410 lines
12 KiB
JavaScript
410 lines
12 KiB
JavaScript
import { app } from '../../../scripts/app.js'
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import { api } from '../../../scripts/api.js'
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import { ComfyWidgets } from '../../../scripts/widgets.js'
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// 和python实现一样
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function run (mutable_prompt, immutable_prompt) {
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// Split the text into an array of words
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const words1 = mutable_prompt.split('\n')
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// Split the text into an array of words
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const words2 = immutable_prompt.split('\n')
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const prompts = []
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for (let i = 0; i < words1.length; i++) {
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words1[i] = words1[i].trim()
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for (let j = 0; j < words2.length; j++) {
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words2[j] = words2[j].trim()
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if (words2[j] && words1[i]) {
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prompts.push(words2[j].replaceAll('``', words1[i]))
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}
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}
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}
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return prompts
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}
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// 更新ui，计算prompt的组合结果
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const updateUI = node => {
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const mutable_prompt_w = node.widgets.filter(
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w => w.name === 'mutable_prompt'
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)[0]
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mutable_prompt_w.inputEl.title = 'Enter keywords, one per line'
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const immutable_prompt_w = node.widgets.filter(
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w => w.name === 'immutable_prompt'
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)[0]
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immutable_prompt_w.inputEl.title =
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'Enter prompts, one per line, variables represented by ``'
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const max_count = node.widgets.filter(w => w.name === 'max_count')[0]
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let prompts = run(mutable_prompt_w.value, immutable_prompt_w.value)
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prompts = prompts.slice(0, max_count.value)
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max_count.value = prompts.length
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// 如果已经存在,删除
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const pw = node.widgets.filter(w => w.name === 'prompts')[0]
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if (pw) {
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// node.widgets[pos].onRemove?.();
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pw.value = prompts.join('\n\n')
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pw.inputEl.title = `Total of ${prompts.length} prompts`
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} else {
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// 动态添加
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const w = ComfyWidgets.STRING(
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node,
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'prompts',
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['STRING', { multiline: true }],
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app
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).widget
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w.inputEl.readOnly = true
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w.inputEl.style.opacity = 0.6
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w.value = prompts.join('\n\n')
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w.inputEl.title = `Total of ${prompts.length} prompts`
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}
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// 移除无关的widget
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// for (let i = 0; i < node.widgets.length; i++) {
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// console.log(node.widgets[i]?.name)
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// if(node.widgets[i]&&!['mutable_prompt','immutable_prompt','max_count','prompts'].includes(node.widgets[i].name)) node.widgets[i].onRemove?.();
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// }
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// console.log(node.widgets.length,node.size);
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node.widgets.length = 5
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node.onResize?.(node.size)
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}
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const exportGraph = () => {
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const graph = app.graph
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var clipboard_info = {
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nodes: [],
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links: []
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}
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var index = 0
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var selected_nodes_array = []
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for (var i in graph._nodes_in_order) {
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var node = graph._nodes_in_order[i]
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if (node.clonable === false) continue
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node._relative_id = index
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selected_nodes_array.push(node)
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index += 1
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}
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for (var i = 0; i < selected_nodes_array.length; ++i) {
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var node = selected_nodes_array[i]
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var cloned = node.clone()
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if (!cloned) {
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console.warn('node type not found: ' + node.type)
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continue
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}
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let nc = {}
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let n = cloned.serialize()
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for (const key in n) {
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if (
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[
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'type',
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'pos',
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'size',
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'flags',
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'order',
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'mode',
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'inputs',
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'outputs',
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'properties',
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'widgets_values'
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].includes(key)
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) {
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nc[key] = n[key]
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}
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}
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clipboard_info.nodes.push(nc)
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if (node.inputs && node.inputs.length) {
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for (var j = 0; j < node.inputs.length; ++j) {
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var input = node.inputs[j]
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if (!input || input.link == null) {
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continue
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}
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var link_info = graph.links[input.link]
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if (!link_info) {
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continue
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}
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var target_node = graph.getNodeById(link_info.origin_id)
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if (!target_node) {
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continue
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}
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clipboard_info.links.push([
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target_node._relative_id,
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link_info.origin_slot, //j,
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node._relative_id,
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link_info.target_slot,
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target_node.id
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])
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}
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}
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}
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localStorage.setItem('_Mixlab_clipboard', JSON.stringify(clipboard_info))
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return clipboard_info
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}
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const my = {
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nodes: [
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{
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type: 'LoadImage',
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pos: [719.5130480797907, 172.9437092123179],
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size: { 0: 315, 1: 314 },
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flags: {},
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order: 0,
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mode: 0,
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outputs: [
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{ name: 'IMAGE', type: 'IMAGE', links: [], shape: 3 },
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{ name: 'MASK', type: 'MASK', links: null, shape: 3 }
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],
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properties: { 'Node name for S&R': 'LoadImage' },
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widgets_values: ['00204211b3c71288c12ed66516a1a20a.jpg', 'image']
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},
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{
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type: 'ControlNetLoader',
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pos: [1199.5130480797907, -331.0562907876821],
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size: { 0: 415.221923828125, 1: 58.84859848022461 },
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flags: {},
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order: 1,
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mode: 0,
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outputs: [
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{ name: 'CONTROL_NET', type: 'CONTROL_NET', links: [], shape: 3 }
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],
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properties: { 'Node name for S&R': 'ControlNetLoader' },
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widgets_values: ['control_v11p_sd15_canny.pth']
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},
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{
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type: 'ControlNetLoader',
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pos: [1204.5130480797907, -169.0562907876821],
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size: { 0: 415.221923828125, 1: 58.84859848022461 },
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flags: {},
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order: 2,
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mode: 0,
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outputs: [
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{ name: 'CONTROL_NET', type: 'CONTROL_NET', links: [], shape: 3 }
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],
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properties: { 'Node name for S&R': 'ControlNetLoader' },
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widgets_values: ['control_v11f1p_sd15_depth.pth']
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},
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{
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type: 'ControlNetLoader',
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pos: [1206.5130480797907, -20.056290787682087],
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size: { 0: 415.221923828125, 1: 58.84859848022461 },
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flags: {},
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order: 3,
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mode: 0,
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outputs: [
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{ name: 'CONTROL_NET', type: 'CONTROL_NET', links: [], shape: 3 }
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],
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properties: { 'Node name for S&R': 'ControlNetLoader' },
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widgets_values: ['t2iadapter_seg-fp16.safetensors']
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},
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{
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type: 'ControlNetLoader',
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pos: [1209.5130480797907, 125.94370921231791],
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size: { 0: 415.221923828125, 1: 58.84859848022461 },
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flags: {},
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order: 4,
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mode: 0,
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outputs: [
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{ name: 'CONTROL_NET', type: 'CONTROL_NET', links: [], shape: 3 }
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],
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properties: { 'Node name for S&R': 'ControlNetLoader' },
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widgets_values: ['control_v11p_sd15_openpose.pth']
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},
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{
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type: 'ControlNetLoader',
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pos: [1214.5130480797907, 293.9437092123179],
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size: { 0: 415.221923828125, 1: 58.84859848022461 },
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flags: {},
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order: 5,
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mode: 0,
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outputs: [
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{ name: 'CONTROL_NET', type: 'CONTROL_NET', links: [], shape: 3 }
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],
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properties: { 'Node name for S&R': 'ControlNetLoader' },
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widgets_values: ['control_v11e_sd15_ip2p.safetensors']
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},
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{
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type: 'ControlNetLoader',
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pos: [1212.5130480797907, 461.9437092123179],
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size: { 0: 415.221923828125, 1: 58.84859848022461 },
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flags: {},
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order: 6,
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mode: 0,
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outputs: [
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{ name: 'CONTROL_NET', type: 'CONTROL_NET', links: [], shape: 3 }
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],
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properties: { 'Node name for S&R': 'ControlNetLoader' },
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widgets_values: ['control_v11p_sd15_inpaint.pth']
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},
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{
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type: 'ControlNetLoader',
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pos: [1216.5130480797907, 636.9437092123179],
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size: { 0: 415.221923828125, 1: 58.84859848022461 },
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flags: {},
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order: 7,
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mode: 0,
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outputs: [
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{ name: 'CONTROL_NET', type: 'CONTROL_NET', links: [], shape: 3 }
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],
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properties: { 'Node name for S&R': 'ControlNetLoader' },
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widgets_values: ['control_v11f1e_sd15_tile.bin']
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},
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{
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type: 'ControlNetLoader',
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pos: [1227.5130480797907, 804.9437092123179],
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size: { 0: 415.221923828125, 1: 58.84859848022461 },
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flags: {},
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order: 8,
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mode: 0,
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outputs: [
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{ name: 'CONTROL_NET', type: 'CONTROL_NET', links: [], shape: 3 }
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],
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properties: { 'Node name for S&R': 'ControlNetLoader' },
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widgets_values: ['control_v11f1e_sd15_tile.bin']
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},
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{
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type: 'ControlNetApplyAdvanced',
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pos: [1816, 94],
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size: { 0: 315, 1: 166 },
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flags: {},
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order: 9,
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mode: 0,
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inputs: [
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{ name: 'positive', type: 'CONDITIONING', link: null },
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{ name: 'negative', type: 'CONDITIONING', link: null },
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{ name: 'control_net', type: 'CONTROL_NET', link: null, slot_index: 2 },
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{ name: 'image', type: 'IMAGE', link: null, slot_index: 3 }
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],
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outputs: [
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{ name: 'positive', type: 'CONDITIONING', links: null, shape: 3 },
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{ name: 'negative', type: 'CONDITIONING', links: null, shape: 3 }
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],
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properties: { 'Node name for S&R': 'ControlNetApplyAdvanced' },
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widgets_values: [1, 0, 1]
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}
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],
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links: [
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[1, 0, 9, 2, 2],
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[0, 0, 9, 3, 1]
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]
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}
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// 添加workflow
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const importWorkflow = (my) => {
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localStorage.setItem('litegrapheditor_clipboard', JSON.stringify(my))
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app.canvas.pasteFromClipboard()
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}
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const node = {
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name: 'RandomPrompt',
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async setup (a) {
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for (const node of app.graph._nodes) {
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if (node.comfyClass === 'RandomPrompt') {
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console.log('#setup', node)
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updateUI(node)
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}
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}
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console.log('[logging]', 'loaded graph node: ', exportGraph(app.graph))
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},
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loadedGraphNode (node, app) {
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// Fires for each node when loading/dragging/etc a workflow json or png
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// If you break something in the backend and want to patch workflows in the frontend
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// This is the place to do this
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// console.log("[logging]", "loaded graph node: ", exportGraph(node.graph));
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},
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async nodeCreated (node) {
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if (node.comfyClass === 'RandomPrompt') {
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updateUI(node)
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}
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if (node.comfyClass === 'RunWorkflow') {
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const pw = node.widgets.filter(w => w.name === 'workflow')[0]
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console.log('nodeCreated', pw)
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// if (pw) {
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// // node.widgets[pos].onRemove?.();
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// pw.value = prompts.join('\n\n');
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// // pw.inputEl=document.createElement('input');
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// }
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// node.widgets.length = 1;
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node.onResize?.(node.size)
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}
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},
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async beforeRegisterNodeDef (nodeType, nodeData, app) {
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// 注册节点前，可以修改节点的数据
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// 可以获取得到其他节点数据
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// 汉化
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// app.graph._nodes // title ='123'
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if (nodeData.name === 'SaveTransparentImage') {
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const onExecuted = nodeType.prototype.onExecuted
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nodeType.prototype.onExecuted = function (message) {
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const r = onExecuted?.apply?.(this, arguments)
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console.log('executed', message)
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const { image_path } = message
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if (image_path) {
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}
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return r
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}
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}
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if (nodeData.name === 'RandomPrompt') {
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const onExecuted = nodeType.prototype.onExecuted
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nodeType.prototype.onExecuted = function (message) {
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const r = onExecuted?.apply?.(this, arguments)
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let prompts = message.prompts
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console.log('executed', message)
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// console.log('#RandomPrompt', this.widgets)
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const pw = this.widgets.filter(w => w.name === 'prompts')[0]
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if (pw) {
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// node.widgets[pos].onRemove?.();
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pw.value = prompts.join('\n\n')
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pw.inputEl.title = `Total of ${prompts.length} prompts`
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} else {
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// 动态添加
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const w = ComfyWidgets.STRING(
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node,
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'prompts',
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['STRING', { multiline: true }],
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app
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).widget
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w.inputEl.readOnly = true
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w.inputEl.style.opacity = 0.6
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w.value = prompts.join('\n\n')
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w.inputEl.title = `Total of ${prompts.length} prompts`
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}
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this.widgets.length = 5
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this.onResize?.(this.size)
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return r
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}
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}
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if (nodeData.name === 'RunWorkflow') {
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const onExecuted = nodeType.prototype.onExecuted
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nodeType.prototype.onExecuted = function (message) {
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const r = onExecuted?.apply?.(this, arguments)
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return r
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}
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}
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}
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}
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app.registerExtension(node)
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