jaidaken
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Includes 30 custom nodes committed directly, 7 Civitai-exclusive loras stored via Git LFS, and a setup script that installs all dependencies and downloads HuggingFace-hosted models on vast.ai. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
393 lines
17 KiB
JavaScript
393 lines
17 KiB
JavaScript
import { rgthreeApi } from "./rgthree_api.js";
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const api = {
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async getEmbeddings() {
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const resp = await rgthreeApi.fetchComfyApi('/embeddings', { cache: 'no-store' });
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return await resp.json();
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}
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};
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function getFromPngBuffer(buffer) {
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const pngData = new Uint8Array(buffer);
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const dataView = new DataView(pngData.buffer);
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if (dataView.getUint32(0) !== 0x89504e47) {
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console.error('Not a valid PNG file');
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return;
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}
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let offset = 8;
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let txt_chunks = {};
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while (offset < pngData.length) {
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const length = dataView.getUint32(offset);
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const type = String.fromCharCode(...pngData.slice(offset + 4, offset + 8));
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if (type === 'tEXt' || type == 'comf' || type === 'iTXt') {
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let keyword_end = offset + 8;
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while (pngData[keyword_end] !== 0) {
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keyword_end++;
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}
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const keyword = String.fromCharCode(...pngData.slice(offset + 8, keyword_end));
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const contentArraySegment = pngData.slice(keyword_end + 1, offset + 8 + length);
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const contentJson = new TextDecoder('utf-8').decode(contentArraySegment);
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txt_chunks[keyword] = contentJson;
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}
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offset += 12 + length;
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}
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return txt_chunks;
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}
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function getFromPngFile(file) {
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return new Promise((r) => {
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const reader = new FileReader();
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reader.onload = (event) => {
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r(getFromPngBuffer(event.target.result));
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};
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reader.readAsArrayBuffer(file);
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});
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}
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function parseExifData(exifData) {
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const isLittleEndian = String.fromCharCode(...exifData.slice(0, 2)) === 'II';
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function readInt(offset, isLittleEndian, length) {
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let arr = exifData.slice(offset, offset + length);
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if (length === 2) {
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return new DataView(arr.buffer, arr.byteOffset, arr.byteLength).getUint16(0, isLittleEndian);
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}
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else if (length === 4) {
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return new DataView(arr.buffer, arr.byteOffset, arr.byteLength).getUint32(0, isLittleEndian);
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}
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throw new Error('Shouldn\'t get here.');
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}
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const ifdOffset = readInt(4, isLittleEndian, 4);
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function parseIFD(offset) {
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const numEntries = readInt(offset, isLittleEndian, 2);
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const result = {};
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for (let i = 0; i < numEntries; i++) {
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const entryOffset = offset + 2 + i * 12;
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const tag = readInt(entryOffset, isLittleEndian, 2);
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const type = readInt(entryOffset + 2, isLittleEndian, 2);
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const numValues = readInt(entryOffset + 4, isLittleEndian, 4);
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const valueOffset = readInt(entryOffset + 8, isLittleEndian, 4);
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let value;
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if (type === 2) {
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value = new TextDecoder('utf-8').decode(exifData.subarray(valueOffset, valueOffset + numValues - 1));
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}
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result[tag] = value;
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}
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return result;
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}
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const ifdData = parseIFD(ifdOffset);
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return ifdData;
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}
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function splitValues(input) {
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var output = {};
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for (var key in input) {
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var value = input[key];
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var splitValues = value.split(':', 2);
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output[splitValues[0]] = splitValues[1];
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}
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return output;
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}
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export function getPngMetadata(file) {
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return getFromPngFile(file);
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}
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export function getWebpMetadata(file) {
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return new Promise((r) => {
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const reader = new FileReader();
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reader.onload = (event) => {
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const webp = new Uint8Array(event.target.result);
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const dataView = new DataView(webp.buffer);
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if (dataView.getUint32(0) !== 0x52494646 ||
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dataView.getUint32(8) !== 0x57454250) {
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console.error('Not a valid WEBP file');
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r({});
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return;
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}
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let offset = 12;
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let txt_chunks = {};
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while (offset < webp.length) {
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const chunk_length = dataView.getUint32(offset + 4, true);
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const chunk_type = String.fromCharCode(...webp.slice(offset, offset + 4));
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if (chunk_type === 'EXIF') {
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if (String.fromCharCode(...webp.slice(offset + 8, offset + 8 + 6)) ==
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'Exif\0\0') {
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offset += 6;
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}
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let data = parseExifData(webp.slice(offset + 8, offset + 8 + chunk_length));
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for (var key in data) {
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const value = data[key];
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if (typeof value === 'string') {
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const index = value.indexOf(':');
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txt_chunks[value.slice(0, index)] = value.slice(index + 1);
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}
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}
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break;
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}
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offset += 8 + chunk_length;
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}
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r(txt_chunks);
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};
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reader.readAsArrayBuffer(file);
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});
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}
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export function getLatentMetadata(file) {
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return new Promise((r) => {
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const reader = new FileReader();
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reader.onload = (event) => {
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const safetensorsData = new Uint8Array(event.target.result);
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const dataView = new DataView(safetensorsData.buffer);
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let header_size = dataView.getUint32(0, true);
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let offset = 8;
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let header = JSON.parse(new TextDecoder().decode(safetensorsData.slice(offset, offset + header_size)));
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r(header.__metadata__);
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};
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var slice = file.slice(0, 1024 * 1024 * 4);
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reader.readAsArrayBuffer(slice);
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});
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}
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export async function importA1111(graph, parameters) {
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const p = parameters.lastIndexOf('\nSteps:');
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if (p > -1) {
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const embeddings = await api.getEmbeddings();
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const opts = parameters
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.substr(p)
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.split('\n')[1]
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.match(new RegExp('\\s*([^:]+:\\s*([^"\\{].*?|".*?"|\\{.*?\\}))\\s*(,|$)', 'g'))
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.reduce((p, n) => {
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const s = n.split(':');
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if (s[1].endsWith(',')) {
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s[1] = s[1].substr(0, s[1].length - 1);
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}
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p[s[0].trim().toLowerCase()] = s[1].trim();
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return p;
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}, {});
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const p2 = parameters.lastIndexOf('\nNegative prompt:', p);
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if (p2 > -1) {
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let positive = parameters.substr(0, p2).trim();
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let negative = parameters.substring(p2 + 18, p).trim();
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const ckptNode = LiteGraph.createNode('CheckpointLoaderSimple');
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const clipSkipNode = LiteGraph.createNode('CLIPSetLastLayer');
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const positiveNode = LiteGraph.createNode('CLIPTextEncode');
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const negativeNode = LiteGraph.createNode('CLIPTextEncode');
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const samplerNode = LiteGraph.createNode('KSampler');
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const imageNode = LiteGraph.createNode('EmptyLatentImage');
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const vaeNode = LiteGraph.createNode('VAEDecode');
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const vaeLoaderNode = LiteGraph.createNode('VAELoader');
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const saveNode = LiteGraph.createNode('SaveImage');
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let hrSamplerNode = null;
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let hrSteps = null;
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const ceil64 = (v) => Math.ceil(v / 64) * 64;
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const getWidget = (node, name) => {
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return node.widgets.find((w) => w.name === name);
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};
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const setWidgetValue = (node, name, value, isOptionPrefix) => {
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const w = getWidget(node, name);
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if (isOptionPrefix) {
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const o = w.options.values.find((w) => w.startsWith(value));
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if (o) {
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w.value = o;
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}
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else {
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console.warn(`Unknown value '${value}' for widget '${name}'`, node);
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w.value = value;
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}
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}
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else {
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w.value = value;
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}
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};
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const createLoraNodes = (clipNode, text, prevClip, prevModel) => {
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const loras = [];
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text = text.replace(/<lora:([^:]+:[^>]+)>/g, function (m, c) {
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const s = c.split(':');
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const weight = parseFloat(s[1]);
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if (isNaN(weight)) {
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console.warn('Invalid LORA', m);
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}
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else {
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loras.push({ name: s[0], weight });
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}
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return '';
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});
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for (const l of loras) {
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const loraNode = LiteGraph.createNode('LoraLoader');
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graph.add(loraNode);
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setWidgetValue(loraNode, 'lora_name', l.name, true);
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setWidgetValue(loraNode, 'strength_model', l.weight);
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setWidgetValue(loraNode, 'strength_clip', l.weight);
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prevModel.node.connect(prevModel.index, loraNode, 0);
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prevClip.node.connect(prevClip.index, loraNode, 1);
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prevModel = { node: loraNode, index: 0 };
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prevClip = { node: loraNode, index: 1 };
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}
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prevClip.node.connect(1, clipNode, 0);
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prevModel.node.connect(0, samplerNode, 0);
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if (hrSamplerNode) {
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prevModel.node.connect(0, hrSamplerNode, 0);
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}
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return { text, prevModel, prevClip };
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};
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const replaceEmbeddings = (text) => {
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if (!embeddings.length)
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return text;
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return text.replaceAll(new RegExp('\\b(' +
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embeddings
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.map((e) => e.replace(/[.*+?^${}()|[\]\\]/g, '\\$&'))
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.join('\\b|\\b') +
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')\\b', 'ig'), 'embedding:$1');
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};
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const popOpt = (name) => {
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const v = opts[name];
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delete opts[name];
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return v;
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};
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graph.clear();
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graph.add(ckptNode);
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graph.add(clipSkipNode);
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graph.add(positiveNode);
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graph.add(negativeNode);
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graph.add(samplerNode);
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graph.add(imageNode);
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graph.add(vaeNode);
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graph.add(vaeLoaderNode);
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graph.add(saveNode);
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ckptNode.connect(1, clipSkipNode, 0);
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clipSkipNode.connect(0, positiveNode, 0);
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clipSkipNode.connect(0, negativeNode, 0);
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ckptNode.connect(0, samplerNode, 0);
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positiveNode.connect(0, samplerNode, 1);
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negativeNode.connect(0, samplerNode, 2);
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imageNode.connect(0, samplerNode, 3);
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vaeNode.connect(0, saveNode, 0);
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samplerNode.connect(0, vaeNode, 0);
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vaeLoaderNode.connect(0, vaeNode, 1);
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const handlers = {
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model(v) {
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setWidgetValue(ckptNode, 'ckpt_name', v, true);
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},
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vae(v) {
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setWidgetValue(vaeLoaderNode, 'vae_name', v, true);
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},
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'cfg scale'(v) {
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setWidgetValue(samplerNode, 'cfg', +v);
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},
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'clip skip'(v) {
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setWidgetValue(clipSkipNode, 'stop_at_clip_layer', -v);
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},
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sampler(v) {
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let name = v.toLowerCase().replace('++', 'pp').replaceAll(' ', '_');
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if (name.includes('karras')) {
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name = name.replace('karras', '').replace(/_+$/, '');
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setWidgetValue(samplerNode, 'scheduler', 'karras');
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}
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else {
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setWidgetValue(samplerNode, 'scheduler', 'normal');
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}
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const w = getWidget(samplerNode, 'sampler_name');
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const o = w.options.values.find((w) => w === name || w === 'sample_' + name);
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if (o) {
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setWidgetValue(samplerNode, 'sampler_name', o);
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}
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},
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size(v) {
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const wxh = v.split('x');
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const w = ceil64(+wxh[0]);
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const h = ceil64(+wxh[1]);
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const hrUp = popOpt('hires upscale');
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const hrSz = popOpt('hires resize');
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hrSteps = popOpt('hires steps');
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let hrMethod = popOpt('hires upscaler');
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setWidgetValue(imageNode, 'width', w);
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setWidgetValue(imageNode, 'height', h);
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if (hrUp || hrSz) {
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let uw, uh;
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if (hrUp) {
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uw = w * hrUp;
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uh = h * hrUp;
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}
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else {
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const s = hrSz.split('x');
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uw = +s[0];
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uh = +s[1];
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}
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let upscaleNode;
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let latentNode;
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if (hrMethod.startsWith('Latent')) {
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latentNode = upscaleNode = LiteGraph.createNode('LatentUpscale');
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graph.add(upscaleNode);
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samplerNode.connect(0, upscaleNode, 0);
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switch (hrMethod) {
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case 'Latent (nearest-exact)':
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hrMethod = 'nearest-exact';
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break;
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}
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setWidgetValue(upscaleNode, 'upscale_method', hrMethod, true);
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}
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else {
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const decode = LiteGraph.createNode('VAEDecodeTiled');
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graph.add(decode);
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samplerNode.connect(0, decode, 0);
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vaeLoaderNode.connect(0, decode, 1);
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const upscaleLoaderNode = LiteGraph.createNode('UpscaleModelLoader');
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graph.add(upscaleLoaderNode);
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setWidgetValue(upscaleLoaderNode, 'model_name', hrMethod, true);
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const modelUpscaleNode = LiteGraph.createNode('ImageUpscaleWithModel');
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graph.add(modelUpscaleNode);
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decode.connect(0, modelUpscaleNode, 1);
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upscaleLoaderNode.connect(0, modelUpscaleNode, 0);
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upscaleNode = LiteGraph.createNode('ImageScale');
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graph.add(upscaleNode);
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modelUpscaleNode.connect(0, upscaleNode, 0);
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const vaeEncodeNode = (latentNode =
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LiteGraph.createNode('VAEEncodeTiled'));
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graph.add(vaeEncodeNode);
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upscaleNode.connect(0, vaeEncodeNode, 0);
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vaeLoaderNode.connect(0, vaeEncodeNode, 1);
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}
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setWidgetValue(upscaleNode, 'width', ceil64(uw));
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setWidgetValue(upscaleNode, 'height', ceil64(uh));
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hrSamplerNode = LiteGraph.createNode('KSampler');
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graph.add(hrSamplerNode);
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ckptNode.connect(0, hrSamplerNode, 0);
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positiveNode.connect(0, hrSamplerNode, 1);
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negativeNode.connect(0, hrSamplerNode, 2);
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latentNode.connect(0, hrSamplerNode, 3);
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hrSamplerNode.connect(0, vaeNode, 0);
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}
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},
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steps(v) {
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setWidgetValue(samplerNode, 'steps', +v);
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},
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seed(v) {
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setWidgetValue(samplerNode, 'seed', +v);
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}
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};
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for (const opt in opts) {
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if (opt in handlers) {
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handlers[opt](popOpt(opt));
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}
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}
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if (hrSamplerNode) {
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setWidgetValue(hrSamplerNode, 'steps', hrSteps ? +hrSteps : getWidget(samplerNode, 'steps').value);
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setWidgetValue(hrSamplerNode, 'cfg', getWidget(samplerNode, 'cfg').value);
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setWidgetValue(hrSamplerNode, 'scheduler', getWidget(samplerNode, 'scheduler').value);
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setWidgetValue(hrSamplerNode, 'sampler_name', getWidget(samplerNode, 'sampler_name').value);
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setWidgetValue(hrSamplerNode, 'denoise', +(popOpt('denoising strength') || '1'));
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}
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let n = createLoraNodes(positiveNode, positive, { node: clipSkipNode, index: 0 }, { node: ckptNode, index: 0 });
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positive = n.text;
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n = createLoraNodes(negativeNode, negative, n.prevClip, n.prevModel);
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negative = n.text;
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setWidgetValue(positiveNode, 'text', replaceEmbeddings(positive));
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setWidgetValue(negativeNode, 'text', replaceEmbeddings(negative));
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graph.arrange();
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for (const opt of [
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'model hash',
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'ensd',
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'version',
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'vae hash',
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'ti hashes',
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'lora hashes',
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'hashes'
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]) {
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delete opts[opt];
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}
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console.warn('Unhandled parameters:', opts);
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}
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}
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}
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