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9 Commits
Author SHA1 Message Date
shadowcz007 05b3088b75 0.35.1 2024-08-04 18:02:13 +08:00
shadowcz007 fe57286959 v0.34.0 2024-08-04 15:28:47 +08:00
shadowcz007 03645bbb33 image batch to list 2024-08-04 13:35:22 +08:00
shadowcz007 93dba9a399 fixbug :load image (base64) 2024-08-04 12:12:41 +08:00
shadowcz007 5627ea8073 Merge branch 'main' of https://github.com/shadowcz007/comfyui-mixlab-nodes 2024-08-04 09:40:43 +08:00
shadowcz007 7ba679c9ce fixbug 2024-08-04 09:40:40 +08:00
shadow c7a450e6ce Merge pull request #289 from ComfyNodePRs/licence-update
Update PyProject Toml - License
2024-08-03 17:50:25 +08:00
snomiao beda5156bf chore(licence-update): Update PyProject Toml - License 2024-08-02 23:03:55 +00:00
shadowcz007 76a9da7163 fixbug 2024-08-02 18:32:27 +08:00
14 changed files with 773 additions and 450 deletions
+7 -3
View File
@@ -1,6 +1,6 @@
![](https://img.shields.io/github/release/shadowcz007/comfyui-mixlab-nodes)
> 适配了最新版 comfyui 的 py3.11 ,torch 2.1.2+cu121
> 适配了最新版 comfyui 的 py3.11 ,torch 2.3.1+cu121
> [Mixlab nodes discord](https://discord.gg/cXs9vZSqeK)
@@ -10,6 +10,8 @@
![alt text](./assets/1722517810720.png)
- 增加 API Key Input 节点,用于管理LLM的Key,同时优化LLM相关节点,为后续agent模式做准备
- 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)
@@ -53,6 +55,7 @@
- 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)
@@ -115,9 +118,10 @@ https://github.com/shadowcz007/comfyui-mixlab-nodes/assets/12645064/e7e77f90-e43
> Support for calling multiple GPTs.Local LLM(llama.cpp)、 ChatGPT、ChatGLM3 、ChatGLM4 , Some code provided by rui. If you are using OpenAI's service, fill in https://api.openai.com/v1 . If you are using a local LLM service, fill in http://127.0.0.1:xxxx/v1 . Azure OpenAI:https://xxxx.openai.azure.com
![gpt-workflow.svg](./assets/gpt-workflow.svg)
[LLM_base_workflow](./workflow/LLM_base_workflow.json)
[workflow-5](./workflow/5-gpt-workflow.json)
- SiliconflowLLM
- ChatGPTOpenAI
<!-- 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。
+43 -39
View File
@@ -22,9 +22,8 @@ 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
@@ -320,22 +319,22 @@ def get_my_workflow_for_app(filename="my_workflow_app.json",category="",is_all=F
# 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":{
@@ -455,6 +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()
@@ -534,7 +534,8 @@ async def new_start(self, address, port, verbose=True, call_on_start=None):
# print("\033[93mStarting server\n")
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))
@@ -754,15 +755,16 @@ def random_seed(seed, data):
for id, value in data.items():
# print(seed,id)
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)
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
@@ -992,16 +994,19 @@ 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 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.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.Audio import AudioPlayNode,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.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
@@ -1037,6 +1042,7 @@ NODE_CLASS_MAPPINGS = {
"ShowLayer":ShowLayer,
"NewLayer":NewLayer,
"ImageListToBatch_":ImageListToBatch_,
"ImageBatchToList_":ImageBatchToList_,
"CompositeImages_":CompositeImages,
"SplitImage":SplitImage,
"CenterImage":CenterImage,
@@ -1061,6 +1067,7 @@ NODE_CLASS_MAPPINGS = {
"SpeechRecognition":SpeechRecognition,
"SpeechSynthesis":SpeechSynthesis,
"KeyInput":KeyInput,
"Color":ColorInput,
"FloatSlider":FloatSlider,
"IntNumber":IntNumber,
@@ -1099,6 +1106,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
"Color":"Color Input ♾️MixlabApp",
"TextInput_":"Text Input ♾️MixlabApp",
"KeyInput":"API Key Input ♾️MixlabApp",
"FloatSlider":"Float Slider Input ♾️MixlabApp",
"IntNumber":"Int Input ♾️MixlabApp",
"ImagesPrompt_":"Images Input ♾️MixlabApp",
@@ -1117,6 +1125,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
"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",
@@ -1153,7 +1162,6 @@ NODE_DISPLAY_NAME_MAPPINGS = {
# 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')
@@ -1162,7 +1170,7 @@ try:
from .nodes.ChatGPT import ChatGPTNode,ShowTextForGPT,CharacterInText,TextSplitByDelimiter,SiliconflowFreeNode
logging.info('ChatGPT.available True')
NODE_CLASS_MAPPINGS_V = {
NODE_CLASS_MAPPINGS_V = {
"ChatGPTOpenAI":ChatGPTNode,
"SiliconflowLLM":SiliconflowFreeNode,
"ShowTextForGPT":ShowTextForGPT,
@@ -1171,7 +1179,7 @@ try:
}
# 一个包含节点友好/可读的标题的字典
NODE_DISPLAY_NAME_MAPPINGS_V = {
NODE_DISPLAY_NAME_MAPPINGS_V = {
"ChatGPTOpenAI":"ChatGPT & Local LLM ♾️Mixlab",
"SiliconflowLLM":"LLM Siliconflow ♾️Mixlab",
"ShowTextForGPT":"Show Text ♾️MixlabApp",
@@ -1268,7 +1276,7 @@ except:
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"
@@ -1283,8 +1291,4 @@ except Exception as e:
logging.info('TripoSR.available False' )
logging.info('\033[93m -------------- \033[0m')
+76 -19
View File
@@ -207,6 +207,36 @@ def chat(client, model_name,messages ):
return content
llm_apis=[
{
"value": "https://api.openai.com/v1",
"label": "openai"
},
{
"value": "https://openai.api2d.net/v1",
"label": "api2d"
},
# {
# "value": "https://docs-test-001.openai.azure.com",
# "label": "https://docs-test-001.openai.azure.com"
# },
{
"value": "https://api.moonshot.cn/v1",
"label": "Kimi"
},
{
"value": "https://api.deepseek.com/v1",
"label": "DeepSeek-V2"
},
{
"value": "https://api.siliconflow.cn/v1",
"label": "SiliconCloud"
}]
llm_apis_dict = {api["label"]: api["value"] for api in llm_apis}
class ChatGPTNode:
def __init__(self):
# self.__client = OpenAI()
@@ -216,8 +246,9 @@ class ChatGPTNode:
@classmethod
def INPUT_TYPES(cls):
model_list=[
"gpt-3.5-turbo",
"gpt-3.5-turbo",
"gpt-3.5-turbo-16k",
"gpt-4o",
"gpt-4o-2024-05-13",
@@ -243,25 +274,32 @@ class ChatGPTNode:
"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}),
"api_url":("URL", {"default": "", "multiline": True,"dynamicPrompts": False}),
# "api_key":("KEY", {"default": "", "multiline": True,"dynamicPrompts": False}),
# "api_key":("STRING", {"forceInput": True,}),
"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}),
"api_url":(list(llm_apis_dict.keys()),
{"default": list(llm_apis_dict.keys())[0]}),
},
"hidden": {
"unique_id": "UNIQUE_ID",
"extra_pnginfo": "EXTRA_PNGINFO",
},
"optional":{
"api_key":("STRING", {"forceInput": True,}),
"custom_model_name":("STRING", {"forceInput": True,}), #适合自定义model
"custom_api_url":("STRING", {"forceInput": True,}), #适合自定义model
},
}
RETURN_TYPES = ("STRING","STRING","STRING",)
@@ -273,12 +311,29 @@ class ChatGPTNode:
def generate_contextual_text(self,
api_key,
api_url,
# api_key,
prompt,
system_content,
model,
seed,context_size,unique_id = None, extra_pnginfo=None):
model,
seed,
context_size,
api_url,
api_key=None,
custom_model_name=None,
custom_api_url=None,
):
if custom_model_name!=None:
model=custom_model_name
api_url=llm_apis_dict[api_url] if api_url in llm_apis_dict else ""
if custom_api_url!=None:
api_url=custom_api_url
if api_key==None:
api_key="lm_studio"
# print(api_key!='',api_url,prompt,system_content,model,seed)
# 可以选择保留会话历史以维持上下文记忆
# 或者在此处清除会话历史 self.session_history.clear()
@@ -291,7 +346,7 @@ class ChatGPTNode:
self.system_content=system_content
# self.session_history=[]
# self.session_history.append({"role": "system", "content": system_content})
print("api_key,api_url",api_key,api_url)
#
if is_azure_url(api_url):
client=azure_client(api_key,api_url)
@@ -359,7 +414,7 @@ class SiliconflowFreeNode:
]
return {
"required": {
"api_key":("KEY", {"default": "", "multiline": True,"dynamicPrompts": False}),
"api_key":("STRING", {"forceInput": True,}),
"prompt": ("STRING", {"multiline": True,"dynamicPrompts": False}),
"system_content": ("STRING",
{
@@ -371,10 +426,9 @@ class SiliconflowFreeNode:
"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",
},
"optional":{
"custom_model_name":("STRING", {"forceInput": True,}), #适合自定义model
},
}
RETURN_TYPES = ("STRING","STRING","STRING",)
@@ -390,8 +444,11 @@ class SiliconflowFreeNode:
prompt,
system_content,
model,
seed,context_size,unique_id = None, extra_pnginfo=None):
seed,context_size,custom_model_name=None):
if custom_model_name!=None:
model=custom_model_name
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
-3
View File
@@ -1829,12 +1829,9 @@ class CompositeImages:
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)
+22
View File
@@ -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
+1 -1
View File
@@ -1,7 +1,7 @@
[project]
name = "comfyui-mixlab-nodes"
description = "3D, ScreenShareNode & FloatingVideoNode, SpeechRecognition & SpeechSynthesis, GPT, LoadImagesFromLocal, Layers, Other Nodes, ..."
version = "0.33.0"
version = "0.35.1"
license = "MIT"
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"]
+14 -4
View File
@@ -1740,7 +1740,7 @@
if (data.class_type === 'CheckpointLoaderSimple') {
if (window._appData.data) window._appData.data[data.id].inputs.ckpt_name = selectDom.value;
//更新输入参数
updateInputData(nodeId, (inputs) => {
updateInputData(data.id, (inputs) => {
inputs.ckpt_name = selectDom.value;
return inputs
})
@@ -1748,7 +1748,7 @@
if (data.class_type === 'LoraLoader') {
if (window._appData.data) window._appData.data[data.id].inputs.lora_name = selectDom.value;
//更新输入参数
updateInputData(nodeId, (inputs) => {
updateInputData(data.id, (inputs) => {
inputs.lora_name = selectDom.value;
return inputs
})
@@ -2870,7 +2870,12 @@
window._appData.category,
window._appData.seed,
inp,
api.clientId
api.clientId,
window._appData.data ? [{
data: {
output: window._appData.data
}
}] : null
).then(res => {
if (!res) {
@@ -2900,7 +2905,12 @@
window._appData.category,
window._appData.seed,
window._appData.input.filter(inp => inp),
api.clientId
api.clientId,
window._appData.data ? [{
data: {
output: window._appData.data
}
}] : null
).then(res => {
if (!res) {
+2 -1
View File
@@ -3,7 +3,8 @@ import { $el } from '../../../scripts/ui.js'
import { api } from '../../../scripts/api.js'
import { td_bg } from './td_background.js'
console.log('td_bg', td_bg)
// console.log('td_bg', td_bg)
//本机安装的插件节点全集
window._nodesAll = null
+1 -1
View File
@@ -3,7 +3,7 @@ import { app } from '../../../scripts/app.js'
const repoOwner = 'shadowcz007' // 替换为仓库的所有者
const repoName = 'comfyui-mixlab-nodes' // 替换为仓库的名称
const version = 'v0.33.0'
const version = 'v0.35.1'
fetch(`https://api.github.com/repos/${repoOwner}/${repoName}/releases/latest`)
.then(response => response.json())
+11 -2
View File
@@ -1,4 +1,9 @@
function get_url () {
// 如果有缓存记录
let hostUrl = localStorage.getItem('_hostUrl') || ''
if (hostUrl) {
return hostUrl
}
let api_host = `${window.location.hostname}:${window.location.port}`
let api_base = ''
let url = `${window.location.protocol}//${api_host}${api_base}`
@@ -137,14 +142,18 @@ async function getPromptResult (category) {
}
// 新的运行工作流的接口
function queuePromptNew (filename, category, seed, input, client_id) {
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({ filename, category, seed, input, client_id })
const data = JSON.stringify(d)
return new Promise((res, rej) => {
fetch(`${url}/mixlab/prompt`, {
method: 'POST',
+1 -334
View File
@@ -1,319 +1,5 @@
import { app } from '../../../scripts/app.js'
// import { api } from '../../../scripts/api.js'
import { ComfyWidgets } from '../../../scripts/widgets.js'
import { $el } from '../../../scripts/ui.js'
async function getConfig () {
let api_host = `${window.location.hostname}:${window.location.port}`
let api_base = ''
let url = `${window.location.protocol}//${api_host}${api_base}`
const res = await fetch(`${url}/mixlab`, {
method: 'POST'
})
return await res.json()
}
function get_position_style (ctx, widget_width, y, node_height) {
const MARGIN = 4 // the margin around the html element
/* Create a transform that deals with all the scrolling and zooming */
const elRect = ctx.canvas.getBoundingClientRect()
const transform = new DOMMatrix()
.scaleSelf(
elRect.width / ctx.canvas.width,
elRect.height / ctx.canvas.height
)
.multiplySelf(ctx.getTransform())
.translateSelf(MARGIN, MARGIN + y)
return {
transformOrigin: '0 0',
transform: transform,
left: `0`,
top: `0`,
cursor: 'pointer',
position: 'absolute',
maxWidth: `${widget_width - MARGIN * 2}px`,
// maxHeight: `${node_height - MARGIN * 2}px`, // we're assuming we have the whole height of the node
width: `${widget_width - MARGIN * 2}px`,
// height: `${node_height * 0.3 - MARGIN * 2}px`,
// background: '#EEEEEE',
display: 'flex',
flexDirection: 'column',
// alignItems: 'center',
justifyContent: 'space-around'
}
}
const getLocalData = key => {
let data = {}
try {
data = JSON.parse(localStorage.getItem(key)) || {}
} catch (error) {
return {}
}
return data
}
app.registerExtension({
name: 'Mixlab.GPT.ChatGPTOpenAI',
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.
},
URL (node, inputName, inputData, app) {
// console.log('node', inputName, inputData[0])
const widget = {
type: inputData[0], // the type, CHEESE
name: inputName, // the name, slice
size: [128, 32], // a default size
draw (ctx, node, width, y) {
// a method to draw the widget (ctx is a CanvasRenderingContext2D)
},
computeSize (...args) {
return [128, 32] // a method to compute the current size of the widget
},
async serializeValue (nodeId, widgetIndex) {
let data = getLocalData('_mixlab_api_url')
return data[node.id] || 'https://api.openai.com/v1'
}
}
// 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 == 'ChatGPTOpenAI') {
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 api_url = this.widgets.filter(w => w.name == 'api_url')[0]
console.log('ChatGPTOpenAI nodeData', this.widgets)
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')
let inputUrl = inputDiv('_mixlab_api_url', 'URL')
widget.div.appendChild(inputKey)
widget.div.appendChild(inputUrl)
this.addCustomWidget(widget)
const onRemoved = this.onRemoved
this.onRemoved = () => {
inputUrl.remove()
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 === 'ChatGPTOpenAI') {
let widget = node.widgets.filter(w => w.div)[0]
let apiKey = getLocalData('_mixlab_api_key'),
url = getLocalData('_mixlab_api_url')
let id = node.id
// console.log('ChatGPTOpenAI serialize_widgets', this)
widget.div.querySelector('.Key').value = apiKey[id] || 'by Mixlab'
widget.div.querySelector('.URL').value =
url[id] || 'https://api.openai.com/v1'
}
}
});
app.registerExtension({
name: 'Mixlab.GPT.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'} ${placeholder}`
div.style = `display: flex;
align-items: center;
margin: 6px 8px;
margin-top: 0;`
ip.placeholder = placeholder
ip.value = placeholder
ip.style = `margin-left: 24px;
outline: none;
border: none;
padding: 4px;width: 100%;`
const label = document.createElement('label')
label.style = 'font-size: 10px;min-width:32px'
label.innerText = placeholder
div.appendChild(label)
div.appendChild(ip)
ip.addEventListener('change', () => {
let data = getLocalData(key)
data[this.id] = ip.value.trim()
localStorage.setItem(key, JSON.stringify(data))
console.log(this.id, key)
})
return div
}
let inputKey = inputDiv('_mixlab_api_key', 'Key')
widget.div.appendChild(inputKey)
this.addCustomWidget(widget)
const onRemoved = this.onRemoved
this.onRemoved = () => {
inputKey.remove()
widget.div.remove()
return onRemoved?.()
}
this.serialize_widgets = true //需要保存参数
}
}
},
async loadedGraphNode (node, app) {
// Fires every time a node is constructed
// You can modify widgets/add handlers/etc here
if (node.type === 'SiliconflowLLM') {
let widget = node.widgets.filter(w => w.div)[0]
let apiKey = getLocalData('_mixlab_api_key');
let id = node.id
widget.div.querySelector('.Key').value = apiKey[id] || 'by Mixlab'
}
}
})
app.registerExtension({
name: 'Mixlab.GPT.ShowTextForGPT',
@@ -328,7 +14,7 @@ app.registerExtension({
for (let i = 0; i < this.widgets.length; i++) {
if (this.widgets[i].name == 'show_text')
this.widgets[i].onRemove?.()
console.log('#ShowTextForGPT', this.widgets[i])
}
this.widgets.length = 2
}
@@ -399,24 +85,5 @@ app.registerExtension({
this.serialize_widgets = true //需要保存参数
}
},
async loadedGraphNode (node, app) {
if (node.type === 'ShowTextForGPT') {
let widget = node.widgets.filter(w => w.name == 'show_text')[0]
// if (widget.value) {
// let [url, prompt] = widget.value
// this[`wavesurfer_${node.id}`] = updateWaveWidgetValue(
// node.widgets,
// node.id,
// url,
// prompt,
// this[`wavesurfer_${node.id}`]
// )
// }
console.log('#loadedGraphNode', node)
}
}
})
+44 -17
View File
@@ -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,
+143 -26
View File
@@ -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 +334,145 @@ 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, 24], // 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: 'input_key',
draw (ctx, node, widget_width, y, widget_height) {
Object.assign(
this.div.style,
get_position_style(ctx, widget_width, 24, node.size[1])
)
}
}
widget.div = $el('div', {})
document.body.appendChild(widget.div)
const inputDiv = (key, placeholder) => {
let div = document.createElement('div')
div.style = `
display: flex;
align-items: center;
margin: 6px 8px;
margin-top:0px;
height:44px;
width:220px;
`
const ip = document.createElement('input')
ip.type = 'password'
ip.className = `${'comfy-multiline-input'} ${placeholder}`
ip.placeholder = placeholder
// ip.value = placeholder
ip.style = `margin-left:8px;
outline: none;
border: none;
padding:12px;
width: 100%;
`
div.appendChild(ip)
ip.addEventListener('change', () => {
let data = getLocalData(key)
data[this.id] = ip.value.trim()
localStorage.setItem(key, JSON.stringify(data))
})
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) {
if (node.type === 'KeyInput') {
let widget = node.widgets.filter(w => w.div)[0]
let apiKey = getLocalData('_mixlab_api_key')
let id = node.id
if (widget.div.querySelector('.Key'))
widget.div.querySelector('.Key').value = apiKey[id] || 'by Mixlab'
}
},
nodeCreated (node, app) {
//数据延迟??
setTimeout(() => {
// console.log('#LoadImagesToBatch', node.type)
if (node.type === 'KeyInput') {
let widget = node.widgets.filter(w => w.div)[0]
let apiKey = getLocalData('_mixlab_api_key')
let id = node.id
if (widget.div.querySelector('.Key'))
widget.div.querySelector('.Key').value = apiKey[id] || 'by Mixlab'
}
}, 1000)
}
})
+408
View File
@@ -0,0 +1,408 @@
{
"last_node_id": 21,
"last_link_id": 16,
"nodes": [
{
"id": 10,
"type": "ChatGPTOpenAI",
"pos": [
489,
689
],
"size": {
"0": 403.2580261230469,
"1": 309.2166442871094
},
"flags": {},
"order": 5,
"mode": 0,
"inputs": [
{
"name": "api_key",
"type": "STRING",
"link": null,
"widget": {
"name": "api_key"
}
},
{
"name": "custom_model_name",
"type": "STRING",
"link": null,
"widget": {
"name": "custom_model_name"
}
},
{
"name": "custom_api_url",
"type": "STRING",
"link": 13,
"widget": {
"name": "custom_api_url"
},
"slot_index": 2
}
],
"outputs": [
{
"name": "text",
"type": "STRING",
"links": [
12
],
"shape": 3,
"slot_index": 0
},
{
"name": "messages",
"type": "STRING",
"links": null,
"shape": 3
},
{
"name": "session_history",
"type": "STRING",
"links": null,
"shape": 3
}
],
"properties": {
"Node name for S&R": "ChatGPTOpenAI"
},
"widgets_values": [
"hi",
"You are ChatGPT, a large language model trained by OpenAI. Answer as concisely as possible.",
"gpt-3.5-turbo",
447210757728856,
"randomize",
1,
"openai",
"",
"",
""
]
},
{
"id": 3,
"type": "ShowTextForGPT",
"pos": [
982,
686
],
"size": {
"0": 400,
"1": 200
},
"flags": {},
"order": 7,
"mode": 0,
"inputs": [
{
"name": "text",
"type": "STRING",
"link": 12,
"widget": {
"name": "text"
}
},
{
"name": "output_dir",
"type": "STRING",
"link": null,
"widget": {
"name": "output_dir"
}
}
],
"outputs": [
{
"name": "STRING",
"type": "STRING",
"links": null,
"shape": 6
}
],
"properties": {
"Node name for S&R": "ShowTextForGPT"
},
"widgets_values": [
"",
"",
" Hi there! What can I help you with?"
]
},
{
"id": 11,
"type": "SiliconflowLLM",
"pos": [
489,
318
],
"size": {
"0": 395.197998046875,
"1": 262
},
"flags": {},
"order": 4,
"mode": 0,
"inputs": [
{
"name": "api_key",
"type": "STRING",
"link": 16,
"widget": {
"name": "api_key"
}
},
{
"name": "custom_model_name",
"type": "STRING",
"link": null,
"widget": {
"name": "custom_model_name"
}
}
],
"outputs": [
{
"name": "text",
"type": "STRING",
"links": [
15
],
"shape": 3,
"slot_index": 0
},
{
"name": "messages",
"type": "STRING",
"links": null,
"shape": 3
},
{
"name": "session_history",
"type": "STRING",
"links": null,
"shape": 3
}
],
"properties": {
"Node name for S&R": "SiliconflowLLM"
},
"widgets_values": [
"",
"",
"You are ChatGPT, a large language model trained by OpenAI. Answer as concisely as possible.",
"Qwen/Qwen2-7B-Instruct",
593422808835285,
"randomize",
1,
""
]
},
{
"id": 17,
"type": "ShowTextForGPT",
"pos": [
975,
329
],
"size": {
"0": 400,
"1": 200
},
"flags": {},
"order": 6,
"mode": 0,
"inputs": [
{
"name": "text",
"type": "STRING",
"link": 15,
"widget": {
"name": "text"
}
},
{
"name": "output_dir",
"type": "STRING",
"link": null,
"widget": {
"name": "output_dir"
}
}
],
"outputs": [
{
"name": "STRING",
"type": "STRING",
"links": null,
"shape": 6
}
],
"properties": {
"Node name for S&R": "ShowTextForGPT"
},
"widgets_values": [
"",
"",
"Hello! How can I assist you today?"
]
},
{
"id": 18,
"type": "KeyInput",
"pos": [
46,
319
],
"size": {
"0": 315,
"1": 70
},
"flags": {},
"order": 0,
"mode": 0,
"outputs": [
{
"name": "key",
"type": "STRING",
"links": [
16
],
"shape": 3
}
],
"properties": {
"Node name for S&R": "KeyInput"
},
"widgets_values": [
null,
null
]
},
{
"id": 12,
"type": "TextInput_",
"pos": [
31,
871
],
"size": [
407.9377612789413,
76
],
"flags": {},
"order": 1,
"mode": 0,
"outputs": [
{
"name": "STRING",
"type": "STRING",
"links": [
13
],
"shape": 3
}
],
"properties": {
"Node name for S&R": "TextInput_"
},
"widgets_values": [
"http://127.0.0.1:8000/v1"
]
},
{
"id": 20,
"type": "Note",
"pos": [
35,
664
],
"size": [
350.04604707424306,
116.54209784249178
],
"flags": {},
"order": 2,
"mode": 0,
"properties": {
"text": ""
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