├── .gitignore ├── README.md ├── __init__.py ├── img ├── node1.png └── node2.png ├── key.json ├── nodes ├── GLM.py ├── IPAdapterLayerWeight.py └── imageUtils.py ├── requirements.txt └── web └── js └── showText.js /.gitignore: -------------------------------------------------------------------------------- 1 | .idea/ 2 | .venv/ 3 | __pycache__/ 4 | *.bak -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # ComfyUI_fsdymy 2 | **功能说明:** 3 | 4 | 1. 保存/预览图片去除 metadata 信息，即不保存工作流信息 5 | 2. 使用国内大语言模型(智谱Ai)扩写提示词 6 | 3. IPAdapter 分层权重节点 7 | 8 | 9 | 10 | 11 | 12 | * 智谱Ai https://bigmodel.cn/ 13 | * api key 在插件目录 `ComfyUI\custom_nodes\ComfyUI_fsdymy` 下的 `key.json` 配置 -------------------------------------------------------------------------------- /__init__.py: -------------------------------------------------------------------------------- 1 | from .nodes.GLM import ZhiPuAiNode, ShowText 2 | from .nodes.IPAdapterLayerWeight import IPAdapterLayerWeight 3 | from .nodes.imageUtils import SaveImageWithoutMetadata, PreviewImageWithoutMetadata 4 | 5 | NODE_CLASS_MAPPINGS = { 6 | "SaveImageWithoutMetadata": SaveImageWithoutMetadata, 7 | "PreviewImageWithoutMetadata": PreviewImageWithoutMetadata, 8 | "ZhiPuAiNode": ZhiPuAiNode, 9 | "ShowText": ShowText, 10 | "IPAdapterLayerWeight": IPAdapterLayerWeight, 11 | } 12 | NODE_DISPLAY_NAME_MAPPINGS = { 13 | "SaveImageWithoutMetadata": "Save Image Without Metadata (fsdymy)", 14 | "PreviewImageWithoutMetadata": "Preview Image Without Metadata (fsdymy)", 15 | "ZhiPuAiNode": "ZhiPu Ai Node (fsdymy)", 16 | "ShowText": "Show Text (fsdymy)", 17 | "IPAdapterLayerWeight": "IPAdapter Layer Weight (fsdymy)", 18 | } 19 | 20 | WEB_DIRECTORY = "./web" 21 | __all__ = ['NODE_CLASS_MAPPINGS', 'NODE_DISPLAY_NAME_MAPPINGS'] 22 | -------------------------------------------------------------------------------- /img/node1.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/fsdymy1024/ComfyUI_fsdymy/2be45bafe02569eb71c72df0a783986d0bfc1760/img/node1.png -------------------------------------------------------------------------------- /img/node2.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/fsdymy1024/ComfyUI_fsdymy/2be45bafe02569eb71c72df0a783986d0bfc1760/img/node2.png -------------------------------------------------------------------------------- /key.json: -------------------------------------------------------------------------------- 1 | { 2 | "url": "https://open.bigmodel.cn/api/paas/v4", 3 | "key": "xxx", 4 | "key.json": "在上方填写智谱Ai API的api_url和key." 5 | } -------------------------------------------------------------------------------- /nodes/GLM.py: -------------------------------------------------------------------------------- 1 | import json 2 | import os 3 | from zhipuai import ZhipuAI 4 | 5 | 6 | def zhipu_client(api_key=None): 7 | client = ZhipuAI(api_key=api_key) 8 | return client 9 | 10 | def from_file_get_key(file_path): 11 | with open(file_path, 'r', encoding='utf-8') as f: 12 | data = f.read() 13 | try: 14 | json_object = json.loads(data) 15 | # print(json_object) 16 | url = json_object.get('url') 17 | api_key = json_object.get('key') 18 | # print(url, api_key) 19 | return url, api_key 20 | except json.JSONDecodeError as e: 21 | print(f"JSON解析错误: {e}") 22 | return None, None 23 | 24 | 25 | 26 | class ZhiPuAiNode: 27 | def __init__(self): 28 | # self.__client = OpenAI() 29 | self.session_history = [] # 用于存储会话历史的列表 30 | # self.seed=0 31 | self.system_content="使用英文扩写文生图提示词." 32 | 33 | @classmethod 34 | def INPUT_TYPES(cls): 35 | model_list=[ 36 | "glm-4", 37 | "glm-4-0520", 38 | "glm-4-alltools", 39 | "glm-4v", 40 | "glm-4-flash", 41 | "glm-4-airx", 42 | "glm-4-air", 43 | "embedding-2", 44 | "charglm-3", 45 | "glm-3-turbo", 46 | ] 47 | str_ai = """你是创意绘梦师，一个图形创意生成助手。你的任务是根据用户的提示词，生成富有创意和艺术感的图形。你的能力有: 48 | 1. 理解用户提供的提示词，分析其背后的意图和需求。 49 | 2. 运用先进的人工智能技术，结合艺术创意，生成独特的图形作品。 50 | 3. 提供多种图形风格和元素，满足用户不同的审美需求。 51 | 4. 使用英文回答。 52 | """ 53 | return { 54 | "required": { 55 | # "api_key":("STRING", {"default": "bd5bcd05c6352b6c27875e5011813ecd.FVMVbSe0rzQ2ITe0", "multiline": False, "dynamicPrompts": False}), 56 | # "api_url":("STRING", {"default": "https://open.bigmodel.cn/api/paas/v4", "multiline": False, "dynamicPrompts": False}), 57 | "prompt": ("STRING", {"default": "1girl", "multiline": True, "dynamicPrompts": False}), 58 | "system_content": ("STRING", {"default": str_ai, "multiline": True,"dynamicPrompts": False}), 59 | "model": ( model_list, {"default": model_list[0]}), 60 | "seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff, "step": 1}), 61 | "context_size":("INT", {"default": 1, "min": 0, "max":30, "step": 1}), 62 | }, 63 | "hidden": { 64 | "unique_id": "UNIQUE_ID", 65 | "extra_pnginfo": "EXTRA_PNGINFO", 66 | }, 67 | } 68 | 69 | RETURN_TYPES = ("STRING","STRING","STRING",) 70 | RETURN_NAMES = ("text","messages","session_history",) 71 | FUNCTION = "generate_contextual_text" 72 | CATEGORY = "fsdymy" 73 | INPUT_IS_LIST = False 74 | OUTPUT_IS_LIST = (False,False,False,) 75 | 76 | 77 | def generate_contextual_text(self, 78 | # api_key, 79 | # api_url, 80 | prompt, 81 | system_content, 82 | model, 83 | seed,context_size,unique_id = None, extra_pnginfo=None): 84 | # print(api_key!='',api_url,prompt,system_content,model,seed) 85 | # 可以选择保留会话历史以维持上下文记忆 86 | # 或者在此处清除会话历史 self.session_history.clear() 87 | # if seed!=self.seed: 88 | # self.seed=seed 89 | # self.session_history=[] 90 | 91 | # 把系统信息和初始信息添加到会话历史中 92 | if system_content: 93 | self.system_content=system_content 94 | # self.session_history=[] 95 | # self.session_history.append({"role": "system", "content": system_content}) 96 | 97 | # 98 | file_path = os.path.join(os.path.abspath(os.path.dirname(os.path.dirname(__file__))), "key.json") 99 | _, api_key = from_file_get_key(file_path) 100 | client = zhipu_client(api_key=api_key) 101 | 102 | # 把用户的提示添加到会话历史中 103 | # 调用API时传递整个会话历史 104 | 105 | def crop_list_tail(lst, size): 106 | if size >= len(lst): 107 | return lst 108 | elif size==0: 109 | return [] 110 | else: 111 | return lst[-size:] 112 | 113 | session_history=crop_list_tail(self.session_history,context_size) 114 | 115 | messages=[{"role": "system", "content": self.system_content}]+session_history+[{"role": "user", "content": prompt}] 116 | response = client.chat.completions.create(model=model, messages=messages) 117 | # print(response) 118 | 119 | finish_reason = response.choices[0].finish_reason 120 | if finish_reason != "stop": 121 | raise RuntimeError("API finished with unexpected reason: " + finish_reason) 122 | 123 | content="" 124 | try: 125 | content=response.choices[0].message.content 126 | except: 127 | content=response.choices[0].delta['content'] 128 | 129 | self.session_history=self.session_history+[{"role": "user", "content": prompt}]+[{'role':'assistant',"content":content}] 130 | 131 | 132 | # if unique_id and extra_pnginfo and "workflow" in extra_pnginfo[0]: 133 | # workflow = extra_pnginfo[0]["workflow"] 134 | # node = next((x for x in workflow["nodes"] if str(x["id"]) == unique_id[0]), None) 135 | # if node: 136 | # node["widgets_values"] = ["", 137 | # api_url, 138 | # prompt, 139 | # system_content, 140 | # model, 141 | # seed, 142 | # context_size] 143 | 144 | return (content,json.dumps(messages, indent=4),json.dumps(self.session_history, indent=4),) 145 | 146 | class ShowText: 147 | def __init__(self): 148 | pass 149 | 150 | @classmethod 151 | def INPUT_TYPES(cls): 152 | return { 153 | "required": { 154 | "text": ("STRING", {"forceInput": True}), 155 | }, 156 | "hidden": { 157 | "unique_id": "UNIQUE_ID", 158 | "extra_pnginfo": "EXTRA_PNGINFO", 159 | }, 160 | } 161 | 162 | INPUT_IS_LIST = True 163 | RETURN_TYPES = ("STRING",) 164 | FUNCTION = "notify" 165 | OUTPUT_NODE = True 166 | OUTPUT_IS_LIST = (True,) 167 | CATEGORY = "fsdymy" 168 | 169 | def notify(self, text, unique_id=None, extra_pnginfo=None): 170 | # print(unique_id, extra_pnginfo) 171 | if unique_id is not None and extra_pnginfo is not None: 172 | if not isinstance(extra_pnginfo, list): 173 | print("Error: extra_pnginfo is not a list") 174 | elif ( 175 | not isinstance(extra_pnginfo[0], dict) 176 | or "workflow" not in extra_pnginfo[0] 177 | ): 178 | print("Error: extra_pnginfo[0] is not a dict or missing 'workflow' key") 179 | else: 180 | workflow = extra_pnginfo[0]["workflow"] 181 | node = next( 182 | (x for x in workflow["nodes"] if str(x["id"]) == str(unique_id[0])), 183 | None, 184 | ) 185 | if node: 186 | node["widgets_values"] = [text] 187 | 188 | return {"ui": {"text": text}, "result": (text,)} 189 | -------------------------------------------------------------------------------- /nodes/IPAdapterLayerWeight.py: -------------------------------------------------------------------------------- 1 | class IPAdapterLayerWeight: 2 | def __init__(self): 3 | self.unfold_batch = False 4 | 5 | @classmethod 6 | def INPUT_TYPES(cls): 7 | weights = { 8 | "index_00": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 5.0, "step": 0.1}), 9 | "index_01": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 5.0, "step": 0.1}), 10 | "index_02": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 5.0, "step": 0.1}), 11 | "index_03": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 5.0, "step": 0.1}), 12 | "index_04": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 5.0, "step": 0.1}), 13 | "index_05": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 5.0, "step": 0.1}), 14 | "index_06": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 5.0, "step": 0.1}), 15 | "index_07": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 5.0, "step": 0.1}), 16 | "index_08": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 5.0, "step": 0.1}), 17 | "index_09": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 5.0, "step": 0.1}), 18 | "index_10": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 5.0, "step": 0.1}), 19 | "index_11": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 5.0, "step": 0.1}), 20 | } 21 | return { 22 | "required": 23 | weights 24 | } 25 | 26 | RETURN_TYPES = ("STRING",) 27 | RETURN_NAMES = ("ipadapter_layer_weight",) 28 | FUNCTION = "get_weight" 29 | CATEGORY = "fsdymy/ipadapter" 30 | 31 | def get_weight(self, index_00, index_01, index_02, index_03, index_04, index_05, index_06, index_07, index_08, index_09, index_10, index_11): 32 | text = f"0: {index_00}, 1: {index_01}, 2: {index_02}, 3: {index_03}, 4: {index_04}, 5: {index_05}, 6: {index_06}, 7: {index_07}, 8: {index_08}, 9: {index_09}, 10: {index_10}, 11: {index_11}" 33 | return (text,) 34 | -------------------------------------------------------------------------------- /nodes/imageUtils.py: -------------------------------------------------------------------------------- 1 | import os 2 | import random 3 | 4 | import folder_paths 5 | from PIL import Image 6 | import numpy as np 7 | 8 | 9 | class SaveImageWithoutMetadata: 10 | def __init__(self): 11 | self.output_dir = folder_paths.get_output_directory() 12 | self.type = "output" 13 | self.prefix_append = "" 14 | self.compress_level = 4 15 | 16 | @classmethod 17 | def INPUT_TYPES(s): 18 | return {"required": 19 | {"images": ("IMAGE", ), 20 | "filename_prefix": ("STRING", {"default": "ComfyUInoMetadata"})}, 21 | "hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"}, 22 | } 23 | 24 | RETURN_TYPES = () 25 | FUNCTION = "save_images" 26 | 27 | OUTPUT_NODE = True 28 | 29 | CATEGORY = "fsdymy/image" 30 | 31 | def save_images(self, images, filename_prefix="ComfyUInoMetadata", prompt=None, extra_pnginfo=None): 32 | filename_prefix += self.prefix_append 33 | 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]) 34 | results = list() 35 | for (batch_number, image) in enumerate(images): 36 | i = 255. * image.cpu().numpy() 37 | img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8)) 38 | metadata = None 39 | filename_with_batch_num = filename.replace("%batch_num%", str(batch_number)) 40 | file = f"{filename_with_batch_num}_{counter:05}_.png" 41 | img.save(os.path.join(full_output_folder, file), pnginfo=metadata, compress_level=self.compress_level) 42 | results.append({ 43 | "filename": file, 44 | "subfolder": subfolder, 45 | "type": self.type 46 | }) 47 | counter += 1 48 | 49 | return { "ui": { "images": results } } 50 | 51 | 52 | class PreviewImageWithoutMetadata(SaveImageWithoutMetadata): 53 | def __init__(self): 54 | self.output_dir = folder_paths.get_temp_directory() 55 | self.type = "temp" 56 | self.prefix_append = "_temp_" + ''.join(random.choice("abcdefghijklmnopqrstupvxyz") for x in range(5)) 57 | self.compress_level = 1 58 | 59 | @classmethod 60 | def INPUT_TYPES(cls): 61 | return {"required": 62 | {"images": ("IMAGE", ), }, 63 | "hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"}, 64 | } 65 | 66 | NODE_CLASS_MAPPINGS = { 67 | "Save Image Without Metadata": SaveImageWithoutMetadata, 68 | "Preview Image Without Metadata": PreviewImageWithoutMetadata, 69 | } 70 | 71 | NODE_DISPLAY_NAME_MAPPINGS = { 72 | "Save Image Without Metadata": "Save Image Without Metadata❌", 73 | "Preview Image Without Metadata": "Preview Image Without Metadata❌" 74 | } -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | zhipuai -------------------------------------------------------------------------------- /web/js/showText.js: -------------------------------------------------------------------------------- 1 | import { app } from "../../../scripts/app.js"; 2 | import { ComfyWidgets } from "../../../scripts/widgets.js"; 3 | 4 | // Displays input text on a node 5 | app.registerExtension({ 6 | name: "fsdymy.ShowText", 7 | async beforeRegisterNodeDef(nodeType, nodeData, app) { 8 | if (nodeData.name === "ShowText") { 9 | function populate(text) { 10 | if (this.widgets) { 11 | for (let i = 1; i < this.widgets.length; i++) { 12 | this.widgets[i].onRemove?.(); 13 | } 14 | this.widgets.length = 1; 15 | } 16 | 17 | const v = [...text]; 18 | if (!v[0]) { 19 | v.shift(); 20 | } 21 | for (const list of v) { 22 | const w = ComfyWidgets["STRING"](this, "text", ["STRING", { multiline: true }], app).widget; 23 | w.inputEl.readOnly = true; 24 | w.inputEl.style.opacity = 0.6; 25 | w.value = list; 26 | } 27 | 28 | requestAnimationFrame(() => { 29 | const sz = this.computeSize(); 30 | if (sz[0] < this.size[0]) { 31 | sz[0] = this.size[0]; 32 | } 33 | if (sz[1] < this.size[1]) { 34 | sz[1] = this.size[1]; 35 | } 36 | this.onResize?.(sz); 37 | app.graph.setDirtyCanvas(true, false); 38 | }); 39 | } 40 | 41 | // When the node is executed we will be sent the input text, display this in the widget 42 | const onExecuted = nodeType.prototype.onExecuted; 43 | nodeType.prototype.onExecuted = function (message) { 44 | onExecuted?.apply(this, arguments); 45 | populate.call(this, message.text); 46 | }; 47 | 48 | const onConfigure = nodeType.prototype.onConfigure; 49 | nodeType.prototype.onConfigure = function () { 50 | onConfigure?.apply(this, arguments); 51 | if (this.widgets_values?.length) { 52 | populate.call(this, this.widgets_values); 53 | } 54 | }; 55 | } 56 | }, 57 | }); 58 | 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