fix:ssl prot occupied

V0.11.0 PromptImage & PromptSimplification

README.md

@@ -33,6 +33,8 @@ APP-JSON:
 
 > 输出节点：PreviewImage 、SaveImage、ShowTextForGPT、VHS_VideoCombine
 
+> seed统一输入控件，支持：SamplerCustom、KSampler
+
 
 ## 🏃🚗🚚🚀  Real-time Design
 > ScreenShareNode & FloatingVideoNode. Now comfyui supports capturing screen pixel streams from any software and can be used for LCM-Lora integration. Let's get started with implementation and design! 💻🌐
@@ -75,6 +77,9 @@ https://github.com/shadowcz007/comfyui-mixlab-nodes/assets/12645064/e7e77f90-e43
 
 [add clip-interrogator](https://github.com/pharmapsychotic/clip-interrogator)
 
+> PromptImage & PromptSimplification,Assist in simplifying prompt words, comparing images and prompt word nodes.
+
+
 ### Layers
 > A new layer class node has been added, allowing you to separate the image into layers. After merging the images, you can input the controlnet for further processing.
 

__init__.py

@@ -351,33 +351,59 @@ async def new_request(self, method, url, *args, **kwargs):
 
 # 应用 Monkey Patch
 aiohttp.ClientSession._request = new_request
+import socket
+
+async def check_port_available(address, port):
+    #检查端口是否可用
+    with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as sock:
+        sock.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
+        try:
+            sock.bind((address, port))
+            return True
+        except socket.error:
+            return False
 
 # https
 async def new_start(self, address, port, verbose=True, call_on_start=None):
-        
-
+    try:
         runner = web.AppRunner(self.app, access_log=None)
         await runner.setup()
+
+        if not await check_port_available(address, port):
+            raise RuntimeError(f"Port {port} is already in use.")
+
         site = web.TCPSite(runner, address, port)
         await site.start()
 
         import ssl
-        crt,key=create_for_https()
+        crt, key = create_for_https()
         ssl_context = ssl.create_default_context(ssl.Purpose.CLIENT_AUTH)
-        ssl_context.load_cert_chain(crt,key)
-        site2 = web.TCPSite(runner, address, port+1,ssl_context=ssl_context)
-        await site2.start()
+        ssl_context.load_cert_chain(crt, key)
+
+        success = False
+        for i in range(10):  # 尝试最多10次
+            if await check_port_available(address, port + 1 + i):
+                https_port = port + 1 + i
+                site2 = web.TCPSite(runner, address, https_port, ssl_context=ssl_context)
+                await site2.start()
+                success = True
+                break
+
+        if not success:
+            raise RuntimeError(f"Ports {port + 1} to {port + 10} are all in use.")
 
         if address == '':
             address = '0.0.0.0'
         if verbose:
-            # print('\033[91mMixlab Nodes: \033[93mLoaded\033[0m')
             print("\033[93mStarting server\n")
             print("\033[93mTo see the GUI go to: http://{}:{}".format(address, port))
-            print("\033[93mTo see the GUI go to: https://{}:{}\033[0m".format(address, port+1))
+            print("\033[93mTo see the GUI go to: https://{}:{}\033[0m".format(address, https_port))
         if call_on_start is not None:
             call_on_start(address, port)
 
+    except Exception as e:
+        print(f"Error starting the server: {e}")
+
         # import webbrowser
         # if os.name == 'nt' and address == '0.0.0.0':
         #     address = '127.0.0.1'
@@ -503,7 +529,7 @@ PromptServer.add_routes=new_add_routes
 
 
 # 导入节点
-from .nodes.PromptNode import RandomPrompt,PromptSlide
+from .nodes.PromptNode import RandomPrompt,PromptSlide,PromptSimplification,PromptImage
 from .nodes.ImageNode import NoiseImage,TransparentImage,GradientImage,LoadImagesFromPath,LoadImagesFromURL,ResizeImage,TextImage,SvgImage,Image3D,ShowLayer,NewLayer,MergeLayers,AreaToMask,SmoothMask,FeatheredMask,SplitLongMask,ImageCropByAlpha,EnhanceImage,FaceToMask
 from .nodes.Vae import VAELoader,VAEDecode
 from .nodes.ScreenShareNode import ScreenShareNode,FloatingVideo
@@ -520,6 +546,8 @@ NODE_CLASS_MAPPINGS = {
     "AppInfo":AppInfo,
     "RandomPrompt":RandomPrompt,
     "PromptSlide":PromptSlide,
+    "PromptSimplification":PromptSimplification,
+    "PromptImage":PromptImage,
     "ClipInterrogator":ClipInterrogator,
     "NoiseImage":NoiseImage,
     "GradientImage":GradientImage,

data/Product-designer.txt

@@ -0,0 +1,30 @@
+Jony Ive
+Dieter Rams
+Philippe Starck
+Karim Rashid
+Yves Béhar
+Marc Newson
+Naoto Fukasawa
+Jonathan Adler
+Patricia Urquiola
+Ross Lovegrove
+Tom Dixon
+Jasper Morrison
+Charles Eames
+Ray Eames
+Achille Castiglioni
+Ron Arad
+Konstantin Grcic
+Marcel Wanders
+Maarten Baas
+Stefan Sagmeister
+Ingo Maurer
+Hella Jongerius
+Sam Hecht
+Kim Colin
+Jaime Hayon
+Michael Anastassiades
+Nendo
+Oki Sato
+Matali Crasset
+Tokujin Yoshioka

data/extension-node-map.json

@@ -4786,6 +4786,7 @@
             "NewLayer",
             "RandomPrompt",
             "PromptSlide",
+            "PromptSimplification",
             "ClipInterrogator",
             "ScreenShare",
             "ShowLayer",

nodes/ChatGPT.py

@@ -180,8 +180,9 @@ class ShowTextForGPT:
     CATEGORY = "♾️Mixlab/GPT"
 
     def run(self, text):
-        # print(session_history)
+        # print(text)
         return {"ui": {"text": text}, "result": (text,)}
+        
 
 
 class CharacterInText:

nodes/ClipInterrogator.py

@@ -42,7 +42,7 @@ def pil2tensor(image):
     return torch.from_numpy(np.array(image).astype(np.float32) / 255.0).unsqueeze(0)
 
 
-def image_analysis(ci,image):
+def image_analysis_fn(ci,image):
     image = image.convert('RGB')
     image_features = ci.image_to_features(image)
 
@@ -88,13 +88,13 @@ class ClipInterrogator:
                              },
                 }
     
-    RETURN_TYPES = ("STRING","STRING",)
-    RETURN_NAMES = ("prompt","analysis",)
+    RETURN_TYPES = ("STRING",)
+    RETURN_NAMES = ("prompt",)
 
     FUNCTION = "run"
 
     CATEGORY = "♾️Mixlab/prompt"
-
+    OUTPUT_NODE = True
     INPUT_IS_LIST = True
     OUTPUT_IS_LIST = (True,)
     global ci
@@ -137,8 +137,8 @@ class ClipInterrogator:
             im=im.convert('RGB')
 
             if analysis=='on':
-                analysis_res=image_analysis(ci,im)
-                analysis_result.append(json.dumps(analysis_res))
+                analysis_res=image_analysis_fn(ci,im)
+                analysis_result.append( analysis_res )
                 pbar.update(1)
 
             prompt=image_to_prompt(ci,im,prompt_mode)
@@ -155,4 +155,6 @@ class ClipInterrogator:
             ci.caption_model = ci.caption_model.to('cpu')
             ci.caption_offloaded = True
 
-        return {"ui":{"prompt": prompt_result,"analysis":analysis_result},"result": (prompt_result,analysis_result,)}
+        # analysis_result=[]
+
+        return {"ui":{"prompt": prompt_result,"analysis":analysis_result},"result": (prompt_result,)}

nodes/ImageNode.py

@@ -591,8 +591,7 @@ def resize_image(layer_image, scale_option, width, height,color="white"):
 #     image=image.convert('RGB')
 
 #     return (image,alpha_image)
-
-def generate_text_image(text, font_path, font_size, text_color, vertical=True, 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):
     # Split text into lines based on line breaks
     lines = text.split("\n")
 
@@ -608,19 +607,17 @@ def generate_text_image(text, font_path, font_size, text_color, vertical=True, s
         x = 0
         y = 0
         for i in range(len(lines)):
-            line=lines[i]
+            line = lines[i]
             for char in line:
                 char_coordinates.append((x, y))
                 y += font_size + spacing
             x += font_size + spacing
             y = 0
-        # print(char_coordinates)
     else:
         x = 0
         y = 0
         for line in lines:
             for char in line:
-                #print('char',char)
                 char_coordinates.append((x, y))
                 x += font_size + spacing
             y += font_size + spacing
@@ -629,35 +626,42 @@ def generate_text_image(text, font_path, font_size, text_color, vertical=True, s
     # 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
+        height = ((len(max(lines, key=len)) + 1) * (font_size + spacing)) + spacing
     else:
         width = (len(max(lines, key=len)) * (font_size + spacing)) - spacing
-        height = ((len(lines)-1) * (font_size + spacing)) + font_size
+        height = ((len(lines) - 1) * (font_size + spacing)) + font_size
 
     # 4. Draw each character on the image
-    image = Image.new('RGBA', (width, height), (255, 255, 255,0))
+    image = Image.new('RGBA', (width, height), (255, 255, 255, 0))
     draw = ImageDraw.Draw(image)
     font = ImageFont.truetype(font_path, font_size)
-    
-    index=0
+
+    index = 0
     for i, line in enumerate(lines):
         for j, char in enumerate(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, y), char, font=font, fill=text_color)
-            index+=1
+            index += 1
 
-    # image.save(output_image_path)
-
-    # 分离alpha通道
+    # Separate alpha channel
     alpha_channel = image.split()[3]
 
-    # 创建一个只有alpha通道的新图像
+    # Create a new image with only the alpha channel
     alpha_image = Image.new('L', image.size)
     alpha_image.putdata(alpha_channel.getdata())
 
-    image=image.convert('RGB')
+    image = image.convert('RGB')
+
+    return (image, alpha_image)
+
 
-    return (image,alpha_image)
 
 def base64_to_image(base64_string):
     # 去除前缀
@@ -1133,6 +1137,7 @@ class TextImage:
                                 }), 
                     "text_color":("STRING",{"multiline": False,"default": "#000000","dynamicPrompts": False}),
                     "vertical":("BOOLEAN", {"default": True},),
+                    "stroke":("BOOLEAN", {"default": False},),
                              },
                 }
     
@@ -1146,11 +1151,11 @@ class TextImage:
     INPUT_IS_LIST = False
     OUTPUT_IS_LIST = (False,False,)
 
-    def run(self,text,font_path,font_size,spacing,text_color,vertical):
+    def run(self,text,font_path,font_size,spacing,text_color,vertical,stroke):
         
         # text_list=list(text)
-
-        img,mask=generate_text_image(text,font_path,font_size,text_color,vertical,spacing)
+        # 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=pil2tensor(img)
         mask=pil2tensor(mask)

nodes/PromptNode.py

@@ -1,9 +1,11 @@
 import random
 import comfy.utils
-import json
+import os
+import numpy as np
 from urllib import request, parse
-
-
+import folder_paths
+from PIL import Image, ImageOps,ImageFilter,ImageEnhance,ImageDraw,ImageSequence, ImageFont
+from PIL.PngImagePlugin import PngInfo
 # def queue_prompt(prompt_workflow):
 #     p = {"prompt": prompt_workflow}
 #     data = json.dumps(p).encode('utf-8')
@@ -45,12 +47,171 @@ default_prompt1='''Swing
 default_prompt1="\n".join([p.strip() for p in default_prompt1.split('\n') if p.strip()!=''])
 
 
+def tensor2pil(image):
+    return Image.fromarray(np.clip(255. * image.cpu().numpy().squeeze(), 0, 255).astype(np.uint8))
+
 def addWeight(text, weight=1):
     if weight == 1:
         return text
     else:
         return f"({text}:{round(weight,2)})"
 
+def prompt_delete_words(sentence, new_words_length):
+    # 使用逗号分割句子，并去除空格
+    words = [word.strip() for word in sentence.split(",")]
+    
+    # 计算需要删除的单词数量
+    num_to_delete = len(words) - new_words_length
+    
+    words_to=[w for w in words]
+
+    # 逐个删除单词并存储在新列表中
+    new_words = []
+    for i in range(len(words)):
+        if num_to_delete > 0:
+            num_to_delete -= 1
+        else:
+            words_to.pop()
+            if len(words_to)>0:
+                new_words.append(", ".join(words_to))
+         
+    return new_words
+
+# # 测试方法
+# sentence = "a computer, a glass tablet with a keyboard on a dark background, 3d illustration, reflection, cgi 8k, clear glass, archaic, cut-away, white outline"
+# new_words_length = 5
+# result = prompt_delete_words(sentence, new_words_length)
+# print(result)
+
+class PromptImage:
+    def __init__(self):
+        self.output_dir = folder_paths.get_output_directory()
+        self.type = "output"
+        self.prefix_append = "PromptImage"
+        self.compress_level = 4
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "prompts": ("STRING", 
+                         {
+                            "multiline": True, 
+                            "default": '',
+                            "dynamicPrompts": False
+                          }),
+
+                "images": ("IMAGE",{"default": None}), 
+                 "save_to_image": (["enable", "disable"],),
+                }
+            }
+    
+    RETURN_TYPES = ()
+   
+    OUTPUT_NODE = True
+
+    INPUT_IS_LIST = True
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/prompt"
+
+    # 运行的函数
+    def run(self,prompts,images,save_to_image):
+        filename_prefix="mixlab_"
+        filename_prefix += self.prefix_append
+        full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(
+            filename_prefix, self.output_dir, images[0].shape[1], images[0].shape[0])
+        
+        results = list()
+
+        save_to_image=save_to_image[0]=='enable'
+
+        for index in range(len(images)):
+            res=[]
+            imgs=images[index]
+
+            for image in imgs:
+                img=tensor2pil(image)
+
+                metadata = None
+                if save_to_image:
+                    metadata = PngInfo()
+                    prompt_text=prompts[index]
+                    if prompt_text is not None:
+                        metadata.add_text("prompt_text", prompt_text)
+                    
+                file = f"{filename}_{index}_{counter:05}_.png"
+                img.save(os.path.join(full_output_folder, file), pnginfo=metadata, compress_level=self.compress_level)
+                res.append({
+                    "filename": file,
+                    "subfolder": subfolder,
+                    "type": self.type
+                })
+                counter += 1
+            results.append(res)
+        
+        return { "ui": { "_images": results,"prompts":prompts } }
+
+
+
+
+class PromptSimplification:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "prompt": ("STRING", 
+                         {
+                            "multiline": True, 
+                            "default": '',
+                            "dynamicPrompts": False
+                          }),
+
+                "length":("INT", {"default": 5, "min": 1,"max":100, "step": 1, "display": "number"}),
+
+                # "min_value":("FLOAT", {
+                #         "default": -2, 
+                #         "min": -10, 
+                #         "max": 0xffffffffffffffff,
+                #         "step": 0.01, 
+                #         "display": "number"  
+                #     }),
+                # "max_value":("FLOAT", {
+                #         "default": 2, 
+                #         "min": -10, 
+                #         "max": 0xffffffffffffffff,
+                #         "step": 0.01, 
+                #         "display": "number"  
+                #     }),
+              
+                }
+            }
+    
+    RETURN_TYPES = ("STRING",)
+    RETURN_NAMES = ("prompts",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/prompt"
+
+    INPUT_IS_LIST = True
+    OUTPUT_IS_LIST = (True,)
+    OUTPUT_NODE = True
+
+    # 运行的函数
+    def run(self,prompt,length):
+        length=length[0]
+        result=[]
+        for p in prompt:
+            nps=prompt_delete_words(p,length)
+            for n in nps:
+                result.append(n)
+
+        result= [elem.strip() for elem in result if elem.strip()]
+
+        return {"ui": {"prompts": result}, "result": (result,)}
+
 
 
 class PromptSlide:
@@ -187,6 +348,8 @@ class RandomPrompt:
         else:
             prompts = prompts[:min(max_count,len(prompts))]
 
+        prompts= [elem.strip() for elem in prompts if elem.strip()]
+
         # return (new_prompt)
         return {"ui": {"prompts": prompts}, "result": (prompts,)}
 

nodes/Utils.py

@@ -188,7 +188,7 @@ class FloatSlider:
                     "number":("FLOAT", {
                         "default": 0, 
                         "min": 0, #Minimum value
-                        "max": 1, #Maximum value
+                        "max": 0xffffffffffffffff, #Maximum value
                         "step": 0.001, #Slider's step
                         "display": "slider" # Cosmetic only: display as "number" or "slider"
                     }),
@@ -225,12 +225,13 @@ class FloatSlider:
     INPUT_IS_LIST = False
     OUTPUT_IS_LIST = (False,)
 
-    def run(self,number,min_value,max_value,step):
+    def run(self, number, min_value, max_value, step):
         if number < min_value:
-            number= min_value
+            number = min_value
         elif number > max_value:
-            number= max_value
-        return (number,)
+            number = max_value
+        scaled_number = (number - min_value) / (max_value - min_value)
+        return (scaled_number,)
     
   
 class IntNumber:
@@ -262,7 +263,7 @@ class IntNumber:
                             "default": 1, 
                             "min": -0xffffffffffffffff,
                             "max": 0xffffffffffffffff,
-                            "step":1, 
+                            "step":1,
                             "display": "number"  
                         }),
                              },
@@ -461,6 +462,7 @@ class AppInfo:
 
     CATEGORY = "♾️Mixlab"
 
+    OUTPUT_NODE = True
     INPUT_IS_LIST = True
     OUTPUT_IS_LIST = (True,)
 

web/index.html

@@ -323,6 +323,15 @@
             height: 56px !important;
             outline: 1px solid white;
         }
+
+
+        /* 给prompt image 节点使用 */
+        .prompt_image {
+            color: #2f2f2f;
+            padding: 0 10px;
+            font-size: 12px;
+            width: 200px;
+        }
     </style>
     <!-- <script src="../../../scripts/api.js" type="module"></script> -->
     <link href="/extensions/comfyui-mixlab-nodes/lib/photoswipe.min.css" rel="stylesheet">
@@ -443,20 +452,27 @@
 
         function randomSeed(seed, data) {
             for (const id in data) {
-
                 if (data[id].inputs.seed != undefined
                     && !Array.isArray(data[id].inputs.seed) //如果是数组，则由其他节点控制
                     && ['increment', 'decrement', 'randomize'].includes(seed[id])) {
                     data[id].inputs.seed = Math.round(Math.random() * 1849378600828930)
                     // console.log('new Seed', data[id])
                 }
+                if (data[id].inputs.noise_seed != undefined
+                    && !Array.isArray(data[id].inputs.noise_seed) //如果是数组，则由其他节点控制
+                    && ['increment', 'decrement', 'randomize'].includes(seed[id])) {
+                    data[id].inputs.noise_seed = Math.round(Math.random() * 1849378600828930)
+
+                }
+                console.log('new Seed', data[id])
             }
             return data
         }
 
         function updateSeed(id, val) {
-            console.log(val)
-            if (!Array.isArray(window._appData.data[id].inputs.seed)) window._appData.data[id].inputs.seed = Math.round(val);
+            // console.log(val)
+            if (window._appData.data[id].inputs.seed && !Array.isArray(window._appData.data[id].inputs.seed)) window._appData.data[id].inputs.seed = Math.round(val);
+            if (window._appData.data[id].inputs.noise_seed && !Array.isArray(window._appData.data[id].inputs.noise_seed)) window._appData.data[id].inputs.noise_seed = Math.round(val);
         }
 
 
@@ -596,7 +612,16 @@
                     div.innerText = Array.isArray(node.inputs.text) ? node.inputs.text[0] : node.inputs.text
                     output_card.appendChild(div);
                 };
-                if (["SaveImage", "PreviewImage"].includes(node.class_type)) {
+
+                if (node.class_type == "ClipInterrogator") {
+                    let div = document.createElement('div');
+                    div.className = "show_text";
+                    div.id = `output_${node.id}`;
+                    div.innerText = '#ClipInterrogator: …… '
+                    output_card.appendChild(div);
+                };
+
+                if (["SaveImage", "PreviewImage", "PromptImage"].includes(node.class_type)) {
 
                     let a = document.createElement('a');
                     a.id = `output_${node.id}`
@@ -929,7 +954,7 @@
 
                     const label = data.title;
 
-                    if (!options.keywords.includes(data.inputs.prompt_keyword)) {
+                    if (options.keywords && !options.keywords?.includes(data.inputs.prompt_keyword)) {
                         options.keywords = [data.inputs.prompt_keyword, ...options.keywords]
                     };
 
@@ -959,16 +984,20 @@
                     let silde = createNumSlide(data.title,
                         data.inputs.number,
                         (v) => {
-                            window._appData.data[data.id].inputs.number = v;
+                            // console.log(data.id,window._appData.data[data.id])
+                            window._appData.data[data.id].inputs.number = data.class_type === 'IntNumber' ? parseInt(v) : parseFloat(v);
                         },
                         options.min,
                         options.max,
-                        data.class_type === 'IntNumber' ? 'int' : 'float')
+                        data.class_type === 'IntNumber' ? 'int' : 'float',
+                        null,
+                        data.id
+                    )
                     container.appendChild(silde);
                 }
 
                 // Check if the class_type is "CLIPTextEncode"
-                if (["TextInput_", "CLIPTextEncode"].includes(data.class_type)) {
+                if (["TextInput_", "CLIPTextEncode", "PromptSimplification"].includes(data.class_type)) {
                     // Create a container for the upload control
                     const uploadContainer = document.createElement("div");
                     uploadContainer.className = 'card';
@@ -981,13 +1010,27 @@
                     // Create an input field for the image name
                     const textInput = document.createElement("textarea");
                     // textInput.className=;
-                    textInput.value = data.inputs.text;
+                    if (data.class_type == "PromptSimplification") {
+                        textInput.value = data.inputs.prompt;
+                    } else {
+                        textInput.value = data.inputs.text;
+                    }
+
                     // uploadImageInput.type = "text";
                     let json = localStorage.getItem(`t_${data.id}`)
                     try {
+                        // 缓存
                         const { value, height } = JSON.parse(json);
                         textInput.value = value;
                         textInput.style.height = height;
+
+                        if (data.class_type == "PromptSimplification") {
+                            window._appData.data[data.id].inputs.prompt = textInput.value;
+                        } else {
+                            window._appData.data[data.id].inputs.text = textInput.value;
+                        }
+
+
                     } catch (error) {
 
                     }
@@ -1003,8 +1046,12 @@
                     textInput.addEventListener('input', (event) => {
                         // console.log(textInput.value)
                         autoResize(textInput);
-                        window._appData.data[data.id].inputs.text = textInput.value;
 
+                        if (data.class_type == "PromptSimplification") {
+                            window._appData.data[data.id].inputs.prompt = textInput.value;
+                        } else {
+                            window._appData.data[data.id].inputs.text = textInput.value;
+                        }
                         localStorage.setItem(`t_${data.id}`, JSON.stringify({
                             value: textInput.value,
                             height: textInput.style.height
@@ -1019,6 +1066,22 @@
                 if (["CheckpointLoaderSimple", "LoraLoader"].includes(data.class_type)) {
                     let value = data.inputs.ckpt_name || data.inputs.lora_name;
 
+                    try {
+                        let v = localStorage.getItem(`_model_${data.id}_${data.class_type}`)
+                        if (v) {
+                            value = v;
+                            if (data.class_type === 'CheckpointLoaderSimple') {
+                                window._appData.data[data.id].inputs.ckpt_name = value;
+                            }
+                            if (data.class_type === 'LoraLoader') {
+                                window._appData.data[data.id].inputs.lora_name = value;
+                            }
+                        }
+                    } catch (error) {
+
+                    }
+
+
                     let [div, selectDom] = createSelectWithOptions(data.title, Array.from(data.options, o => {
                         return {
                             value: o,
@@ -1035,6 +1098,8 @@
                         if (data.class_type === 'LoraLoader') {
                             window._appData.data[data.id].inputs.lora_name = selectDom.value;
                         }
+
+                        localStorage.setItem(`_model_${data.id}_${data.class_type}`, selectDom.value)
                     })
 
                     container.appendChild(div);
@@ -1162,8 +1227,11 @@
 
             value = 'float' ? parseFloat(value.toFixed(3)) : parseInt(value)
             try {
-                let i=parseFloat(localStorage.getItem(`_slider_${targetId}`))
-                if(!!i) value = i
+                let i = parseFloat(localStorage.getItem(`_slider_${targetId}`))
+                if (!!i) {
+                    value = i;
+                    callback && callback(value)
+                }
             } catch (error) {
 
             }
@@ -1192,6 +1260,8 @@
 
                 let defaultValue = (targetId ? localStorage.getItem(`_slide_${targetId}`) : '') || keywords[0];
 
+                window._appData.data[targetId].inputs.prompt_keyword = defaultValue;
+
                 let selectTag = createSelect(Array.from(keywords, (k, i) => {
                     return {
                         value: k,
@@ -1515,7 +1585,7 @@
 
                         }
 
-                        if (val && type == "images" && output.querySelector(`#output_${id} img`)) {
+                        if (val && (type == "images" || type == 'images_prompts') && output.querySelector(`#output_${id} img`)) {
                             let imgDiv = output.querySelector(`#output_${id}`)
                             imgDiv.style.display = 'none';
 
@@ -1523,7 +1593,16 @@
                             // Array.from(imgDiv.parentElement.querySelectorAll('.output_images'), im => im.remove());
 
                             for (const v of val) {
-                                let im = await createImage(v);
+
+                                let url = v, prompt = ''
+
+                                if (type == 'images_prompts') {
+                                    // 是个数组，多了对应的prompt
+                                    url = v[0];
+                                    prompt = v[1];
+                                }
+
+                                let im = await createImage(url);
 
                                 // 构建新的
                                 let a = document.createElement('a');
@@ -1531,12 +1610,22 @@
                                 a.setAttribute('data-pswp-width', im.naturalWidth);
                                 a.setAttribute('data-pswp-height', im.naturalHeight);
                                 a.setAttribute('target', "_blank");
-                                a.setAttribute('href', v);
+                                a.setAttribute('href', url);
+
 
                                 let img = new Image();
                                 // img;
-                                img.src = v;
-                                a.appendChild(img)
+                                img.src = url;
+                                a.appendChild(img);
+
+                                if (prompt) {
+                                    a.style.textDecoration = 'none';
+                                    let p = document.createElement('p')
+                                    p.className = 'prompt_image'
+                                    p.innerText = prompt;
+                                    a.appendChild(p)
+                                }
+
                                 // imgDiv.parentElement.appendChild(a);
                                 imgDiv.parentElement.insertBefore(a, imgDiv.parentElement.firstChild);
                             }
@@ -1695,19 +1784,25 @@
             };
 
             api.addEventListener("status", ({ detail }) => {
-                console.log("status", detail);
+                console.log("status", detail, detail.exec_info?.queue_remaining);
                 try {
-                    ui.status.update(`queue#${detail.exec_info.queue_remaining}`);
+                    ui.status.update(`queue#${detail.exec_info?.queue_remaining}`);
+                    if (detail.exec_info?.queue_remaining === 0) {
+                        // 运行按钮重设
+                        ui.submitButton.reset()
+                        console.log('运行按钮重设')
+                    }
                 } catch (error) {
-
+                    console.log(error)
                 }
 
             });
 
             api.addEventListener("progress", ({ detail }) => {
                 console.log("progress", detail);
+                const class_type = window._appData.data[detail?.node]?.class_type || ''
                 try {
-                    ui.status.update(`${detail.value}/${detail.max}`);
+                    ui.status.update(`${parseFloat(100 * detail.value / detail.max).toFixed(1)}% ${class_type}`);
                     ui.submitButton.running()
                 } catch (error) {
 
@@ -1721,6 +1816,12 @@
                 const text = detail?.output?.text;
                 const gifs = detail?.output?.gifs;
 
+                const prompt = detail?.output?.prompt;
+                const analysis = detail?.output?.analysis;
+
+                const _images = detail?.output?._images;
+                const prompts = detail?.output?.prompts;
+
                 if (images) {
                     // if (!images) return;
 
@@ -1730,17 +1831,38 @@
                         return `${url}/view?filename=${encodeURIComponent(img.filename)}&type=${img.type}&subfolder=${encodeURIComponent(img.subfolder)}&t=${+new Date()}`;
                     }), detail.node, 'images');
 
+                } else if (_images && prompts) {
+                    let url = get_url();
+
+                    let items = [];
+                    // 支持图片的batch
+                    Array.from(_images, (imgs, i) => {
+
+                        for (const img of imgs) {
+                            items.push([`${url}/view?filename=${encodeURIComponent(img.filename)
+                                }&type=${img.type}&subfolder=${encodeURIComponent(img.subfolder)
+                                }&t=${+new Date()}`, prompts[i]])
+                        }
+
+                    })
+
+                    show(items, detail.node, 'images_prompts');
+
                 } else if (text) {
-                    ui.output.update("text", Array.isArray(text) ? text[0] : text, detail.node)
+                    ui.output.update("text", Array.isArray(text) ? text.join('\n\n') : text, detail.node)
                 } else if (gifs && gifs[0]) {
                     // if (!images) return; 
                     const src = `${get_url()}/view?filename=${encodeURIComponent(gifs[0].filename)}&type=${gifs[0].type}&subfolder=${encodeURIComponent(gifs[0].subfolder)
                         }&&format=${gifs[0].format}&t=${+new Date()}`;
 
                     show(src, detail.node, gifs[0].format.match('video') ? 'video' : 'image');
+                } else if (prompt && analysis) {
+                    // #ClipInterrogator: …… 
+                    ui.output.update("text", `${prompt.join('\n\n')}\n${JSON.stringify(analysis, null, 2)}`, detail.node)
                 }
 
 
+
                 try {
                     ui.status.update(`executed_#${window._appData.data[detail.node]?.class_type}`);
                     ui.submitButton.reset()
@@ -1768,6 +1890,11 @@
             //     console.log("b_preview", detail)
             //     show(URL.createObjectURL(detail));
             // });
+            api.addEventListener("execution_error", ({ detail }) => {
+
+                console.log("execution_error", detail)
+                // show(URL.createObjectURL(detail));
+            });
 
 
             api.addEventListener('execution_start', async ({ detail }) => {

web/javascript/app_mixlab.js

@@ -126,11 +126,11 @@ function extractInputAndOutputData (jsonData, inputIds = [], outputIds = []) {
         output[outputIds.indexOf(id)] = { ...data[id], title: node.title, id }
       }
 
-      if (node.type === 'KSampler') {
+      if (node.type === 'KSampler'||node.type=='SamplerCustom') {
         // seed 的类型收集
         try {
           seed[id] = node.widgets.filter(
-            w => w.name === 'seed'
+            w => (w.name === 'seed'||w.name=='noise_seed')
           )[0].linkedWidgets[0].value
         } catch (error) {}
       }

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 = 'v0.10.0'
+const version = 'v0.11.0'
 
 fetch(`https://api.github.com/repos/${repoOwner}/${repoName}/releases/latest`)
   .then(response => response.json())

web/javascript/clipInterrogator_mixlab.js

@@ -0,0 +1,65 @@
+import { app } from '../../../scripts/app.js'
+// import { api } from '../../../scripts/api.js'
+import { ComfyWidgets } from '../../../scripts/widgets.js'
+import { $el } from '../../../scripts/ui.js'
+
+app.registerExtension({
+  name: 'Mixlab.prompt.ClipInterrogator',
+  async beforeRegisterNodeDef (nodeType, nodeData, app) {
+    if (nodeData.name === 'ClipInterrogator') {
+      function populate (prompts, items) {
+        if (this.widgets) {
+          for (let i = 0; i < this.widgets.length; i++) {
+            if (this.widgets[i].type !== 'combo') this.widgets[i].onRemove?.()
+          }
+          this.widgets.length = 2
+        }
+
+        const w = ComfyWidgets['STRING'](
+          this,
+          'text',
+          ['STRING', { multiline: true }],
+          app
+        ).widget
+        w.inputEl.readOnly = true
+        w.inputEl.style.opacity = 0.6
+
+        w.value = prompts.join('\n\n')
+
+        const w2 = ComfyWidgets['STRING'](
+          this,
+          'text',
+          ['STRING', { multiline: true }],
+          app
+        ).widget
+        w2.inputEl.readOnly = true
+        w2.inputEl.style.opacity = 0.6
+
+        w2.value = JSON.stringify(items, null, 2)
+
+        console.log('ClipInterrogator',w,w2)
+        requestAnimationFrame(() => {
+          const sz = this.computeSize()
+          if (sz[0] < this.size[0]) {
+            sz[0] = this.size[0]
+          }
+          if (sz[1] < this.size[1]) {
+            sz[1] = this.size[1]
+          }
+          this.onResize?.(sz)
+          app.graph.setDirtyCanvas(true, false)
+        })
+      }
+
+      // When the node is executed we will be sent the input text, display this in the widget
+      const onExecuted = nodeType.prototype.onExecuted
+      nodeType.prototype.onExecuted = function (message) {
+        onExecuted?.apply(this, arguments)
+        console.log('##', message)
+        populate.call(this, message.prompt, message.analysis)
+      }
+
+      this.serialize_widgets = true //需要保存参数
+    }
+  }
+})

web/javascript/gpt_mixlab.js

@@ -256,6 +256,7 @@ app.registerExtension({
 			const onExecuted = nodeType.prototype.onExecuted;
 			nodeType.prototype.onExecuted = function (message) {
 				onExecuted?.apply(this, arguments);
+        console.log('##',message.text)
 				populate.call(this, message.text);
 			};
 

web/javascript/prompt_mixlab.js

@@ -35,6 +35,24 @@ function get_position_style (ctx, widget_width, y, node_height) {
     justifyContent: 'space-between'
   }
 }
+function createImage (url) {
+  let im = new Image()
+  return new Promise((res, rej) => {
+    im.onload = () => res(im)
+    im.src = url
+  })
+}
+
+async function fetchImage (url) {
+  try {
+    const response = await fetch(url)
+    const blob = await response.blob()
+
+    return blob
+  } catch (error) {
+    console.error('出现错误:', error)
+  }
+}
 
 const getLocalData = key => {
   let data = {}
@@ -72,6 +90,116 @@ const createSelect = (select, opts, targetWidget) => {
   })
 }
 
+app.registerExtension({
+  name: 'Mixlab.prompt.RandomPrompt',
+  async beforeRegisterNodeDef (nodeType, nodeData, app) {
+    if (nodeType.comfyClass == 'RandomPrompt') {
+      const orig_nodeCreated = nodeType.prototype.onNodeCreated
+      nodeType.prototype.onNodeCreated = async function () {
+        orig_nodeCreated?.apply(this, arguments)
+        name
+
+        const mutable_prompt = this.widgets.filter(
+          w => w.name == 'mutable_prompt'
+        )[0]
+        // console.log('PromptSlide nodeData', prompt_keyword)
+
+        const widget = {
+          type: 'div',
+          name: 'upload',
+          draw (ctx, node, widget_width, y, widget_height) {
+            Object.assign(
+              this.div.style,
+              get_position_style(ctx, widget_width, y, node.size[1])
+            )
+          }
+        }
+
+        widget.div = $el('div', {})
+
+        const btn = document.createElement('button')
+        btn.innerText = 'Upload Keywords'
+
+        btn.style = `cursor: pointer;
+        font-weight: 300;
+        margin: 2px; 
+        color: var(--descrip-text);
+        background-color: var(--comfy-input-bg);
+        border-radius: 8px;
+        border-color: var(--border-color);
+        border-style: solid;    height: 30px;min-width: 122px;
+       `
+
+        // const btn=document.createElement('button');
+        // btn.innerText='Upload'
+        btn.addEventListener('click', () => {
+          let inp = document.createElement('input')
+          inp.type = 'file'
+          inp.accept = '.txt'
+          inp.click()
+          inp.addEventListener('change', event => {
+            // 获取选择的文件
+            const file = event.target.files[0]
+            this.title = file.name.split('.')[0]
+
+            // console.log(file.name.split('.')[0])
+            // 创建文件读取器
+            const reader = new FileReader()
+
+            // 定义读取完成事件的回调函数
+            reader.onload = event => {
+              // 读取完成后的文本内容
+              const fileContent = event.target.result.split('\n')
+              const keywords = Array.from(fileContent, f => f.trim()).filter(
+                f => f
+              )
+              // 打印文件内容
+              //   console.log(keywords)
+
+              mutable_prompt.value = keywords.join('\n')
+
+              inp.remove()
+            }
+
+            // 以文本方式读取文件
+            reader.readAsText(file)
+          })
+        })
+
+        widget.div.appendChild(btn)
+        document.body.appendChild(widget.div)
+        this.addCustomWidget(widget)
+
+        const onRemoved = this.onRemoved
+        this.onRemoved = () => {
+          widget.div.remove()
+          return onRemoved?.()
+        }
+
+        if (this.onResize) {
+          this.onResize(this.size)
+        }
+
+        this.serialize_widgets = true //需要保存参数
+      }
+    }
+  },
+  async loadedGraphNode (node, app) {
+    if (node.type === 'RandomPrompt') {
+      // try {
+      //   let mutable_prompt = node.widgets.filter(w => w.name === 'mutable_prompt')[0]
+      //   // let ks = getLocalData(`_mixlab_PromptSlide`)
+      //   let uploadWidget = node.widgets.filter(w => w.name == 'upload')[0]
+      //   // console.log('##widget', uploadWidget.value)
+      //   let keywords = JSON.parse(uploadWidget.value)
+      //   if (keywords && keywords[0]) {
+      //     mutable_prompt.value=keywords.join('\n')
+      //   }
+      // } catch (error) {}
+    }
+  }
+})
+
 app.registerExtension({
   name: 'Mixlab.prompt.PromptSlide',
   async beforeRegisterNodeDef (nodeType, nodeData, app) {
@@ -132,8 +260,8 @@ app.registerExtension({
           inp.click()
           inp.addEventListener('change', event => {
             // 获取选择的文件
-            const file = event.target.files[0];
-            this.title=file.name.split('.')[0];
+            const file = event.target.files[0]
+            this.title = file.name.split('.')[0]
 
             // console.log(file.name.split('.')[0])
             // 创建文件读取器
@@ -149,10 +277,11 @@ app.registerExtension({
               // 打印文件内容
               //   console.log(keywords)
 
-              // widget.value = keywords
-              let ks = getLocalData(`_mixlab_PromptSlide`)
-              ks[this.id] = keywords
-              setLocalDataOfWin(`_mixlab_PromptSlide`, ks)
+              widget.value = JSON.stringify(keywords)
+
+              // let ks = getLocalData(`_mixlab_PromptSlide`)
+              // ks[this.id] = keywords
+              // setLocalDataOfWin(`_mixlab_PromptSlide`, ks)
 
               createSelect(select, keywords, prompt_keyword)
 
@@ -187,14 +316,13 @@ app.registerExtension({
     if (node.type === 'PromptSlide') {
       try {
         let prompt = node.widgets.filter(w => w.name === 'prompt_keyword')[0]
-        let ks = getLocalData(`_mixlab_PromptSlide`)
-
-        let keywords = ks[node.id]
+        // let ks = getLocalData(`_mixlab_PromptSlide`)
+        let uploadWidget = node.widgets.filter(w => w.name == 'upload')[0]
+        // console.log('##widget', uploadWidget.value)
+        let keywords = JSON.parse(uploadWidget.value)
         // console.log('keywords',keywords)
         let widget = node.widgets.filter(w => w.select)[0]
         if (keywords && keywords[0]) {
-          // let widget = node.widgets.filter(w => w.select)[0]
-          // console.log('select',widget,widget.value)
           widget.select.style.display = 'block'
           createSelect(widget.select, keywords, prompt)
         }
@@ -202,3 +330,152 @@ app.registerExtension({
     }
   }
 })
+
+const _createResult = async (node, widget, message) => {
+  widget.div.innerHTML = ``
+
+  const width = node.size[0] * 0.5 - 12
+
+  let height_add = 0
+
+  for (let index = 0; index < message._images.length; index++) {
+    const imgs = message._images[index]
+
+    for (const img of imgs) {
+      let url = api.apiURL(
+        `/view?filename=${encodeURIComponent(img.filename)}&type=${
+          img.type
+        }&subfolder=${
+          img.subfolder
+        }${app.getPreviewFormatParam()}${app.getRandParam()}`
+      )
+
+      let image = await createImage(url)
+
+      // 创建card
+      let div = document.createElement('div')
+      div.className = 'card'
+      div.draggable = true
+
+      div.ondragend = async event => {
+        console.log('拖动停止')
+        let url = div.querySelector('img').src
+
+        let blob = await fetchImage(url)
+
+        let imageNode = null
+        // No image node selected: add a new one
+        if (!imageNode) {
+          const newNode = LiteGraph.createNode('LoadImage')
+          newNode.pos = [...app.canvas.graph_mouse]
+          imageNode = app.graph.add(newNode)
+          app.graph.change()
+        }
+
+        // const blob = item.getAsFile();
+        imageNode.pasteFile(blob)
+      }
+
+      div.setAttribute('data-scale', image.naturalHeight / image.naturalWidth)
+
+      let h = (image.naturalHeight * width) / image.naturalWidth
+      if (index % 2 === 0) height_add += h
+      div.style = `width: ${width}px;height:${h}px;position: relative;margin: 4px;`
+      div.innerHTML = `<img src="${url}" style='width: 100%'/>
+            <p style="position: absolute;
+            bottom: 0;
+            left: 0; 
+            background:#444444c2;
+            margin: 0;
+            font-size: 12px;
+            padding: 5px;
+            text-align: left;">${message.prompts[index]}</p>`
+      widget.div.appendChild(div)
+    }
+  }
+
+  node.size[1] = 98 + height_add
+}
+
+app.registerExtension({
+  name: 'Mixlab.prompt.PromptImage',
+
+  async beforeRegisterNodeDef (nodeType, nodeData, app) {
+    if (nodeType.comfyClass == 'PromptImage') {
+      const orig_nodeCreated = nodeType.prototype.onNodeCreated
+      nodeType.prototype.onNodeCreated = function () {
+        orig_nodeCreated?.apply(this, arguments)
+        console.log('#orig_nodeCreated', this)
+        const widget = {
+          type: 'div',
+          name: 'result',
+          draw (ctx, node, widget_width, y, widget_height) {
+            Object.assign(this.div.style, {
+              ...get_position_style(ctx, widget_width, y, node.size[1]),
+              flexWrap: 'wrap',
+              justifyContent: 'space-between',
+              // outline: '1px solid red',
+              paddingLeft: '0px',
+              width: widget_width + 'px'
+            })
+          }
+        }
+
+        widget.div = $el('div', {})
+
+        document.body.appendChild(widget.div)
+
+        this.addCustomWidget(widget)
+
+        const onRemoved = this.onRemoved
+        this.onRemoved = () => {
+          widget.div.remove()
+          return onRemoved?.()
+        }
+
+        const onResize = this.onResize
+        this.onResize = function () {
+          // 缩放发生
+          // console.log('##缩放发生', this.size)
+          let w = this.size[0] * 0.5 - 12
+          Array.from(widget.div.querySelectorAll('.card'), card => {
+            card.style.width = `${w}px`
+            card.style.height = `${
+              w * parseFloat(card.getAttribute('data-scale'))
+            }px`
+          })
+          return onResize?.apply(this, arguments)
+        }
+
+        // this.serialize_widgets = true //需要保存参数
+      }
+
+      const onExecuted = nodeType.prototype.onExecuted
+      nodeType.prototype.onExecuted = async function (message) {
+        onExecuted?.apply(this, arguments)
+        console.log('#PromptImage', message.prompts, message._images)
+        // window._mixlab_app_json = message.json
+        try {
+          let widget = this.widgets.filter(w => w.name === 'result')[0]
+          widget.value = message
+          _createResult(this, widget, { ...message })
+        } catch (error) {
+          console.log(error)
+        }
+      }
+
+      this.serialize_widgets = true //需要保存参数
+    }
+  },
+  async loadedGraphNode (node, app) {
+    if (node.type === 'PromptImage') {
+      // await sleep(0)
+      let widget = node.widgets.filter(w => w.name === 'result')[0]
+      console.log('widget.value', widget.value)
+      let cards = widget.div.querySelectorAll('.card')
+      if (cards.length == 0) node.size = [280, 120]
+
+      _createResult(node, widget, widget.value)
+    }
+  }
+})

web/javascript/utils_mixlab.js

@@ -159,7 +159,7 @@ app.registerExtension({
           el: `#${inputColor.id}`,
           theme: 'classic', // or 'monolith', or 'nano'
           // closeOnScroll: true,
-          default:'#000000',
+          default: '#000000',
           swatches: [
             'rgba(244, 67, 54, 1)',
             'rgba(233, 30, 99, 0.95)',
@@ -257,7 +257,6 @@ app.registerExtension({
 
 app.registerExtension({
   name: 'Mixlab.utils.TextToNumber',
-
   async beforeRegisterNodeDef (nodeType, nodeData, app) {
     if (nodeType.comfyClass == 'TextToNumber') {
       const onExecuted = nodeType.prototype.onExecuted
@@ -276,3 +275,62 @@ app.registerExtension({
     }
   }
 })
+
+const min_max = node => {
+  if(node.widgets){
+    const min_value = node.widgets.filter(w => w.name === 'min_value')[0]
+    const max_value = node.widgets.filter(w => w.name === 'max_value')[0]
+  
+    const number = node.widgets.filter(w => w.name === 'number')[0]
+    if (number) {
+      number.options.min = min_value.value
+      number.options.max = max_value.value
+  
+      number.value = Math.min(number.options.max, number.value)
+      number.value = Math.max(number.options.min, number.value)
+    }
+  
+    if (min_value)
+      min_value.callback = e => {
+        number.options.min = e
+        number.value = e
+      }
+    if (max_value)
+      max_value.callback = e => {
+        number.options.max = e
+        number.value = e
+      }
+  }
+  
+}
+
+app.registerExtension({
+  name: 'Mixlab.utils.FloatSlider',
+  async beforeRegisterNodeDef (nodeType, nodeData, app) {
+    const orig_nodeCreated = nodeType.prototype.onNodeCreated
+    nodeType.prototype.onNodeCreated = function () {
+      orig_nodeCreated?.apply(this, arguments)
+      min_max(this)
+    }
+  },
+  async loadedGraphNode (node, app) {
+    if (node.type === 'FloatSlider') {
+      min_max(node)
+    }
+  }
+})
+app.registerExtension({
+  name: 'Mixlab.utils.IntNumber',
+  async beforeRegisterNodeDef (nodeType, nodeData, app) {
+    const orig_nodeCreated = nodeType.prototype.onNodeCreated
+    nodeType.prototype.onNodeCreated = function () {
+      orig_nodeCreated?.apply(this, arguments)
+      min_max(this)
+    }
+  },
+  async loadedGraphNode (node, app) {
+    if (node.type === 'IntNumber') {
+      min_max(node)
+    }
+  }
+})