image_update": ("IMAGE_FILE",)
+                        },
+                   
+                }
+
+    CATEGORY = "♾️Mixlab/Mask"
+
+    RETURN_TYPES = ("IMAGE", "MASK")
+    RETURN_NAMES = ("image", "mask")
+
+    FUNCTION = "edit"
+
+    OUTPUT_NODE = True
+
+    def edit(self, image,image_update=None):
+
+        # 根据image输入来判断是否是新的图片
+        if self.image_id==None:
+            self.image_id=tensor_to_hash(image)
+            image_update=None
+        else:
+            image_id=tensor_to_hash(image)
+            if image_id!=self.image_id:
+                image_update=None
+                self.image_id=image_id
+
+
+        image_path=None
+        # print('#image_update',self.image_id,image_update)
+        if image_update==None:
+            print('--')
+        else:
+            if 'images' in image_update:
+                images=image_update['images']
+                filename=images[0]['filename']
+                subfolder=images[0]['subfolder']
+                type=images[0]['type']
+                name, base_dir=folder_paths.annotated_filepath(filename)
+                if type.endswith("output"):
+                    base_dir = folder_paths.get_output_directory() 
+                elif type.endswith("input"):
+                    base_dir = folder_paths.get_input_directory() 
+                elif type.endswith("temp"):
+                    base_dir = folder_paths.get_temp_directory() 
+                #base_dir = folder_paths.get_input_directory()  
+                # print(base_dir,subfolder, name)
+                image_path = os.path.join(base_dir,subfolder, name)
+        
+        if image_path==None:
+            image_path,images=create_temp_file(image)
+
+        print('#image_path',os.path.exists(image_path),image_path)
+        # image_path = folder_paths.get_annotated_filepath(image) #文件名
+        
+        if not os.path.exists(image_path):
+            image_path,images=create_temp_file(image)
+
+
+        img = node_helpers.pillow(Image.open, image_path)
+        
+        output_images = []
+        output_masks = []
+        w, h = None, None
+
+        excluded_formats = ['MPO']
+        
+        for i in ImageSequence.Iterator(img):
+            i = node_helpers.pillow(ImageOps.exif_transpose, i)
+
+            if i.mode == 'I':
+                i = i.point(lambda i: i * (1 / 255))
+            image = i.convert("RGB")
+
+            if len(output_images) == 0:
+                w = image.size[0]
+                h = image.size[1]
+            
+            if image.size[0] != w or image.size[1] != h:
+                continue
+            
+            image = np.array(image).astype(np.float32) / 255.0
+            image = torch.from_numpy(image)[None,]
+            if 'A' in i.getbands():
+                mask = np.array(i.getchannel('A')).astype(np.float32) / 255.0
+                mask = 1. - torch.from_numpy(mask)
+            else:
+                # 尺寸不对，需要按照image来
+                mask = torch.zeros((h, w), dtype=torch.float32, device="cpu")
+
+            output_images.append(image)
+            output_masks.append(mask.unsqueeze(0))
+
+        if len(output_images) > 1 and img.format not in excluded_formats:
+            output_image = torch.cat(output_images, dim=0)
+            output_mask = torch.cat(output_masks, dim=0)
+        else:
+            output_image = output_images[0]
+            output_mask = output_masks[0]
+
+        return {"ui":{"images": images},"result": (output_image, output_mask)}
+
+        # return (output_image, output_mask)

nodes/video_formats/av1-webm.json

@@ -0,0 +1,10 @@
+{
+    "main_pass":
+    [
+        "-n", "-c:v", "libsvtav1",
+        "-pix_fmt", "yuv420p10le",
+        "-crf", "23"
+    ],
+     "extension": "webm",
+     "environment": {"SVT_LOG": "1"}
+}

nodes/video_formats/h264-mp4.json

@@ -0,0 +1,9 @@
+{
+    "main_pass":
+    [
+        "-n", "-c:v", "libx264",
+        "-pix_fmt", "yuv420p",
+        "-crf", "19"
+    ],
+     "extension": "mp4"
+}

nodes/video_formats/h265-mp4.json

@@ -0,0 +1,11 @@
+{
+    "main_pass":
+    [
+        "-n", "-c:v", "libx265",
+        "-pix_fmt", "yuv420p10le",
+        "-preset", "medium",
+        "-crf", "22",
+        "-x265-params", "log-level=quiet"
+    ],
+     "extension": "mp4"
+}

nodes/video_formats/webm.json

@@ -0,0 +1,9 @@
+{
+    "main_pass":
+    [
+        "-n",
+        "-pix_fmt", "yuv420p",
+        "-crf", "23"
+    ],
+     "extension": "webm"
+}

pyproject.toml

@@ -0,0 +1,15 @@
+[project]
+name = "comfyui-mixlab-nodes"
+description = "3D, ScreenShareNode & FloatingVideoNode, SpeechRecognition & SpeechSynthesis, GPT, LoadImagesFromLocal, Layers, Other Nodes, ..."
+version = "0.34.0"
+license = { text = "MIT License" }
+dependencies = ["numpy", "pyOpenSSL", "watchdog", "opencv-python-headless", "matplotlib", "openai", "simple-lama-inpainting", "clip-interrogator==0.6.0", "transformers>=4.36.0", "lark-parser", "imageio-ffmpeg", "rembg[gpu]", "omegaconf==2.3.0", "Pillow>=9.5.0", "einops==0.7.0", "trimesh>=4.0.5", "huggingface-hub", "scikit-image"]
+
+[project.urls]
+Repository = "https://github.com/shadowcz007/comfyui-mixlab-nodes"
+#  Used by Comfy Registry https://comfyregistry.org
+
+[tool.comfy]
+PublisherId = "shadow"
+DisplayName = "comfyui-mixlab-nodes"
+Icon = ""

requirements.txt

@@ -15,4 +15,6 @@ Pillow>=9.5.0
 einops==0.7.0
 trimesh>=4.0.5
 huggingface-hub
-scikit-image
+scikit-image
+torchaudio
+soundfile>=0.12.1

web/ar.html

@@ -0,0 +1,22 @@
+<!DOCTYPE html>
+<html lang="en">
+
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Mixlab AR</title>
+</head>
+
+<body>
+
+    <script type="module">
+
+        import { api } from "../../../scripts/api.js";
+        import Command from '/extensions/comfyui-mixlab-nodes/javascript/command.js'
+
+
+    </script>
+
+</body>
+
+</html>

web/javascript/app_mixlab.js

@@ -2,6 +2,9 @@ import { app } from '../../../scripts/app.js'
 import { $el } from '../../../scripts/ui.js'
 import { api } from '../../../scripts/api.js'
 
+import { td_bg } from './td_background.js'
+// console.log('td_bg', td_bg)
+
 //本机安装的插件节点全集
 window._nodesAll = null
 
@@ -70,7 +73,8 @@ function get_position_style (ctx, widget_width, y, node_height) {
     display: 'flex',
     flexDirection: 'column',
     // alignItems: 'center',
-    justifyContent: 'flex-start'
+    justifyContent: 'flex-start',
+    zIndex: 9999999
   }
 }
 
@@ -184,6 +188,25 @@ async function extractInputAndOutputData (
         if (node.type == 'Color') {
         }
 
+        // 语音输入的支持
+        if (node.type == 'LoadAndCombinedAudio_') {
+          // if (
+          //   data[id].widgets_values &&
+          //   data[id].widgets_values[0] &&
+          //   data[id].widgets_values[0].base64 &&
+          //   data[id].widgets_values[0].base64.length > 0
+          // ) {
+          //   options.defaultBase64 = data[id].widgets_values[0].base64
+          // }
+
+          input[inputIds.indexOf(id)] = {
+            ...data[id],
+            title: node.title,
+            id,
+            options
+          }
+        }
+
         if (node.type === 'LoadImage') {
           // loadImage的mask支持
           let output = node.outputs.filter(ot => ot.type == 'MASK')[0]
@@ -192,7 +215,7 @@ async function extractInputAndOutputData (
             options.hasMask = true
           }
           // loadImage的默认图，转为base64
-          let imgurl = app.graph.getNodeById(id).imgs[0].src
+          let imgurl = app.graph.getNodeById(id).imgs[0].src + '&channel=rgb'
 
           options.defaultImage = await drawImageToCanvas(imgurl, 512)
           console.log('#loadImage的默认图', options)
@@ -234,7 +257,9 @@ async function extractInputAndOutputData (
         node.type === 'KSampler' ||
         node.type == 'SamplerCustom' ||
         node.type === 'ChinesePrompt_Mix' ||
-        node.type === 'Seed_'
+        node.type === 'Seed_'||
+        node.type==='SiliconflowLLM'||
+        node.type==='ChatGPTOpenAI'
       ) {
         // seed 的类型收集
         try {
@@ -396,11 +421,11 @@ async function save (json, download = false, showInfo = true) {
 
 function getInputsAndOutputs () {
   const inputs =
-      `LoadImage LoadImagesToBatch ImagesPrompt_ VHS_LoadVideo CLIPTextEncode PromptSlide TextInput_ Color FloatSlider IntNumber CheckpointLoaderSimple LoraLoader`.split(
+      `LoadImage LoadImagesToBatch ImagesPrompt_ LoadAndCombinedAudio_ LoadVideoAndSegment_ VHS_LoadVideo CLIPTextEncode PromptSlide TextInput_ Color FloatSlider IntNumber CheckpointLoaderSimple LoraLoader`.split(
         ' '
       ),
     outputs =
-      `SaveTripoSRMesh,PreviewImage,SaveImage,TransparentImage,ShowTextForGPT,VHS_VideoCombine,VideoCombine_Adv,Image Save,SaveImageAndMetadata_,ClipInterrogator`.split(
+      `SaveTripoSRMesh,PreviewImage,SaveImage,TransparentImage,ShowTextForGPT,CombineAudioVideo,VHS_VideoCombine,VideoCombine_Adv,Image Save,SaveImageAndMetadata_,ClipInterrogator`.split(
         ','
       )
 
@@ -444,19 +469,18 @@ app.registerExtension({
         const { input, output } = getInputsAndOutputs()
         input_ids.value = input.join('\n')
         output_ids.value = output.join('\n')
-
         const widget = {
           type: 'div',
           name: 'AppInfoRun',
           draw (ctx, node, widget_width, y, widget_height) {
             Object.assign(
               this.div.style,
-              get_position_style(
+              {...get_position_style(
                 ctx,
                 widget_width,
                 node.size[1] - widget_height,
                 node.size[1]
-              )
+              ),zIndex:1}
             )
           }
         }
@@ -502,6 +526,21 @@ app.registerExtension({
           }
         })
 
+        //td bg
+        const tdBG = document.createElement('button')
+        tdBG.innerText = 'Canvas Mode'
+        tdBG.style = style
+        tdBG.style.marginLeft = '12px'
+
+        tdBG.addEventListener('click', () => {
+          td_bg.toggle()
+          if (td_bg.running) {
+            tdBG.style.background = 'yellow'
+          } else {
+            tdBG.style.background = 'transparent'
+          }
+        })
+
         // author
         let author = document.createElement('div')
         // author.style=`display: flex`
@@ -658,6 +697,7 @@ app.registerExtension({
 
         btns.appendChild(btn)
         btns.appendChild(download)
+        btns.appendChild(tdBG)
 
         document.body.appendChild(widget.div)
         this.addCustomWidget(widget)
@@ -671,6 +711,7 @@ app.registerExtension({
         this.serialize_widgets = true //需要保存参数
 
         window._mixlab_app_json = null
+ 
       }
 
       const onExecuted = nodeType.prototype.onExecuted
@@ -686,9 +727,8 @@ app.registerExtension({
           }
 
           const div = this.widgets.filter(w => w.div)[0].div
-          Array.from(
-            div.querySelectorAll('button'),
-            b => (b.style.background = 'yellow')
+          Array.from(div.querySelectorAll('button'), b =>
+            b.innerText != 'Canvas Mode' ? (b.style.background = 'yellow') : ''
           )
         } catch (error) {}
       }

web/javascript/audio_mixlab.js

@@ -396,3 +396,218 @@ app.registerExtension({
     }
   }
 })
+
+// 上传音频转为base64
+async function uploadAndConvertAudio (file) {
+  if (!file) {
+    alert('Please select a WAV file.')
+    return
+  }
+
+  if (file.type !== 'audio/wav') {
+    alert('Only WAV files are supported.')
+    return
+  }
+
+  try {
+    const base64Audio = await readFileAsDataURL(file)
+    return base64Audio
+  } catch (error) {
+    console.error('Error reading file:', error)
+    alert('Error reading file.')
+  }
+}
+
+function readFileAsDataURL (file) {
+  return new Promise((resolve, reject) => {
+    const reader = new FileReader()
+
+    reader.onload = function (event) {
+      resolve(event.target.result)
+    }
+
+    reader.onerror = function (error) {
+      reject(error)
+    }
+
+    reader.readAsDataURL(file)
+  })
+}
+
+const createInputAudioForBatch = (base64, widget) => {
+  // Create an audio element
+  let audio = document.createElement('audio')
+  audio.src = base64
+  audio.controls = true
+  audio.style = 'width: 120px; display: block'
+
+  // Create a delete button
+  let deleteButton = document.createElement('button')
+  deleteButton.textContent = 'Delete'
+
+  deleteButton.style = `cursor: pointer;
+        font-weight: 300;
+        margin: 2px; 
+        margin-left: 10px;
+        color: var(--descrip-text);
+        background-color: var(--comfy-input-bg);
+        border-radius: 8px;
+        border-color: var(--border-color);
+        border-style: solid;height: 30px;min-width: 122px;
+       `
+
+  // Create a container for the audio and delete button
+  let container = document.createElement('div')
+  container.appendChild(audio)
+  container.appendChild(deleteButton)
+  container.style = `display: flex;margin-top: 12px;`
+
+  // Add event listener for the delete button
+  deleteButton.addEventListener('click', e => {
+    let newValue = []
+    let items = widget.value?.base64 || []
+    for (const v of items) {
+      if (v != base64) newValue.push(v)
+    }
+    widget.value.base64 = newValue
+    container.remove()
+  })
+
+  return container
+}
+
+app.registerExtension({
+  name: 'Mixlab.Comfy.LoadAndCombinedAudio_',
+  async getCustomWidgets (app) {
+    return {
+      AUDIOBASE64 (node, inputName, inputData, app) {
+        // console.log('##node', node)
+        const widget = {
+          value: {
+            base64: []
+          }, // 不能[x,x,x]
+          type: inputData[0], // the type
+          name: inputName, // the name, slice
+          size: [128, 32], // a default size
+          draw (ctx, node, width, y) {},
+          computeSize (...args) {
+            return [128, 122] // a method to compute the current size of the widget
+          }
+          // serializeValue (nodeId, widgetIndex) {
+          //   return widget.value
+          // },
+        }
+        //  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 == 'LoadAndCombinedAudio_') {
+      const orig_nodeCreated = nodeType.prototype.onNodeCreated
+
+      nodeType.prototype.onNodeCreated = function () {
+        orig_nodeCreated?.apply(this, arguments)
+
+        let audiosWidget = this.widgets.filter(w => w.name == 'audios')[0]
+
+        const widget = {
+          type: 'div',
+          name: 'audio_base64',
+          draw (ctx, node, widget_width, y, widget_height) {
+            Object.assign(
+              this.div.style,
+              get_position_style(ctx, widget_width, 44, node.size[1])
+            )
+          },
+          serialize: false
+        }
+
+        widget.div = $el('div', {})
+
+        document.body.appendChild(widget.div)
+
+        let audioPreview = document.createElement('div')
+        let audiosDiv = document.createElement('div') //显示图片
+        audiosDiv.className = 'audios_preview'
+        audiosDiv.style = `width: calc(100% - 14px);
+        display: flex;
+        flex-wrap: wrap;
+        padding: 7px;    justify-content: space-between;
+        align-items: center;`
+
+        const btn = document.createElement('button')
+        btn.innerText = 'Upload Audio'
+
+        btn.style = `cursor: pointer;
+        font-weight: 300;
+        margin: 2px; 
+        color: var(--descrip-text);
+        background-color: var(--comfy-input-bg);
+        border-radius: 8px;
+        border-color: var(--border-color);
+        border-style: solid;height: 30px;min-width: 122px;
+       `
+
+        btn.addEventListener('click', e => {
+          e.preventDefault()
+          let inputAudio = document.createElement('input')
+          inputAudio.type = 'file'
+          inputAudio.accept = "audio/*"
+          inputAudio.style.display = 'none'
+          inputAudio.addEventListener('change', async e => {
+            e.preventDefault()
+            const file = e.target.files[0]
+            let base64 = await uploadAndConvertAudio(file)
+            if (!audiosWidget.value) audiosWidget.value = { base64: [] }
+            audiosWidget.value.base64.push(base64)
+
+            let a = createInputAudioForBatch(base64, audiosWidget)
+            audiosDiv.appendChild(a)
+          })
+
+          inputAudio.click()
+          inputAudio.remove()
+        })
+
+        widget.div.appendChild(audioPreview)
+        audioPreview.appendChild(audiosDiv)
+        audioPreview.appendChild(btn)
+        // audioPreview.appendChild(inputAudio)
+
+        this.addCustomWidget(widget)
+
+        // document.addEventListener('wheel', handleMouseWheel)
+
+        const onRemoved = this.onRemoved
+        this.onRemoved = () => {
+          widget.div.remove()
+          try {
+            // document.removeEventListener('wheel', handleMouseWheel)
+          } catch (error) {
+            console.log(error)
+          }
+
+          return onRemoved?.()
+        }
+
+        this.serialize_widgets = true //需要保存参数
+      }
+    }
+  },
+  async loadedGraphNode (node, app) {
+    if (node.type === 'LoadAndCombinedAudio_') {
+      // await sleep(0)
+      let audiosWidget = node.widgets.filter(w => w.name === 'audios')[0]
+      let audioPreview = node.widgets.filter(w => w.name == 'audio_base64')[0]
+
+      let pre = audioPreview.div.querySelector('.audios_preview')
+      for (const d of audiosWidget.value?.base64 || []) {
+        let im = createInputAudioForBatch(d, audiosWidget)
+        pre.appendChild(im)
+      }
+    }
+  }
+})

web/javascript/chat.js

@@ -2,7 +2,7 @@ async function* completion (url, messages, controller) {
   let data = {
     model: 'gpt-3.5-turbo-16k',
     messages,
-    temperature: 0.6,
+    temperature: 0.05,
     stream: true
   }
   // if (imageNode) {

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 = 'v0.26.0'
+const version = 'v0.34.0'
 
 fetch(`https://api.github.com/repos/${repoOwner}/${repoName}/releases/latest`)
   .then(response => response.json())

web/javascript/command.js

@@ -0,0 +1,689 @@
+function get_url () {
+  // 如果有缓存记录
+  let hostUrl = localStorage.getItem('_hostUrl') || ''
+  if (hostUrl) {
+    return hostUrl
+  }
+  let api_host = `${window.location.hostname}:${window.location.port}`
+  let api_base = ''
+  let url = `${window.location.protocol}//${api_host}${api_base}`
+  return url
+}
+
+function getFilenameAndCategoryFromUrl (url) {
+  const queryString = url.split('?')[1]
+  if (!queryString) {
+    return {}
+  }
+
+  const params = new URLSearchParams(queryString)
+
+  const filename = params.get('filename')
+    ? decodeURIComponent(params.get('filename'))
+    : null
+  const category = params.get('category')
+    ? decodeURIComponent(params.get('category') || '')
+    : ''
+
+  return { category, filename }
+}
+
+async function get_my_app (category = '', filename = null) {
+  let url = get_url()
+  const res = await fetch(`${url}/mixlab/workflow`, {
+    method: 'POST',
+    mode: 'cors', // 允许跨域请求
+    headers: {
+      'Content-Type': 'application/json'
+    },
+    body: JSON.stringify({
+      task: 'my_app',
+      filename,
+      category
+    })
+  })
+  let result = await res.json()
+  let data = []
+  try {
+    for (const res of result.data) {
+      let { output, app } = res.data
+      if (app.filename)
+        data.push({
+          ...app,
+          data: output,
+          date: res.date
+        })
+    }
+  } catch (error) {}
+
+  return data
+}
+
+async function getAppInit () {
+  const { category, filename } = getFilenameAndCategoryFromUrl(
+    window.location.href
+  )
+  return await get_my_app(category, filename)
+}
+
+function success (isSuccess, btn, text) {
+  isSuccess ? (btn.innerText = 'success') : text
+  setTimeout(() => {
+    btn.innerText = text
+  }, 5000)
+}
+
+async function interrupt () {
+  try {
+    await fetch(`${get_url()}/interrupt`, {
+      method: 'POST',
+      headers: {
+        'Content-Type': 'application/json'
+      },
+      body: undefined
+    })
+  } catch (error) {
+    console.error(error)
+  }
+  return true
+}
+
+async function getQueue (clientId) {
+  try {
+    const res = await fetch(`${get_url()}/queue`)
+    const data = await res.json()
+    return {
+      // Running action uses a different endpoint for cancelling
+      Running: Array.from(data.queue_running, prompt => {
+        if (prompt[3].client_id === clientId) {
+          let prompt_id = prompt[1]
+          return {
+            prompt_id,
+            remove: () => interrupt()
+          }
+        }
+      }),
+      Pending: data.queue_pending.map(prompt => ({ prompt }))
+    }
+  } catch (error) {
+    console.error(error)
+    return { Running: [], Pending: [] }
+  }
+}
+
+// 请求历史数据
+async function getPromptResult (category) {
+  let url = get_url()
+  try {
+    const response = await fetch(`${url}/mixlab/prompt_result`, {
+      method: 'POST',
+      headers: {
+        'Content-Type': 'application/json'
+      },
+      body: JSON.stringify({
+        action: 'all'
+      })
+    })
+
+    if (response.ok) {
+      const data = await response.json()
+      console.log('#getPromptResult:', category, data)
+
+      return data.result.filter(r => r.appInfo.category == category)
+      // 处理返回的数据
+    } else {
+      console.log('Error:', response.status)
+      // 处理错误情况
+    }
+  } catch (error) {
+    console.log('Error:', error)
+    // 处理异常情况
+  }
+}
+
+// 新的运行工作流的接口
+function queuePromptNew (filename, category, seed, input, client_id,apps=null) {
+  let url = get_url()
+  // var filename = "Text-to-Image_1.json", category = "";
+
+  // 随机seed
+  //  promptWorkflow = randomSeed(seed, promptWorkflow);
+  let d = { filename, category, seed, input, client_id }
+  if (apps) {
+    d.apps = apps
+  }
+
+  const data = JSON.stringify(d)
+  return new Promise((res, rej) => {
+    fetch(`${url}/mixlab/prompt`, {
+      method: 'POST',
+      headers: {
+        'Content-Type': 'application/json'
+      },
+      body: data
+    })
+      .then(response => {
+        if (!response.ok) {
+          // Handle HTTP error responses
+          if (response.status === 400) {
+            return response.json().then(errorData => {
+              // Process the error data
+              console.error('Error 400:', errorData)
+              alert(JSON.stringify(errorData, null, 2))
+              res(null)
+            })
+          }
+          throw new Error('Network response was not ok')
+        }
+        return response.json() // Process the response data
+      })
+      .then(data => {
+        // Handle the response data
+        console.log('Success:', data)
+        res(true)
+      })
+      .catch(error => {
+        // Handle fetch errors
+        console.error('Fetch error:', error)
+        res(null)
+      })
+  })
+}
+
+// 保存历史数据
+async function savePromptResult (data) {
+  let url = get_url()
+  try {
+    const response = await fetch(`${url}/mixlab/prompt_result`, {
+      method: 'POST',
+      headers: {
+        'Content-Type': 'application/json'
+      },
+      body: JSON.stringify({
+        action: 'save',
+        data
+      })
+    })
+
+    if (response.ok) {
+      const res = await response.json()
+      console.log('Response:', res)
+      return res
+      // 处理返回的数据
+    } else {
+      console.log('Error:', response.status)
+      // 处理错误情况
+    }
+  } catch (error) {
+    console.log('Error:', error)
+    // 处理异常情况
+  }
+}
+
+async function uploadImage (blob, fileType = '.png', filename) {
+  const body = new FormData()
+  body.append(
+    'image',
+    new File([blob], (filename || new Date().getTime()) + fileType)
+  )
+
+  const url = get_url()
+
+  const resp = await fetch(`${url}/upload/image`, {
+    method: 'POST',
+    body
+  })
+
+  let data = await resp.json()
+  // console.log(data)
+  let { name, subfolder } = data
+  let src = `${url}/view?filename=${encodeURIComponent(
+    name
+  )}&type=input&subfolder=${subfolder}&rand=${Math.random()}`
+
+  return { url: src, name }
+}
+
+async function uploadMask (arrayBuffer, imgurl) {
+  const body = new FormData()
+  const filename = 'clipspace-mask-' + performance.now() + '.png'
+
+  let original_url = new URL(imgurl)
+
+  const original_ref = { filename: original_url.searchParams.get('filename') }
+
+  let original_subfolder = original_url.searchParams.get('subfolder')
+  if (original_subfolder) original_ref.subfolder = original_subfolder
+
+  let original_type = original_url.searchParams.get('type')
+  if (original_type) original_ref.type = original_type
+
+  body.append('image', arrayBuffer, filename)
+  body.append('original_ref', JSON.stringify(original_ref))
+  body.append('type', 'input')
+  body.append('subfolder', 'clipspace')
+
+  const url = get_url()
+
+  const resp = await fetch(`${url}/upload/mask`, {
+    method: 'POST',
+    body
+  })
+
+  // console.log(resp)
+  let data = await resp.json()
+  let { name, subfolder, type } = data
+  let src = `${url}/view?filename=${encodeURIComponent(
+    name
+  )}&type=${type}&subfolder=${subfolder}&rand=${Math.random()}`
+
+  return { url: src, name: 'clipspace/' + name }
+}
+
+const parseImageToBase64 = 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)
+      })
+  })
+}
+
+function createImage (url) {
+  let im = new Image()
+  return new Promise((res, rej) => {
+    im.onload = () => res(im)
+    im.src = url
+  })
+}
+
+function convertImageToBlackBasedOnAlpha (image) {
+  const canvas = document.createElement('canvas')
+  const ctx = canvas.getContext('2d')
+
+  // Draw the image onto the canvas
+  canvas.width = image.width
+  canvas.height = image.height
+  ctx.drawImage(image, 0, 0)
+
+  // Get the image data from the canvas
+  const imageData = ctx.getImageData(0, 0, canvas.width, canvas.height)
+  const pixels = imageData.data
+
+  // Modify the RGB values based on the alpha channel
+  for (let i = 0; i < pixels.length; i += 4) {
+    const alpha = pixels[i + 3]
+    if (alpha !== 0) {
+      // Set non-transparent pixels to black
+      pixels[i] = 0 // Red
+      pixels[i + 1] = 0 // Green
+      pixels[i + 2] = 0 // Blue
+    }
+  }
+
+  // Put the modified image data back onto the canvas
+  ctx.putImageData(imageData, 0, 0)
+
+  // Convert the modified canvas to base64 data URL
+  const base64ImageData = canvas.toDataURL('image/png') // Replace 'png' with your desired image format
+
+  return base64ImageData
+}
+
+const blobToBase64 = blob => {
+  return new Promise((res, rej) => {
+    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)
+  })
+}
+
+function base64ToBlob (base64) {
+  // 去除base64编码中的前缀
+  const base64WithoutPrefix = base64.replace(/^data:image\/\w+;base64,/, '')
+
+  // 将base64编码转换为字节数组
+  const byteCharacters = atob(base64WithoutPrefix)
+
+  // 创建一个存储字节数组的数组
+  const byteArrays = []
+
+  // 将字节数组放入数组中
+  for (let offset = 0; offset < byteCharacters.length; offset += 1024) {
+    const slice = byteCharacters.slice(offset, offset + 1024)
+
+    const byteNumbers = new Array(slice.length)
+    for (let i = 0; i < slice.length; i++) {
+      byteNumbers[i] = slice.charCodeAt(i)
+    }
+
+    const byteArray = new Uint8Array(byteNumbers)
+    byteArrays.push(byteArray)
+  }
+
+  // 创建blob对象
+  const blob = new Blob(byteArrays, { type: 'image/png' }) // 根据实际情况设置MIME类型
+
+  return blob
+}
+
+async function calculateImageHash (blob) {
+  const buffer = await blob.arrayBuffer()
+  const hashBuffer = await crypto.subtle.digest('SHA-256', buffer)
+  const hashArray = Array.from(new Uint8Array(hashBuffer))
+  const hashHex = hashArray
+    .map(byte => byte.toString(16).padStart(2, '0'))
+    .join('')
+  return hashHex
+}
+
+// 获取 rembg 模型
+async function get_rembg_models () {
+  try {
+    const response = await fetch(`${get_url()}/mixlab/folder_paths`, {
+      method: 'POST',
+      headers: {
+        'Content-Type': 'application/json'
+      },
+      body: JSON.stringify({
+        type: 'rembg'
+      })
+    })
+
+    const data = await response.json()
+    // console.log(data)
+    return data.names
+  } catch (error) {
+    console.error(error)
+  }
+}
+
+//自动抠图
+async function run_rembg (model, base64) {
+  try {
+    const response = await fetch(`${get_url()}/mixlab/rembg`, {
+      method: 'POST',
+      headers: {
+        'Content-Type': 'application/json'
+      },
+      body: JSON.stringify({
+        model,
+        base64
+      })
+    })
+
+    const data = await response.json()
+    // console.log(data)
+    return data.data
+  } catch (error) {
+    console.error(error)
+  }
+}
+
+function copyHtmlWithImagesToClipboard (data, cb) {
+  // 创建一个临时div元素
+  const tempDiv = document.createElement('div')
+
+  // 将HTML字符串赋值给div的innerHTML属性
+  tempDiv.innerHTML = data
+
+  // 获取div中的所有图像元素
+  const images = tempDiv.getElementsByTagName('img')
+
+  // 遍历图像元素，并将图像数据转换为Base64编码
+  for (let i = 0; i < images.length; i++) {
+    const image = images[i]
+    const canvas = document.createElement('canvas')
+    const context = canvas.getContext('2d')
+
+    // 设置canvas尺寸与图像尺寸相同
+    canvas.width = image.width
+    canvas.height = image.height
+
+    // 在canvas上绘制图像
+    context.drawImage(image, 0, 0)
+
+    // 将canvas转换为Base64编码
+    const imageData = canvas.toDataURL()
+
+    // 将Base64编码替换图像元素的src属性
+    image.src = imageData
+  }
+
+  let richText = tempDiv.innerHTML
+
+  // 创建一个新的Blob对象，并将富文本字符串作为数据传递进去
+  const blob = new Blob([richText], { type: 'text/html' })
+
+  // 创建一个ClipboardItem对象，并将Blob对象添加到其中
+  const clipboardItem = new ClipboardItem({ 'text/html': blob })
+
+  // 使用Clipboard API将内容复制到剪贴板
+  navigator.clipboard
+    .write([clipboardItem])
+    .then(() => {
+      console.log('富文本已成功复制到剪贴板')
+      tempDiv.remove()
+      if (cb) cb(true)
+    })
+    .catch(error => {
+      console.error('复制到剪贴板失败:', error)
+      tempDiv.remove()
+      if (cb) cb(false)
+    })
+}
+
+function copyImagesToClipboard (html, cb) {
+  const tempDiv = document.createElement('div')
+  tempDiv.innerHTML = html
+  const images = tempDiv.querySelectorAll('img')
+  const promises = Array.from(images).map(image => {
+    return new Promise(resolve => {
+      const img = new Image()
+      img.src = image.src
+      img.onload = () => {
+        const canvas = document.createElement('canvas')
+        const context = canvas.getContext('2d')
+        canvas.width = img.width
+        canvas.height = img.height
+        context.drawImage(img, 0, 0)
+        canvas.toBlob(blob => {
+          const clipboardItem = new ClipboardItem({ 'image/png': blob })
+          navigator.clipboard
+            .write([clipboardItem])
+            .then(() => {
+              resolve()
+              tempDiv.remove()
+              if (cb) cb(true)
+            })
+            .catch(error => {
+              reject(error)
+              tempDiv.remove()
+              if (cb) cb(false)
+            })
+        })
+      }
+    })
+  })
+  Promise.all([...promises])
+    .then(() => {
+      console.log('所有图片已成功复制到剪贴板')
+      if (cb) cb(true)
+      tempDiv.remove()
+    })
+    .catch(error => {
+      console.error('复制到剪贴板失败:', error)
+      if (cb) cb(false)
+      tempDiv.remove()
+    })
+}
+
+function copyTextToClipboard (html, cb) {
+  const tempDiv = document.createElement('div')
+  tempDiv.innerHTML = html
+
+  const text = tempDiv.innerText
+  const textData = new ClipboardItem({
+    'text/plain': new Blob([text], { type: 'text/plain' })
+  })
+
+  navigator.clipboard
+    .write([textData])
+    .then(() => {
+      console.log('所有文本已成功复制到剪贴板', text)
+      if (cb) cb(true)
+      tempDiv.remove()
+    })
+    .catch(error => {
+      console.error('复制到剪贴板失败:', error)
+      if (cb) cb(false)
+      tempDiv.remove()
+    })
+}
+
+// ComfyUI\web\extensions\core\dynamicPrompts.js
+// 官方实现修改
+// Allows for simple dynamic prompt replacement
+// Inputs in the format {a|b} will have a random value of a or b chosen when the prompt is queued.
+
+/*
+ * Strips C-style line and block comments from a string
+ */
+function dynamicPrompts (prompt) {
+  prompt = prompt.replace(/\/\*[\s\S]*?\*\/|\/\/.*/g, '')
+  while (
+    prompt.replace('\\{', '').includes('{') &&
+    prompt.replace('\\}', '').includes('}')
+  ) {
+    const startIndex = prompt.replace('\\{', '00').indexOf('{')
+    const endIndex = prompt.replace('\\}', '00').indexOf('}')
+
+    const optionsString = prompt.substring(startIndex + 1, endIndex)
+    const options = optionsString.split('|')
+
+    const randomIndex = Math.floor(Math.random() * options.length)
+    const randomOption = options[randomIndex]
+
+    prompt =
+      prompt.substring(0, startIndex) +
+      randomOption +
+      prompt.substring(endIndex + 1)
+  }
+  return prompt
+}
+
+// 遍历所有组合,语法同 动态提示
+function generateAllCombinations (prompt) {
+  prompt = prompt.replace(/\/\*[\s\S]*?\*\/|\/\/.*/g, '')
+
+  // Helper function to get all combinations
+  function getAllCombinations (parts) {
+    if (parts.length === 0) return ['']
+    const [firstPart, ...restParts] = parts
+    const restCombinations = getAllCombinations(restParts)
+    const allCombinations = []
+
+    firstPart.forEach(option => {
+      restCombinations.forEach(combination => {
+        allCombinations.push(option + combination)
+      })
+    })
+
+    return allCombinations
+  }
+
+  // Split prompt into static parts and dynamic parts
+  let parts = []
+  let startIndex = 0
+
+  while (
+    prompt.replace('\\{', '').includes('{') &&
+    prompt.replace('\\}', '').includes('}')
+  ) {
+    startIndex = prompt.replace('\\{', '00').indexOf('{')
+    const endIndex = prompt.replace('\\}', '00').indexOf('}')
+    const staticPart = prompt.substring(0, startIndex)
+    const optionsString = prompt.substring(startIndex + 1, endIndex)
+    const options = optionsString.split('|')
+
+    parts.push([staticPart])
+    parts.push(options)
+
+    prompt = prompt.substring(endIndex + 1)
+  }
+
+  // Add the remaining static part
+  parts.push([prompt])
+
+  // Get all combinations
+  const combinations = getAllCombinations(parts)
+
+  return combinations
+}
+
+const _textNodes = [
+    'TextInput_',
+    'CLIPTextEncode',
+    'PromptSimplification',
+    'ChinesePrompt_Mix'
+  ],
+  _loraNodes = ['CheckpointLoaderSimple', 'LoraLoader'],
+  _numberNodes = ['FloatSlider', 'IntNumber'],
+  _slideNodes = ['PromptSlide'],
+  _imageNodes = [
+    'LoadImage',
+    'VHS_LoadVideo',
+    'ImagesPrompt_',
+    'LoadImagesToBatch'
+  ],
+  _colorNodes = ['Color'],
+  _audioNodes = ['LoadAndCombinedAudio_']
+
+export default {
+  get_url,
+  get_my_app,
+  getAppInit,
+  getFilenameAndCategoryFromUrl,
+  success,
+  interrupt,
+  getQueue,
+  queuePromptNew,
+  savePromptResult,
+  uploadImage,
+  uploadMask,
+  run_rembg,
+  get_rembg_models,
+  parseImageToBase64,
+  createImage,
+  convertImageToBlackBasedOnAlpha,
+  blobToBase64,
+  base64ToBlob,
+  calculateImageHash,
+  copyHtmlWithImagesToClipboard,
+  copyImagesToClipboard,
+  copyTextToClipboard,
+  dynamicPrompts,
+  generateAllCombinations,
+
+  _textNodes,
+  _loraNodes,
+  _numberNodes,
+  _slideNodes,
+  _imageNodes,
+  _colorNodes,
+  _audioNodes
+}

web/javascript/gpt_mixlab.js

@@ -199,6 +199,120 @@ app.registerExtension({
         url[id] || 'https://api.openai.com/v1'
     }
   }
+});
+
+
+app.registerExtension({
+  name: 'Mixlab.GPT.SiliconflowLLM',
+  async getCustomWidgets (app) {
+    return {
+      KEY (node, inputName, inputData, app) {
+        // console.log('##inputData', inputData)
+        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_api_key')
+            return data[node.id] || 'by 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 == 'SiliconflowLLM') {
+      const orig_nodeCreated = nodeType.prototype.onNodeCreated
+      nodeType.prototype.onNodeCreated = function () {
+        orig_nodeCreated?.apply(this, arguments)
+
+        const api_key = this.widgets.filter(w => w.name == 'api_key')[0]
+       
+        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, api_key.y, node.size[1])
+            )
+          }
+        }
+
+        widget.div = $el('div', {})
+
+        document.body.appendChild(widget.div)
+
+        const inputDiv = (key, placeholder) => {
+          let div = document.createElement('div')
+          const ip = document.createElement('input')
+          ip.type = placeholder === 'Key' ? 'password' : 'text'
+          ip.className = `${'comfy-multiline-input'} ${placeholder}`
+          div.style = `display: flex;
+          align-items: center; 
+          margin: 6px 8px;
+          margin-top: 0;`
+          ip.placeholder = placeholder
+          ip.value = placeholder
+
+          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)
+
+          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
+        }
+
+        let inputKey = inputDiv('_mixlab_api_key', 'Key') 
+
+        widget.div.appendChild(inputKey) 
+
+        this.addCustomWidget(widget)
+
+        const onRemoved = this.onRemoved
+        this.onRemoved = () => { 
+          inputKey.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 === 'SiliconflowLLM') {
+      let widget = node.widgets.filter(w => w.div)[0]
+
+      let apiKey = getLocalData('_mixlab_api_key');
+
+      let id = node.id
+ 
+      widget.div.querySelector('.Key').value = apiKey[id] || 'by Mixlab' 
+    }
+  }
 })
 
 app.registerExtension({
@@ -209,13 +323,16 @@ app.registerExtension({
         text = text.filter(t => t && t?.trim())
 
         if (this.widgets) {
+          // console.log('#ShowTextForGPT',this.widgets)
           // const pos = this.widgets.findIndex(w => w.name === 'text')
           for (let i = 0; i < this.widgets.length; i++) {
-            if (this.widgets[i].name == 'show_text') this.widgets[i].onRemove?.()
+            if (this.widgets[i].name == 'show_text')
+              this.widgets[i].onRemove?.()
+            console.log('#ShowTextForGPT', this.widgets[i])
           }
-          this.widgets.length = 1
+          this.widgets.length = 2
         }
-        // console.log('ShowTextForGPT',text)
+
         for (let list of text) {
           if (list) {
             // console.log('#####', list)
@@ -228,6 +345,8 @@ app.registerExtension({
             w.inputEl.readOnly = true
             w.inputEl.style.opacity = 0.6
 
+            // w.inputEl.style.display='none'
+
             try {
               if (typeof list != 'string') {
                 let data = JSON.parse(list)
@@ -280,5 +399,24 @@ app.registerExtension({
 
       this.serialize_widgets = true //需要保存参数
     }
+  },
+  async loadedGraphNode (node, app) {
+    if (node.type === 'ShowTextForGPT') {
+      let widget = node.widgets.filter(w => w.name == 'show_text')[0]
+
+      // if (widget.value) {
+      //   let [url, prompt] = widget.value
+
+      //   this[`wavesurfer_${node.id}`] = updateWaveWidgetValue(
+      //     node.widgets,
+      //     node.id,
+      //     url,
+      //     prompt,
+      //     this[`wavesurfer_${node.id}`]
+      //   )
+      // }
+
+      console.log('#loadedGraphNode', node)
+    }
   }
 })

web/javascript/image_mixlab.js

@@ -675,6 +675,17 @@ const createInputImageForBatch = (base64, widget) => {
   return im
 }
 
+// 添加新图片
+const addBase64ToWidgetForLoadImagesToBatch = (
+  base64,
+  imagesWidget,
+  imagesDiv
+) => {
+  imagesWidget.value.base64.push(base64)
+  let im = createInputImageForBatch(base64, imagesWidget)
+  imagesDiv.appendChild(im)
+}
+
 app.registerExtension({
   name: 'Mixlab.Comfy.LoadImagesToBatch',
   async getCustomWidgets (app) {
@@ -705,7 +716,6 @@ app.registerExtension({
 
   async beforeRegisterNodeDef (nodeType, nodeData, app) {
     if (nodeType.comfyClass == 'LoadImagesToBatch') {
-
       const orig_nodeCreated = nodeType.prototype.onNodeCreated
 
       nodeType.prototype.onNodeCreated = function () {
@@ -751,13 +761,18 @@ app.registerExtension({
             base64 = await loadImageToCanvas(base64)
             // console.log(base64)
             if (!imagesWidget.value) imagesWidget.value = { base64: [] }
-            imagesWidget.value.base64.push(base64)
-            let im = createInputImageForBatch(base64, imagesWidget)
-            imagesDiv.appendChild(im)
+            addBase64ToWidgetForLoadImagesToBatch(
+              base64,
+              imagesWidget,
+              imagesDiv
+            )
           }
           reader.readAsDataURL(file)
         })
 
+        // 如果是复制的，有数据 , 这个不生效，取不到数据， 需要在nodeCreated里获取
+        // console.log('#LoadImagesToBatch', imagesWidget.value?.base64)
+
         const btn = document.createElement('button')
         btn.innerText = 'Upload Image'
 
@@ -829,18 +844,36 @@ app.registerExtension({
       }
     }
   },
+
   async loadedGraphNode (node, app) {
     if (node.type === 'LoadImagesToBatch') {
-      // await sleep(0)
       let imagesWidget = node.widgets.filter(w => w.name === 'images')[0]
       let imagePreview = node.widgets.filter(w => w.name == 'image_base64')[0]
+      // console.log('#LoadImagesToBatch', imagesWidget.value?.base64)
+      let imagesDiv = imagePreview.div.querySelector('.images_preview')
 
-      let pre = imagePreview.div.querySelector('.images_preview')
       for (const d of imagesWidget.value?.base64 || []) {
         let im = createInputImageForBatch(d, imagesWidget)
-        pre.appendChild(im)
+        imagesDiv.appendChild(im)
       }
     }
+  },
+  nodeCreated (node, app) {
+    //数据延迟？？
+    setTimeout(() => {
+      console.log('#LoadImagesToBatch', node.type)
+      if (node.type === 'LoadImagesToBatch') {
+        let imagesWidget = node.widgets.filter(w => w.name === 'images')[0]
+        let imagePreview = node.widgets.filter(w => w.name == 'image_base64')[0]
+
+        let imagesDiv = imagePreview?.div?.querySelector('.images_preview')
+
+        for (const d of imagesWidget.value?.base64 || []) {
+          let im = createInputImageForBatch(d, imagesWidget)
+          imagesDiv.appendChild(im)
+        }
+      }
+    }, 1000)
   }
 })
 
@@ -868,8 +901,8 @@ app.registerExtension({
       const onNodeCreated = nodeType.prototype.onNodeCreated
       nodeType.prototype.onNodeCreated = function () {
         const r = onNodeCreated
-        ? onNodeCreated.apply(this, arguments)
-        : undefined
+          ? onNodeCreated.apply(this, arguments)
+          : undefined
 
         this.size = [400, this.size[1]]
         console.log('##onNodeCreated', this)
@@ -891,20 +924,15 @@ app.registerExtension({
         this.addCustomWidget(widget)
         this.serialize_widgets = true //需要保存参数
 
-
         const onRemoved = this.onRemoved
         this.onRemoved = () => {
           widget.div.remove()
           return onRemoved?.()
         }
 
-
-       return r
-
+        return r
       }
 
-     
-
       const onExecuted = nodeType.prototype.onExecuted
       nodeType.prototype.onExecuted = function (message) {
         onExecuted?.apply(this, arguments)
@@ -964,7 +992,7 @@ app.registerExtension({
             label: 'After'
           }
         ]
-        this.size=[this.size[0],300]
+        this.size = [this.size[0], 300]
       }
     }
   },
@@ -974,7 +1002,6 @@ app.registerExtension({
       // node.widgets[0].div.id = 'mix_comparingtowframes_' + node.id
       // if (node.widgets_values && node.widgets_values[0]) {
       //   node.widgets[0].div.innerHTML = ''
-
       //   let slider = new juxtapose.JXSlider(
       //     '#mix_comparingtowframes_' + node.id,
       //     node.widgets_values,

web/javascript/main_mixlab.js

@@ -1267,7 +1267,7 @@ app.registerExtension({
         })
 
         widget.PictureInPicture = $el('button', {
-          innerText: 'PictureInPicture',
+          innerText: 'Picture In Picture',
           style: {
             display: 'pictureInPictureEnabled' in document ? 'block' : 'none',
             cursor: 'pointer',

web/javascript/sound-lab.js

@@ -0,0 +1,295 @@
+import { app } from '../../../scripts/app.js'
+import { api } from '../../../scripts/api.js'
+import { ComfyWidgets } from '../../../scripts/widgets.js'
+import { $el } from '../../../scripts/ui.js'
+
+import WaveSurfer from 'https://cdn.jsdelivr.net/npm/wavesurfer.js@7/dist/wavesurfer.esm.js'
+
+function get_position_style (ctx, widget_width, y, node_height) {
+  const MARGIN = 4 // the margin around the html element
+
+  /* Create a transform that deals with all the scrolling and zooming */
+  const elRect = ctx.canvas.getBoundingClientRect()
+  const transform = new DOMMatrix()
+    .scaleSelf(
+      elRect.width / ctx.canvas.width,
+      elRect.height / ctx.canvas.height
+    )
+    .multiplySelf(ctx.getTransform())
+    .translateSelf(MARGIN, MARGIN + y)
+
+  return {
+    transformOrigin: '0 0',
+    transform: transform,
+    left: `0`,
+    top: '0',
+    cursor: 'pointer',
+    position: 'absolute',
+    maxWidth: `${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: `${node_height * 0.3 - MARGIN * 2}px`,
+    // background: '#EEEEEE',
+    display: 'flex',
+    flexDirection: 'column',
+    // alignItems: 'center',
+    justifyContent: 'space-around'
+  }
+}
+
+//把文件转为url访问
+const parseUrl = data => {
+  let { filename, subfolder, type, prompt } = data
+  return {
+    url: api.apiURL(
+      `/view?filename=${encodeURIComponent(
+        filename
+      )}&type=${type}&subfolder=${subfolder}${app.getPreviewFormatParam()}${app.getRandParam()}`
+    ),
+    prompt
+  }
+}
+
+const createWaveSurfer = (wavesurfer, id,url) => {
+  // Create an instance of WaveSurfer
+  if (wavesurfer) {
+    wavesurfer.destroy()
+  }
+  wavesurfer = WaveSurfer.create({
+    container: '#' + id,
+    waveColor: 'rgb(200, 0, 200)',
+    progressColor: 'rgb(100, 0, 100)',
+    // Set a bar width
+    barWidth: 10,
+    // Optionally, specify the spacing between bars
+    barGap: 2,
+    // And the bar radius
+    barRadius: 6,
+    url
+  })
+
+  wavesurfer._auto = true
+
+  // 监听播放结束事件，重新开始播放以实现循环播放
+  wavesurfer.on('finish', function () {
+    // console.log(wavesurfer)
+    if (wavesurfer._auto) wavesurfer.play()
+  })
+
+  wavesurfer.on('interaction', () => {
+    wavesurfer._auto = false
+    if (!wavesurfer.isPlaying()) wavesurfer.play()
+  })
+
+  // 获取当前播放时间的峰值
+  wavesurfer.on('audioprocess', () => {
+    if (wavesurfer.isPlaying()&&wavesurfer.getDecodedData()) {
+      const channelData = wavesurfer.getDecodedData().getChannelData(0); 
+      const currentTime = wavesurfer.getCurrentTime()
+      // console.log(wavesurfer)
+      const sampleRate = wavesurfer.getDecodedData().sampleRate
+
+      // 定义要分析的时间窗口（例如1秒）
+      const windowSize = 1
+      const startSample = Math.floor(currentTime * sampleRate)
+      const endSample = Math.min(
+        startSample + windowSize * sampleRate,
+        channelData.length
+      )
+
+      let peak = 0
+      for (let i = startSample; i < endSample; i++) {
+        const value = Math.abs(channelData[i])
+        if (value > peak) {
+          peak = value
+        }
+      }
+      // console.log('Current Peak:', peak)
+    }
+  })
+
+  return wavesurfer
+}
+
+//更新gui
+function updateWaveWidgetValue (widgets, id, url, prompt, wavesurfer) {
+  let widget = widgets.filter(w => w.name == 'AudioPlay')[0]
+  // 手动更新widget值
+  widget.value = [url, prompt]
+
+  if (widget.div) {
+    widget.div.querySelector('.wave').id = `AudioPlay_${id}`
+  }
+
+  wavesurfer = createWaveSurfer(wavesurfer, `AudioPlay_${id}`,url)
+
+  wavesurfer.on('ready', duration => {
+    console.log('Audio duration: ' + duration + ' seconds')
+    if (widget.div) {
+      widget.div.setAttribute('data-url', url)
+      widget.div.querySelector('.link').setAttribute('href', url)
+      widget.div.querySelector(
+        '.info'
+      ).innerHTML = `<span style="font-size: 12px;
+      margin: 8px;">${duration.toFixed(
+        2
+      )} seconds</span> <br><span style="font-size: 14px;">${prompt||''}</span> <br>`
+    }
+  })
+  
+  
+  wavesurfer.load(url)
+  // console.log('updateWaveWidgetValue' ,url,wavesurfer)
+  return wavesurfer
+}
+
+app.registerExtension({
+  name: 'SoundLab.AudioPlay',
+  async beforeRegisterNodeDef (nodeType, nodeData, app) {
+    if (nodeType.comfyClass == 'AudioPlay') {
+      let that = this
+      // console.log('that', that)
+
+      const orig_nodeCreated = nodeType.prototype.onNodeCreated
+      nodeType.prototype.onNodeCreated = function () {
+        orig_nodeCreated?.apply(this, arguments)
+
+        const widget = {
+          type: 'div',
+          name: 'AudioPlay',
+          draw (ctx, node, widget_width, y, widget_height) {
+            Object.assign(
+              this.div.style,
+              get_position_style(ctx, widget_width, y, node.size[1])
+            )
+          }
+        }
+
+        // console.log('AudioPlay nodeData', this)
+        widget.div = $el('div', {})
+
+        document.body.appendChild(widget.div)
+
+        // wave
+        const waveDiv = document.createElement('div')
+        waveDiv.className = 'wave'
+        waveDiv.style.minHeight = '172px'
+        widget.div.appendChild(waveDiv)
+
+        //prompt 相关信息展示
+        const infoDiv = document.createElement('div')
+        infoDiv.className = 'info'
+        infoDiv.style.marginBottom = '20px'
+        widget.div.appendChild(infoDiv)
+
+        // 按钮的区域
+        let btns = document.createElement('div')
+        btns.className = 'btns'
+        btns.style = `display: flex;
+        width: 100%;
+        justify-content: space-between;`
+        widget.div.appendChild(btns)
+
+        //play button
+        const playBtn = document.createElement('a')
+        playBtn.innerText = 'Play/Pause'
+
+        playBtn.style = `
+        display: flex;
+        padding: 4px 15px;
+        background-color: var(--comfy-input-bg);
+        border-radius: 8px;
+        border-color: var(--border-color);
+        border-style: solid;
+        color: var(--descrip-text);
+        text-decoration: none;
+        border-radius: 5px;
+        transition: background-color 0.3s ease 0s;
+          `
+
+        playBtn.addEventListener('click', e => {
+          e.preventDefault()
+          if (that[`wavesurfer_${this.id}`]) {
+            that[`wavesurfer_${this.id}`]?.playPause()
+            that[`wavesurfer_${this.id}`]._auto = true
+          }
+        })
+        btns.appendChild(playBtn)
+
+        const urlLink = document.createElement('a')
+        urlLink.className = 'link'
+        urlLink.innerText = 'URL'
+        urlLink.setAttribute('target', '_blank')
+        urlLink.style = `display: flex;
+        padding: 4px 15px;
+        background-color: var(--comfy-input-bg);
+        border-radius: 8px;
+        border-color: var(--border-color);
+        border-style: solid;
+        color: var(--descrip-text);
+        text-decoration: none;
+        border-radius: 5px;
+        transition: background-color 0.3s ease 0s;`
+        // urlLink.style.minHeight = '200px'
+        btns.appendChild(urlLink)
+
+
+        //todo 导出视频 that[`wavesurfer_${this.id}`].renderer.exportImage('image/png',1,'dataURL')
+        // https://github.com/diffusion-studio/ffmpeg-js
+
+
+        this.addCustomWidget(widget)
+
+        const onRemoved = this.onRemoved
+        this.onRemoved = () => {
+          widget.div.remove()
+          return onRemoved?.()
+        }
+
+        this.size = [this.size[0], 280]
+        this.serialize_widgets = true //需保存widget的值
+      }
+
+      const onExecuted = nodeType.prototype.onExecuted
+      nodeType.prototype.onExecuted = function (message) {
+        onExecuted?.apply(this, arguments)
+        const audio = message.audio
+        console.log('#onExecuted', `AudioPlay_${this.id}`, message,audio)
+        try {
+          let { url, prompt } = parseUrl(audio[0])
+
+          that[`wavesurfer_${this.id}`] = updateWaveWidgetValue(
+            this.widgets,
+            this.id,
+            url,
+            prompt,
+            that[`wavesurfer_${this.id}`]
+          )
+
+          that[`wavesurfer_${this.id}`]?.playPause()
+        } catch (error) {
+          console.log(error)
+        }
+      }
+    }
+  },
+  async loadedGraphNode (node, app) {
+    if (node.type === 'AudioPlay') {
+      let widget = node.widgets.filter(w => w.name == 'AudioPlay')[0]
+
+      if (widget.value) {
+        let [url, prompt] = widget.value
+
+        this[`wavesurfer_${node.id}`] = updateWaveWidgetValue(
+          node.widgets,
+          node.id,
+          url,
+          prompt,
+          this[`wavesurfer_${node.id}`]
+        )
+      }
+
+      console.log('#loadedGraphNode', node)
+    }
+  }
+})

web/javascript/td_background.js

@@ -0,0 +1,323 @@
+// touchdesigner的背景效果，把appinfo的输出，选择一张图片作为背景
+
+window._bg_img = null
+
+/**
+ * draws the back canvas (the one containing the background and the connections)
+ * @method drawBackCanvas
+ **/
+LGraphCanvas.prototype.drawBackCanvas = function () {
+  var canvas = this.bgcanvas
+  if (
+    canvas.width != this.canvas.width ||
+    canvas.height != this.canvas.height
+  ) {
+    canvas.width = this.canvas.width
+    canvas.height = this.canvas.height
+  }
+
+  if (!this.bgctx) {
+    this.bgctx = this.bgcanvas.getContext('2d')
+  }
+  var ctx = this.bgctx
+  if (ctx.start) {
+    ctx.start()
+  }
+
+  var viewport = this.viewport || [0, 0, ctx.canvas.width, ctx.canvas.height]
+
+  //clear
+  if (this.clear_background) {
+    ctx.clearRect(viewport[0], viewport[1], viewport[2], viewport[3])
+  }
+
+  //show subgraph stack header
+  if (this._graph_stack && this._graph_stack.length) {
+    ctx.save()
+    var parent_graph = this._graph_stack[this._graph_stack.length - 1]
+    var subgraph_node = this.graph._subgraph_node
+    ctx.strokeStyle = subgraph_node.bgcolor
+    ctx.lineWidth = 10
+    ctx.strokeRect(1, 1, canvas.width - 2, canvas.height - 2)
+    ctx.lineWidth = 1
+    ctx.font = '40px Arial'
+    ctx.textAlign = 'center'
+    ctx.fillStyle = subgraph_node.bgcolor || '#AAA'
+    var title = ''
+    for (var i = 1; i < this._graph_stack.length; ++i) {
+      title += this._graph_stack[i]._subgraph_node.getTitle() + ' >> '
+    }
+    ctx.fillText(title + subgraph_node.getTitle(), canvas.width * 0.5, 40)
+    ctx.restore()
+  }
+
+  var bg_already_painted = false
+  if (this.onRenderBackground) {
+    bg_already_painted = this.onRenderBackground(canvas, ctx)
+  }
+
+  //reset in case of error
+  if (!this.viewport) {
+    ctx.restore()
+    ctx.setTransform(1, 0, 0, 1, 0, 0)
+  }
+  this.visible_links.length = 0
+
+  if (this.graph) {
+    //apply transformations
+    ctx.save()
+    this.ds.toCanvasContext(ctx)
+
+    //render BG
+    if (
+      this.ds.scale < 1 &&
+      !bg_already_painted &&
+      this.clear_background_color
+    ) {
+      ctx.fillStyle = this.clear_background_color
+      ctx.fillRect(
+        this.visible_area[0],
+        this.visible_area[1],
+        this.visible_area[2],
+        this.visible_area[3]
+      )
+    }
+
+    // 主要修改
+    if (this.background_image && this.ds.scale > 0.5 && !bg_already_painted) {
+      if (this.zoom_modify_alpha) {
+        //使得 alpha 越接近0时变化越缓慢。
+        let alpha = (1.0 - 0.5 / this.ds.scale) * this.editor_alpha
+        ctx.globalAlpha = Math.min(Math.max(0, Math.sqrt(alpha)), 1)
+        // console.log((1.0 - 0.5 / this.ds.scale) * this.editor_alpha)
+      } else {
+        ctx.globalAlpha = this.editor_alpha
+      }
+      ctx.imageSmoothingEnabled = ctx.imageSmoothingEnabled = false // ctx.mozImageSmoothingEnabled =
+      if (!this._bg_img || this._bg_img.name != this.background_image) {
+        this._bg_img = new Image()
+        this._bg_img.name = this.background_image
+        this._bg_img.src = this.background_image
+        var that = this
+        this._bg_img.onload = function () {
+          that.draw(true, true)
+        }
+      }
+
+      var pattern = null
+      if (this._pattern == null && this._bg_img.width > 0) {
+        pattern = ctx.createPattern(this._bg_img, 'repeat')
+        this._pattern_img = this._bg_img
+        this._pattern = pattern
+      } else {
+        pattern = this._pattern
+      }
+
+      if (pattern) {
+        ctx.fillStyle = pattern
+        ctx.fillRect(
+          this.visible_area[0],
+          this.visible_area[1],
+          this.visible_area[2],
+          this.visible_area[3]
+        )
+        ctx.fillStyle = 'transparent'
+      }
+
+      ctx.globalAlpha = 1.0
+      ctx.imageSmoothingEnabled = ctx.imageSmoothingEnabled = true //= ctx.mozImageSmoothingEnabled
+    }
+
+    //groups
+    if (this.graph._groups.length && !this.live_mode) {
+      this.drawGroups(canvas, ctx)
+    }
+
+    if (this.onDrawBackground) {
+      this.onDrawBackground(ctx, this.visible_area)
+    }
+    if (this.onBackgroundRender) {
+      //LEGACY
+      console.error(
+        'WARNING! onBackgroundRender deprecated, now is named onDrawBackground '
+      )
+      this.onBackgroundRender = null
+    }
+
+    //DEBUG: show clipping area
+    //ctx.fillStyle = "red";
+    //ctx.fillRect( this.visible_area[0] + 10, this.visible_area[1] + 10, this.visible_area[2] - 20, this.visible_area[3] - 20);
+
+    //bg
+    if (this.render_canvas_border) {
+      ctx.strokeStyle = '#235'
+      ctx.strokeRect(0, 0, canvas.width, canvas.height)
+    }
+
+    if (this.render_connections_shadows) {
+      ctx.shadowColor = '#000'
+      ctx.shadowOffsetX = 0
+      ctx.shadowOffsetY = 0
+      ctx.shadowBlur = 6
+    } else {
+      ctx.shadowColor = 'rgba(0,0,0,0)'
+    }
+
+    //draw connections
+    if (!this.live_mode) {
+      this.drawConnections(ctx)
+    }
+
+    ctx.shadowColor = 'rgba(0,0,0,0)'
+
+    //restore state
+    ctx.restore()
+  }
+
+  if (ctx.finish) {
+    ctx.finish()
+  }
+
+  this.dirty_bgcanvas = false
+  this.dirty_canvas = true //to force to repaint the front canvas with the bgcanvas
+}
+
+function imgToCanvasBase64 (img) {
+  const canvas = document.createElement('canvas')
+  const ctx = canvas.getContext('2d')
+  canvas.width = img.width
+  canvas.height = img.height
+  ctx.drawImage(img, 0, 0)
+  const base64 = canvas.toDataURL('image/png')
+
+  return base64
+}
+
+// 使用示例
+function convertImageToBase64 (img) {
+  //   const img = new Image()
+  //   img.src = 'path/to/your/image.jpg' // 替换为你的图片路径
+  // console.log('convertImageToBase64',img)
+  try {
+    const base64 = imgToCanvasBase64(img)
+    return base64
+  } catch (error) {
+    console.error(error)
+  }
+}
+
+function getInputsAndOutputs () {
+  const outputs =
+    `PreviewImage,SaveImage,TransparentImage,VHS_VideoCombine,VideoCombine_Adv,Image Save,SaveImageAndMetadata_`.split(
+      ','
+    )
+
+  let outputsId = []
+
+  for (let node of app.graph._nodes) {
+    if (outputs.includes(node.type)) {
+      outputsId.push(node.id)
+    }
+  }
+
+  return outputsId
+}
+
+function getRandomElement (arr) {
+  const randomIndex = Math.floor(Math.random() * arr.length)
+  return arr[randomIndex]
+}
+
+async function getBG () {
+  var outputs = []
+
+  for (let id of app.graph
+    .getNodeById(50)
+    .widgets.filter(w => w.name === 'output_ids')[0]
+    .value.split('\n')) {
+    if (getInputsAndOutputs().map(Number).includes(Number(id))) {
+      if (app.graph.getNodeById(id).imgs && app.graph.getNodeById(id).imgs[0]) {
+        let b = convertImageToBase64(app.graph.getNodeById(id).imgs[0])
+        // console.log(b)
+        outputs.push(b)
+      }
+    }
+  }
+
+  var BACKGROUND_IMAGE = getRandomElement(outputs),
+    CLEAR_BACKGROUND_COLOR = 'rgba(0,0,0,0.9)'
+
+  if (!window._bg_img) {
+    window._bg_img = app.canvas._bg_img.src
+  }
+  // let img=new Image();
+  // img.src=BACKGROUND_IMAGE;
+
+  //去掉透明度过度
+  // app.canvas.zoom_modify_alpha=false;
+  //整体透明度
+  app.canvas.editor_alpha = 1.1
+  //   app.canvas._pattern=ctx.createPattern(img, "no-repeat");
+  app.canvas.updateBackground(BACKGROUND_IMAGE, CLEAR_BACKGROUND_COLOR)
+  app.canvas.draw(true, true)
+}
+
+class BgRunner {
+  constructor () {
+    this.intervalId = null
+    this.running = false
+  }
+
+  // 要运行的方法
+  bg () {
+    console.log('方法bg正在运行')
+    getBG()
+  }
+
+  // 启动bg方法每秒运行一次
+  start () {
+    if (!this.running) {
+      this.intervalId = setInterval(() => this.bg(), 1500)
+      this.running = true
+    }
+  }
+
+  // 停止bg方法的运行
+  stop () {
+    if (this.running) {
+      clearInterval(this.intervalId)
+      this.intervalId = null
+      this.running = false
+
+      if (window._bg_img) {
+        var BACKGROUND_IMAGE = window._bg_img,
+          CLEAR_BACKGROUND_COLOR = 'rgba(0,0,0,1)'
+        app.canvas.editor_alpha = 1
+
+        app.canvas.updateBackground(BACKGROUND_IMAGE, CLEAR_BACKGROUND_COLOR)
+        app.canvas.draw(true, true)
+      }
+    }
+  }
+
+  // 切换start和stop
+  toggle () {
+    if (this.running) {
+      this.stop()
+    } else {
+      this.start()
+    }
+  }
+
+  // 获取运行状态
+  isRunning () {
+    return this.running
+  }
+}
+
+// 示例用法
+// const runner = new BgRunner();
+// runner.start();
+// setTimeout(() => runner.stop(), 5000);
+
+export const td_bg = new BgRunner()

web/javascript/ui_mixlab.js

@@ -26,7 +26,35 @@ function showTextByLanguage (key, json) {
 }
 
 //系统prompt
-const systemPrompt = `You are a prompt creator, your task is to create prompts for the user input request, the prompts are image descriptions that include keywords for (an adjective, type of image, framing/composition, subject, subject appearance/action, environment, lighting situation, details of the shoot/illustration, visuals aesthetics and artists), brake keywords by comas, provide high quality, non-verboose, coherent, brief, concise, and not superfluous prompts, the subject from the input request must be included verbatim on the prompt,the prompt is english`
+// const systemPrompt = `You are a prompt creator, your task is to create prompts for the user input request, the prompts are image descriptions that include keywords for (an adjective, type of image, framing/composition, subject, subject appearance/action, environment, lighting situation, details of the shoot/illustration, visuals aesthetics and artists), brake keywords by comas, provide high quality, non-verboose, coherent, brief, concise, and not superfluous prompts, the subject from the input request must be included verbatim on the prompt,the prompt is english`
+
+let tool ={
+  "name": "create_prompt",
+  "description": "Create a prompt with a given subject, content, and style based on user input for image descriptions.",
+  "parameter": {
+    "type": "object",
+    "properties": {
+      "subject": {
+        "type": "string",
+        "description": "The subject of the prompt, included verbatim from the input request.",
+        "required": true
+      },
+      "content": {
+        "type": "string",
+        "description": "The content of the prompt, primarily focusing on the scene and objects, including keywords for adjective, type of image, framing/composition, subject appearance/action, and environment.",
+        "required": true
+      },
+      "style": {
+        "type": "string",
+        "description": "The style of the prompt, including lighting situation, details of the shoot/illustration, visual aesthetics, and artists. Ensure it is high quality, non-verbose, coherent, brief, concise, and not superfluous.",
+        "required": true
+      }
+    }
+  }
+}
+
+const systemPrompt=`You are a helpful assistant with access to the following functions. Use them if required - ${JSON.stringify(tool,null,2)}`
+
 
 if (!localStorage.getItem('_mixlab_system_prompt')) {
   localStorage.setItem('_mixlab_system_prompt', systemPrompt)
@@ -46,7 +74,7 @@ async function get_llamafile_models () {
     })
 
     const data = await response.json()
-    console.log(data)
+    // console.log(data)
     return data.names
   } catch (error) {
     console.error(error)
@@ -72,7 +100,7 @@ async function start_llama (model = 'Phi-3-mini-4k-instruct-Q5_K_S.gguf') {
     })
 
     const data = await response.json()
-    if (data.llama_cpp_error) {
+    if (data.llama_cpp_error||!data.port) {
       return
     }
 
@@ -135,17 +163,20 @@ async function createMenu () {
 
     // appsButton.onclick = () =>
     appsButton.onclick = async () => {
-      if (window._mixlab_llamacpp) {
-        //显示运行的模型
-        createModelsModal([
-          window._mixlab_llamacpp.url,
-          window._mixlab_llamacpp.model
-        ])
-      } else {
-        let ms = await get_llamafile_models()
-        ms = ms.filter(m => !m.match('-mmproj-'))
-        if (ms.length > 0) createModelsModal(ms)
-      }
+      // if (window._mixlab_llamacpp&&window._mixlab_llamacpp.model&&window._mixlab_llamacpp.model.length>0) {
+      //   //显示运行的模型
+      //   createModelsModal([
+      //     window._mixlab_llamacpp.url,
+      //     window._mixlab_llamacpp.model
+      //   ])
+      // } else {
+      //   // let ms = await get_llamafile_models()
+      //   // ms = ms.filter(m => !m.match('-mmproj-'))
+      //   // if (ms.length > 0) createModelsModal(ms)
+      // }
+      createModelsModal([
+      
+      ])
     }
     menu.append(appsButton)
   }
@@ -539,7 +570,6 @@ injectCSS(`::-webkit-scrollbar {
   border-left: 2px solid var(--input-text); 
 }
  
-
 `)
 
 async function getCustomnodeMappings (mode = 'url') {
@@ -771,6 +801,22 @@ async function fetchReadmeContent (url) {
   }
 }
 
+async function startLLM (model) {
+  let res = await start_llama(model)
+  window._mixlab_llamacpp = res||{ model:[] }
+
+  localStorage.setItem('_mixlab_llama_select', res?.model||'')
+
+  if (document.body.querySelector('#mixlab_chatbot_by_llamacpp')&&window._mixlab_llamacpp?.url) {
+    document.body
+      .querySelector('#mixlab_chatbot_by_llamacpp')
+      .setAttribute('title', window._mixlab_llamacpp.url)
+  }
+  if (document.body.querySelector('#llm_status_btn')&&window._mixlab_llamacpp) {
+    document.body.querySelector('#llm_status_btn').innerText = window._mixlab_llamacpp.model
+  }
+}
+
 function createModelsModal (models) {
   var div =
     document.querySelector('#model-modal') || document.createElement('div')
@@ -826,7 +872,7 @@ function createModelsModal (models) {
       color: var(--descrip-text);
       font-size: 18px;
       display: flex;
-      align-items: center;
+      align-items: flex-start;
       flex: 1;
       overflow: hidden;
       text-decoration: none;
@@ -845,6 +891,27 @@ function createModelsModal (models) {
   })
   linkIcon.style.padding = '4px'
 
+  const statusIcon = document.createElement('small')
+  statusIcon.textContent = showTextByLanguage('Status', {
+    Status: 'OFF'
+  })
+  statusIcon.id = 'llm_status_btn'
+  statusIcon.style=`padding: 4px;
+  background-color: rgb(102, 255, 108);
+  color: black;
+  font-size: 12px;
+  margin-left: 12px;`
+  if (window._mixlab_llamacpp?.url) {
+    statusIcon.textContent = window._mixlab_llamacpp.model
+    statusIcon.style.backgroundColor = '#66ff6c'
+    statusIcon.style.color = 'black'
+  } else {
+  }
+  statusIcon.addEventListener('click', e => {
+    e.stopPropagation()
+    // startLLM()
+  })
+
   const n_gpu = document.createElement('input')
   n_gpu.type = 'number'
   n_gpu.setAttribute('min', -1)
@@ -868,31 +935,33 @@ function createModelsModal (models) {
   const n_gpu_p = document.createElement('p')
   n_gpu_p.innerText = 'n_gpu_layers'
 
-  const n_gpu_div = document.createElement('div')
-  n_gpu_div.style = `display: flex;
+  const batchPageBtn = document.createElement('div')
+  batchPageBtn.style = `display: flex;
   justify-content: center;
   align-items: center;
   font-size: 12px;`
-  n_gpu_div.appendChild(n_gpu_p)
-  n_gpu_div.appendChild(n_gpu)
+  batchPageBtn.innerHTML=`<a href="${get_url()}/mixlab/app" target="_blank" style="color: var(--input-text);
+  background-color: var(--comfy-input-bg);">App</a>`
 
   const title = document.createElement('p')
-  title.innerText = 'Models'
+  title.innerText = 'Mixlab Nodes'
   title.style = `font-size: 18px;
-  margin-right: 8px;`
+  margin-right: 8px;
+  margin-top: 0;`
 
   const left_d = document.createElement('div')
   left_d.style = `display: flex;
   justify-content: center;
-  align-items: center;
-  font-size: 12px;`
+  align-items: flex-start;
+  font-size: 12px;
+  flex-direction: column; `
   left_d.appendChild(title)
-
-  left_d.appendChild(linkIcon)
-
+  // title.appendChild(statusIcon)
+  // left_d.appendChild(linkIcon)
+  left_d.appendChild(batchPageBtn)
   headTitleElement.appendChild(left_d)
 
-  headTitleElement.appendChild(n_gpu_div)
+  // headTitleElement.appendChild(n_gpu_div)
 
   //重启
   const reStart = document.createElement('small')
@@ -900,7 +969,11 @@ function createModelsModal (models) {
     restart: '重启'
   })
 
-  reStart.style.padding = '4px'
+  reStart.style=`padding: 8px;
+  font-size: 16px;
+  outline: 1px solid;
+  padding-top: 4px;
+  padding-bottom: 4px;`
 
   headTitleElement.appendChild(reStart)
 
@@ -940,48 +1013,41 @@ function createModelsModal (models) {
   var modalContent = document.createElement('div')
   modalContent.classList.add('modal-content')
 
-  var input = document.createElement('textarea')
-  input.className = 'comfy-multiline-input'
-  input.style = `    height: 260px;
+  var inputForSystemPrompt = document.createElement('textarea')
+  inputForSystemPrompt.className = 'comfy-multiline-input'
+  inputForSystemPrompt.style = `    height: 260px;
   width: 480px;
   font-size: 16px;
   padding: 18px;`
-  input.value = localStorage.getItem('_mixlab_system_prompt')
+  inputForSystemPrompt.value = localStorage.getItem('_mixlab_system_prompt')
 
-  input.addEventListener('change', e => {
+  inputForSystemPrompt.addEventListener('change', e => {
     e.stopPropagation()
-    localStorage.setItem('_mixlab_system_prompt', input.value)
+    localStorage.setItem('_mixlab_system_prompt', inputForSystemPrompt.value)
   })
 
-  input.addEventListener('click', e => {
+  inputForSystemPrompt.addEventListener('click', e => {
     e.stopPropagation()
   })
 
-  modalContent.appendChild(input)
+  // modalContent.appendChild(inputForSystemPrompt)
 
-  for (const m of models) {
-    let d = document.createElement('div')
-    d.innerText = m
-    d.className = `mix_tag`
+  if (!window._mixlab_llamacpp||(window._mixlab_llamacpp?.model?.length==0)) {
+    for (const m of models) {
+      let d = document.createElement('div')
+      d.innerText = `${showTextByLanguage('Run', {
+        Run: '运行'
+      })} ${m}`
+      d.className = `mix_tag`
 
-    if (!window._mixlab_llamacpp) {
       d.addEventListener('click', async e => {
         e.stopPropagation()
         div.remove()
-        let res = await start_llama(m)
-        window._mixlab_llamacpp = res
-
-        localStorage.setItem('_mixlab_llama_select', res.model)
-
-        if (document.body.querySelector('#mixlab_chatbot_by_llamacpp')) {
-          document.body
-            .querySelector('#mixlab_chatbot_by_llamacpp')
-            .setAttribute('title', window._mixlab_llamacpp.url)
-        }
+        // startLLM(m)
       })
-    }
 
-    modalContent.appendChild(d)
+      // modalContent.appendChild(d)
+    }
   }
   modal.appendChild(modalContent)
 
@@ -995,8 +1061,8 @@ function createModelsModal (models) {
   cursor: pointer;
   font-size: 12px;
   color: white;`
-  helpInfo.href="https://discord.gg/cXs9vZSqeK"
-  helpInfo.target="_blank"
+  helpInfo.href = 'https://discord.gg/cXs9vZSqeK'
+  helpInfo.target = '_blank'
   modal.appendChild(helpInfo)
 
   document.body.appendChild(div)
@@ -1350,6 +1416,8 @@ app.registerExtension({
           .querySelector('#mixlab_chatbot_by_llamacpp')
           .setAttribute('title', res.url)
       })
+    }else{
+      // startLLM('')
     }
 
     LGraphCanvas.prototype.helpAboutNode = async function (node) {
@@ -1358,7 +1426,13 @@ app.registerExtension({
           ? nodesMap
           : await getCustomnodeMappings('url')
 
-      console.log('node & node map', node, nodesMap, nodesMap[node.type])
+      console.log(
+        '%c### node & node map',
+        'background: yellow; color: black',
+        node,
+        nodesMap,
+        nodesMap[node.type]
+      )
       let repo = nodesMap[node.type]
       if (repo) {
         let markdown = await fetchReadmeContent(repo.url)
@@ -1368,10 +1442,14 @@ app.registerExtension({
 
     LGraphCanvas.prototype.fixTheNode = function (node) {
       let new_node = LiteGraph.createNode(node.comfyClass)
-      new_node.pos = [node.pos[0], node.pos[1]]
-      app.canvas.graph.add(new_node, false)
-      copyNodeValues(node, new_node)
-      app.canvas.graph.remove(node)
+      console.log(node)
+      if(new_node){
+        new_node.pos = [node.pos[0], node.pos[1]]
+        app.canvas.graph.add(new_node, false)
+        copyNodeValues(node, new_node)
+        app.canvas.graph.remove(node)
+      }
+     
     }
 
     smart_init()
@@ -1389,6 +1467,7 @@ app.registerExtension({
         let userInput = widget.value
         widget.value = widget.value.trim()
         widget.value += '\n'
+        let jsonStr="";
         try {
           await completion_(
             window._mixlab_llamacpp.url + '/v1/chat/completions',
@@ -1403,6 +1482,7 @@ app.registerExtension({
             t => {
               // console.log(t)
               widget.value += t
+              jsonStr+=t
             }
           )
         } catch (error) {
@@ -1428,13 +1508,27 @@ app.registerExtension({
                 t => {
                   // console.log(t)
                   widget.value += t
+                  jsonStr+=t
                 }
               )
             })
           }
         }
 
-        widget.value = widget.value.trim()
+        let json=null;
+
+        try {
+          json=JSON.parse(jsonStr.trim())
+        } catch (error) {
+          json=JSON.parse(jsonStr.trim()+"}")
+        }
+
+        if(json){
+          widget.value = [json.subject,json.content,json.style].join('\n')
+        }else{
+          widget.value = widget.value.trim()
+        }
+        
       }
     }
 
@@ -1697,6 +1791,7 @@ app.registerExtension({
         {
           content: 'Help ♾️Mixlab', // with a name
           callback: () => {
+            // console.log('#data',node)
             LGraphCanvas.prototype.helpAboutNode(node)
           } // and the callback
         },

web/javascript/utils_mixlab.js

@@ -1,5 +1,5 @@
 import { app } from '../../../scripts/app.js'
-import { $el } from '../../../scripts/ui.js' 
+import { $el } from '../../../scripts/ui.js'
 
 const getLocalData = key => {
   let data = {}
@@ -122,7 +122,7 @@ app.registerExtension({
       nodeType.prototype.onNodeCreated = function () {
         orig_nodeCreated?.apply(this, arguments)
 
-        // console.log('Color nodeData', this.widgets)
+        console.log('Color nodeData', this.div)
 
         const widget = {
           type: 'div',
@@ -273,19 +273,19 @@ app.registerExtension({
 })
 
 const min_max = node => {
-  if(node.widgets){
+  if (node.widgets) {
     const min_value = node.widgets.filter(w => w.name === 'min_value')[0]
     const max_value = node.widgets.filter(w => w.name === 'max_value')[0]
-  
+
     const number = node.widgets.filter(w => w.name === 'number')[0]
     if (number) {
       number.options.min = min_value.value
       number.options.max = max_value.value
-  
+
       number.value = Math.min(number.options.max, number.value)
       number.value = Math.max(number.options.min, number.value)
     }
-  
+
     if (min_value)
       min_value.callback = e => {
         number.options.min = e
@@ -297,22 +297,18 @@ const min_max = node => {
         number.value = e
       }
   }
-  
 }
 
 app.registerExtension({
   name: 'Mixlab.utils.FloatSlider',
   async beforeRegisterNodeDef (nodeType, nodeData, app) {
-
     if (nodeType.comfyClass == 'FloatSlider') {
-      const orig_nodeCreated = nodeType.prototype.onNodeCreated;
+      const orig_nodeCreated = nodeType.prototype.onNodeCreated
       nodeType.prototype.onNodeCreated = function () {
         orig_nodeCreated?.apply(this, arguments)
         min_max(this)
       }
     }
-
-   
   },
   async loadedGraphNode (node, app) {
     if (node.type === 'FloatSlider') {
@@ -323,7 +319,6 @@ app.registerExtension({
 app.registerExtension({
   name: 'Mixlab.utils.IntNumber',
   async beforeRegisterNodeDef (nodeType, nodeData, app) {
-    
     if (nodeType.comfyClass == 'IntNumber') {
       const orig_nodeCreated = nodeType.prototype.onNodeCreated
       nodeType.prototype.onNodeCreated = function () {
@@ -331,7 +326,6 @@ app.registerExtension({
         min_max(this)
       }
     }
-   
   },
   async loadedGraphNode (node, app) {
     if (node.type === 'IntNumber') {
@@ -340,22 +334,128 @@ app.registerExtension({
   }
 })
 
-
 app.registerExtension({
   name: 'Mixlab.utils.TESTNODE_',
   async beforeRegisterNodeDef (nodeType, nodeData, app) {
-    
     if (nodeType.comfyClass == 'TESTNODE_') {
-    
-      const onExecuted = nodeType.prototype.onExecuted;
-			nodeType.prototype.onExecuted = function (message) {
-				onExecuted?.apply(this, arguments);
-        console.log('##',message)
-				 
-			};
-
-
+      const onExecuted = nodeType.prototype.onExecuted
+      nodeType.prototype.onExecuted = function (message) {
+        onExecuted?.apply(this, arguments)
+        console.log('##', message)
+      }
     }
-   
-  }, 
+  }
+})
+
+app.registerExtension({
+  name: 'Mixlab.utils.KeyInput',
+  init () {},
+  async getCustomWidgets (app) {
+    return {
+      KEY (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_api_key')
+            return data[node.id] || 'by 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 == 'KeyInput') {
+      const orig_nodeCreated = nodeType.prototype.onNodeCreated
+      nodeType.prototype.onNodeCreated = function () {
+        orig_nodeCreated?.apply(this, arguments)
+
+        const widget = {
+          type: 'div',
+          name: 'key_inp',
+          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 = $el('div', {})
+
+        const inputDiv = (key, placeholder) => {
+          let div = document.createElement('div')
+          const ip = document.createElement('input')
+          ip.type = placeholder === 'Key' ? 'password' : 'text'
+          ip.className = `${'comfy-multiline-input'} ${placeholder}`
+          div.style = `display: flex;
+          align-items: center; 
+          margin: 6px 8px;
+          margin-top: 0;`
+          ip.placeholder = placeholder
+          ip.value = placeholder
+
+          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)
+
+          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
+        }
+
+        let inputKey = inputDiv('_mixlab_api_key', 'Key') 
+
+        widget.div.appendChild(inputKey) 
+
+        this.addCustomWidget(widget)
+ 
+        console.log('KeyInput nodeData',widget.div)
+
+      
+        const onRemoved = this.onRemoved
+        this.onRemoved = () => {
+          inputKey.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 === 'KeyInput') {
+      let widget = node.widgets.filter(w => w.div)[0]
+
+      let apiKey = getLocalData('_mixlab_api_key');
+
+      let id = node.id
+ 
+      widget.div.querySelector('.Key').value = apiKey[id] || 'by Mixlab' 
+    }
+  }
 })

web/javascript/video_mixlab.js

@@ -6,8 +6,6 @@ import { $el } from '../../../scripts/ui.js'
 
 // The code is based on ComfyUI-VideoHelperSuite modification.
 
-
-
 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')
@@ -240,15 +238,7 @@ app.registerExtension({
   }
 })
 
-
-function offsetDOMWidget(
-  widget,
-  ctx,
-  node,
-  widgetWidth,
-  widgetY,
-  height
-) {
+function offsetDOMWidget (widget, ctx, node, widgetWidth, widgetY, height) {
   const margin = 10
   const elRect = ctx.canvas.getBoundingClientRect()
   const transform = new DOMMatrix()
@@ -270,18 +260,18 @@ function offsetDOMWidget(
     position: 'absolute',
     background: !node.color ? '' : node.color,
     color: !node.color ? '' : 'white',
-    zIndex: 5, //app.graph._nodes.indexOf(node),
+    zIndex: 5 //app.graph._nodes.indexOf(node),
   })
 }
 
-export const hasWidgets = (node) => {
+export const hasWidgets = node => {
   if (!node.widgets || !node.widgets?.[Symbol.iterator]) {
     return false
   }
   return true
 }
 
-export const cleanupNode = (node) => {
+export const cleanupNode = node => {
   if (!hasWidgets(node)) {
     return
   }
@@ -298,43 +288,43 @@ export const cleanupNode = (node) => {
   }
 }
 
-const CreatePreviewElement = (name, val, format) => {
-  const [type] = format.split('/')  
+const createPreviewElement = (name, val, format) => {
+  const [type] = format.split('/')
   const w = {
-      name,
-      type,
-      value: val,
-      draw: function (ctx, node, widgetWidth, widgetY, height) {
-        const [cw, ch] = this.computeSize(widgetWidth)
-        offsetDOMWidget(this, ctx, node, widgetWidth, widgetY, ch)
-      },
-      computeSize: function (_) {
-        const ratio = this.inputRatio || 1
-        const width = Math.max(220, this.parent.size[0])
-        return [width, (width / ratio + 10)]
-      },
-      onRemoved: function () {
-        if (this.inputEl) {
-          this.inputEl.remove()
-        }
-      },
+    name,
+    type,
+    value: val,
+    draw: function (ctx, node, widgetWidth, widgetY, height) {
+      const [cw, ch] = this.computeSize(widgetWidth)
+      offsetDOMWidget(this, ctx, node, widgetWidth, widgetY, ch)
+    },
+    computeSize: function (_) {
+      const ratio = this.inputRatio || 1
+      const width = Math.max(220, this.parent.size[0])
+      return [width, width / ratio + 10]
+    },
+    onRemoved: function () {
+      if (this.inputEl) {
+        this.inputEl.remove()
+      }
     }
-
-    w.inputEl = document.createElement(type === 'video' ? 'video' : 'img')
-    w.inputEl.src = w.value
-    if (type === 'video') {
-      w.inputEl.setAttribute('type', 'video/webm');
-      w.inputEl.autoplay = true
-      w.inputEl.loop = true
-      w.inputEl.controls = false;
-    }
-    w.inputEl.onload = function () {
-      w.inputRatio = w.inputEl.naturalWidth / w.inputEl.naturalHeight
-    }
-    document.body.appendChild(w.inputEl)
-    return w
   }
 
+  w.inputEl = document.createElement(type === 'video' ? 'video' : 'img')
+  w.inputEl.src = w.value
+
+  if (type === 'video' || format.match('.mp4')) {
+    w.inputEl.setAttribute('type', 'video/webm')
+    w.inputEl.autoplay = true
+    w.inputEl.loop = true
+    w.inputEl.controls = true
+  }
+  w.inputEl.onload = function () {
+    w.inputRatio = w.inputEl.naturalWidth / w.inputEl.naturalHeight
+  }
+  document.body.appendChild(w.inputEl)
+  return w
+}
 
 app.registerExtension({
   name: 'Mixlab.Video.ImageListReplace',
@@ -469,12 +459,17 @@ app.registerExtension({
       }
     }
 
-    if (nodeData?.name == 'VideoCombine_Adv') {
+    if (
+      nodeData?.name == 'VideoCombine_Adv' ||
+      nodeData?.name == 'CombineAudioVideo'
+    ) {
       const onExecuted = nodeType.prototype.onExecuted
       nodeType.prototype.onExecuted = function (message) {
         const prefix = 'vhs_gif_preview_'
         const r = onExecuted ? onExecuted.apply(this, message) : undefined
 
+        if(!this.widgets) this.widgets=[]
+
         if (this.widgets) {
           const pos = this.widgets.findIndex(w => w.name === `${prefix}_0`)
           if (pos !== -1) {
@@ -489,12 +484,13 @@ app.registerExtension({
                 '/view?' + new URLSearchParams(params).toString()
               )
               const w = this.addCustomWidget(
-                CreatePreviewElement(
+                createPreviewElement(
                   `${prefix}_${i}`,
                   previewUrl,
                   params.format || 'image/gif'
                 )
               )
+              console.log(w)
               w.parent = this
             })
           }

web/lib/miniPaint-4.14.2/dist/bundle.js.LICENSE.txt

@@ -0,0 +1,47 @@
+/*
+object-assign
+(c) Sindre Sorhus
+@license MIT
+*/
+
+/*!
+
+pica
+https://github.com/nodeca/pica
+
+*/
+
+/*!
+ * Block below copied from Protovis: http://mbostock.github.com/protovis/
+ * Copyright 2010 Stanford Visualization Group
+ * Licensed under the BSD License: http://www.opensource.org/licenses/bsd-license.php
+ * @license
+ */
+
+/*!
+ * jQuery JavaScript Library v3.7.1
+ * https://jquery.com/
+ *
+ * Copyright OpenJS Foundation and other contributors
+ * Released under the MIT license
+ * https://jquery.org/license
+ *
+ * Date: 2023-08-28T13:37Z
+ */
+
+/*!
+ * quantize.js Copyright 2008 Nick Rabinowitz.
+ * Licensed under the MIT license: http://www.opensource.org/licenses/mit-license.php
+ * @license
+ */
+
+/*! alertifyjs - v1.13.1 - Mohammad Younes <Mohammad@alertifyjs.com> (http://alertifyjs.com) */
+
+/*! regenerator-runtime -- Copyright (c) 2014-present, Facebook, Inc. -- license (MIT): https://github.com/facebook/regenerator/blob/main/LICENSE */
+
+/**
+ * hermite-resize - Canvas image resize/resample using Hermite filter with JavaScript.
+ * @version v2.2.10
+ * @link https://github.com/viliusle/miniPaint
+ * @license MIT
+ */

web/lib/miniPaint-4.14.2/dist/bundle.js.map

@@ -0,0 +1 @@
+{"version":3,"file":"bundle.js","sources":["webpack://miniPaint/bundle.js"],"mappings":";AAAA","sourceRoot":""}

web/lib/miniPaint-4.14.2/images/favicon.svg

@@ -0,0 +1,13 @@
+<?xml version="1.0" encoding="iso-8859-1"?>
+<!-- Generator: Adobe Illustrator 18.1.1, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<svg version="1.1" id="Capa_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 viewBox="0 0 298.73 298.73" style="enable-background:new 0 0 298.73 298.73;" xml:space="preserve">
+<g>
+	<path style="fill:#010002;" d="M264.959,9.35H33.787C15.153,9.35,0,24.498,0,43.154v212.461c0,18.634,15.153,33.766,33.787,33.766
+		h231.171c18.634,0,33.771-15.132,33.771-33.766V43.154C298.73,24.498,283.593,9.35,264.959,9.35z M193.174,59.623
+		c18.02,0,32.634,14.615,32.634,32.634s-14.615,32.634-32.634,32.634c-18.025,0-32.634-14.615-32.634-32.634
+		S175.149,59.623,193.174,59.623z M254.363,258.149H149.362H49.039c-9.013,0-13.027-6.521-8.964-14.566l56.006-110.93
+		c4.058-8.044,11.792-8.762,17.269-1.605l56.316,73.596c5.477,7.158,15.05,7.767,21.386,1.354l13.777-13.951
+		c6.331-6.413,15.659-5.619,20.826,1.762l35.675,50.959C266.487,252.16,263.376,258.149,254.363,258.149z"/>
+</g>
+</svg>

web/lib/miniPaint-4.14.2/images/icons/animation.svg

@@ -0,0 +1,13 @@
+<?xml version="1.0" encoding="iso-8859-1"?>
+<!-- Generator: Adobe Illustrator 18.1.1, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<svg version="1.1" id="Capa_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 viewBox="0 0 30.051 30.051" style="enable-background:new 0 0 30.051 30.051;" xml:space="preserve">
+<g>
+	<path d="M19.982,14.438l-6.24-4.536c-0.229-0.166-0.533-0.191-0.784-0.062c-0.253,0.128-0.411,0.388-0.411,0.669v9.069
+		c0,0.284,0.158,0.543,0.411,0.671c0.107,0.054,0.224,0.081,0.342,0.081c0.154,0,0.31-0.049,0.442-0.146l6.24-4.532
+		c0.197-0.145,0.312-0.369,0.312-0.607C20.295,14.803,20.177,14.58,19.982,14.438z"/>
+	<path d="M15.026,0.002C6.726,0.002,0,6.728,0,15.028c0,8.297,6.726,15.021,15.026,15.021c8.298,0,15.025-6.725,15.025-15.021
+		C30.052,6.728,23.324,0.002,15.026,0.002z M15.026,27.542c-6.912,0-12.516-5.601-12.516-12.514c0-6.91,5.604-12.518,12.516-12.518
+		c6.911,0,12.514,5.607,12.514,12.518C27.541,21.941,21.937,27.542,15.026,27.542z"/>
+</g>
+</svg>

web/lib/miniPaint-4.14.2/images/icons/arrow-down.svg

@@ -0,0 +1,5 @@
+<svg width="124" height="150" viewBox="0 0 124 150" xmlns="http://www.w3.org/2000/svg">
+<rect x="55" y="14" width="14" height="63"/>
+<rect x="116" width="14" height="61" transform="rotate(90 116 0)"/>
+<path d="M62 150L8.30643 75L115.694 75L62 150Z"/>
+</svg>

web/lib/miniPaint-4.14.2/images/icons/blur.svg

@@ -0,0 +1,28 @@
+<?xml version="1.0" encoding="iso-8859-1"?>
+<!-- Generator: Adobe Illustrator 19.0.0, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<svg version="1.1" id="Layer_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 viewBox="0 0 512 512" style="enable-background:new 0 0 512 512;" xml:space="preserve">
+<g>
+	<g>
+		<path d="M264.574,4.675C262.697,1.761,259.467,0,256,0c-3.467,0-6.697,1.761-8.574,4.675
+			c-6.532,10.14-159.966,249.362-159.966,338.784C87.459,436.393,163.066,512,256,512s168.541-75.607,168.541-168.541
+			C424.541,254.037,271.106,14.815,264.574,4.675z M256,491.602c-81.686,0-148.142-66.456-148.142-148.143
+			c0-34.037,26.926-101.269,77.865-194.427C213.83,97.626,242.219,51.324,256,29.29c13.77,22.016,42.123,68.259,70.223,119.64
+			c50.976,93.212,77.92,160.478,77.92,194.529C404.142,425.146,337.686,491.602,256,491.602z"/>
+	</g>
+</g>
+<g>
+	<g>
+		<path d="M375.907,332.939c-5.633,0-10.199,4.566-10.199,10.199c0,43.197-25.482,82.521-64.919,100.181
+			c-5.141,2.301-7.442,8.335-5.14,13.476c1.695,3.788,5.416,6.034,9.314,6.034c1.393,0,2.809-0.287,4.163-0.893
+			c46.764-20.941,76.981-67.572,76.981-118.797C386.106,337.505,381.54,332.939,375.907,332.939z"/>
+	</g>
+</g>
+<g>
+	<g>
+		<path d="M281.818,460.702c-0.729-5.586-5.85-9.519-11.435-8.791c-4.736,0.619-9.574,0.933-14.383,0.933
+			c-5.633,0-10.199,4.566-10.199,10.199c0,5.633,4.566,10.199,10.199,10.199c5.69,0,11.419-0.372,17.028-1.106
+			C278.613,471.407,282.548,466.287,281.818,460.702z"/>
+	</g>
+</g>
+</svg>

web/lib/miniPaint-4.14.2/images/icons/bold.svg

@@ -0,0 +1,4 @@
+<?xml version="1.0" encoding="iso-8859-1"?>
+<svg width="1em" height="1em" viewBox="0 0 16 16" fill="currentColor" xmlns="http://www.w3.org/2000/svg">
+	<path d="M8.21 13c2.106 0 3.412-1.087 3.412-2.823 0-1.306-.984-2.283-2.324-2.386v-.055a2.176 2.176 0 0 0 1.852-2.14c0-1.51-1.162-2.46-3.014-2.46H3.843V13H8.21zM5.908 4.674h1.696c.963 0 1.517.451 1.517 1.244 0 .834-.629 1.32-1.73 1.32H5.908V4.673zm0 6.788V8.598h1.73c1.217 0 1.88.492 1.88 1.415 0 .943-.643 1.449-1.832 1.449H5.907z"/>
+</svg>

web/lib/miniPaint-4.14.2/images/icons/brush.svg

@@ -0,0 +1 @@
+<svg height="443pt" viewBox="0 0 443.06138 443" width="443pt" xmlns="http://www.w3.org/2000/svg"><path d="m431.328125 25.894531-14.136719-14.136719c-8.070312-8.078124-19.210937-12.320312-30.613281-11.6601558-11.402344.6601558-21.976563 6.1640628-29.058594 15.1249998l-117.023437 164.839844c-4.089844 5.761719-10.511719 9.425781-17.554688 10.019531-7.039062.59375-13.984375-1.945312-18.980468-6.941406l-34.234376-34.207031c-9.480468-9.109375-24.46875-9.109375-33.949218 0l-11.296875 11.304687 158.398437 158.398438 11.304688-11.304688c4.527344-4.488281 7.070312-10.597656 7.070312-16.96875 0-6.375-2.542968-12.484375-7.070312-16.972656l-34.222656-34.234375c-4.996094-4.996094-7.535157-11.941406-6.941407-18.980469.59375-7.042969 4.257813-13.464843 10.019531-17.554687l165-117.183594c8.890626-7.109375 14.332032-17.671875 14.960938-29.035156.628906-11.367188-3.617188-22.464844-11.671875-30.507813zm-24 43.808594c-9.375 9.371094-24.570313 9.371094-33.945313 0-9.371093-9.375-9.371093-24.574219 0-33.945313 9.496094-9.0625 24.441407-9.0625 33.9375 0 9.375 9.371094 9.378907 24.570313.007813 33.945313zm0 0"/><path d="m390.351562 44.734375c-3.234374 0-6.152343 1.949219-7.390624 4.9375-1.234376 2.988281-.550782 6.429687 1.734374 8.71875 3.160157 3.03125 8.148438 3.03125 11.304688 0 2.289062-2.289063 2.972656-5.730469 1.734375-8.71875s-4.15625-4.9375-7.390625-4.9375zm0 0"/><path d="m135.792969 420.429688 22.65625 22.65625 113.085937-113.167969-158.398437-158.402344-113.136719 113.121094 22.65625 22.65625 84.847656-84.855469c2.007813-2.078125 4.984375-2.914062 7.78125-2.183594 2.796875.734375 4.980469 2.917969 5.710938 5.714844.734375 2.796875-.101563 5.773438-2.179688 7.78125l-84.847656 84.855469 22.632812 22.625 50.902344-50.90625c3.140625-3.03125 8.128906-2.988281 11.214844.097656s3.128906 8.078125.097656 11.214844l-50.90625 50.921875 22.617188 22.621094 62.214844-62.222657c3.125-3.125 8.191406-3.128906 11.316406-.003906 3.128906 3.125 3.128906 8.191406.003906 11.316406l-62.222656 62.222657 22.625 22.625 73.535156-73.535157c3.140625-3.03125 8.128906-2.988281 11.214844.097657 3.085937 3.085937 3.128906 8.074218.097656 11.214843zm0 0"/></svg>

web/lib/miniPaint-4.14.2/images/icons/bulge_pinch.svg

@@ -0,0 +1,17 @@
+<?xml version="1.0" encoding="iso-8859-1"?>
+<!-- Generator: Adobe Illustrator 19.0.0, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<svg version="1.1" id="Capa_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 viewBox="0 0 402.56 402.56" style="enable-background:new 0 0 402.56 402.56;" xml:space="preserve">
+<g>
+	<g>
+		<polygon points="38.613,234.88 38.4,274.56 96.64,274.56 116.693,265.173 9.6,372.48 39.68,402.56 147.2,295.253 137.813,316.587 
+			137.813,373.76 177.493,374.187 177.493,234.88 		"/>
+	</g>
+</g>
+<g>
+	<g>
+		<polygon points="306.987,128.213 285.653,137.6 392.96,30.08 362.88,0 255.573,107.307 264.96,87.04 264.96,28.8 225.28,29.013 
+			225.28,167.893 364.587,167.893 364.16,128.213 		"/>
+	</g>
+</g>
+</svg>

web/lib/miniPaint-4.14.2/images/icons/clone.svg

@@ -0,0 +1,21 @@
+<?xml version="1.0" encoding="iso-8859-1"?>
+<!-- Generator: Adobe Illustrator 19.1.0, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<svg version="1.1" id="Capa_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 viewBox="0 0 540.721 540.721" style="enable-background:new 0 0 540.721 540.721;" xml:space="preserve">
+<g>
+	<g>
+		<path d="M521.858,465.271H18.862c-7.545,0-12.575,5.03-12.575,12.575v50.3c0,7.545,5.03,12.575,12.575,12.575h502.996
+			c7.545,0,12.575-5.03,12.575-12.575v-50.3C534.433,470.301,529.403,465.271,521.858,465.271z"/>
+		<path d="M227.606,98.084c5.03-5.03,20.12-12.575,30.18-12.575c7.545,0,12.575-5.03,12.575-12.575c0-7.545-5.03-10.06-12.575-10.06
+			l0,0c-17.605,0-37.725,7.545-47.785,17.605c-12.575,10.06-22.635,27.665-22.635,47.785c0,7.545,5.03,10.06,12.575,10.06l0,0
+			c7.545,0,12.575-2.515,12.575-10.06C212.516,118.204,220.061,103.114,227.606,98.084z"/>
+		<path d="M18.862,440.121h502.996c5.03,0,7.545-2.515,10.06-5.03c2.515-2.515,2.515-7.545,0-12.575l-47.785-100.599
+			c0-5.03-5.03-7.545-10.06-7.545H333.235v-77.964c25.15-20.12,60.359-60.36,60.359-110.659C393.594,55.33,338.265,0,270.36,0
+			S147.126,57.845,147.126,125.749c-2.515,47.785,35.21,88.024,60.36,110.659v77.964H66.647c-5.03,0-10.06,2.515-10.06,7.545
+			L8.802,422.517c-2.515,5.03-2.515,7.545,0,12.575C11.317,440.121,13.832,440.121,18.862,440.121z M169.761,125.749
+			c0-55.33,45.27-100.599,98.084-100.599c52.815,0,98.084,45.27,98.084,100.599c0,37.725-27.665,75.449-55.33,93.054
+			c-2.515,2.515-5.03,5.03-5.03,10.06v123.234c0,2.515-12.575,10.06-22.635,10.06h-37.725c-7.545,0-15.09-7.545-15.09-10.06V228.863
+			c0-5.03-2.515-7.545-5.03-10.06C207.486,206.228,169.761,168.504,169.761,125.749z"/>
+	</g>
+</g>
+</svg>

web/lib/miniPaint-4.14.2/images/icons/crop.svg

@@ -0,0 +1,17 @@
+<?xml version="1.0" encoding="iso-8859-1"?>
+<!-- Generator: Adobe Illustrator 16.0.0, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd">
+<svg version="1.1" id="Capa_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 width="956.815px" height="956.815px" viewBox="0 0 956.815 956.815" style="enable-background:new 0 0 956.815 956.815;"
+	 xml:space="preserve">
+<g>
+	<path d="M137.621,162.622H20c-11.046,0-20,8.954-20,20v72.919c0,11.046,8.954,20,20,20h117.622L137.621,162.622L137.621,162.622z"
+		/>
+	<path d="M774.193,956.815c11.046,0,20-8.954,20-20V819.193H681.274v117.621c0,11.046,8.954,20,20,20L774.193,956.815
+		L774.193,956.815z"/>
+	<path d="M794.193,656.275V182.622c0-11.046-8.954-20-20-20H300.54v112.919h380.734v380.734H794.193z"/>
+	<path d="M936.814,681.275H794.193H681.274H275.54V275.541V162.622V20c0-11.046-8.954-20-20-20h-72.918c-11.046,0-20,8.954-20,20
+		v142.622v112.919v498.653c0,11.046,8.954,20,20,20h498.653h112.918h142.622c11.045,0,20-8.954,20-20v-72.918
+		C956.814,690.229,947.86,681.275,936.814,681.275z"/>
+</g>
+</svg>

web/lib/miniPaint-4.14.2/images/icons/delete.svg

@@ -0,0 +1,6 @@
+<svg height="365pt" viewBox="0 0 365.71733 365" width="365pt" xmlns="http://www.w3.org/2000/svg">
+	<g fill="#f44336">
+		<path d="m356.339844 296.347656-286.613282-286.613281c-12.5-12.5-32.765624-12.5-45.246093 0l-15.105469 15.082031c-12.5 12.503906-12.5 32.769532 0 45.25l286.613281 286.613282c12.503907 12.5 32.769531 12.5 45.25 0l15.082031-15.082032c12.523438-12.480468 12.523438-32.75.019532-45.25zm0 0"/>
+		<path d="m295.988281 9.734375-286.613281 286.613281c-12.5 12.5-12.5 32.769532 0 45.25l15.082031 15.082032c12.503907 12.5 32.769531 12.5 45.25 0l286.632813-286.59375c12.503906-12.5 12.503906-32.765626 0-45.246094l-15.082032-15.082032c-12.5-12.523437-32.765624-12.523437-45.269531-.023437zm0 0"/>
+	</g>
+</svg>

web/lib/miniPaint-4.14.2/images/icons/desaturate.svg

@@ -0,0 +1,7 @@
+<?xml version="1.0" encoding="utf-8"?>
+<!-- Svg Vector Icons : http://www.onlinewebfonts.com/icon -->
+<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd">
+<svg version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px" viewBox="0 0 1000 1000" enable-background="new 0 0 1000 1000" xml:space="preserve">
+<metadata> Svg Vector Icons : http://www.onlinewebfonts.com/icon </metadata>
+<g><g transform="translate(0.000000,511.000000) scale(0.100000,-0.100000)"><path d="M2646.5,3789.8c-1040.2-119.8-2106-953.5-2445-1917.3l-91.8-260.1L102,355.5c-5.1-1081-2.5-1279.9,33.1-1415c155.5-609.4,578.8-986.7,1282.4-1139.7c300.9-66.3,670.5-96.9,1534.8-127.5c400.3-12.7,831.2-43.3,961.2-63.7c464-76.5,836.3-229.5,1448.1-599.2c698.6-420.7,1063.2-550.7,1682.7-599.2c234.6-17.9,645,20.4,866.9,81.6c494.6,132.6,1007.1,476.8,1341.1,902.6c318.7,405.4,484.4,749.6,589,1223.8c53.5,255,56.1,313.6,58.6,1527.2c0,1155-5.1,1274.8-45.9,1415c-186.1,596.6-609.4,917.9-1374.2,1045.3c-135.1,22.9-550.7,51-963.7,63.7c-1560.3,53.5-1828,112.2-2957.5,662.9c-685.8,334-928,415.6-1328.3,458.9C2944.8,3820.4,2919.3,3820.4,2646.5,3789.8z M3378.2,3165.2c255-51,461.5-135.1,1014.7-413c543.1-270.3,821-382.4,1213.6-487c311-84.2,798-155.5,1042.8-155.5c142.8,0,158.1-5.1,234.6-91.8c112.2-124.9,214.2-163.2,420.7-163.2c193.8,0,359.5,61.2,423.2,153c40.8,56.1,48.5,58.6,328.9,43.3c894.9-51,1249.3-328.9,1246.7-971.4c0-117.3-7.6-247.3-17.8-288.1c-30.6-147.9-94.3-331.4-168.3-494.6l-76.5-168.3l-158.1-12.7c-379.9-30.6-563.4-270.3-372.2-487l73.9-86.7l-81.6-76.5c-211.6-198.9-527.8-359.5-843.9-428.3c-160.6-35.7-272.8-43.3-560.9-30.6c-555.8,20.4-777.6,99.4-1494,525.2C5111.9-174.8,4857-52.4,4482.2,70c-410.5,137.7-685.8,175.9-1402.3,206.5c-1287.5,51-1596,86.7-1891.8,219.3c-191.2,84.1-379.9,288.1-443.6,471.7c-66.3,193.8-58.6,471.7,17.9,696l61.2,175.9l155.5,5.1c226.9,5.1,402.8,119.8,433.4,280.5c20.4,107.1,0,168.3-84.1,249.9l-66.3,66.3l61.2,66.3c249.9,267.7,808.2,571.1,1200.8,657.8C2745.9,3213.6,3143.6,3213.6,3378.2,3165.2z M3391-391.5c221.8-112.2,397.7-351.8,362-492.1c-51-211.6-418.1-183.6-657.8,51C2972.8-712.8,2921.8-610.8,2932-496c5.1,79.1,22.9,102,96.9,137.7C3130.9-307.4,3240.5-317.6,3391-391.5z M1328.3-414.5c140.2-86.7,221.8-209.1,221.8-323.8c0-216.7-392.6-153-573.7,91.8C792.9-394.1,1040.2-230.9,1328.3-414.5z M5550.4-1273.7c135.1-84.1,244.8-257.5,221.8-349.3c-23-89.2-145.3-132.6-267.7-96.9c-137.7,43.4-293.2,163.2-341.7,267.7c-56.1,117.3-53.5,160.6,10.2,224.4C5244.5-1156.4,5387.3-1174.2,5550.4-1273.7z M2682.2-1339.9c293.2-165.7,341.6-476.8,73.9-476.8c-196.3,0-466.6,232-466.6,397.8C2289.5-1278.7,2503.7-1238,2682.2-1339.9z M6659.5-2446.5c209-107.1,372.2-308.5,372.2-461.5c0-68.8-79-150.4-163.2-173.4c-168.3-40.8-517.6,158.1-617,351.8C6111.3-2459.2,6353.6-2290.9,6659.5-2446.5z"/><path d="M3013.6,2639.9c-135.1-45.9-221.8-130-221.8-219.3c0-160.6,181-270.3,453.8-270.3c418.1-2.5,599.2,288.1,280.5,453.8C3408.8,2665.4,3138.5,2683.3,3013.6,2639.9z"/><path d="M2213,1490.1c-168.3-48.5-295.8-132.6-334-226.9c-28-68.8-25.5-89.2,17.9-168.3c188.7-351.9,1106.5-288.1,1106.5,79c0,48.5-22.9,114.7-51,150.4C2837.7,1472.2,2450.2,1556.4,2213,1490.1z"/><path d="M5693.2,1492.6c-119.8-40.8-216.7-145.3-216.7-232c0-267.7,594-372.2,846.5-147.9c201.4,181-17.9,410.5-387.5,407.9C5843.6,1520.7,5736.6,1507.9,5693.2,1492.6z"/><path d="M8051.6,1278.5c-124.9-53.5-178.5-109.6-178.5-188.7c0-137.7,165.7-229.5,415.6-229.5c175.9,0,341.7,73.9,377.3,168.3C8737.4,1227.5,8321.8,1395.8,8051.6,1278.5z"/><path d="M4321.5,1013.3c-147.9-28-234.6-102-234.6-204c0-124.9,96.9-186.1,313.6-198.9c204-12.7,346.7,35.7,392.6,132.6C4869.7,916.4,4609.6,1064.3,4321.5,1013.3z"/><path d="M6662.1,225.5c-196.3-48.4-344.2-181-344.2-311c0-323.8,775.1-453.8,1070.8-175.9C7671.7,3.7,7161.8,345.3,6662.1,225.5z"/></g></g>
+</svg>

web/lib/miniPaint-4.14.2/images/icons/erase.svg

@@ -0,0 +1,14 @@
+<?xml version="1.0" encoding="iso-8859-1"?>
+<!-- Generator: Adobe Illustrator 16.0.0, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd">
+<svg version="1.1" id="Capa_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 width="548.157px" height="548.157px" viewBox="0 0 548.157 548.157" style="enable-background:new 0 0 548.157 548.157;"
+	 xml:space="preserve">
+<g>
+	<path d="M545.027,112.765c-3.046-6.471-7.57-11.657-13.565-15.555c-5.996-3.9-12.614-5.852-19.846-5.852H292.351
+		c-11.04,0-20.175,4.184-27.408,12.56L9.13,396.279c-4.758,5.328-7.661,11.56-8.708,18.698c-1.049,7.139-0.144,13.941,2.712,20.417
+		c3.044,6.468,7.564,11.652,13.561,15.553c5.997,3.898,12.612,5.853,19.845,5.853h219.268c11.042,0,20.177-4.179,27.41-12.56
+		l255.813-292.363c4.75-5.33,7.655-11.561,8.699-18.699C548.788,126.039,547.877,119.238,545.027,112.765z M255.811,420.254H36.54
+		l95.93-109.632h219.27L255.811,420.254z"/>
+</g>
+</svg>

web/lib/miniPaint-4.14.2/images/icons/fill.svg

@@ -0,0 +1,19 @@
+<?xml version="1.0" encoding="iso-8859-1"?>
+<!-- Generator: Adobe Illustrator 19.0.0, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<svg version="1.1" id="Capa_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 viewBox="0 0 512 512" style="enable-background:new 0 0 512 512;" xml:space="preserve">
+<g>
+	<path d="M494.412,245.154L371.59,122.507l93.792-93.934L437.07,0.304L343.28,94.237l-56.613-56.532L37.714,286.659
+		l207.754,207.459c11.699,11.699,27.069,17.549,42.436,17.549c15.367,0,30.735-5.849,42.436-17.549l164.082-164.082
+		c11.389-11.388,17.632-26.53,17.578-42.635C511.946,271.446,505.704,256.446,494.412,245.154z M466.131,301.745L302.048,465.828
+		c-7.799,7.8-20.489,7.8-28.3-0.01L94.314,286.638L286.687,94.266l28.324,28.283L211.272,226.445l28.312,28.269L343.322,150.82
+		l122.811,122.636c3.761,3.761,5.842,8.761,5.859,14.079C472.009,292.902,469.928,297.948,466.131,301.745z"/>
+</g>
+<g>
+	<path d="M95.137,398.966c-10.179-15.198-20.245-27.482-20.669-27.997l-15.455-18.808l-15.455,18.808
+		c-0.424,0.516-10.49,12.799-20.669,27.997C2.372,429.596,0,444.293,0,452.684c0,32.54,26.474,59.012,59.012,59.012
+		c32.539,0,59.012-26.473,59.012-59.012C118.025,444.293,115.652,429.596,95.137,398.966z M59.012,471.688
+		c-10.479,0-19.004-8.525-19.005-18.956c0.004-0.08,0.526-8.271,16.291-31.757c0.907-1.35,1.813-2.678,2.714-3.972
+		c0.899,1.294,1.806,2.622,2.714,3.972c15.491,23.079,16.265,31.388,16.29,31.745C77.996,463.182,69.48,471.688,59.012,471.688z"/>
+</g>
+</svg>

web/lib/miniPaint-4.14.2/images/icons/italic.svg

@@ -0,0 +1,2 @@
+<?xml version="1.0" encoding="iso-8859-1"?>
+<svg width="1em" height="1em" viewBox="0 0 16 16" class="bi bi-type-italic" fill="currentColor" xmlns="http://www.w3.org/2000/svg"><path d="M7.991 11.674L9.53 4.455c.123-.595.246-.71 1.347-.807l.11-.52H7.211l-.11.52c1.06.096 1.128.212 1.005.807L6.57 11.674c-.123.595-.246.71-1.346.806l-.11.52h3.774l.11-.52c-1.06-.095-1.129-.211-1.006-.806z"/></svg>

web/lib/miniPaint-4.14.2/images/icons/magic_erase.svg

@@ -0,0 +1,12 @@
+<?xml version="1.0" encoding="utf-8"?>
+<!-- Generator: Adobe Illustrator 19.0.0, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<svg version="1.1" id="Layer_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 viewBox="0 0 512 512" style="enable-background:new 0 0 512 512;" xml:space="preserve">
+<g id="XMLID_1_">
+	<path id="XMLID_12_" d="M128.4,96.2L64.2,32H32.6v31.6l64.2,64.2L128.4,96.2z M160,0.4h31.6v64.2H160V0.4z M287.5,160.4h64.2V192
+		h-64.2V160.4z M320,64.6V33h-31.6l-64.2,64.2l31.6,31.6L320,64.6z M0,160.4h64.2V192H0V160.4z M160,287.9h31.6v64.2H160V287.9z
+		 M31.6,287.9v31.6h31.6l64.2-64.2l-31.6-31.6L31.6,287.9z M504.2,441.4L187,123.2c-9.3-9.3-24.2-9.3-33.5,0L123.7,153
+		c-9.3,9.3-9.3,24.2,0,33.5l318.2,318.2c9.3,9.3,24.2,9.3,33.5,0l29.8-29.8C514.4,465.5,514.4,450.7,504.2,441.4z M240,272
+		l-95.8-95.8l31.6-31.6l95.8,95.8L240,272z"/>
+</g>
+</svg>

web/lib/miniPaint-4.14.2/images/icons/media.svg

@@ -0,0 +1,24 @@
+<?xml version="1.0" encoding="iso-8859-1"?>
+<!-- Generator: Adobe Illustrator 16.0.0, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd">
+<svg version="1.1" id="Capa_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 width="548.176px" height="548.176px" viewBox="0 0 548.176 548.176" style="enable-background:new 0 0 548.176 548.176;"
+	 xml:space="preserve">
+<g>
+	<g>
+		<path d="M534.75,68.238c-8.945-8.945-19.694-13.417-32.261-13.417H45.681c-12.562,0-23.313,4.471-32.264,13.417
+			C4.471,77.185,0,87.936,0,100.499v347.173c0,12.566,4.471,23.318,13.417,32.264c8.951,8.946,19.702,13.419,32.264,13.419h456.815
+			c12.56,0,23.312-4.473,32.258-13.419c8.945-8.945,13.422-19.697,13.422-32.264V100.499
+			C548.176,87.936,543.699,77.185,534.75,68.238z M511.623,447.672c0,2.478-0.899,4.613-2.707,6.427
+			c-1.81,1.8-3.952,2.703-6.427,2.703H45.681c-2.473,0-4.615-0.903-6.423-2.703c-1.807-1.813-2.712-3.949-2.712-6.427V100.495
+			c0-2.474,0.902-4.611,2.712-6.423c1.809-1.803,3.951-2.708,6.423-2.708h456.815c2.471,0,4.613,0.905,6.42,2.708
+			c1.801,1.812,2.707,3.949,2.707,6.423V447.672L511.623,447.672z"/>
+		<path d="M127.91,237.541c15.229,0,28.171-5.327,38.831-15.987c10.657-10.66,15.987-23.601,15.987-38.826
+			c0-15.23-5.333-28.171-15.987-38.832c-10.66-10.656-23.603-15.986-38.831-15.986c-15.227,0-28.168,5.33-38.828,15.986
+			c-10.656,10.66-15.986,23.601-15.986,38.832c0,15.225,5.327,28.169,15.986,38.826C99.742,232.211,112.683,237.541,127.91,237.541z
+			"/>
+		<polygon points="210.134,319.765 164.452,274.088 73.092,365.447 73.092,420.267 475.085,420.267 475.085,292.36 356.315,173.587 
+					"/>
+	</g>
+</g>
+</svg>

web/lib/miniPaint-4.14.2/images/icons/menu.svg

@@ -0,0 +1,11 @@
+<?xml version="1.0" encoding="iso-8859-1"?>
+<!-- Generator: Adobe Illustrator 16.0.0, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd">
+<svg version="1.1" id="Capa_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 width="124px" height="124px" viewBox="0 0 124 124" style="enable-background:new 0 0 124 124;" xml:space="preserve">
+<g>
+	<path d="M112,6H12C5.4,6,0,11.4,0,18s5.4,12,12,12h100c6.6,0,12-5.4,12-12S118.6,6,112,6z"/>
+	<path d="M112,50H12C5.4,50,0,55.4,0,62c0,6.6,5.4,12,12,12h100c6.6,0,12-5.4,12-12C124,55.4,118.6,50,112,50z"/>
+	<path d="M112,94H12c-6.6,0-12,5.4-12,12s5.4,12,12,12h100c6.6,0,12-5.4,12-12S118.6,94,112,94z"/>
+</g>
+</svg>

web/lib/miniPaint-4.14.2/images/icons/pencil.svg

@@ -0,0 +1,22 @@
+<?xml version="1.0" encoding="iso-8859-1"?>
+<!-- Generator: Adobe Illustrator 19.0.0, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<svg version="1.1" id="Capa_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 viewBox="0 0 512 512" style="enable-background:new 0 0 512 512;" xml:space="preserve">
+<g>
+	<g>
+		<polygon points="51.2,353.28 0,512 158.72,460.8 		"/>
+	</g>
+</g>
+<g>
+	<g>
+		
+			<rect x="89.73" y="169.097" transform="matrix(0.7071 -0.7071 0.7071 0.7071 -95.8575 260.3719)" width="353.277" height="153.599"/>
+	</g>
+</g>
+<g>
+	<g>
+		<path d="M504.32,79.36L432.64,7.68c-10.24-10.24-25.6-10.24-35.84,0l-23.04,23.04l107.52,107.52l23.04-23.04
+			C514.56,104.96,514.56,89.6,504.32,79.36z"/>
+	</g>
+</g>
+</svg>

web/lib/miniPaint-4.14.2/images/icons/pick_color.svg

@@ -0,0 +1,19 @@
+<?xml version="1.0" encoding="iso-8859-1"?>
+<!-- Generator: Adobe Illustrator 17.1.0, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd">
+<svg version="1.1" id="Capa_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 viewBox="0 0 296.135 296.135" style="enable-background:new 0 0 296.135 296.135;" xml:space="preserve">
+<path d="M284.5,11.635C276.997,4.132,267.021,0,256.411,0s-20.586,4.132-28.089,11.635l-64.681,64.68l-6.658-6.658
+	c-2.777-2.777-6.2-4.512-9.786-5.206c-0.598-0.116-1.2-0.202-1.804-0.26s-1.211-0.087-1.817-0.087s-1.213,0.029-1.817,0.087
+	s-1.206,0.145-1.804,0.26c-3.585,0.694-7.009,2.43-9.786,5.206v0c-1.388,1.388-2.516,2.938-3.384,4.59
+	c-0.289,0.55-0.55,1.112-0.781,1.683c-0.694,1.712-1.128,3.505-1.302,5.317c-0.058,0.604-0.087,1.211-0.087,1.817
+	c0,1.213,0.116,2.426,0.347,3.621c0.347,1.793,0.954,3.545,1.822,5.196c0.868,1.651,1.996,3.201,3.384,4.59l4.319,4.319
+	L21.468,213.811c-1.434,1.434-2.563,3.143-3.316,5.025l-16.19,40.387c-3.326,8.298-2.338,17.648,2.644,25.013
+	c5.04,7.451,13.356,11.899,22.244,11.899c3.432,0,6.817-0.659,10.063-1.961L77.3,277.984c1.882-0.754,3.592-1.883,5.025-3.316
+	l113.021-113.021l4.318,4.318c0.463,0.463,0.944,0.897,1.44,1.302c0.993,0.81,2.049,1.504,3.15,2.083
+	c2.752,1.446,5.785,2.169,8.818,2.169l0,0c0.029,0,0.058-0.004,0.087-0.004c1.791-0.008,3.58-0.264,5.312-0.777
+	c2.345-0.694,4.583-1.851,6.569-3.471c0.497-0.405,0.977-0.839,1.44-1.302v0c2.314-2.314,3.905-5.077,4.772-8.009
+	c0.694-2.345,0.926-4.798,0.694-7.216c-0.116-1.209-0.347-2.408-0.694-3.581s-0.81-2.318-1.388-3.419
+	c-0.868-1.651-1.996-3.201-3.384-4.59l-6.658-6.658l64.68-64.68C299.988,52.326,299.988,27.124,284.5,11.635z M63.285,251.282
+	l-30.764,12.331l12.332-30.763l110.848-110.848l18.432,18.432L63.285,251.282z"/>
+</svg>

web/lib/miniPaint-4.14.2/images/icons/refresh.svg

@@ -0,0 +1,15 @@
+<?xml version="1.0" encoding="iso-8859-1"?>
+<!-- Generator: Adobe Illustrator 19.0.0, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<svg version="1.1" id="Capa_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 viewBox="0 0 512 512" style="enable-background:new 0 0 512 512;" xml:space="preserve">
+<g>
+	<g>
+		<path d="M403.678,272c0,40.005-15.615,77.651-43.989,106.011C331.33,406.385,293.683,422,253.678,422
+			c-40.005,0-77.651-15.615-106.011-43.989c-28.374-28.359-43.989-66.006-43.989-106.011s15.615-77.651,43.989-106.011
+			C176.027,137.615,213.673,122,253.678,122c25.298,0,49.849,6.343,71.88,18.472L267.023,212h231.299L440.49,0l-57.393,70.13
+			C344.323,45.14,299.865,32,253.678,32c-64.116,0-124.395,24.961-169.702,70.298C38.639,147.605,13.678,207.884,13.678,272
+			s24.961,124.395,70.298,169.702C129.284,487.039,189.562,512,253.678,512s124.395-24.961,169.702-70.298
+			c45.337-45.308,70.298-105.586,70.298-169.702v-15h-90V272z"/>
+	</g>
+</g>
+</svg>

web/lib/miniPaint-4.14.2/images/icons/select.svg

@@ -0,0 +1,14 @@
+<?xml version="1.0" encoding="iso-8859-1"?>
+<!-- Generator: Adobe Illustrator 19.0.0, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<svg version="1.1" id="Layer_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 viewBox="0 0 262.474 262.474" style="enable-background:new 0 0 262.474 262.474;" xml:space="preserve">
+<g id="XMLID_351_">
+	<path id="XMLID_352_" d="M217.327,210.541l-38.815-71.507l31.813-17.271c4.652-2.525,7.628-7.315,7.833-12.604
+		c0.204-5.289-2.395-10.294-6.837-13.17L66.756,2.408c-4.609-2.984-10.481-3.211-15.308-0.591c-4.826,2.62-7.835,7.667-7.844,13.159
+		l-0.277,172.206c-0.008,5.293,2.773,10.198,7.32,12.909c4.545,2.709,10.185,2.824,14.836,0.298l31.811-17.268l38.816,71.506
+		c2.718,5.007,7.873,7.847,13.196,7.847c2.417,0,4.869-0.586,7.143-1.82l54.849-29.774
+		C218.58,226.928,221.279,217.822,217.327,210.541z M155.321,227.132l-38.816-71.507c-1.898-3.496-5.107-6.095-8.922-7.225
+		c-1.395-0.414-2.831-0.618-4.261-0.618c-2.478,0-4.94,0.614-7.157,1.817l-22.797,12.376L73.56,42.55l100.255,64.898l-22.799,12.377
+		c-7.281,3.952-9.979,13.058-6.027,20.338l38.815,71.507L155.321,227.132z"/>
+</g>
+</svg>

web/lib/miniPaint-4.14.2/images/icons/selection.svg

@@ -0,0 +1,69 @@
+<?xml version="1.0" encoding="iso-8859-1"?>
+<!-- Generator: Adobe Illustrator 19.0.0, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<svg version="1.1" id="Capa_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 viewBox="0 0 511.997 511.997" style="enable-background:new 0 0 511.997 511.997;" xml:space="preserve">
+<g>
+	<g>
+		<rect x="137.809" y="471.577" width="89.817" height="39.919"/>
+	</g>
+</g>
+<g>
+	<g>
+		<rect x="283.463" y="471.577" width="89.817" height="39.919"/>
+	</g>
+</g>
+<g>
+	<g>
+		<path d="M60.963,471.581c-11.579,0-21-9.421-21-21.001v-19.959H0.044v19.959c0,33.592,27.327,60.92,60.919,60.92h19.959v-39.919
+			H60.963z"/>
+	</g>
+</g>
+<g>
+	<g>
+		<path d="M471.083,430.621v19.959c0,11.58-9.42,21.001-21,21.001h-19.959V511.5h19.959c33.592,0,60.919-27.328,60.919-60.92
+			v-19.959H471.083z"/>
+	</g>
+</g>
+<g>
+	<g>
+		<rect x="137.809" y="0.497" width="89.817" height="39.919"/>
+	</g>
+</g>
+<g>
+	<g>
+		<rect x="283.463" y="0.497" width="89.817" height="39.919"/>
+	</g>
+</g>
+<g>
+	<g>
+		<path d="M60.963,0.497c-33.592,0-60.92,27.328-60.92,60.92v19.959h39.919h0.001V61.417c0-11.58,9.42-21.001,21-21.001h19.959
+			V0.497H60.963z"/>
+	</g>
+</g>
+<g>
+	<g>
+		<path d="M450.083,0.497h-19.959v39.919h19.959c11.579,0,21,9.421,21,21.001v19.959h39.919V61.417
+			C511.002,27.825,483.675,0.497,450.083,0.497z"/>
+	</g>
+</g>
+<g>
+	<g>
+		<rect y="288.909" width="39.919" height="89.817"/>
+	</g>
+</g>
+<g>
+	<g>
+		<rect y="143.246" width="39.919" height="89.817"/>
+	</g>
+</g>
+<g>
+	<g>
+		<rect x="472.078" y="288.909" width="39.919" height="89.817"/>
+	</g>
+</g>
+<g>
+	<g>
+		<rect x="472.078" y="143.246" width="39.919" height="89.817"/>
+	</g>
+</g>
+</svg>

web/lib/miniPaint-4.14.2/images/icons/shape.svg

@@ -0,0 +1,6 @@
+<svg xmlns="http://www.w3.org/2000/svg" viewBox="1 2 31 27" x="0px" y="0px">
+	<title>shapes</title>
+	<g>
+		<path d="M30.87,16.33l-7.5-13a1,1,0,0,0-1.73,0l-5,8.69a8.15,8.15,0,0,0-1.61,0V7a1,1,0,0,0-1-1H2A1,1,0,0,0,1,7V19a1,1,0,0,0,1,1H8a8,8,0,1,0,15.69-2.17H30a1,1,0,0,0,.87-1.5ZM3,18V8H13v4.58l0,0A8,8,0,0,0,8.28,18H3Zm13,8a6,6,0,0,1-6-6,4.62,4.62,0,0,1,.07-.86,6,6,0,0,1,4.22-4.89A5.92,5.92,0,0,1,16,14a5.29,5.29,0,0,1,1,.09A6,6,0,0,1,16,26Zm6.83-10.17h0a8,8,0,0,0-4.12-3.34l0,0L22.5,5.84l5.77,10Z"/>
+	</g>
+</svg>

web/lib/miniPaint-4.14.2/images/icons/sharpen.svg

@@ -0,0 +1,13 @@
+<?xml version="1.0" encoding="iso-8859-1"?>
+<!-- Generator: Adobe Illustrator 19.0.0, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<svg version="1.1" id="Capa_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 viewBox="0 0 512 512" style="enable-background:new 0 0 512 512;" xml:space="preserve">
+<g>
+	<g>
+		<path d="M508.867,190.394l-111-143.568C394.996,43.113,390.52,41,386,41H126c-4.498,0-8.98,2.092-11.867,5.825l-111,143.568
+			c-4.509,5.832-4.112,14.076,0.937,19.447l241,256.432c2.655,2.824,6.568,4.728,10.93,4.728c4.3,0,8.221-1.845,10.93-4.728
+			l241-256.432C512.979,204.469,513.376,196.226,508.867,190.394z M241,418.137L34.694,198.62l93.584-121.043L241,172.957V418.137z
+			 M256,146.351L166.949,71h178.102L256,146.351z M271,418.137v-245.18l112.722-95.38l93.585,121.043L271,418.137z"/>
+	</g>
+</g>
+</svg>

web/lib/miniPaint-4.14.2/images/icons/strikethrough.svg

@@ -0,0 +1,4 @@
+<?xml version="1.0" encoding="iso-8859-1"?>
+<svg width="1em" height="1em" viewBox="0 0 16 16" xmlns="http://www.w3.org/2000/svg">
+	<path d="M8.527 13.164c-2.153 0-3.589-1.107-3.705-2.81h1.23c.144 1.06 1.129 1.703 2.544 1.703 1.34 0 2.31-.705 2.31-1.675 0-.827-.547-1.374-1.914-1.675L8.046 8.5h3.45c.468.437.675.994.675 1.697 0 1.826-1.436 2.967-3.644 2.967zM6.602 6.5H5.167a2.776 2.776 0 0 1-.099-.76c0-1.627 1.436-2.768 3.48-2.768 1.969 0 3.39 1.175 3.445 2.85h-1.23c-.11-1.08-.964-1.743-2.25-1.743-1.23 0-2.18.602-2.18 1.607 0 .31.083.581.27.814z"/><path fill-rule="evenodd" d="M15 8.5H1v-1h14v1z"/>
+</svg>

web/lib/miniPaint-4.14.2/images/icons/text.svg

@@ -0,0 +1,14 @@
+<?xml version="1.0" encoding="iso-8859-1"?>
+<!-- Generator: Adobe Illustrator 16.0.0, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd">
+<svg version="1.1" id="Capa_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 width="977.7px" height="977.7px" viewBox="0 0 977.7 977.7" style="enable-background:new 0 0 977.7 977.7;" xml:space="preserve"
+	>
+<g>
+	<path d="M770.7,930.6v-35.301c0-23.398-18-42.898-41.3-44.799c-17.9-1.5-35.8-3.1-53.7-5c-34.5-3.6-72.5-7.4-72.5-50.301L603,131.7
+		c136-2,210.5,76.7,250,193.2c6.3,18.7,23.8,31.3,43.5,31.3h36.2c24.9,0,45-20.1,45-45V47.1c0-24.9-20.1-45-45-45H488.9h-0.2H45
+		c-24.9,0-45,20.1-45,45v264.1c0,24.9,20.1,45,45,45h36.2c19.7,0,37.2-12.6,43.5-31.3c39.4-116.5,114-195.2,250-193.2l-0.3,663.5
+		c0,42.9-38,46.701-72.5,50.301c-17.9,1.9-35.8,3.5-53.7,5c-23.3,1.9-41.3,21.4-41.3,44.799V930.6c0,24.9,20.1,45,45,45h236.8h0.3
+		h236.7C750.5,975.6,770.7,955.401,770.7,930.6z"/>
+</g>
+</svg>

web/lib/miniPaint-4.14.2/images/icons/underline.svg

@@ -0,0 +1,2 @@
+<?xml version="1.0" encoding="iso-8859-1"?>
+<svg width="1em" height="1em" viewBox="0 0 16 16" class="bi bi-type-underline" fill="currentColor" xmlns="http://www.w3.org/2000/svg"><path d="M5.313 3.136h-1.23V9.54c0 2.105 1.47 3.623 3.917 3.623s3.917-1.518 3.917-3.623V3.136h-1.23v6.323c0 1.49-.978 2.57-2.687 2.57-1.709 0-2.687-1.08-2.687-2.57V3.136z"/><path fill-rule="evenodd" d="M12.5 15h-9v-1h9v1z"/></svg>

web/lib/miniPaint-4.14.2/images/icons/undo.svg

@@ -0,0 +1 @@
+<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24"><path d="M18.885 3.515c-4.617-4.618-12.056-4.676-16.756-.195l-2.129-2.258v7.938h7.484l-2.066-2.191c2.82-2.706 7.297-2.676 10.073.1 4.341 4.341 1.737 12.291-5.491 12.291v4.8c3.708 0 6.614-1.244 8.885-3.515 4.686-4.686 4.686-12.284 0-16.97z"/></svg>

web/lib/miniPaint-4.14.2/images/icons/view.svg

@@ -0,0 +1,20 @@
+<?xml version="1.0" encoding="iso-8859-1"?>
+<!-- Generator: Adobe Illustrator 19.0.0, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<svg version="1.1" id="Capa_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 viewBox="0 0 461.312 461.312" style="enable-background:new 0 0 461.312 461.312;" xml:space="preserve">
+<g>
+	<g>
+		<path d="M230.656,156.416c-40.96,0-74.24,33.28-74.24,74.24s33.28,74.24,74.24,74.24s74.24-33.28,74.24-74.24
+			S271.616,156.416,230.656,156.416z M225.024,208.64c-9.216,0-16.896,7.68-16.896,16.896h-24.576
+			c0.512-23.04,18.944-41.472,41.472-41.472V208.64z"/>
+	</g>
+</g>
+<g>
+	<g>
+		<path d="M455.936,215.296c-25.088-31.232-114.688-133.12-225.28-133.12S30.464,184.064,5.376,215.296
+			c-7.168,8.704-7.168,21.504,0,30.72c25.088,31.232,114.688,133.12,225.28,133.12s200.192-101.888,225.28-133.12
+			C463.104,237.312,463.104,224.512,455.936,215.296z M230.656,338.176c-59.392,0-107.52-48.128-107.52-107.52
+			s48.128-107.52,107.52-107.52s107.52,48.128,107.52,107.52S290.048,338.176,230.656,338.176z"/>
+	</g>
+</g>
+</svg>

web/lib/miniPaint-4.14.2/index.html

@@ -0,0 +1,139 @@
+<!DOCTYPE html>
+<html dir="ltr" lang="en-US">
+
+<head>
+	<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
+	<meta http-equiv="x-ua-compatible" content="IE=edge" />
+	<title>miniPaint - image editor</title>
+	<meta name="description"
+		content="miniPaint is free online image editor using HTML5. Edit, adjust your images, add effects online in your browser, without installing anything..." />
+	<meta name="keywords"
+		content="photo, image, picture, transparent, layers, free, edit, html5, canvas, javascript, online, photoshop, gimp, effects, sharpen, blur, magic eraser tool, clone tool, rotate, resize, photoshop online, online tools, tilt shift, sprites, keypoints" />
+	<meta name="viewport" content="width=device-width, initial-scale=1, maximum-scale=1.0, user-scalable=0" />
+	<link rel="icon" sizes="192x192" href="images/favicon.png">
+	<!-- <link rel="manifest" href="dist/manifest.json"> -->
+	<!-- Google -->
+	<meta itemprop="name" content="miniPaint" />
+	<meta itemprop="description"
+		content="miniPaint is free online image editor using HTML5. Edit, adjust your images, add effects online in your browser, without installing anything..." />
+	<meta itemprop="image" content="https://viliusle.github.io/miniPaint/images/preview.jpg" />
+	<!-- Twitter -->
+	<meta name="twitter:card" content="summary_large_image" />
+	<meta name="twitter:title" content="miniPaint" />
+	<meta name="twitter:description"
+		content="miniPaint is free online image editor using HTML5. Edit, adjust your images, add effects online in your browser, without installing anything..." />
+	<meta name="twitter:image" content="https://viliusle.github.io/miniPaint/images/preview.jpg" />
+	<meta name="twitter:image:alt"
+		content="miniPaint is free online image editor using HTML5. Edit, adjust your images, add effects online in your browser, without installing anything..." />
+	<!-- Facebook, Pinterest -->
+	<meta property="og:title" content="miniPaint" />
+	<meta property="og:type" content="article" />
+	<meta property="og:url" content="https://viliusle.github.io/miniPaint/" />
+	<meta property="og:image" content="https://viliusle.github.io/miniPaint/images/preview.jpg" />
+	<meta property="og:description"
+		content="miniPaint is free online image editor using HTML5. Edit, adjust your images, add effects online in your browser, without installing anything..." />
+	<meta property="og:site_name" content="miniPaint" />
+
+	<script src="dist/bundle.ejs"></script>
+</head>
+
+<body>
+	<div class="wrapper">
+
+		<nav aria-label="Main Menu" class="main_menu" id="main_menu"></nav>
+
+		<div class="submenu">
+			<!-- <a class="logo" href="#">miniPaint</a> -->
+			<div class="block attributes" id="action_attributes"></div>
+			
+			<select id="automask_models_mixlab"></select>
+
+			<button id="automask_image_mixlab" type="button" style="width: 98px;
+			height: 36px;margin-right: 18px;
+			color: white;">
+				RemoveBg
+			</button>
+
+			<button id="cancel_image_mixlab" type="button" style="width: 98px;
+			height: 36px;
+			color: white;">
+				Cancel
+			</button>
+			<button id="save_image_mixlab" type="button" style="width: 98px;
+			height: 36px;
+			color: white;">
+				Save
+			</button>
+
+			<a  
+			target="_blank" href="https://discord.gg/xbP2GZF6gn" 
+			style="width: 98px;
+			color: white;
+			text-decoration: none;"> Help/帮助 </a>
+
+			<button class="undo_button" id="undo_button" type="button">
+				<span class="sr_only">Undo</span>
+			</button>
+		</div>
+
+		<div class="sidebar_left" id="tools_container"></div>
+
+
+		<div class="middle_area" id="middle_area">
+
+			<canvas class="ruler_left" id="ruler_left"></canvas>
+			<canvas class="ruler_top" id="ruler_top"></canvas>
+
+			<div class="main_wrapper" id="main_wrapper">
+				<div class="canvas_wrapper" id="canvas_wrapper">
+					<div id="mouse"></div>
+					<div class="transparent-grid" id="canvas_minipaint_background"></div>
+					<canvas id="canvas_minipaint">
+						<div class="trn error">
+							Your browser does not support canvas or JavaScript is not enabled.
+						</div>
+					</canvas>
+				</div>
+			</div>
+		</div>
+
+		<div class="sidebar_right">
+			<div class="preview block" style="display: none;">
+				<h2 class="trn toggle" data-target="toggle_preview">Preview</h2>
+				<div id="toggle_preview"></div>
+			</div>
+
+			<div class="colors block">
+				<h2 class="trn toggle" data-target="toggle_colors">Colors</h2>
+				<div class="content" id="toggle_colors"></div>
+			</div>
+
+			<div class="block" id="info_base" style="display: none;">
+				<h2 class="trn toggle toggle-full" data-target="toggle_info">Information</h2>
+				<div class="content" id="toggle_info"></div>
+			</div>
+
+			<div class="details block" id="details_base">
+				<h2 class="trn toggle toggle-full" data-target="toggle_details">Layer details</h2>
+				<div class="content details-content" id="toggle_details"></div>
+			</div>
+
+			<div class="layers block">
+				<h2 class="trn">Layers</h2>
+				<div class="content" id="layers_base"></div>
+			</div>
+		</div>
+	</div>
+	<div class="mobile_menu">
+		<button class="left_mobile_menu" id="left_mobile_menu_button" type="button">
+			<span class="sr_only">Toggle Menu</span>
+		</button>
+		<button class="right_mobile_menu" id="mobile_menu_button" type="button">
+			<span class="sr_only">Toggle Menu</span>
+		</button>
+	</div>
+	<div class="hidden" id="tmp"></div>
+	<div id="popups"></div>
+</body>
+
+</html>