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...
12 Commits
Author SHA1 Message Date
shadowcz007 0846013378 增加 MiniCPM-V 2.6 int4 2024-08-22 14:46:11 +08:00
shadowcz007 c141ba405f fixbug: 自动监听文件夹 2024-08-20 15:06:58 +08:00
shadowcz007 0320f13a9f fixbug 2024-08-19 11:46:55 +08:00
shadowcz007 8adc34be4d fixbug 2024-08-19 10:29:54 +08:00
shadowcz007 cb6810d3c1 Update TextGenerateNode.py 2024-08-18 14:31:22 +08:00
shadowcz007 d384f64abf update :text-to-text 2024-08-17 22:15:31 +08:00
shadowcz007 ef7035f8ee update 2024-08-17 15:11:22 +08:00
shadowcz007 bfcadde5c3 update 2024-08-17 14:22:31 +08:00
shadowcz007 496ff41782 新ui支持,适配后,暂未全面测试 2024-08-16 18:13:05 +08:00
shadowcz007 46f0be5484 add image 2024-08-14 00:27:50 +08:00
shadowcz007 f3db0131c1 fixbug 2024-08-14 00:02:18 +08:00
shadowcz007 83a8d47f51 Update README.md 2024-08-13 23:32:10 +08:00
121 changed files with 1500 additions and 112262 deletions
+28 -15
View File
@@ -3,26 +3,34 @@
> 适配了最新版 comfyui 的 py3.11 ,torch 2.3.1+cu121
> [Mixlab nodes discord](https://discord.gg/cXs9vZSqeK)
商务合作请联系 389570357@qq.com
For business cooperation, please contact email 389570357@qq.com
##### `最新`:
- 移动端适配、修改app模式的Mask编辑器
- 增加p5.js作为输入节点
[workflow](./workflow/p5workflow.json)
[workflow2](./workflow/p5-video-workflow.json)
- 增加 MiniCPM-V 2.6 int4
- App模式增加batch prompt,批量提示词,可以把动态提示词批量组成后运行
This is the int4 quantized version of MiniCPM-V 2.6.
Running with int4 version would use lower GPU memory (about 7GB).
- 移动端适配、修改 app 模式的 Mask 编辑器
- 增加 p5.js 作为输入节点
[workflow](./workflow/p5workflow.json)
[workflow2](./workflow/p5-video-workflow.json)
- App 模式增加 batch prompt,批量提示词,可以把动态提示词批量组成后运行
![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 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 SiliconflowLLM,可以使用由 Siliconflow 提供的免费 LLM
<!-- - ChatGPT 节点支持 Local LLM(llama.cpp),Phi3、llama3 都可以直接一个节点运行了。模型下载后,放置到 `models/llamafile/` -->
<!-- - 右键菜单支持 text-to-text,方便对 prompt 词补全 -->
<!--
<!--
强烈推荐:
[Phi-3-mini-4k-instruct-function-calling-GGUF](https://huggingface.co/nold/Phi-3-mini-4k-instruct-function-calling-GGUF)
@@ -33,7 +41,6 @@
![](./assets/prompt_ai_setup.png)
![](./assets/prompt-ai.png) -->
#### `相关插件推荐`
[comfyui-liveportrait](https://github.com/shadowcz007/comfyui-liveportrait)
@@ -57,8 +64,8 @@
- 发布为 app 的 workflow,可以在右键里再次编辑了
- web app 可以设置分类,在 comfyui 右键菜单可以编辑更新 web app
- 支持动态提示
- 支持把输出显示到comfyui背景(TouchDesigner 风格)
- 如果转为web app打开是空白的,注意检查下插件目录的名字需要是:comfyui-mixlab-nodes(如果是zip包下载会多了个-main的后缀,需要去掉)
- 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)
@@ -187,7 +194,6 @@ pip install llama-cpp-python \
> The composite images node overlays a foreground image onto a background image at specified positions and scales, with optional blending modes and masking capabilities. position : 'overall',"center_center","left_bottom","center_bottom","right_bottom","left_top","center_top","right_top"
![layers](./assets/layers-workflow.svg)
![poster](./assets/poster-workflow.svg)
@@ -221,9 +227,16 @@ pip install llama-cpp-python \
#### TextImage
> [下载字体](https://drxie.github.io/OSFCC/)放到 ```custom_nodes/comfyui-mixlab-nodes/assets/fonts```
> [下载字体](https://drxie.github.io/OSFCC/)放到 `custom_nodes/comfyui-mixlab-nodes/assets/fonts`
#### MiniCPM-VQA Simple
This is the int4 quantized version of MiniCPM-V 2.6.
Running with int4 version would use lower GPU memory (about 7GB).
[模型](https://huggingface.co/openbmb/MiniCPM-V-2_6-int4)
![alt text](assets/1724308322276.png)
### Style
@@ -266,11 +279,11 @@ Add edges to an image.
> LaMaInpainting(需要手动安装)
* simple-lama-inpainting 里的pillow造成冲突,暂时从依赖里移除,如果有安装 simple-lama-inpainting ,节点会自动添加,没有,则不会自动添加。
- simple-lama-inpainting 里的 pillow 造成冲突,暂时从依赖里移除,如果有安装 simple-lama-inpainting ,节点会自动添加,没有,则不会自动添加。
from [simple-lama-inpainting](https://github.com/enesmsahin/simple-lama-inpainting)
* [问题汇总](https://github.com/shadowcz007/comfyui-mixlab-nodes/issues/294)
- [问题汇总](https://github.com/shadowcz007/comfyui-mixlab-nodes/issues/294)
> rembgNode
+97 -1
View File
@@ -32,6 +32,7 @@ _URL_=None
# except:
# print("##nodes.ChatGPT ImportError")
from .nodes.ChatGPT import openai_client
from .nodes.RembgNode import get_rembg_models,U2NET_HOME,run_briarmbg,run_rembg
@@ -584,17 +585,101 @@ async def mixlab_hander(request):
print(e)
return web.json_response(data)
# llm的api key,使用硅基流动
@routes.post('/mixlab/llm_api_key')
async def mixlab_llm_api_key_handler(request):
data = await request.json()
api_key = data.get('key')
app_folder = os.path.join(current_path, "app")
key_file_path = os.path.join(app_folder, "llm_api_key.txt")
if api_key:
if not os.path.exists(app_folder):
os.makedirs(app_folder)
try:
with open(key_file_path, 'w') as f:
f.write(api_key)
return web.json_response({'message': 'API key saved successfully'})
except Exception as e:
return web.json_response({'error': str(e)}, status=500)
else:
if os.path.exists(key_file_path):
try:
with open(key_file_path, 'r') as f:
saved_api_key = f.read().strip()
return web.json_response({'key': saved_api_key})
except Exception as e:
return web.json_response({'error': str(e)}, status=500)
else:
return web.json_response({'error': 'No API key provided and no key found in local storage'}, status=400)
@routes.post('/chat/completions')
async def chat_completions(request):
data = await request.json()
messages = data.get('messages')
key=data.get('key')
if not messages:
return web.json_response({"error": "No messages provided"}, status=400)
async def generate():
try:
client=openai_client(key,"https://api.siliconflow.cn/v1")
response = client.chat.completions.create(
model="01-ai/Yi-1.5-9B-Chat-16K",
messages=messages,
stream=True
)
for chunk in response:
if hasattr(chunk.choices[0].delta, 'content'):
content = chunk.choices[0].delta.content
if content is not None:
yield content.encode('utf-8') + b"\r\n"
except Exception as e:
yield f"Error: {str(e)}".encode('utf-8') + b"\r\n"
return web.Response(body=generate(), content_type='text/event-stream')
@routes.get('/mixlab/app')
async def mixlab_app_handler(request):
html_file = os.path.join(current_path, "web/index.html")
html_file = os.path.join(current_path, "webApp/index.html")
if os.path.exists(html_file):
with open(html_file, 'r', encoding='utf-8', errors='ignore') as f:
html_data = f.read()
return web.Response(text=html_data, content_type='text/html')
else:
return web.Response(text="HTML file not found", status=404)
# web app模式独立
@routes.get('/mixlab/app/{filename:.*}')
async def static_file_handler(request):
filename = request.match_info['filename']
file_path = os.path.join(current_path, "webApp", filename)
print(file_path)
if os.path.exists(file_path) and os.path.isfile(file_path):
if filename.endswith('.js'):
content_type = 'application/javascript'
elif filename.endswith('.css'):
content_type = 'text/css'
elif filename.endswith('.html'):
content_type = 'text/html'
elif filename.endswith('.svg'):
content_type = 'image/svg+xml'
else:
content_type = 'application/octet-stream'
with open(file_path, 'r', encoding='utf-8', errors='ignore') as f:
file_data = f.read()
return web.Response(text=file_data, content_type=content_type)
else:
return web.Response(text="File not found", status=404)
@routes.post('/mixlab/workflow')
async def mixlab_workflow_hander(request):
@@ -1312,5 +1397,16 @@ try:
except Exception as e:
logging.info('TripoSR.available False' )
from .nodes.MiniCPMNode import MiniCPM_VQA_Simple
try:
logging.info('MiniCPMNode.available')
# logging.info( folder_paths.get_temp_directory())
NODE_CLASS_MAPPINGS['MiniCPM_VQA_Simple']=MiniCPM_VQA_Simple
NODE_DISPLAY_NAME_MAPPINGS["MiniCPM_VQA_Simple"]= "MiniCPM VQA Simple"
except Exception as e:
logging.info('MiniCPMNode.available False' )
logging.info('\033[93m -------------- \033[0m')
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+127
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@@ -0,0 +1,127 @@
# Referenced some code:https://github.com/IuvenisSapiens/ComfyUI_MiniCPM-V-2_6-int4
import os
import torch
import folder_paths
from transformers import AutoTokenizer, AutoModel
from torchvision.transforms.v2 import ToPILImage
from decord import VideoReader, cpu # pip install decord
from PIL import Image
def get_model_path(n=""):
try:
return folder_paths.get_folder_paths(n)[0]
except:
return os.path.join(folder_paths.models_dir, n)
class MiniCPM_VQA_Simple:
def __init__(self):
self.model_checkpoint = None
self.tokenizer = None
self.model = None
self.device = (
torch.device("cuda") if torch.cuda.is_available() else torch.device("cpu")
)
self.bf16_support = (
torch.cuda.is_available()
and torch.cuda.get_device_capability(self.device)[0] >= 8
)
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"images": ("IMAGE",),
"text": ("STRING", {"default": "", "multiline": True}),
"seed": ("INT", {"default": -1}), # add seed parameter, default is -1
"temperature": (
"FLOAT",
{
"default": 0.7,
},
),
"keep_model_loaded": ("BOOLEAN", {"default": False}),
},
}
RETURN_TYPES = ("STRING",)
FUNCTION = "inference"
CATEGORY = "♾️Mixlab/Image"
def inference(
self,
images,
text,
seed, # add seed parameter, default is -1
temperature,
keep_model_loaded,
):
if seed != -1:
torch.manual_seed(seed)
model_id = "openbmb/MiniCPM-V-2_6-int4"
self.model_checkpoint = os.path.join( get_model_path("prompt_generator"), os.path.basename(model_id))
if not os.path.exists(self.model_checkpoint):
from huggingface_hub import snapshot_download
snapshot_download(
repo_id=model_id,
local_dir=self.model_checkpoint,
local_dir_use_symlinks=False,
endpoint='https://hf-mirror.com'
)
if self.tokenizer is None:
self.tokenizer = AutoTokenizer.from_pretrained(
self.model_checkpoint,
trust_remote_code=True,
low_cpu_mem_usage=True,
)
if self.model is None:
self.model = AutoModel.from_pretrained(
self.model_checkpoint,
trust_remote_code=True,
low_cpu_mem_usage=True,
attn_implementation="sdpa",
torch_dtype=torch.bfloat16 if self.bf16_support else torch.float16,
)
with torch.no_grad():
images = images.permute([0, 3, 1, 2])
images = [ToPILImage()(img).convert("RGB") for img in images]
msgs = [{"role": "user", "content": images + [text]}]
params = {"use_image_id": False, }
# offload model to CPU
# self.model = self.model.to(torch.device("cpu"))
# self.model.eval()
result = self.model.chat(
image=None,
msgs=msgs,
tokenizer=self.tokenizer,
sampling=True,
# top_k=top_k,
# top_p=top_p,
temperature=temperature,
# repetition_penalty=repetition_penalty,
# max_new_tokens=max_new_tokens,
**params,
)
# offload model to GPU
# self.model = self.model.to(torch.device("cpu"))
# self.model.eval()
if not keep_model_loaded:
del self.tokenizer # release tokenizer memory
del self.model # release model memory
self.tokenizer = None # set tokenizer to None
self.model = None # set model to None
torch.cuda.empty_cache() # release GPU memory
torch.cuda.ipc_collect()
return (result,)
+7 -1
View File
@@ -18,7 +18,13 @@ import json
# req = request.Request("http://127.0.0.1:8188/prompt", data=data)
# request.urlopen(req)
embeddings_path=os.path.join(folder_paths.models_dir, "embeddings")
def get_model_path(n=""):
try:
return folder_paths.get_folder_paths(n)[0]
except:
return os.path.join(folder_paths.models_dir, n)
embeddings_path=get_model_path("embeddings")
def get_files_with_extension(directory, extension):
+10 -8
View File
@@ -280,7 +280,7 @@ class ChinesePrompt:
},
"optional":{
"seed":("INT", {"default": 100, "min": 100, "max": 1000000}),
"seed":("INT", {"default": 100, "min": 100, "max": 0xffffffffffffffff}),
},
@@ -331,13 +331,15 @@ class ChinesePrompt:
for t in texts:
if t:
# translated_text = translated_word = translate(zh_en_tokenizer,zh_en_model,str(t))
parser = Lark(grammar, start="start", parser="lalr", transformer=ChinesePromptTranslate())
# print('t',t)
result = parser.parse(t).children
# print('en_result',result)
# en_text=translate(zh_en_tokenizer,zh_en_model,text_without_syntax)
en_texts.append(result[0])
try:
result = parser.parse(t).children
en_texts.append(result[0])
except:
print(f"Error parsing '{t}'")
t = translate(str(t))
en_texts.append(t)
zh_en_model.to('cpu')
print("test en_text",en_texts)
@@ -384,7 +386,7 @@ class PromptGenerate:
"optional":{
"multiple": (["off","on"],),
"seed":("INT", {"default": 100, "min": 100, "max": 1000000}),
"seed":("INT", {"default": 100, "min": 100, "max": 0xffffffffffffffff}),
},
}
+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 = "0.37.0"
version = "0.39.0"
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"]
+5 -1
View File
@@ -18,4 +18,8 @@ huggingface-hub
scikit-image
torchaudio
soundfile>=0.12.1
json-repair
json-repair
decord
bitsandbytes
accelerate
+11 -1
View File
@@ -2,6 +2,8 @@ import { app } from '../../../scripts/app.js'
import { api } from '../../../scripts/api.js'
import { $el } from '../../../scripts/ui.js'
import { loadExternalScript } from './common.js'
const getLocalData = key => {
let data = {}
try {
@@ -99,7 +101,10 @@ function get_position_style (ctx, widget_width, y, node_height) {
return {
transformOrigin: '0 0',
transform: transform,
left: `0`,
left:
document.querySelector('.comfy-menu').style.display === 'none'
? `60px`
: `0`,
top: `0`,
cursor: 'pointer',
position: 'absolute',
@@ -266,6 +271,11 @@ app.registerExtension({
if (nodeType.comfyClass == '3DImage') {
const orig_nodeCreated = nodeType.prototype.onNodeCreated
nodeType.prototype.onNodeCreated = async function () {
await loadExternalScript(
'/mixlab/app/lib/model-viewer.min.js',
'module'
)
orig_nodeCreated?.apply(this, arguments)
const uploadWidget = this.widgets.filter(w => w.name == 'upload')[0]
+9 -67
View File
@@ -4,28 +4,11 @@ import { api } from '../../../scripts/api.js'
import { td_bg } from './td_background.js'
// console.log('td_bg', td_bg)
import { getUrl, base64Df, get_position_style, getObjectInfo } from './common.js'
//本机安装的插件节点全集
window._nodesAll = null
//获取当前系统的插件,节点清单
function getObjectInfo () {
return new Promise(async (resolve, reject) => {
let url = getUrl()
try {
const response = await fetch(`${url}/object_info`)
const data = await response.json()
resolve(data)
} catch (error) {
reject(error)
}
})
}
const base64Df =
'data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAwAAAAMCAYAAABWdVznAAAAAXNSR0IArs4c6QAAALZJREFUKFOFkLERwjAQBPdbgBkInECGaMLUQDsE0AkRVRAYWqAByxldPPOWHwnw4OBGye1p50UDSoA+W2ABLPN7i+C5dyC6R/uiAUXRQCs0bXoNIu4QPQzAxDKxHoALOrZcqtiyR/T6CXw7+3IGHhkYcy6BOR2izwT8LptG8rbMiCRAUb+CQ6WzQVb0SNOi5Z2/nX35DRyb/ENazhpWKoGwrpD6nICp5c2qogc4of+c7QcrhgF4Aa/aoAFHiL+RAAAAAElFTkSuQmCC'
const parseImageToBase64 = url => {
return new Promise((res, rej) => {
fetch(url)
@@ -45,39 +28,6 @@ const parseImageToBase64 = url => {
})
}
function get_position_style (ctx, widget_width, y, node_height) {
const MARGIN = 12 // 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: 'flex-start',
zIndex: 9999999
}
}
async function drawImageToCanvas (imageUrl, sFactor = 320) {
var canvas = document.createElement('canvas')
var ctx = canvas.getContext('2d')
@@ -257,9 +207,9 @@ async function extractInputAndOutputData (
node.type === 'KSampler' ||
node.type == 'SamplerCustom' ||
node.type === 'ChinesePrompt_Mix' ||
node.type === 'Seed_'||
node.type==='SiliconflowLLM'||
node.type==='ChatGPTOpenAI'
node.type === 'Seed_' ||
node.type === 'SiliconflowLLM' ||
node.type === 'ChatGPTOpenAI'
) {
// seed 的类型收集
try {
@@ -279,13 +229,6 @@ async function extractInputAndOutputData (
return { input, output, seed, seedTitle }
}
function getUrl () {
let api_host = `${window.location.hostname}:${window.location.port}`
let api_base = ''
let url = `${window.location.protocol}//${api_host}${api_base}`
return url
}
const getLocalData = key => {
let data = {}
try {
@@ -473,15 +416,15 @@ app.registerExtension({
type: 'div',
name: 'AppInfoRun',
draw (ctx, node, widget_width, y, widget_height) {
Object.assign(
this.div.style,
{...get_position_style(
Object.assign(this.div.style, {
...get_position_style(
ctx,
widget_width,
node.size[1] - widget_height,
node.size[1]
),zIndex:1}
)
),
zIndex: 1
})
}
}
@@ -711,7 +654,6 @@ app.registerExtension({
this.serialize_widgets = true //需要保存参数
window._mixlab_app_json = null
}
const onExecuted = nodeType.prototype.onExecuted
+4 -1
View File
@@ -19,7 +19,10 @@ function get_position_style (ctx, widget_width, y, node_height) {
return {
transformOrigin: '0 0',
transform: transform,
left: `0`,
left:
document.querySelector('.comfy-menu').style.display === 'none'
? `60px`
: `0`,
top: `0`,
cursor: 'pointer',
position: 'absolute',
+77 -10
View File
@@ -1,3 +1,5 @@
import { getUrl } from './common.js'
async function* completion (url, messages, controller) {
let data = {
model: 'gpt-3.5-turbo-16k',
@@ -91,16 +93,81 @@ async function* completion (url, messages, controller) {
return content
// return (await response.json()).content
}
export async function completion_ (url, messages, controller, callback) {
let request = await completion(url, messages, controller)
export async function completion_ (apiKey, url, messages, controller, callback) {
let request = await chatCompletion(apiKey, url, messages, controller)
for await (const chunk of request) {
let content = chunk.data.choices[0].delta.content || ''
if (chunk.data.choices[0].role == 'assistant') {
//开始
content = ''
}
if (callback) callback(content)
if (callback) callback(chunk)
}
}
export async function* chatCompletion (apiKey, url, messages, controller) {
url = `${getUrl()}/chat/completions`
const requestBody = {
model: '01-ai/Yi-1.5-9B-Chat-16K',
messages: messages,
stream: true,
key: apiKey
}
let response = await fetch(url, {
method: 'POST',
headers: {
'Content-Type': 'application/json',
Authorization: `Bearer ${apiKey}`
},
body: JSON.stringify(requestBody),
mode: 'cors', // This is to ensure the request is made with CORS
signal: controller.signal
})
const reader = response.body.getReader()
const decoder = new TextDecoder()
let content = ''
let leftover = '' // Buffer for partially read lines
try {
let cont = true
while (cont) {
let result = await reader.read()
if (result.done) {
break
}
// Add any leftover data to the current chunk of data
const text = leftover + decoder.decode(result.value)
// Check if the last character is a line break
const endsWithLineBreak = text.endsWith('\r\n')
// Split the text into lines
let lines = text.split('\r\n')
// If the text doesn't end with a line break, then the last line is incomplete
// Store it in leftover to be added to the next chunk of data
if (!endsWithLineBreak) {
leftover = lines.pop()
} else {
leftover = '' // Reset leftover if we have a line break at the end
}
for (const line of lines) {
if (line) {
content += line
yield line // Yield the trimmed line
} else {
cont = false
break
}
}
}
} catch (e) {
console.error('chat error: ', e)
throw e
} finally {
controller.abort()
}
return content
}
+1 -1
View File
@@ -3,7 +3,7 @@ import { app } from '../../../scripts/app.js'
const repoOwner = 'shadowcz007' // 替换为仓库的所有者
const repoName = 'comfyui-mixlab-nodes' // 替换为仓库的名称
const version = 'v0.37.0'
const version = 'v0.39.0'
fetch(`https://api.github.com/repos/${repoOwner}/${repoName}/releases/latest`)
.then(response => response.json())
+175
View File
@@ -0,0 +1,175 @@
export const base64Df =
'data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAwAAAAMCAYAAABWdVznAAAAAXNSR0IArs4c6QAAALZJREFUKFOFkLERwjAQBPdbgBkInECGaMLUQDsE0AkRVRAYWqAByxldPPOWHwnw4OBGye1p50UDSoA+W2ABLPN7i+C5dyC6R/uiAUXRQCs0bXoNIu4QPQzAxDKxHoALOrZcqtiyR/T6CXw7+3IGHhkYcy6BOR2izwT8LptG8rbMiCRAUb+CQ6WzQVb0SNOi5Z2/nX35DRyb/ENazhpWKoGwrpD6nICp5c2qogc4of+c7QcrhgF4Aa/aoAFHiL+RAAAAAElFTkSuQmCC'
export function getUrl () {
let api_host = `${window.location.hostname}:${window.location.port}`
let api_base = ''
let url = `${window.location.protocol}//${api_host}${api_base}`
return url
}
// 更新或者获取key
export const updateLLMAPIKey = async key => {
try {
const res = await fetch(`${getUrl()}/mixlab/llm_api_key`, {
method: 'POST',
headers: {
'Content-Type': 'application/json'
},
body: JSON.stringify({
key: key || null
})
})
const data = await res.json()
if (!res.ok) {
console.error('Error:', data.error)
return
}
if (key) {
console.log('API key saved successfully:', data.message)
return key
} else {
console.log('Retrieved API key:', data.key)
return data.key
}
} catch (error) {
console.error('Request failed:', error)
}
}
//获取当前系统的插件,节点清单
export function getObjectInfo () {
return new Promise(async (resolve, reject) => {
let url = getUrl()
try {
const response = await fetch(`${url}/object_info`)
const data = await response.json()
resolve(data)
} catch (error) {
reject(error)
}
})
}
export function get_position_style (
ctx,
widget_width,
y,
node_height,
left = 44
) {
const MARGIN = 0 // the margin around the html element
/* Create a transform that deals with all the scrolling and zooming */
const elRect = ctx.canvas.getBoundingClientRect()
const scaleX = elRect.width / ctx.canvas.width
const scaleY = elRect.height / ctx.canvas.height
const transform = new DOMMatrix()
.scaleSelf(scaleX, scaleY)
.multiplySelf(ctx.getTransform())
.translateSelf(MARGIN, MARGIN + y)
return {
transformOrigin: '0 0',
transform: transform,
left:
document.querySelector('.comfy-menu').style.display === 'none'
? `${left}px`
: `0`,
top: `0`,
cursor: 'pointer',
position: 'absolute',
maxWidth: `${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: `${node_height * 0.3 - MARGIN * 2}px`,
// background: '#EEEEEE',
display: 'flex',
flexDirection: 'column',
// alignItems: 'center',
justifyContent: 'flex-start',
zIndex: 99
}
}
export function loadExternalScript (url, type) {
return new Promise((resolve, reject) => {
const existingScript = document.querySelector(`script[src="${url}"]`)
if (existingScript) {
existingScript.onload = () => {
resolve()
}
existingScript.onerror = reject
return
}
const script = document.createElement('script')
script.src = url
if (type) script.type = type // Add this line to load the script as an ES module
script.onload = () => {
resolve()
}
script.onerror = reject
document.head.appendChild(script)
})
}
export async function getQueue () {
try {
const res = await fetch(`${getUrl()}/queue`)
const data = await res.json()
// console.log(data.queue_running,data.queue_pending)
return {
// Running action uses a different endpoint for cancelling
Running: data.queue_running.length,
Pending: data.queue_pending.length
}
} catch (error) {
console.error(error)
return { Running: 0, Pending: 0 }
}
}
export async function interrupt () {
const resp = await fetch(`${getUrl()}/interrupt`, {
method: 'POST'
})
}
export async function sleep (t = 200) {
return new Promise((res, rej) => {
setTimeout(() => {
res(true)
}, t)
})
}
export function createImage (url) {
let im = new Image()
return new Promise((res, rej) => {
im.onload = () => res(im)
im.src = url
})
}
export const getLocalData = key => {
let data = {}
try {
data = JSON.parse(localStorage.getItem(key)) || {}
} catch (error) {
return {}
}
return data
}
export const saveLocalData = (key, id, val) => {
let data = getLocalData(key)
data[id] = val
localStorage.setItem(key, JSON.stringify(data))
}
+45 -38
View File
@@ -4,6 +4,8 @@ import { api } from '../../../scripts/api.js'
import { $el } from '../../../scripts/ui.js'
import { applyTextReplacements } from '../../../scripts/utils.js'
import { loadExternalScript, get_position_style } from './common.js'
function loadImageToCanvas (base64Image) {
var img = new Image()
var canvas = document.createElement('canvas')
@@ -88,37 +90,40 @@ function getContentTypeFromBase64 (base64Data) {
// const blob = base64ToBlob(base64Data, contentType);
// console.log(blob);
function get_position_style (ctx, widget_width, y, node_height) {
const MARGIN = 4 // the margin around the html element
// function get_position_style (ctx, widget_width, y, node_height) {
// const MARGIN = 4 // the margin around the html element
/* Create a transform that deals with all the scrolling and zooming */
const elRect = ctx.canvas.getBoundingClientRect()
const transform = new DOMMatrix()
.scaleSelf(
elRect.width / ctx.canvas.width,
elRect.height / ctx.canvas.height
)
.multiplySelf(ctx.getTransform())
.translateSelf(MARGIN, MARGIN + y)
// /* Create a transform that deals with all the scrolling and zooming */
// const elRect = ctx.canvas.getBoundingClientRect()
// const transform = new DOMMatrix()
// .scaleSelf(
// elRect.width / ctx.canvas.width,
// elRect.height / ctx.canvas.height
// )
// .multiplySelf(ctx.getTransform())
// .translateSelf(MARGIN, MARGIN + y)
return {
transformOrigin: '0 0',
transform: transform,
left: `0`,
top: `0`,
cursor: 'pointer',
position: 'absolute',
maxWidth: `${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: `${node_height * 0.3 - MARGIN * 2}px`,
// background: '#EEEEEE',
display: 'flex',
flexDirection: 'column',
// alignItems: 'center',
justifyContent: 'space-around'
}
}
// return {
// transformOrigin: '0 0',
// transform: transform,
// left:
// document.querySelector('.comfy-menu').style.display === 'none'
// ? `60px`
// : `0`,
// top: `0`,
// cursor: 'pointer',
// position: 'absolute',
// maxWidth: `${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 = {}
@@ -344,7 +349,7 @@ app.registerExtension({
draw (ctx, node, widget_width, y, widget_height) {
Object.assign(
this.div.style,
get_position_style(ctx, widget_width, 44, node.size[1])
get_position_style(ctx, widget_width, 44, node.size[1], 36)
)
}
}
@@ -530,7 +535,7 @@ app.registerExtension({
draw (ctx, node, widget_width, y, widget_height) {
Object.assign(
this.div.style,
get_position_style(ctx, widget_width, y, node.size[1])
get_position_style(ctx, widget_width, y, node.size[1], 36)
)
}
}
@@ -681,7 +686,7 @@ const addBase64ToWidgetForLoadImagesToBatch = (
imagesWidget,
imagesDiv
) => {
if(!imagesWidget.value.base64) imagesWidget.value.base64=[]
if (!imagesWidget.value.base64) imagesWidget.value.base64 = []
imagesWidget.value.base64.push(base64)
let im = createInputImageForBatch(base64, imagesWidget)
imagesDiv.appendChild(im)
@@ -730,7 +735,7 @@ app.registerExtension({
draw (ctx, node, widget_width, y, widget_height) {
Object.assign(
this.div.style,
get_position_style(ctx, widget_width, 44, node.size[1])
get_position_style(ctx, widget_width, 44, node.size[1], 44)
)
},
serialize: false
@@ -882,9 +887,11 @@ app.registerExtension({
app.registerExtension({
name: 'Mixlab.output.ComparingTwoFrames_',
init () {
loadExternalScript('/mixlab/app/lib/juxtapose.min.js')
$el('link', {
rel: 'stylesheet',
href: '/extensions/comfyui-mixlab-nodes/lib/juxtapose.css',
href: '/mixlab/app/lib/juxtapose.css',
parent: document.head
})
@@ -911,10 +918,10 @@ app.registerExtension({
type: 'div',
name: 'preview',
draw (ctx, node, widget_width, y, widget_height) {
Object.assign(
this.div.style,
get_position_style(ctx, 400, 44, node.size[1])
)
let s = get_position_style(ctx, widget_width, 44, node.size[1], 36)
delete s.height
Object.assign(this.div.style, s)
},
serialize: false
}
+4 -1
View File
@@ -81,7 +81,10 @@ function get_position_style (ctx, widget_width, y, node_height) {
return {
transformOrigin: '0 0',
transform: transform,
left: `0`,
left:
document.querySelector('.comfy-menu').style.display === 'none'
? `60px`
: `0`,
top: `0`,
cursor: 'pointer',
position: 'absolute',
+15 -87
View File
@@ -3,31 +3,17 @@ import { app } from '../../../scripts/app.js'
import { ComfyWidgets } from '../../../scripts/widgets.js'
import { $el } from '../../../scripts/ui.js'
let api_host = `${window.location.hostname}:${window.location.port}`
let api_base = ''
let url = `${window.location.protocol}//${api_host}${api_base}`
import {
getQueue,
interrupt,
get_position_style,
base64Df,
getUrl,
createImage,
sleep
} from './common.js'
async function getQueue () {
try {
const res = await fetch(`${url}/queue`)
const data = await res.json()
// console.log(data.queue_running,data.queue_pending)
return {
// Running action uses a different endpoint for cancelling
Running: data.queue_running.length,
Pending: data.queue_pending.length
}
} catch (error) {
console.error(error)
return { Running: 0, Pending: 0 }
}
}
async function interrupt () {
const resp = await fetch(`${url}/interrupt`, {
method: 'POST'
})
}
// let url = getUrl()
async function clipboardWriteImage (win, url) {
const canvas = document.createElement('canvas')
@@ -208,22 +194,6 @@ async function shareScreen (
}
}
async function sleep (t = 200) {
return new Promise((res, rej) => {
setTimeout(() => {
res(true)
}, t)
})
}
function createImage (url) {
let im = new Image()
return new Promise((res, rej) => {
im.onload = () => res(im)
im.src = url
})
}
async function compareImages (threshold, previousImage, currentImage) {
// 将 base64 转换为 Image 对象
var previousImg = await createImage(previousImage)
@@ -458,44 +428,6 @@ async function requestCamera () {
return false
}
/*
A method that returns the required style for the html
*/
function get_position_style (ctx, widget_width, y, node_height, top) {
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: `${top}px`,
cursor: 'pointer',
position: 'absolute',
maxWidth: `${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 - MARGIN * 2}px`,
// background: '#EEEEEE',
display: 'flex',
flexDirection: 'column',
// alignItems: 'center',
justifyContent: 'space-around'
}
}
const base64Df =
'data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAwAAAAMCAYAAABWdVznAAAAAXNSR0IArs4c6QAAALZJREFUKFOFkLERwjAQBPdbgBkInECGaMLUQDsE0AkRVRAYWqAByxldPPOWHwnw4OBGye1p50UDSoA+W2ABLPN7i+C5dyC6R/uiAUXRQCs0bXoNIu4QPQzAxDKxHoALOrZcqtiyR/T6CXw7+3IGHhkYcy6BOR2izwT8LptG8rbMiCRAUb+CQ6WzQVb0SNOi5Z2/nX35DRyb/ENazhpWKoGwrpD6nICp5c2qogc4of+c7QcrhgF4Aa/aoAFHiL+RAAAAAElFTkSuQmCC'
app.registerExtension({
name: 'Mixlab.image.ScreenShareNode',
async getCustomWidgets (app) {
@@ -593,17 +525,12 @@ app.registerExtension({
type: 'HTML', // whatever
name: 'sreen_share', // whatever
draw (ctx, node, widget_width, y, widget_height) {
// console.log('ScreenSHare', y, widget_height)
// console.log('ScreenSHare', node)
Object.assign(
this.card.style,
get_position_style(
ctx,
widget_width,
widget_height * 5,
node.size[1],
40
)
get_position_style(ctx, widget_width, y, node.size[1], 40)
)
}
}
@@ -1043,12 +970,13 @@ async function setArea (src) {
div.innerHTML = `
<div id='ml_overlay' style='position: absolute;top:0;background: #251f1fc4;
height: 100vh;
z-index:999999;
z-index:99999999999999;
width: 100%;'>
<img id='ml_video' style='position: absolute;
height: ${displayHeight}px;user-select: none;
-webkit-user-drag: none;
outline: 2px solid #eaeaea;
left: 0;
box-shadow: 8px 9px 17px #575757;' />
<div id='ml_selection' style='position: absolute;
border: 2px dashed red;
+10 -34
View File
@@ -2,6 +2,8 @@ import { app } from '../../../scripts/app.js'
import { api } from '../../../scripts/api.js'
import { $el } from '../../../scripts/ui.js'
import { get_position_style } from './common.js'
function base64ToBlobFromURL (base64URL, contentType) {
return fetch(base64URL).then(response => response.blob())
}
@@ -37,38 +39,6 @@ async function uploadBase64ToFile (base64) {
return url
}
function get_position_style (ctx, widget_width, y, node_height) {
const MARGIN = 4 // the margin around the html element
/* Create a transform that deals with all the scrolling and zooming */
const elRect = ctx.canvas.getBoundingClientRect()
const transform = new DOMMatrix()
.scaleSelf(
elRect.width / ctx.canvas.width,
elRect.height / ctx.canvas.height
)
.multiplySelf(ctx.getTransform())
.translateSelf(MARGIN, MARGIN + y)
return {
transformOrigin: '0 0',
transform: transform,
left: `0`,
top: `0`,
cursor: 'pointer',
position: 'absolute',
maxWidth: `${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: `${node_height * 0.3 - MARGIN * 2}px`,
// background: '#EEEEEE',
display: 'flex',
flexDirection: 'column',
// alignItems: 'center',
justifyContent: 'space-around'
}
}
const p5InputNode = {
name: 'Mixlab.Comfy.P5Input',
async getCustomWidgets (app) {
@@ -106,7 +76,13 @@ const p5InputNode = {
draw (ctx, node, widget_width, y, widget_height) {
Object.assign(
this.div.style,
get_position_style(ctx, widget_width - 24, 44, node.size[1])
get_position_style(
ctx,
widget_width - 24,
44,
node.size[1] * 2.8,
44
)
)
},
serialize: false
@@ -179,7 +155,7 @@ const p5InputNode = {
let nodeId = node.id
//延迟才能获得this.id
widget.div.innerHTML = `<iframe src="extensions/comfyui-mixlab-nodes/p5_export/p5.html?id=${nodeId}"
widget.div.innerHTML = `<iframe src="mixlab/app/p5_export/p5.html?id=${nodeId}"
style="border:0;width:100%;height:100%;"
></iframe>`
+17 -10
View File
@@ -3,7 +3,7 @@ import { api } from '../../../scripts/api.js'
import { ComfyWidgets } from '../../../scripts/widgets.js'
import { $el } from '../../../scripts/ui.js'
import PhotoSwipeLightbox from '/extensions/comfyui-mixlab-nodes/lib/photoswipe-lightbox.esm.min.js'
import PhotoSwipeLightbox from '/mixlab/app/lib/photoswipe-lightbox.esm.min.js'
function loadCSS (url) {
var link = document.createElement('link')
link.rel = 'stylesheet'
@@ -40,14 +40,14 @@ function loadCSS (url) {
// Append the style element to the document head
document.head.appendChild(style)
}
loadCSS('/extensions/comfyui-mixlab-nodes/lib/photoswipe.min.css')
loadCSS('/mixlab/app/lib/photoswipe.min.css')
function initLightBox () {
const lightbox = new PhotoSwipeLightbox({
gallery: '.prompt_image_output',
children: 'a',
pswpModule: () =>
import('/extensions/comfyui-mixlab-nodes/lib/photoswipe.esm.min.js')
import('/mixlab/app/lib/photoswipe.esm.min.js')
})
lightbox.on('uiRegister', function () {
@@ -100,7 +100,10 @@ function get_position_style (ctx, widget_width, y, node_height) {
return {
transformOrigin: '0 0',
transform: transform,
left: `0`,
left:
document.querySelector('.comfy-menu').style.display === 'none'
? `60px`
: `0`,
top: `0`,
cursor: 'pointer',
position: 'absolute',
@@ -178,7 +181,7 @@ app.registerExtension({
const orig_nodeCreated = nodeType.prototype.onNodeCreated
nodeType.prototype.onNodeCreated = async function () {
orig_nodeCreated?.apply(this, arguments)
const mutable_prompt = this.widgets.filter(
w => w.name == 'mutable_prompt'
)[0]
@@ -190,7 +193,12 @@ app.registerExtension({
draw (ctx, node, widget_width, y, widget_height) {
Object.assign(
this.div.style,
get_position_style(ctx, widget_width, y, node.size[1])
get_position_style(
ctx,
widget_width,
y + widget_height + 24,
node.size[1]
)
)
}
}
@@ -207,7 +215,7 @@ app.registerExtension({
background-color: var(--comfy-input-bg);
border-radius: 8px;
border-color: var(--border-color);
border-style: solid; height: 30px;min-width: 122px;
border-style: solid;height: 30px;min-width: 122px;
`
// const btn=document.createElement('button');
@@ -266,7 +274,6 @@ app.registerExtension({
},
async loadedGraphNode (node, app) {
if (node.type === 'RandomPrompt') {
}
}
})
@@ -408,7 +415,7 @@ const _createResult = async (node, widget, message) => {
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]
@@ -559,7 +566,7 @@ app.registerExtension({
let cards = widget.div.querySelectorAll('.card')
if (cards.length == 0) node.size = [280, 120]
if(widget.value) _createResult(node, widget, widget.value)
if (widget.value) _createResult(node, widget, widget.value)
}
}
})
+4 -1
View File
@@ -19,7 +19,10 @@ function get_position_style (ctx, widget_width, y, node_height) {
return {
transformOrigin: '0 0',
transform: transform,
left: `0`,
left:
document.querySelector('.comfy-menu').style.display === 'none'
? `60px`
: `0`,
top: `0`,
cursor: 'pointer',
position: 'absolute',
+4 -1
View File
@@ -21,7 +21,10 @@ function get_position_style (ctx, widget_width, y, node_height) {
return {
transformOrigin: '0 0',
transform: transform,
left: `0`,
left:
document.querySelector('.comfy-menu').style.display === 'none'
? `60px`
: `0`,
top: '0',
cursor: 'pointer',
position: 'absolute',
+311 -289
View File
@@ -11,6 +11,10 @@ import { smart_init, addSmartMenu } from './smart_connect.js'
import { completion_ } from './chat.js'
import { getLocalData, saveLocalData, updateLLMAPIKey } from './common.js'
const BIZYAIR_SERVER_ADDRESS = 'https://api.siliconflow.cn'
function showTextByLanguage (key, json) {
// 获取浏览器语言
var language = navigator.language
@@ -28,33 +32,48 @@ function showTextByLanguage (key, json) {
//系统prompt
// const systemPrompt = `You are a prompt creator, your task is to create prompts for the user input request, the prompts are image descriptions that include keywords for (an adjective, type of image, framing/composition, subject, subject appearance/action, environment, lighting situation, details of the shoot/illustration, visuals aesthetics and artists), brake keywords by comas, provide high quality, non-verboose, coherent, brief, concise, and not superfluous prompts, the subject from the input request must be included verbatim on the prompt,the prompt is english`
let tool ={
"name": "create_prompt",
"description": "Create a prompt with a given subject, content, and style based on user input for image descriptions.",
"parameter": {
"type": "object",
"properties": {
"subject": {
"type": "string",
"description": "The subject of the prompt, included verbatim from the input request.",
"required": true
let tool = {
name: 'create_prompt',
description:
'Create a prompt with a given subject, content, and style based on user input for image descriptions.',
parameter: {
type: 'object',
properties: {
subject: {
type: 'string',
description:
'The subject of the prompt, included verbatim from the input request.',
required: true
},
"content": {
"type": "string",
"description": "The content of the prompt, primarily focusing on the scene and objects, including keywords for adjective, type of image, framing/composition, subject appearance/action, and environment.",
"required": true
content: {
type: 'string',
description:
'The content of the prompt, primarily focusing on the scene and objects, including keywords for adjective, type of image, framing/composition, subject appearance/action, and environment.',
required: true
},
"style": {
"type": "string",
"description": "The style of the prompt, including lighting situation, details of the shoot/illustration, visual aesthetics, and artists. Ensure it is high quality, non-verbose, coherent, brief, concise, and not superfluous.",
"required": true
style: {
type: 'string',
description:
'The style of the prompt, including lighting situation, details of the shoot/illustration, visual aesthetics, and artists. Ensure it is high quality, non-verbose, coherent, brief, concise, and not superfluous.',
required: true
}
}
}
}
const systemPrompt=`You are a helpful assistant with access to the following functions. Use them if required - ${JSON.stringify(tool,null,2)}`
const systemPrompt = `
Prompt:
Describe a scene with a specific theme in fluent and highly detailed English, focusing on the content and style. The description should be within 100 words.
Theme: [Insert Theme Here]
Example:
Theme: Sunset
The sun sets in a blaze of orange and pink, casting a warm glow over a tranquil lake. Silhouetted trees line the shore, their reflections shimmering in the water. A lone figure sits at the end of a wooden pier, feet dangling above the mirrored surface, lost in thought. The scene exudes peacefulness and quiet beauty.
`
if (!localStorage.getItem('_mixlab_system_prompt')) {
localStorage.setItem('_mixlab_system_prompt', systemPrompt)
@@ -100,7 +119,7 @@ async function start_llama (model = 'Phi-3-mini-4k-instruct-Q5_K_S.gguf') {
})
const data = await response.json()
if (data.llama_cpp_error||!data.port) {
if (data.llama_cpp_error || !data.port) {
return
}
@@ -145,6 +164,31 @@ function resizeImage (base64Image) {
})
}
const createMixlabBtn = () => {
const appsButton = document.createElement('button')
appsButton.id = 'mixlab_chatbot_by_llamacpp'
appsButton.className = 'comfyui-button'
appsButton.textContent = '♾️Mixlab'
// appsButton.onclick = () =>
appsButton.onclick = async () => {
let llm_key = await updateLLMAPIKey()
// if (window._mixlab_llamacpp&&window._mixlab_llamacpp.model&&window._mixlab_llamacpp.model.length>0) {
// //显示运行的模型
// createModelsModal([
// window._mixlab_llamacpp.url,
// window._mixlab_llamacpp.model
// ])
// } else {
// // let ms = await get_llamafile_models()
// // ms = ms.filter(m => !m.match('-mmproj-'))
// // if (ms.length > 0) createModelsModal(ms)
// }
createModelsModal([], llm_key)
}
return appsButton
}
// 菜单入口
async function createMenu () {
const menu = document.querySelector('.comfy-menu')
@@ -156,29 +200,16 @@ async function createMenu () {
`
menu.append(separator)
if (!menu.querySelector('#mixlab_chatbot_by_llamacpp')) {
const appsButton = document.createElement('button')
appsButton.id = 'mixlab_chatbot_by_llamacpp'
appsButton.textContent = '♾️Mixlab'
// appsButton.onclick = () =>
appsButton.onclick = async () => {
// if (window._mixlab_llamacpp&&window._mixlab_llamacpp.model&&window._mixlab_llamacpp.model.length>0) {
// //显示运行的模型
// createModelsModal([
// window._mixlab_llamacpp.url,
// window._mixlab_llamacpp.model
// ])
// } else {
// // let ms = await get_llamafile_models()
// // ms = ms.filter(m => !m.match('-mmproj-'))
// // if (ms.length > 0) createModelsModal(ms)
// }
createModelsModal([
])
if (
menu.style.display === 'none' &&
document.querySelector('.comfyui-menu-push')
) {
//新版ui
document.querySelector('.comfyui-menu-push').append(createMixlabBtn())
} else {
if (!menu.querySelector('#mixlab_chatbot_by_llamacpp')) {
menu.append(createMixlabBtn())
}
menu.append(appsButton)
}
}
@@ -191,6 +222,16 @@ function loadExternalScript (url) {
return
}
const existingScript = document.querySelector(`script[src="${url}"]`)
if (existingScript) {
existingScript.onload = () => {
isScriptLoaded[url] = true
resolve()
}
existingScript.onerror = reject
return
}
const script = document.createElement('script')
script.src = url
script.onload = () => {
@@ -233,9 +274,7 @@ function createChart (chartDom, nodes) {
}
async function createNodesCharts () {
await loadExternalScript(
'/extensions/comfyui-mixlab-nodes/lib/echarts.min.js'
)
await loadExternalScript('/mixlab/app/lib/echarts.min.js')
const templates = await loadTemplate()
var nodes = {}
Array.from(templates, t => {
@@ -666,7 +705,10 @@ function get_position_style (ctx, widget_width, y, node_height) {
return {
transformOrigin: '0 0',
transform: transform,
left: `0`,
left:
document.querySelector('.comfy-menu').style.display === 'none'
? `60px`
: `0`,
top: `0`,
cursor: 'pointer',
position: 'absolute',
@@ -803,21 +845,67 @@ async function fetchReadmeContent (url) {
async function startLLM (model) {
let res = await start_llama(model)
window._mixlab_llamacpp = res||{ model:[] }
window._mixlab_llamacpp = res || { model: [] }
localStorage.setItem('_mixlab_llama_select', res?.model||'')
localStorage.setItem('_mixlab_llama_select', res?.model || '')
if (document.body.querySelector('#mixlab_chatbot_by_llamacpp')&&window._mixlab_llamacpp?.url) {
if (
document.body.querySelector('#mixlab_chatbot_by_llamacpp') &&
window._mixlab_llamacpp?.url
) {
document.body
.querySelector('#mixlab_chatbot_by_llamacpp')
.setAttribute('title', window._mixlab_llamacpp.url)
}
if (document.body.querySelector('#llm_status_btn')&&window._mixlab_llamacpp) {
document.body.querySelector('#llm_status_btn').innerText = window._mixlab_llamacpp.model
if (
document.body.querySelector('#llm_status_btn') &&
window._mixlab_llamacpp
) {
document.body.querySelector('#llm_status_btn').innerText =
window._mixlab_llamacpp.model
}
}
function createModelsModal (models) {
function createInputOfLabel (labelText, key, id) {
const label = document.createElement('p')
label.innerText = labelText
const input = document.createElement('input')
input.type = 'text'
input.style = `color: var(--input-text);
background-color: var(--comfy-input-bg);
border-radius: 8px;
border-color: var(--border-color);
height: 26px;
padding: 4px 10px;
width: 150px;
margin-left: 12px;`
input.value =
getLocalData(key)['-'] || Object.values(getLocalData(key))[0] || 'by Mixlab'
input.addEventListener('change', e => {
e.stopPropagation()
e.preventDefault()
saveLocalData(key, '-', input.value)
})
const div = document.createElement('div')
div.style = `display: flex;
justify-content: flex-start;
align-items: baseline;padding: 0 18px;`
div.addEventListener('click', e => {
e.stopPropagation()
})
div.appendChild(label)
div.appendChild(input)
return div
}
function createModelsModal (models, llmKey) {
var div =
document.querySelector('#model-modal') || document.createElement('div')
div.id = 'model-modal'
@@ -883,8 +971,6 @@ function createModelsModal (models) {
user-select: none;
`
// headTitleElement.href = 'https://github.com/shadowcz007/comfyui-mixlab-nodes'
// headTitleElement.target = '_blank'
const linkIcon = document.createElement('small')
linkIcon.textContent = showTextByLanguage('Auto Open', {
'Auto Open': '自动开启'
@@ -896,7 +982,7 @@ function createModelsModal (models) {
Status: 'OFF'
})
statusIcon.id = 'llm_status_btn'
statusIcon.style=`padding: 4px;
statusIcon.style = `padding: 4px;
background-color: rgb(102, 255, 108);
color: black;
font-size: 12px;
@@ -912,37 +998,25 @@ function createModelsModal (models) {
// startLLM()
})
const n_gpu = document.createElement('input')
n_gpu.type = 'number'
n_gpu.setAttribute('min', -1)
n_gpu.setAttribute('max', 9999)
n_gpu.style = `color: var(--input-text);
background-color: var(--comfy-input-bg);
border-radius: 8px;
border-color: var(--border-color);
height: 26px;
padding: 4px 10px;
width: 48px;
margin-left: 12px;`
if (localStorage.getItem('_mixlab_llama_n_gpu')) {
n_gpu.value = parseInt(localStorage.getItem('_mixlab_llama_n_gpu'))
} else {
n_gpu.value = -1
localStorage.setItem('_mixlab_llama_n_gpu', -1)
}
const n_gpu_p = document.createElement('p')
n_gpu_p.innerText = 'n_gpu_layers'
const batchPageBtn = document.createElement('div')
batchPageBtn.style = `display: flex;
justify-content: center;
align-items: center;
font-size: 12px;`
batchPageBtn.innerHTML=`<a href="${get_url()}/mixlab/app" target="_blank" style="color: var(--input-text);
batchPageBtn.innerHTML = `<a href="${get_url()}/mixlab/app" target="_blank" style="color: var(--input-text);
background-color: var(--comfy-input-bg);">App</a>`
const siliconflowHelp = document.createElement('a')
siliconflowHelp.textContent = showTextByLanguage('Siliconflow', {
Siliconflow: '硅基流动'
})
siliconflowHelp.style = `color: var(--input-text);
background-color: var(--comfy-input-bg);margin-top:14px`
siliconflowHelp.href = 'https://cloud.siliconflow.cn/s/mixlabs'
siliconflowHelp.target = '_blank'
const title = document.createElement('p')
title.innerText = 'Mixlab Nodes'
title.style = `font-size: 18px;
@@ -956,12 +1030,10 @@ function createModelsModal (models) {
font-size: 12px;
flex-direction: column; `
left_d.appendChild(title)
// title.appendChild(statusIcon)
// left_d.appendChild(linkIcon)
left_d.appendChild(batchPageBtn)
headTitleElement.appendChild(left_d)
left_d.appendChild(siliconflowHelp)
// headTitleElement.appendChild(n_gpu_div)
headTitleElement.appendChild(left_d)
//重启
const reStart = document.createElement('small')
@@ -969,7 +1041,7 @@ function createModelsModal (models) {
restart: '重启'
})
reStart.style=`padding: 8px;
reStart.style = `padding: 8px;
font-size: 16px;
outline: 1px solid;
padding-top: 4px;
@@ -1002,23 +1074,23 @@ function createModelsModal (models) {
})
})
n_gpu.addEventListener('click', e => {
e.stopPropagation()
localStorage.setItem('_mixlab_llama_n_gpu', n_gpu.value)
})
modal.appendChild(headTitleElement)
// Create modal content area
var modalContent = document.createElement('div')
modalContent.classList.add('modal-content')
let llmKeyDiv = createInputOfLabel('LLM Key', '_mixlab_llm_api_key', '-')
saveLocalData('_mixlab_llm_api_url', '-', BIZYAIR_SERVER_ADDRESS)
let llmAPIDiv = createInputOfLabel('LLM API', '_mixlab_llm_api_url', '-')
modalContent.appendChild(llmKeyDiv)
modalContent.appendChild(llmAPIDiv)
var inputForSystemPrompt = document.createElement('textarea')
inputForSystemPrompt.className = 'comfy-multiline-input'
inputForSystemPrompt.style = ` height: 260px;
width: 480px;
font-size: 16px;
padding: 18px;`
inputForSystemPrompt.style = `height: 260px;width: 480px;font-size: 16px;padding: 18px;`
inputForSystemPrompt.value = localStorage.getItem('_mixlab_system_prompt')
inputForSystemPrompt.addEventListener('change', e => {
@@ -1030,25 +1102,8 @@ function createModelsModal (models) {
e.stopPropagation()
})
// modalContent.appendChild(inputForSystemPrompt)
modalContent.appendChild(inputForSystemPrompt)
if (!window._mixlab_llamacpp||(window._mixlab_llamacpp?.model?.length==0)) {
for (const m of models) {
let d = document.createElement('div')
d.innerText = `${showTextByLanguage('Run', {
Run: '运行'
})} ${m}`
d.className = `mix_tag`
d.addEventListener('click', async e => {
e.stopPropagation()
div.remove()
// startLLM(m)
})
// modalContent.appendChild(d)
}
}
modal.appendChild(modalContent)
const helpInfo = document.createElement('a')
@@ -1416,7 +1471,7 @@ app.registerExtension({
.querySelector('#mixlab_chatbot_by_llamacpp')
.setAttribute('title', res.url)
})
}else{
} else {
// startLLM('')
}
@@ -1443,19 +1498,17 @@ app.registerExtension({
LGraphCanvas.prototype.fixTheNode = function (node) {
let new_node = LiteGraph.createNode(node.comfyClass)
console.log(node)
if(new_node){
if (new_node) {
new_node.pos = [node.pos[0], node.pos[1]]
app.canvas.graph.add(new_node, false)
copyNodeValues(node, new_node)
app.canvas.graph.remove(node)
}
}
smart_init()
LGraphCanvas.prototype.text2text = async function (node) {
// console.log(node)
let widget = node.widgets.filter(
w => w.name === 'text' && typeof w.value == 'string'
)[0]
@@ -1467,10 +1520,14 @@ app.registerExtension({
let userInput = widget.value
widget.value = widget.value.trim()
widget.value += '\n'
let jsonStr="";
let jsonStr = ''
try {
await completion_(
window._mixlab_llamacpp.url + '/v1/chat/completions',
getLocalData('_mixlab_llm_api_key')['-'] ||
Object.values(getLocalData('_mixlab_llm_api_key'))[0],
getLocalData('_mixlab_llm_api_url')['-'] ||
Object.values(getLocalData('_mixlab_llm_api_url'))[0],
[
{
role: 'system',
@@ -1480,55 +1537,15 @@ app.registerExtension({
],
controller,
t => {
// console.log(t)
// console.log(t.endsWith('\r'))
widget.value += t
jsonStr+=t
jsonStr += t
}
)
} catch (error) {
//是否要自动加载模型
if (localStorage.getItem('_mixlab_auto_llama_open')) {
let model = localStorage.getItem('_mixlab_llama_select')
start_llama(model).then(async res => {
window._mixlab_llamacpp = res
document.body
.querySelector('#mixlab_chatbot_by_llamacpp')
.setAttribute('title', res.url)
await completion_(
window._mixlab_llamacpp.url + '/v1/chat/completions',
[
{
role: 'system',
content: localStorage.getItem('_mixlab_system_prompt')
},
{ role: 'user', content: userInput }
],
controller,
t => {
// console.log(t)
widget.value += t
jsonStr+=t
}
)
})
}
console.log(error)
}
let json=null;
try {
json=JSON.parse(jsonStr.trim())
} catch (error) {
json=JSON.parse(jsonStr.trim()+"}")
}
if(json){
widget.value = [json.subject,json.content,json.style].join('\n')
}else{
widget.value = widget.value.trim()
}
}
}
@@ -1812,12 +1829,17 @@ app.registerExtension({
inp => inp.name == 'text' && inp.type == 'STRING'
)
const llm_api_key =
getLocalData('_mixlab_llm_api_key')['-'] ||
Object.values(getLocalData('_mixlab_llm_api_key'))[0],
llm_api_url =
getLocalData('_mixlab_llm_api_url')['-'] ||
Object.values(getLocalData('_mixlab_llm_api_url'))[0]
if (
text_input &&
text_input.length == 0 &&
text_widget &&
text_widget.length == 1 &&
window._mixlab_llamacpp &&
llm_api_key &&llm_api_url&&
node.type != 'ShowTextForGPT'
) {
opts.push({
@@ -1828,19 +1850,19 @@ app.registerExtension({
})
}
if (
node.imgs &&
node.imgs.length > 0 &&
window._mixlab_llamacpp &&
window._mixlab_llamacpp.chat_format === 'llava-1-5'
) {
opts.push({
content: 'Image-to-Text ♾️Mixlab', // with a name
callback: () => {
LGraphCanvas.prototype.image2text(node)
} // and the callback
})
}
// if (
// node.imgs &&
// node.imgs.length > 0 &&
// window._mixlab_llamacpp &&
// window._mixlab_llamacpp.chat_format === 'llava-1-5'
// ) {
// opts.push({
// content: 'Image-to-Text ♾️Mixlab', // with a name
// callback: () => {
// LGraphCanvas.prototype.image2text(node)
// } // and the callback
// })
// }
}
return [...opts, null, ...options] // and return the options
@@ -1901,127 +1923,127 @@ app.registerExtension({
// Add canvas menu options
const orig = LGraphCanvas.prototype.getCanvasMenuOptions
const apps = await get_my_app()
if (!apps) return
// const apps = await get_my_app()
// if (!apps) return
console.log('apps', apps)
// console.log('apps', apps)
let apps_map = { 0: [] }
// let apps_map = { 0: [] }
for (const app of apps) {
if (app.category) {
if (!apps_map[app.category]) apps_map[app.category] = []
apps_map[app.category].push(app)
} else {
apps_map['0'].push(app)
}
}
// for (const app of apps) {
// if (app.category) {
// if (!apps_map[app.category]) apps_map[app.category] = []
// apps_map[app.category].push(app)
// } else {
// apps_map['0'].push(app)
// }
// }
let apps_opts = []
for (const category in apps_map) {
// console.log('category', typeof category)
if (category === '0') {
apps_opts.push(
...Array.from(apps_map[category], a => {
// console.log('#1级',a)
return {
content: `${a.name}_${a.version}`,
has_submenu: false,
callback: async () => {
try {
let ddd = await get_my_app(a.filename)
if (!ddd) return
let item = ddd[0]
if (item) {
if (item.author) {
// 有作者信息
if (item.author.avatar)
localStorage.setItem(
'_mixlab_author_avatar',
item.author.avatar
)
if (item.author.name)
localStorage.setItem(
'_mixlab_author_name',
item.author.name
)
// for (const category in apps_map) {
// // console.log('category', typeof category)
// if (category === '0') {
// apps_opts.push(
// ...Array.from(apps_map[category], a => {
// // console.log('#1级',a)
// return {
// content: `${a.name}_${a.version}`,
// has_submenu: false,
// callback: async () => {
// try {
// let ddd = await get_my_app(a.filename)
// if (!ddd) return
// let item = ddd[0]
// if (item) {
// if (item.author) {
// // 有作者信息
// if (item.author.avatar)
// localStorage.setItem(
// '_mixlab_author_avatar',
// item.author.avatar
// )
// if (item.author.name)
// localStorage.setItem(
// '_mixlab_author_name',
// item.author.name
// )
if (item.author.link)
localStorage.setItem(
'_mixlab_author_link',
item.author.link
)
}
// if (item.author.link)
// localStorage.setItem(
// '_mixlab_author_link',
// item.author.link
// )
// }
// console.log(item.data)
app.loadGraphData(item.data)
setTimeout(() => {
const node = app.graph._nodes_in_order[0]
if (!node) return
app.canvas.centerOnNode(node)
app.canvas.setZoom(0.5)
}, 1000)
}
} catch (error) {}
}
}
})
)
} else {
// 二级
apps_opts.push({
content: '🚀 ' + category,
has_submenu: true,
disabled: false,
submenu: {
options: Array.from(apps_map[category], a => {
// console.log('#二级',a)
return {
content: `${a.name}_${a.version}`,
callback: async () => {
try {
let ddd = await get_my_app(a.filename, a.category)
// // console.log(item.data)
// app.loadGraphData(item.data)
// setTimeout(() => {
// const node = app.graph._nodes_in_order[0]
// if (!node) return
// app.canvas.centerOnNode(node)
// app.canvas.setZoom(0.5)
// }, 1000)
// }
// } catch (error) {}
// }
// }
// })
// )
// } else {
// // 二级
// apps_opts.push({
// content: '🚀 ' + category,
// has_submenu: true,
// disabled: false,
// submenu: {
// options: Array.from(apps_map[category], a => {
// // console.log('#二级',a)
// return {
// content: `${a.name}_${a.version}`,
// callback: async () => {
// try {
// let ddd = await get_my_app(a.filename, a.category)
if (!ddd) return
let item = ddd[0]
if (item) {
console.log(item)
if (item.author) {
// 有作者信息
if (item.author.avatar)
localStorage.setItem(
'_mixlab_author_avatar',
item.author.avatar
)
if (item.author.name)
localStorage.setItem(
'_mixlab_author_name',
item.author.name
)
if (item.author.link)
localStorage.setItem(
'_mixlab_author_link',
item.author.link
)
}
// if (!ddd) return
// let item = ddd[0]
// if (item) {
// console.log(item)
// if (item.author) {
// // 有作者信息
// if (item.author.avatar)
// localStorage.setItem(
// '_mixlab_author_avatar',
// item.author.avatar
// )
// if (item.author.name)
// localStorage.setItem(
// '_mixlab_author_name',
// item.author.name
// )
// if (item.author.link)
// localStorage.setItem(
// '_mixlab_author_link',
// item.author.link
// )
// }
// console.log(item.data)
app.loadGraphData(item.data)
setTimeout(() => {
const node = app.graph._nodes_in_order[0]
if (!node) return
app.canvas.centerOnNode(node)
app.canvas.setZoom(0.5)
}, 1000)
}
} catch (error) {}
}
}
})
}
})
}
}
// // console.log(item.data)
// app.loadGraphData(item.data)
// setTimeout(() => {
// const node = app.graph._nodes_in_order[0]
// if (!node) return
// app.canvas.centerOnNode(node)
// app.canvas.setZoom(0.5)
// }, 1000)
// }
// } catch (error) {}
// }
// }
// })
// }
// })
// }
// }
// console.log('apps',apps_map, apps_opts,apps)
LGraphCanvas.prototype.getCanvasMenuOptions = function () {
+30 -51
View File
@@ -1,46 +1,13 @@
import { app } from '../../../scripts/app.js'
import { $el } from '../../../scripts/ui.js'
import {
loadExternalScript,
updateLLMAPIKey,
get_position_style,
getLocalData
} from './common.js'
const getLocalData = key => {
let data = {}
try {
data = JSON.parse(localStorage.getItem(key)) || {}
} catch (error) {
return {}
}
return data
}
function get_position_style (ctx, widget_width, y, node_height) {
const MARGIN = 4 // the margin around the html element
/* Create a transform that deals with all the scrolling and zooming */
const elRect = ctx.canvas.getBoundingClientRect()
const transform = new DOMMatrix()
.scaleSelf(
elRect.width / ctx.canvas.width,
elRect.height / ctx.canvas.height
)
.multiplySelf(ctx.getTransform())
.translateSelf(MARGIN, MARGIN + y)
return {
transformOrigin: '0 0',
transform: transform,
left: `0`,
top: `0`,
cursor: 'pointer',
position: 'absolute',
maxWidth: `${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'
}
}
loadExternalScript('/mixlab/app/lib/pickr.min.js')
function hexToRGBA (hexColor) {
var hex = hexColor.replace('#', '')
@@ -62,7 +29,7 @@ app.registerExtension({
init () {
$el('link', {
rel: 'stylesheet',
href: '/extensions/comfyui-mixlab-nodes/lib/classic.min.css',
href: '/mixlab/app/lib/classic.min.css',
parent: document.head
})
@@ -122,7 +89,7 @@ app.registerExtension({
nodeType.prototype.onNodeCreated = function () {
orig_nodeCreated?.apply(this, arguments)
console.log('Color nodeData', this.div)
// console.log('Color nodeData', this.div)
const widget = {
type: 'div',
@@ -363,7 +330,7 @@ app.registerExtension({
return [128, 32] // a method to compute the current size of the widget
},
async serializeValue (nodeId, widgetIndex) {
let data = getLocalData('_mixlab_api_key')
let data = getLocalData('_mixlab_llm_api_key')
return data[node.id] || 'by Mixlab'
}
}
@@ -380,6 +347,7 @@ app.registerExtension({
nodeType.prototype.onNodeCreated = function () {
orig_nodeCreated?.apply(this, arguments)
const rowHeight = this.rowHeight
const widget = {
type: 'div',
name: 'input_key',
@@ -414,11 +382,11 @@ app.registerExtension({
// ip.value = placeholder
ip.style = `margin-left:8px;
outline: none;
border: none;
padding:12px;
width: 100%;
`
outline: none;
border: none;
padding:12px;
width: 100%;
`
div.appendChild(ip)
@@ -426,12 +394,13 @@ app.registerExtension({
let data = getLocalData(key)
data[this.id] = ip.value.trim()
localStorage.setItem(key, JSON.stringify(data))
updateLLMAPIKey(data[this.id])
})
return div
}
let inputKey = inputDiv('_mixlab_api_key', 'Key')
let inputKey = inputDiv('_mixlab_llm_api_key', 'Key')
widget.div.appendChild(inputKey)
@@ -444,6 +413,12 @@ app.registerExtension({
return onRemoved?.()
}
// const processMouseWheel=app.canvas.processMouseWheel
// app.canvas.processMouseWheel=()=>{
// console.log(app.canvas.ds.scale)
// return processMouseWheel?.()
// }
this.serialize_widgets = true //需要保存参数
}
}
@@ -452,11 +427,13 @@ app.registerExtension({
if (node.type === 'KeyInput') {
let widget = node.widgets.filter(w => w.div)[0]
let apiKey = getLocalData('_mixlab_api_key')
let apiKey = getLocalData('_mixlab_llm_api_key')
let id = node.id
if (widget.div.querySelector('.Key'))
widget.div.querySelector('.Key').value = apiKey[id] || 'by Mixlab'
if (apiKey[id]) updateLLMAPIKey(apiKey[id])
}
},
nodeCreated (node, app) {
@@ -466,12 +443,14 @@ app.registerExtension({
if (node.type === 'KeyInput') {
let widget = node.widgets.filter(w => w.div)[0]
let apiKey = getLocalData('_mixlab_api_key')
let apiKey = getLocalData('_mixlab_llm_api_key')
let id = node.id
if (widget.div.querySelector('.Key'))
widget.div.querySelector('.Key').value = apiKey[id] || 'by Mixlab'
if (apiKey[id]) updateLLMAPIKey(apiKey[id])
}
}, 1000)
}
+4 -1
View File
@@ -43,7 +43,10 @@ function get_position_style (ctx, widget_width, y, node_height) {
return {
transformOrigin: '0 0',
transform: transform,
left: `0`,
left:
document.querySelector('.comfy-menu').style.display === 'none'
? `60px`
: `0`,
top: `0`,
cursor: 'pointer',
position: 'absolute',
+1 -1
View File
@@ -40,7 +40,7 @@ class Visualizer {
scrolling: 'no',
overflow: 'hidden'
})
this.iframe.src = '/extensions/comfyui-mixlab-nodes/' + visualSrc + '.html'
this.iframe.src = '/mixlab/app/' + visualSrc + '.html'
console.log('#Visualizer', container, this.iframe)
container.appendChild(this.iframe)
}
+5 -2
View File
@@ -34,7 +34,10 @@ function get_position_style (ctx, widget_width, y, node_height) {
return {
transformOrigin: '0 0',
transform: transform,
left: `0`,
left:
document.querySelector('.comfy-menu').style.display === 'none'
? `60px`
: `0`,
top: `0`,
cursor: 'pointer',
position: 'absolute',
@@ -125,7 +128,7 @@ app.registerExtension({
window._mixlab_file_path_watcher = json.event_type
// widget.card.innerText = window._mixlab_file_path_watcher || ''
//运行
// document.querySelector('#queue-button').click()
if (app) app.queuePrompt()
}
})
}, 1000)
File diff suppressed because one or more lines are too long
-47
View File
@@ -1,47 +0,0 @@
/*
object-assign
(c) Sindre Sorhus
@license MIT
*/
/*!
pica
https://github.com/nodeca/pica
*/
/*!
* Block below copied from Protovis: http://mbostock.github.com/protovis/
* Copyright 2010 Stanford Visualization Group
* Licensed under the BSD License: http://www.opensource.org/licenses/bsd-license.php
* @license
*/
/*!
* jQuery JavaScript Library v3.7.1
* https://jquery.com/
*
* Copyright OpenJS Foundation and other contributors
* Released under the MIT license
* https://jquery.org/license
*
* Date: 2023-08-28T13:37Z
*/
/*!
* quantize.js Copyright 2008 Nick Rabinowitz.
* Licensed under the MIT license: http://www.opensource.org/licenses/mit-license.php
* @license
*/
/*! alertifyjs - v1.13.1 - Mohammad Younes <Mohammad@alertifyjs.com> (http://alertifyjs.com) */
/*! regenerator-runtime -- Copyright (c) 2014-present, Facebook, Inc. -- license (MIT): https://github.com/facebook/regenerator/blob/main/LICENSE */
/**
* hermite-resize - Canvas image resize/resample using Hermite filter with JavaScript.
* @version v2.2.10
* @link https://github.com/viliusle/miniPaint
* @license MIT
*/
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<!DOCTYPE html>
<html dir="ltr" lang="en-US">
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
<meta http-equiv="x-ua-compatible" content="IE=edge" />
<title>miniPaint - image editor</title>
<meta name="description"
content="miniPaint is free online image editor using HTML5. Edit, adjust your images, add effects online in your browser, without installing anything..." />
<meta name="keywords"
content="photo, image, picture, transparent, layers, free, edit, html5, canvas, javascript, online, photoshop, gimp, effects, sharpen, blur, magic eraser tool, clone tool, rotate, resize, photoshop online, online tools, tilt shift, sprites, keypoints" />
<meta name="viewport" content="width=device-width, initial-scale=1, maximum-scale=1.0, user-scalable=0" />
<link rel="icon" sizes="192x192" href="images/favicon.png">
<!-- <link rel="manifest" href="dist/manifest.json"> -->
<!-- Google -->
<meta itemprop="name" content="miniPaint" />
<meta itemprop="description"
content="miniPaint is free online image editor using HTML5. Edit, adjust your images, add effects online in your browser, without installing anything..." />
<meta itemprop="image" content="https://viliusle.github.io/miniPaint/images/preview.jpg" />
<!-- Twitter -->
<meta name="twitter:card" content="summary_large_image" />
<meta name="twitter:title" content="miniPaint" />
<meta name="twitter:description"
content="miniPaint is free online image editor using HTML5. Edit, adjust your images, add effects online in your browser, without installing anything..." />
<meta name="twitter:image" content="https://viliusle.github.io/miniPaint/images/preview.jpg" />
<meta name="twitter:image:alt"
content="miniPaint is free online image editor using HTML5. Edit, adjust your images, add effects online in your browser, without installing anything..." />
<!-- Facebook, Pinterest -->
<meta property="og:title" content="miniPaint" />
<meta property="og:type" content="article" />
<meta property="og:url" content="https://viliusle.github.io/miniPaint/" />
<meta property="og:image" content="https://viliusle.github.io/miniPaint/images/preview.jpg" />
<meta property="og:description"
content="miniPaint is free online image editor using HTML5. Edit, adjust your images, add effects online in your browser, without installing anything..." />
<meta property="og:site_name" content="miniPaint" />
<script src="dist/bundle.ejs"></script>
</head>
<body>
<div class="wrapper">
<nav aria-label="Main Menu" class="main_menu" id="main_menu"></nav>
<div class="submenu">
<!-- <a class="logo" href="#">miniPaint</a> -->
<div class="block attributes" id="action_attributes"></div>
<select id="automask_models_mixlab"></select>
<button id="automask_image_mixlab" type="button" style="width: 98px;
height: 36px;margin-right: 18px;
color: white;">
RemoveBg
</button>
<button id="cancel_image_mixlab" type="button" style="width: 98px;
height: 36px;
color: white;">
Cancel
</button>
<button id="save_image_mixlab" type="button" style="width: 98px;
height: 36px;
color: white;">
Save
</button>
<a
target="_blank" href="https://discord.gg/xbP2GZF6gn"
style="width: 98px;
color: white;
text-decoration: none;"> Help/帮助 </a>
<button class="undo_button" id="undo_button" type="button">
<span class="sr_only">Undo</span>
</button>
</div>
<div class="sidebar_left" id="tools_container"></div>
<div class="middle_area" id="middle_area">
<canvas class="ruler_left" id="ruler_left"></canvas>
<canvas class="ruler_top" id="ruler_top"></canvas>
<div class="main_wrapper" id="main_wrapper">
<div class="canvas_wrapper" id="canvas_wrapper">
<div id="mouse"></div>
<div class="transparent-grid" id="canvas_minipaint_background"></div>
<canvas id="canvas_minipaint">
<div class="trn error">
Your browser does not support canvas or JavaScript is not enabled.
</div>
</canvas>
</div>
</div>
</div>
<div class="sidebar_right">
<div class="preview block" style="display: none;">
<h2 class="trn toggle" data-target="toggle_preview">Preview</h2>
<div id="toggle_preview"></div>
</div>
<div class="colors block">
<h2 class="trn toggle" data-target="toggle_colors">Colors</h2>
<div class="content" id="toggle_colors"></div>
</div>
<div class="block" id="info_base" style="display: none;">
<h2 class="trn toggle toggle-full" data-target="toggle_info">Information</h2>
<div class="content" id="toggle_info"></div>
</div>
<div class="details block" id="details_base">
<h2 class="trn toggle toggle-full" data-target="toggle_details">Layer details</h2>
<div class="content details-content" id="toggle_details"></div>
</div>
<div class="layers block">
<h2 class="trn">Layers</h2>
<div class="content" id="layers_base"></div>
</div>
</div>
</div>
<div class="mobile_menu">
<button class="left_mobile_menu" id="left_mobile_menu_button" type="button">
<span class="sr_only">Toggle Menu</span>
</button>
<button class="right_mobile_menu" id="mobile_menu_button" type="button">
<span class="sr_only">Toggle Menu</span>
</button>
</div>
<div class="hidden" id="tmp"></div>
<div id="popups"></div>
</body>
</html>
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-70
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function setup () {
createCanvas(400, 400, WEBGL)
angleMode(DEGREES)
}
function draw () {
if (frameCount === 1) {
capturer.start()
}
background(30)
noStroke()
translate(0, 0, sin(frameCount) * 400 - 800)
rotateX(frameCount)
rotateY(frameCount)
rotateZ(frameCount)
var w = 20
randomSeed(1)
for (var x = -width / 2; x <= width / 2; x += w) {
for (var y = -width / 2; y <= width / 2; y += w) {
for (var z = -width / 2; z <= width / 2; z += w) {
var r = random(255)
var g = random(255)
var b = random(255)
fill(r, g, b)
push()
translate(x, y, z)
box(w)
pop()
}
}
}
// console.log(frameRate());
if (frameCount < 60) {
capturer.capture(canvas)
} else if (frameCount === 60) {
capturer.save(function (blob) {
// console.log(blob)
// 示例用法
// const blob = new Blob([/* 数据 */], { type: 'video/webm' });
blobToBase64(blob).then(base64String => {
console.log(base64String);
const video = document.createElement('video');
video.controls = true; // 显示视频控件(播放、暂停等)
video.src = base64String; // 设置视频的 src 属性为 Base64 数据 URL
video.width = 640; // 设置视频宽度
video.height = 360; // 设置视频高度
// 将 video 元素添加到页面中
document.body.appendChild(video)
// 自动播放视频
video.play();
}).catch(error => {
console.error('转换失败:', error);
});
})
capturer.stop()
}
}
+2 -2
View File
@@ -11,8 +11,8 @@
<script type="module">
import { api } from "../../../scripts/api.js";
import Command from '/extensions/comfyui-mixlab-nodes/javascript/command.js'
import { api } from "/mixlab/app/javascript/api.js";
import Command from '/mixlab/app/javascript/command.js'
</script>
+11 -14
View File
@@ -716,13 +716,12 @@
color: #4a4a4a !important;
}
</style>
<!-- <script src="../../../scripts/api.js" type="module"></script> -->
<link href="/extensions/comfyui-mixlab-nodes/lib/photoswipe.min.css" rel="stylesheet">
<link href="/extensions/comfyui-mixlab-nodes/lib/classic.min.css" rel="stylesheet">
<script src="/extensions/comfyui-mixlab-nodes/lib/pickr.min.js"></script>
<!-- <script src="/extensions/comfyui-mixlab-nodes/lib/filerobot-image-editor.min.js"></script> -->
<script type="module" src="/extensions/comfyui-mixlab-nodes/lib/model-viewer.min.js"></script>
<link rel="stylesheet" href="/extensions/comfyui-mixlab-nodes/lib/login.css">
<link href="/mixlab/app/lib/photoswipe.min.css" rel="stylesheet">
<link href="/mixlab/app/lib/classic.min.css" rel="stylesheet">
<script src="/mixlab/app/lib/pickr.min.js"></script>
<script type="module" src="/mixlab/app/lib/model-viewer.min.js"></script>
<link rel="stylesheet" href="/mixlab/app/lib/login.css">
</head>
<body>
@@ -780,13 +779,11 @@
<a id="author"></a>
<!-- <script type="module" src="https://cdn.bootcdn.net/ajax/libs/photoswipe/5.4.0/photoswipe-lightbox.esm.min.js"></script> -->
<script type="module">
import PhotoSwipeLightbox from '/extensions/comfyui-mixlab-nodes/lib/photoswipe-lightbox.esm.min.js'
import PhotoSwipeLightbox from '/mixlab/app/lib/photoswipe-lightbox.esm.min.js'
// console.log(Lightbox)
import { api } from "../../../scripts/api.js";
import Command from '/extensions/comfyui-mixlab-nodes/javascript/command.js'
// console.log('api', api)
import { api } from "/mixlab/app/javascript/api.js";
import Command from '/mixlab/app/javascript/command.js'
const base64Df =
'data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAwAAAAMCAYAAABWdVznAAAAAXNSR0IArs4c6QAAALZJREFUKFOFkLERwjAQBPdbgBkInECGaMLUQDsE0AkRVRAYWqAByxldPPOWHwnw4OBGye1p50UDSoA+W2ABLPN7i+C5dyC6R/uiAUXRQCs0bXoNIu4QPQzAxDKxHoALOrZcqtiyR/T6CXw7+3IGHhkYcy6BOR2izwT8LptG8rbMiCRAUb+CQ6WzQVb0SNOi5Z2/nX35DRyb/ENazhpWKoGwrpD6nICp5c2qogc4of+c7QcrhgF4Aa/aoAFHiL+RAAAAAElFTkSuQmCC'
@@ -3219,7 +3216,7 @@
const lightbox = new PhotoSwipeLightbox({
gallery: '.output_card',
children: 'a',
pswpModule: () => import('/extensions/comfyui-mixlab-nodes/lib/photoswipe.esm.min.js'),
pswpModule: () => import('/mixlab/app/lib/photoswipe.esm.min.js'),
// appendToEl: document.querySelector('#result')
});
lightbox.on('uiRegister', function () {
+482
View File
@@ -0,0 +1,482 @@
class ComfyApi extends EventTarget {
#registered = new Set();
constructor() {
super();
this.api_host = location.host;
this.api_base = location.pathname.split('/').slice(0, -1).join('/');
this.initialClientId = sessionStorage.getItem("clientId");
}
apiURL(route) {
return this.api_base + route;
}
fetchApi(route, options) {
if (!options) {
options = {};
}
if (!options.headers) {
options.headers = {};
}
options.headers["Comfy-User"] = this.user;
return fetch(this.apiURL(route), options);
}
addEventListener(type, callback, options) {
super.addEventListener(type, callback, options);
this.#registered.add(type);
}
/**
* Poll status for colab and other things that don't support websockets.
*/
#pollQueue() {
setInterval(async () => {
try {
const resp = await this.fetchApi("/prompt");
const status = await resp.json();
this.dispatchEvent(new CustomEvent("status", { detail: status }));
} catch (error) {
this.dispatchEvent(new CustomEvent("status", { detail: null }));
}
}, 1000);
}
/**
* Creates and connects a WebSocket for realtime updates
* @param {boolean} isReconnect If the socket is connection is a reconnect attempt
*/
#createSocket(isReconnect) {
if (this.socket) {
return;
}
let opened = false;
let existingSession = window.name;
if (existingSession) {
existingSession = "?clientId=" + existingSession;
}
this.socket = new WebSocket(
`ws${window.location.protocol === "https:" ? "s" : ""}://${this.api_host}${this.api_base}/ws${existingSession}`
);
this.socket.binaryType = "arraybuffer";
this.socket.addEventListener("open", () => {
opened = true;
if (isReconnect) {
this.dispatchEvent(new CustomEvent("reconnected"));
}
});
this.socket.addEventListener("error", () => {
if (this.socket) this.socket.close();
if (!isReconnect && !opened) {
this.#pollQueue();
}
});
this.socket.addEventListener("close", () => {
setTimeout(() => {
this.socket = null;
this.#createSocket(true);
}, 300);
if (opened) {
this.dispatchEvent(new CustomEvent("status", { detail: null }));
this.dispatchEvent(new CustomEvent("reconnecting"));
}
});
this.socket.addEventListener("message", (event) => {
try {
if (event.data instanceof ArrayBuffer) {
const view = new DataView(event.data);
const eventType = view.getUint32(0);
const buffer = event.data.slice(4);
switch (eventType) {
case 1:
const view2 = new DataView(event.data);
const imageType = view2.getUint32(0)
let imageMime
switch (imageType) {
case 1:
default:
imageMime = "image/jpeg";
break;
case 2:
imageMime = "image/png"
}
const imageBlob = new Blob([buffer.slice(4)], { type: imageMime });
this.dispatchEvent(new CustomEvent("b_preview", { detail: imageBlob }));
break;
default:
throw new Error(`Unknown binary websocket message of type ${eventType}`);
}
}
else {
const msg = JSON.parse(event.data);
switch (msg.type) {
case "status":
if (msg.data.sid) {
this.clientId = msg.data.sid;
window.name = this.clientId; // use window name so it isnt reused when duplicating tabs
sessionStorage.setItem("clientId", this.clientId); // store in session storage so duplicate tab can load correct workflow
}
this.dispatchEvent(new CustomEvent("status", { detail: msg.data.status }));
break;
case "progress":
this.dispatchEvent(new CustomEvent("progress", { detail: msg.data }));
break;
case "executing":
this.dispatchEvent(new CustomEvent("executing", { detail: msg.data.node }));
break;
case "executed":
this.dispatchEvent(new CustomEvent("executed", { detail: msg.data }));
break;
case "execution_start":
this.dispatchEvent(new CustomEvent("execution_start", { detail: msg.data }));
break;
case "execution_success":
this.dispatchEvent(new CustomEvent("execution_success", { detail: msg.data }));
break;
case "execution_error":
this.dispatchEvent(new CustomEvent("execution_error", { detail: msg.data }));
break;
case "execution_cached":
this.dispatchEvent(new CustomEvent("execution_cached", { detail: msg.data }));
break;
default:
if (this.#registered.has(msg.type)) {
this.dispatchEvent(new CustomEvent(msg.type, { detail: msg.data }));
} else {
throw new Error(`Unknown message type ${msg.type}`);
}
}
}
} catch (error) {
console.warn("Unhandled message:", event.data, error);
}
});
}
/**
* Initialises sockets and realtime updates
*/
init() {
this.#createSocket();
}
/**
* Gets a list of extension urls
* @returns An array of script urls to import
*/
async getExtensions() {
const resp = await this.fetchApi("/extensions", { cache: "no-store" });
return await resp.json();
}
/**
* Gets a list of embedding names
* @returns An array of script urls to import
*/
async getEmbeddings() {
const resp = await this.fetchApi("/embeddings", { cache: "no-store" });
return await resp.json();
}
/**
* Loads node object definitions for the graph
* @returns The node definitions
*/
async getNodeDefs() {
const resp = await this.fetchApi("/object_info", { cache: "no-store" });
return await resp.json();
}
/**
*
* @param {number} number The index at which to queue the prompt, passing -1 will insert the prompt at the front of the queue
* @param {object} prompt The prompt data to queue
*/
async queuePrompt(number, { output, workflow }) {
const body = {
client_id: this.clientId,
prompt: output,
extra_data: { extra_pnginfo: { workflow } },
};
if (number === -1) {
body.front = true;
} else if (number != 0) {
body.number = number;
}
const res = await this.fetchApi("/prompt", {
method: "POST",
headers: {
"Content-Type": "application/json",
},
body: JSON.stringify(body),
});
if (res.status !== 200) {
throw {
response: await res.json(),
};
}
return await res.json();
}
/**
* Loads a list of items (queue or history)
* @param {string} type The type of items to load, queue or history
* @returns The items of the specified type grouped by their status
*/
async getItems(type) {
if (type === "queue") {
return this.getQueue();
}
return this.getHistory();
}
/**
* Gets the current state of the queue
* @returns The currently running and queued items
*/
async getQueue() {
try {
const res = await this.fetchApi("/queue");
const data = await res.json();
return {
// Running action uses a different endpoint for cancelling
Running: data.queue_running.map((prompt) => ({
prompt,
remove: { name: "Cancel", cb: () => api.interrupt() },
})),
Pending: data.queue_pending.map((prompt) => ({ prompt })),
};
} catch (error) {
console.error(error);
return { Running: [], Pending: [] };
}
}
/**
* Gets the prompt execution history
* @returns Prompt history including node outputs
*/
async getHistory(max_items=200) {
try {
const res = await this.fetchApi(`/history?max_items=${max_items}`);
return { History: Object.values(await res.json()) };
} catch (error) {
console.error(error);
return { History: [] };
}
}
/**
* Gets system & device stats
* @returns System stats such as python version, OS, per device info
*/
async getSystemStats() {
const res = await this.fetchApi("/system_stats");
return await res.json();
}
/**
* Sends a POST request to the API
* @param {*} type The endpoint to post to
* @param {*} body Optional POST data
*/
async #postItem(type, body) {
try {
await this.fetchApi("/" + type, {
method: "POST",
headers: {
"Content-Type": "application/json",
},
body: body ? JSON.stringify(body) : undefined,
});
} catch (error) {
console.error(error);
}
}
/**
* Deletes an item from the specified list
* @param {string} type The type of item to delete, queue or history
* @param {number} id The id of the item to delete
*/
async deleteItem(type, id) {
await this.#postItem(type, { delete: [id] });
}
/**
* Clears the specified list
* @param {string} type The type of list to clear, queue or history
*/
async clearItems(type) {
await this.#postItem(type, { clear: true });
}
/**
* Interrupts the execution of the running prompt
*/
async interrupt() {
await this.#postItem("interrupt", null);
}
/**
* Gets user configuration data and where data should be stored
* @returns { Promise<{ storage: "server" | "browser", users?: Promise<string, unknown>, migrated?: boolean }> }
*/
async getUserConfig() {
return (await this.fetchApi("/users")).json();
}
/**
* Creates a new user
* @param { string } username
* @returns The fetch response
*/
createUser(username) {
return this.fetchApi("/users", {
method: "POST",
headers: {
"Content-Type": "application/json",
},
body: JSON.stringify({ username }),
});
}
/**
* Gets all setting values for the current user
* @returns { Promise<string, unknown> } A dictionary of id -> value
*/
async getSettings() {
return (await this.fetchApi("/settings")).json();
}
/**
* Gets a setting for the current user
* @param { string } id The id of the setting to fetch
* @returns { Promise<unknown> } The setting value
*/
async getSetting(id) {
return (await this.fetchApi(`/settings/${encodeURIComponent(id)}`)).json();
}
/**
* Stores a dictionary of settings for the current user
* @param { Record<string, unknown> } settings Dictionary of setting id -> value to save
* @returns { Promise<void> }
*/
async storeSettings(settings) {
return this.fetchApi(`/settings`, {
method: "POST",
body: JSON.stringify(settings)
});
}
/**
* Stores a setting for the current user
* @param { string } id The id of the setting to update
* @param { unknown } value The value of the setting
* @returns { Promise<void> }
*/
async storeSetting(id, value) {
return this.fetchApi(`/settings/${encodeURIComponent(id)}`, {
method: "POST",
body: JSON.stringify(value)
});
}
/**
* Gets a user data file for the current user
* @param { string } file The name of the userdata file to load
* @param { RequestInit } [options]
* @returns { Promise<Response> } The fetch response object
*/
async getUserData(file, options) {
return this.fetchApi(`/userdata/${encodeURIComponent(file)}`, options);
}
/**
* Stores a user data file for the current user
* @param { string } file The name of the userdata file to save
* @param { unknown } data The data to save to the file
* @param { RequestInit & { overwrite?: boolean, stringify?: boolean, throwOnError?: boolean } } [options]
* @returns { Promise<Response> }
*/
async storeUserData(file, data, options = { overwrite: true, stringify: true, throwOnError: true }) {
const resp = await this.fetchApi(`/userdata/${encodeURIComponent(file)}?overwrite=${options?.overwrite}`, {
method: "POST",
body: options?.stringify ? JSON.stringify(data) : data,
...options,
});
if (resp.status !== 200 && options?.throwOnError !== false) {
throw new Error(`Error storing user data file '${file}': ${resp.status} ${(await resp).statusText}`);
}
return resp;
}
/**
* Deletes a user data file for the current user
* @param { string } file The name of the userdata file to delete
*/
async deleteUserData(file) {
const resp = await this.fetchApi(`/userdata/${encodeURIComponent(file)}`, {
method: "DELETE",
});
if (resp.status !== 204) {
throw new Error(`Error removing user data file '${file}': ${resp.status} ${(resp).statusText}`);
}
}
/**
* Move a user data file for the current user
* @param { string } source The userdata file to move
* @param { string } dest The destination for the file
*/
async moveUserData(source, dest, options = { overwrite: false }) {
const resp = await this.fetchApi(`/userdata/${encodeURIComponent(source)}/move/${encodeURIComponent(dest)}?overwrite=${options?.overwrite}`, {
method: "POST",
});
return resp;
}
/**
* @overload
* Lists user data files for the current user
* @param { string } dir The directory in which to list files
* @param { boolean } [recurse] If the listing should be recursive
* @param { true } [split] If the paths should be split based on the os path separator
* @returns { Promise<string[][]>> } The list of split file paths in the format [fullPath, ...splitPath]
*/
/**
* @overload
* Lists user data files for the current user
* @param { string } dir The directory in which to list files
* @param { boolean } [recurse] If the listing should be recursive
* @param { false | undefined } [split] If the paths should be split based on the os path separator
* @returns { Promise<string[]>> } The list of files
*/
async listUserData(dir, recurse, split) {
const resp = await this.fetchApi(
`/userdata?${new URLSearchParams({
recurse,
dir,
split,
})}`
);
if (resp.status === 404) return [];
if (resp.status !== 200) {
throw new Error(`Error getting user data list '${dir}': ${resp.status} ${resp.statusText}`);
}
return resp.json();
}
}
export const api = new ComfyApi();
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