v3.1.3: Fix SPA redeclaration errors, update docker-compose for cookies
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This commit is contained in:
KV-Tube Deployer
parent
663ef6ba44
commit
79f69772a0
3 changed files with 304 additions and 295 deletions
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@ -14,11 +14,14 @@ services:
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volumes:
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# Persist data (Easy setup: Just maps a folder)
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- ./data:/app/data
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# Cookies file for YouTube (Required for NAS/Server to fix "Transcript not available")
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- ./data/cookies.txt:/app/cookies.txt
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# Local videos folder (Optional)
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# - ./videos:/app/youtube_downloads
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environment:
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- PYTHONUNBUFFERED=1
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- FLASK_ENV=production
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- COOKIES_FILE=/app/cookies.txt
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healthcheck:
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test: [ "CMD", "curl", "-f", "http://localhost:5000/" ]
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interval: 30s
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587
static/js/webllm-service.js
Normal file → Executable file
587
static/js/webllm-service.js
Normal file → Executable file
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@ -3,338 +3,343 @@
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* Uses MLC's WebLLM for on-device AI inference via WebGPU
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*/
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class WebLLMService {
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constructor() {
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this.engine = null;
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this.isLoading = false;
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this.loadProgress = 0;
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this.currentModel = null;
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// Guard against redeclaration on SPA navigation
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if (typeof WebLLMService === 'undefined') {
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// Model configurations - Qwen2 chosen for Vietnamese support
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this.models = {
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'qwen2-0.5b': 'Qwen2-0.5B-Instruct-q4f16_1-MLC',
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'phi-3.5-mini': 'Phi-3.5-mini-instruct-q4f16_1-MLC',
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'smollm2': 'SmolLM2-360M-Instruct-q4f16_1-MLC'
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};
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class WebLLMService {
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constructor() {
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this.engine = null;
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this.isLoading = false;
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this.loadProgress = 0;
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this.currentModel = null;
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// Default to lightweight Qwen2 for Vietnamese support
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this.selectedModel = 'qwen2-0.5b';
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// Callbacks
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this.onProgressCallback = null;
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this.onReadyCallback = null;
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this.onErrorCallback = null;
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}
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/**
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* Check if WebGPU is supported
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*/
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static isSupported() {
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return 'gpu' in navigator;
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}
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/**
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* Initialize WebLLM with selected model
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* @param {string} modelKey - Model key from this.models
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* @param {function} onProgress - Progress callback (percent, status)
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* @returns {Promise<boolean>}
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*/
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async init(modelKey = null, onProgress = null) {
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if (!WebLLMService.isSupported()) {
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console.warn('WebGPU not supported in this browser');
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if (this.onErrorCallback) {
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this.onErrorCallback('WebGPU not supported. Using server-side AI.');
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}
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return false;
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}
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if (this.engine && this.currentModel === (modelKey || this.selectedModel)) {
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console.log('WebLLM already initialized with this model');
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return true;
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}
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this.isLoading = true;
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this.onProgressCallback = onProgress;
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try {
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// Dynamic import of WebLLM
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const webllm = await import('https://esm.run/@mlc-ai/web-llm');
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const modelId = this.models[modelKey || this.selectedModel];
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console.log('Loading WebLLM model:', modelId);
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// Progress callback wrapper
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const initProgressCallback = (progress) => {
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this.loadProgress = Math.round(progress.progress * 100);
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const status = progress.text || 'Loading model...';
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console.log(`WebLLM: ${this.loadProgress}% - ${status}`);
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if (this.onProgressCallback) {
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this.onProgressCallback(this.loadProgress, status);
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}
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// Model configurations - Qwen2 chosen for Vietnamese support
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this.models = {
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'qwen2-0.5b': 'Qwen2-0.5B-Instruct-q4f16_1-MLC',
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'phi-3.5-mini': 'Phi-3.5-mini-instruct-q4f16_1-MLC',
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'smollm2': 'SmolLM2-360M-Instruct-q4f16_1-MLC'
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};
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// Create engine
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this.engine = await webllm.CreateMLCEngine(modelId, {
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initProgressCallback: initProgressCallback
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});
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// Default to lightweight Qwen2 for Vietnamese support
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this.selectedModel = 'qwen2-0.5b';
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this.currentModel = modelKey || this.selectedModel;
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this.isLoading = false;
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this.loadProgress = 100;
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// Callbacks
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this.onProgressCallback = null;
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this.onReadyCallback = null;
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this.onErrorCallback = null;
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}
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console.log('WebLLM ready!');
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if (this.onReadyCallback) {
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this.onReadyCallback();
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/**
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* Check if WebGPU is supported
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*/
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static isSupported() {
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return 'gpu' in navigator;
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}
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/**
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* Initialize WebLLM with selected model
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* @param {string} modelKey - Model key from this.models
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* @param {function} onProgress - Progress callback (percent, status)
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* @returns {Promise<boolean>}
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*/
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async init(modelKey = null, onProgress = null) {
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if (!WebLLMService.isSupported()) {
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console.warn('WebGPU not supported in this browser');
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if (this.onErrorCallback) {
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this.onErrorCallback('WebGPU not supported. Using server-side AI.');
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}
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return false;
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}
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return true;
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} catch (error) {
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console.error('WebLLM initialization failed:', error);
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this.isLoading = false;
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if (this.onErrorCallback) {
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this.onErrorCallback(error.message);
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if (this.engine && this.currentModel === (modelKey || this.selectedModel)) {
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console.log('WebLLM already initialized with this model');
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return true;
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}
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return false;
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}
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}
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this.isLoading = true;
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this.onProgressCallback = onProgress;
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/**
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* Check if engine is ready
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*/
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isReady() {
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return this.engine !== null && !this.isLoading;
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}
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try {
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// Dynamic import of WebLLM
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const webllm = await import('https://esm.run/@mlc-ai/web-llm');
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/**
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* Summarize text using local AI
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* @param {string} text - Text to summarize
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* @param {string} language - Output language ('en' or 'vi')
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* @returns {Promise<string>}
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*/
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async summarize(text, language = 'en') {
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if (!this.isReady()) {
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throw new Error('WebLLM not ready. Call init() first.');
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}
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const modelId = this.models[modelKey || this.selectedModel];
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console.log('Loading WebLLM model:', modelId);
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// Truncate text to avoid token limits
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const maxChars = 4000;
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if (text.length > maxChars) {
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text = text.substring(0, maxChars) + '...';
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}
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// Progress callback wrapper
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const initProgressCallback = (progress) => {
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this.loadProgress = Math.round(progress.progress * 100);
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const status = progress.text || 'Loading model...';
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console.log(`WebLLM: ${this.loadProgress}% - ${status}`);
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const langInstruction = language === 'vi'
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? 'Respond in Vietnamese (Tiếng Việt).'
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: 'Respond in English.';
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if (this.onProgressCallback) {
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this.onProgressCallback(this.loadProgress, status);
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}
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};
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const messages = [
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{
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role: 'system',
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content: `You are a helpful AI assistant that creates detailed, insightful video summaries. ${langInstruction}`
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},
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{
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role: 'user',
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content: `Provide a comprehensive summary of this video transcript in 4-6 sentences. Include the main topic, key points discussed, and any important insights or conclusions. Make the summary informative and meaningful:\n\n${text}`
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// Create engine
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this.engine = await webllm.CreateMLCEngine(modelId, {
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initProgressCallback: initProgressCallback
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});
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this.currentModel = modelKey || this.selectedModel;
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this.isLoading = false;
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this.loadProgress = 100;
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console.log('WebLLM ready!');
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if (this.onReadyCallback) {
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this.onReadyCallback();
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}
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return true;
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} catch (error) {
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console.error('WebLLM initialization failed:', error);
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this.isLoading = false;
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if (this.onErrorCallback) {
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this.onErrorCallback(error.message);
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}
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return false;
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}
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];
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try {
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const response = await this.engine.chat.completions.create({
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messages: messages,
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temperature: 0.7,
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max_tokens: 350
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});
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return response.choices[0].message.content.trim();
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} catch (error) {
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console.error('Summarization error:', error);
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throw error;
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}
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}
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/**
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* Translate text between English and Vietnamese
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* @param {string} text - Text to translate
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* @param {string} sourceLang - Source language ('en' or 'vi')
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* @param {string} targetLang - Target language ('en' or 'vi')
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* @returns {Promise<string>}
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*/
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async translate(text, sourceLang = 'en', targetLang = 'vi') {
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if (!this.isReady()) {
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throw new Error('WebLLM not ready. Call init() first.');
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}
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const langNames = {
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'en': 'English',
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'vi': 'Vietnamese (Tiếng Việt)'
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};
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/**
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* Check if engine is ready
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*/
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isReady() {
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return this.engine !== null && !this.isLoading;
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}
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const messages = [
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{
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role: 'system',
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content: `You are a professional translator. Translate the following text from ${langNames[sourceLang]} to ${langNames[targetLang]}. Provide only the translation, no explanations.`
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},
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{
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role: 'user',
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content: text
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/**
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* Summarize text using local AI
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* @param {string} text - Text to summarize
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* @param {string} language - Output language ('en' or 'vi')
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* @returns {Promise<string>}
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*/
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async summarize(text, language = 'en') {
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if (!this.isReady()) {
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throw new Error('WebLLM not ready. Call init() first.');
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}
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];
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try {
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const response = await this.engine.chat.completions.create({
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messages: messages,
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temperature: 0.3,
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max_tokens: 500
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});
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// Truncate text to avoid token limits
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const maxChars = 4000;
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if (text.length > maxChars) {
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text = text.substring(0, maxChars) + '...';
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}
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return response.choices[0].message.content.trim();
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const langInstruction = language === 'vi'
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? 'Respond in Vietnamese (Tiếng Việt).'
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: 'Respond in English.';
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} catch (error) {
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console.error('Translation error:', error);
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throw error;
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}
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}
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const messages = [
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{
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role: 'system',
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content: `You are a helpful AI assistant that creates detailed, insightful video summaries. ${langInstruction}`
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},
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{
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role: 'user',
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content: `Provide a comprehensive summary of this video transcript in 4-6 sentences. Include the main topic, key points discussed, and any important insights or conclusions. Make the summary informative and meaningful:\n\n${text}`
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}
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];
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/**
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* Extract key points from text
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* @param {string} text - Text to analyze
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* @param {string} language - Output language
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* @returns {Promise<string[]>}
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*/
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async extractKeyPoints(text, language = 'en') {
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if (!this.isReady()) {
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throw new Error('WebLLM not ready. Call init() first.');
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try {
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const response = await this.engine.chat.completions.create({
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messages: messages,
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temperature: 0.7,
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max_tokens: 350
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});
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return response.choices[0].message.content.trim();
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} catch (error) {
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console.error('Summarization error:', error);
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throw error;
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}
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}
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const maxChars = 3000;
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if (text.length > maxChars) {
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text = text.substring(0, maxChars) + '...';
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/**
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* Translate text between English and Vietnamese
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* @param {string} text - Text to translate
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* @param {string} sourceLang - Source language ('en' or 'vi')
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* @param {string} targetLang - Target language ('en' or 'vi')
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* @returns {Promise<string>}
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*/
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async translate(text, sourceLang = 'en', targetLang = 'vi') {
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if (!this.isReady()) {
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throw new Error('WebLLM not ready. Call init() first.');
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}
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const langNames = {
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'en': 'English',
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'vi': 'Vietnamese (Tiếng Việt)'
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};
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const messages = [
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{
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role: 'system',
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content: `You are a professional translator. Translate the following text from ${langNames[sourceLang]} to ${langNames[targetLang]}. Provide only the translation, no explanations.`
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},
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{
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role: 'user',
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content: text
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}
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];
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try {
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const response = await this.engine.chat.completions.create({
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messages: messages,
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temperature: 0.3,
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max_tokens: 500
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});
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return response.choices[0].message.content.trim();
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} catch (error) {
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console.error('Translation error:', error);
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throw error;
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}
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}
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const langInstruction = language === 'vi'
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? 'Respond in Vietnamese.'
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: 'Respond in English.';
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/**
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* Extract key points from text
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* @param {string} text - Text to analyze
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* @param {string} language - Output language
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* @returns {Promise<string[]>}
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*/
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async extractKeyPoints(text, language = 'en') {
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if (!this.isReady()) {
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throw new Error('WebLLM not ready. Call init() first.');
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}
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const messages = [
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{
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role: 'system',
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content: `You extract the main IDEAS and CONCEPTS from video content. ${langInstruction} Focus on:
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const maxChars = 3000;
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if (text.length > maxChars) {
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text = text.substring(0, maxChars) + '...';
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}
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const langInstruction = language === 'vi'
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? 'Respond in Vietnamese.'
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: 'Respond in English.';
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const messages = [
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{
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role: 'system',
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content: `You extract the main IDEAS and CONCEPTS from video content. ${langInstruction} Focus on:
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- Main topics discussed
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- Key insights or takeaways
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- Important facts or claims
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- Conclusions or recommendations
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Do NOT copy sentences from the transcript. Instead, synthesize the core ideas in your own words. List 3-5 key points, one per line, without bullet points or numbers.`
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},
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{
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role: 'user',
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content: `What are the main ideas and takeaways from this video transcript?\n\n${text}`
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}
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];
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try {
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const response = await this.engine.chat.completions.create({
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messages: messages,
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temperature: 0.6,
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max_tokens: 400
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});
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const content = response.choices[0].message.content.trim();
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const points = content.split('\n')
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.map(line => line.replace(/^[\d\.\-\*\•]+\s*/, '').trim())
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.filter(line => line.length > 10);
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return points.slice(0, 5);
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} catch (error) {
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console.error('Key points extraction error:', error);
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throw error;
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}
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}
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/**
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* Stream chat completion for real-time output
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* @param {string} prompt - User prompt
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* @param {function} onChunk - Callback for each chunk
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* @returns {Promise<string>}
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*/
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async streamChat(prompt, onChunk) {
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if (!this.isReady()) {
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throw new Error('WebLLM not ready.');
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}
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const messages = [
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{ role: 'user', content: prompt }
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];
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try {
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const chunks = await this.engine.chat.completions.create({
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messages: messages,
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temperature: 0.7,
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stream: true
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});
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let fullResponse = '';
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for await (const chunk of chunks) {
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const delta = chunk.choices[0]?.delta?.content || '';
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fullResponse += delta;
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if (onChunk) {
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onChunk(delta, fullResponse);
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},
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{
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role: 'user',
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content: `What are the main ideas and takeaways from this video transcript?\n\n${text}`
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}
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];
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try {
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const response = await this.engine.chat.completions.create({
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messages: messages,
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temperature: 0.6,
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max_tokens: 400
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});
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|
||||
const content = response.choices[0].message.content.trim();
|
||||
const points = content.split('\n')
|
||||
.map(line => line.replace(/^[\d\.\-\*\•]+\s*/, '').trim())
|
||||
.filter(line => line.length > 10);
|
||||
|
||||
return points.slice(0, 5);
|
||||
|
||||
} catch (error) {
|
||||
console.error('Key points extraction error:', error);
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Stream chat completion for real-time output
|
||||
* @param {string} prompt - User prompt
|
||||
* @param {function} onChunk - Callback for each chunk
|
||||
* @returns {Promise<string>}
|
||||
*/
|
||||
async streamChat(prompt, onChunk) {
|
||||
if (!this.isReady()) {
|
||||
throw new Error('WebLLM not ready.');
|
||||
}
|
||||
|
||||
return fullResponse;
|
||||
const messages = [
|
||||
{ role: 'user', content: prompt }
|
||||
];
|
||||
|
||||
} catch (error) {
|
||||
console.error('Stream chat error:', error);
|
||||
throw error;
|
||||
try {
|
||||
const chunks = await this.engine.chat.completions.create({
|
||||
messages: messages,
|
||||
temperature: 0.7,
|
||||
stream: true
|
||||
});
|
||||
|
||||
let fullResponse = '';
|
||||
for await (const chunk of chunks) {
|
||||
const delta = chunk.choices[0]?.delta?.content || '';
|
||||
fullResponse += delta;
|
||||
if (onChunk) {
|
||||
onChunk(delta, fullResponse);
|
||||
}
|
||||
}
|
||||
|
||||
return fullResponse;
|
||||
|
||||
} catch (error) {
|
||||
console.error('Stream chat error:', error);
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Get available models
|
||||
*/
|
||||
getModels() {
|
||||
return Object.keys(this.models).map(key => ({
|
||||
id: key,
|
||||
name: this.models[key],
|
||||
selected: key === this.selectedModel
|
||||
}));
|
||||
}
|
||||
|
||||
/**
|
||||
* Set selected model (requires re-init)
|
||||
*/
|
||||
setModel(modelKey) {
|
||||
if (this.models[modelKey]) {
|
||||
this.selectedModel = modelKey;
|
||||
// Reset engine to force reload with new model
|
||||
this.engine = null;
|
||||
this.currentModel = null;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Cleanup and release resources
|
||||
*/
|
||||
async destroy() {
|
||||
if (this.engine) {
|
||||
// WebLLM doesn't have explicit destroy, but we can nullify
|
||||
this.engine = null;
|
||||
this.currentModel = null;
|
||||
this.loadProgress = 0;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Get available models
|
||||
*/
|
||||
getModels() {
|
||||
return Object.keys(this.models).map(key => ({
|
||||
id: key,
|
||||
name: this.models[key],
|
||||
selected: key === this.selectedModel
|
||||
}));
|
||||
// Global singleton instance
|
||||
window.webLLMService = new WebLLMService();
|
||||
|
||||
// Export for module usage
|
||||
if (typeof module !== 'undefined' && module.exports) {
|
||||
module.exports = WebLLMService;
|
||||
}
|
||||
|
||||
/**
|
||||
* Set selected model (requires re-init)
|
||||
*/
|
||||
setModel(modelKey) {
|
||||
if (this.models[modelKey]) {
|
||||
this.selectedModel = modelKey;
|
||||
// Reset engine to force reload with new model
|
||||
this.engine = null;
|
||||
this.currentModel = null;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Cleanup and release resources
|
||||
*/
|
||||
async destroy() {
|
||||
if (this.engine) {
|
||||
// WebLLM doesn't have explicit destroy, but we can nullify
|
||||
this.engine = null;
|
||||
this.currentModel = null;
|
||||
this.loadProgress = 0;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Global singleton instance
|
||||
window.webLLMService = new WebLLMService();
|
||||
|
||||
// Export for module usage
|
||||
if (typeof module !== 'undefined' && module.exports) {
|
||||
module.exports = WebLLMService;
|
||||
}
|
||||
} // End guard block for WebLLMService
|
||||
|
|
|
|||
|
|
@ -1703,10 +1703,11 @@
|
|||
|
||||
<script>
|
||||
// Track current language state and WebLLM status
|
||||
let currentSummaryLang = 'en';
|
||||
let webllmInitialized = false;
|
||||
let currentTranscriptText = null;
|
||||
let currentSummaryData = { en: null, vi: null };
|
||||
// Use var and guards to prevent redeclaration errors on SPA navigation
|
||||
if (typeof currentSummaryLang === 'undefined') var currentSummaryLang = 'en';
|
||||
if (typeof webllmInitialized === 'undefined') var webllmInitialized = false;
|
||||
if (typeof currentTranscriptText === 'undefined') var currentTranscriptText = null;
|
||||
if (typeof currentSummaryData === 'undefined') var currentSummaryData = { en: null, vi: null };
|
||||
|
||||
// WebLLM Progress Update Handler - Silent loading (just log to console)
|
||||
function updateWebLLMProgress(percent, status) {
|
||||
|
|
|
|||
Loading…
Reference in a new issue