🎓 YouTube Comment Analyzer

Analyze educational YouTube videos for student engagement, questions, and learning insights using AI.

\n \n \n \n

✨ What You'll Get:

📊 Educational engagement metrics

❓ Student questions analysis

💡 Content improvement recommendations

👨‍🏫 Teacher satisfaction insights

📈 Learning effectiveness scores

🎯 Actionable feedback for educators

\n \n \n `;\n}\n\nfunction renderResultPage(result, videoUrl) {\n if (!result.success) {\n return renderErrorPage(result.error);\n }\n\n const analysis = result.analysis_result;\n const metrics = analysis.educational_metrics?.scores || {};\n const grades = analysis.educational_metrics?.grades || {};\n const insights = analysis.actionable_insights || {};\n const videoInfo = result.video_info || {};\n\n return `\n \n \n \n \n \n Analysis Results - YouTube Comment Analyzer\n \n \n \n

\n \n \n

Overall Grade

${grades.overall || 'N/A'}

Quality Score: ${analysis.educational_metrics?.comment_quality_score || 0}/10

\n \n

Engagement

${(metrics.comment_to_view_ratio || 0).toFixed(1)}

per 1000 views

\n \n

Questions

${(metrics.question_ratio || 0).toFixed(1)}%

student questions

\n \n

Success Rate

${(metrics.success_signal_ratio || 0).toFixed(1)}%

learning success

\n \n ${insights.student_questions?.total_questions > 0 ? `\n

\n ❓ Student Questions (${insights.student_questions.total_questions})\n

\n ${(insights.student_questions.top_questions || []).slice(0, 5).map((q, i) => `\n

\n Q${i+1}: ${q.question || q.full_text || 'No question text'}
\n 👤 ${q.author || 'Unknown'} • 👍 ${q.likes || 0} likes\n

\n `).join('')}\n

\n ` : ''}\n \n ${(analysis.recommendations || []).length > 0 ? `\n

\n 💡 Recommendations\n

\n ${analysis.recommendations.slice(0, 8).map(rec => `\n

${rec}

\n `).join('')}\n

\n ` : ''}\n \n ← Analyze Another Video\n

\n \n \n `;\n}\n\nfunction renderErrorPage(errorMessage) {\n return `\n \n \n \n \n \n Error - YouTube Comment Analyzer\n \n \n \n

❌ Analysis Failed

${errorMessage}

\n ← Back to Home\n

\n \n \n `;\n}","deleted","label","children",[],[100],{"_105":173,"_96":174,"_156":175,"_157":-5,"_158":142,"_159":176,"_160":119,"_107":177,"_101":162,"_163":164,"_165":178,"_167":22,"_168":-5,"_169":179,"_99":180},"c6eb7018-8cf5-11f0-b7a0-0224a6c84d84","main.tsx","2f26960a-865a-11f0-997f-0224a6c84d84",27,["D",1757364768055],"/** @jsxImportSource https://esm.sh/react */\nimport React, { useState, useEffect } from \"https://esm.sh/react\";\n\n// YouTube Comment Processor Class\nclass YouTubeCommentProcessor {\n constructor(apiKey, n8nWebhookUrl) {\n this.apiKey = apiKey;\n this.n8nWebhookUrl = n8nWebhookUrl;\n }\n \n extractVideoId(url) {\n if (!url || typeof url !== 'string') {\n throw new Error(\"Invalid URL: URL must be a non-empty string\");\n }\n \n url = url.trim();\n const patterns = [\n /(?:youtube\\.com\\/watch\\?v=)([^&\\n]+)/,\n /(?:youtu\\.be\\/)([^&\\n]+)/,\n /(?:youtube\\.com\\/embed\\/)([^&\\n]+)/,\n /(?:youtube\\.com\\/shorts\\/)([^&\\n]+)/,\n /(?:youtube\\.com\\/v\\/)([^&\\n]+)/,\n /(?:youtube\\.com\\/live\\/)([^&\\n]+)/,\n /(?:youtube\\.com\\/watch\\?.*v=)([^&\\n]+)/\n ];\n \n for (const pattern of patterns) {\n const match = url.match(pattern);\n if (match) {\n const videoId = match[1].split('&')[0].split('?')[0];\n if (videoId.length === 11) {\n return videoId;\n }\n }\n }\n \n const cleanId = url.replace(/[^a-zA-Z0-9_-]/g, '');\n if (cleanId.length === 11) {\n return cleanId;\n }\n \n throw new Error(`Could not extract video ID from URL: ${url}`);\n }\n \n async getVideoInfo(videoId) {\n if (!videoId) {\n throw new Error(\"Video ID cannot be empty\");\n }\n \n const url = \"https://www.googleapis.com/youtube/v3/videos\";\n const params = new URLSearchParams({\n key: this.apiKey,\n id: videoId,\n part: 'snippet,statistics,status'\n });\n \n const response = await fetch(`${url}?${params}`);\n \n if (!response.ok) {\n throw new Error(`Network error while fetching video info: ${response.status}`);\n }\n \n const data = await response.json();\n \n if (data.error) {\n throw new Error(`YouTube API Error (${data.error.code}): ${data.error.message}`);\n }\n \n if (!data.items || data.items.length === 0) {\n throw new Error(`Video not found or is private/deleted (ID: ${videoId})`);\n }\n \n const video = data.items[0];\n const status = video.status || {};\n const snippet = video.snippet || {};\n const statistics = video.statistics || {};\n \n if (status.privacyStatus === 'private') {\n throw new Error(\"Video is private\");\n }\n \n return {\n video_id: video.id,\n video_title: snippet.title || 'Unknown Title',\n channel_id: snippet.channelId || '',\n channel_name: snippet.channelTitle || 'Unknown Channel',\n published_at: snippet.publishedAt || '',\n description: snippet.description || '',\n view_count: statistics.viewCount || '0',\n like_count: statistics.likeCount || '0',\n comment_count: statistics.commentCount || '0',\n video_url: `https://youtube.com/watch?v=${video.id}`,\n privacy_status: status.privacyStatus || 'unknown',\n comments_disabled: !statistics.commentCount\n };\n }\n \n async fetchAllComments(videoId, maxComments = 500) {\n const allComments = [];\n let pageToken = '';\n let requestCount = 0;\n const maxRequests = 10;\n \n while (allComments.length < maxComments && requestCount < maxRequests) {\n requestCount++;\n \n const url = \"https://www.googleapis.com/youtube/v3/commentThreads\";\n const params = new URLSearchParams({\n key: this.apiKey,\n videoId: videoId,\n part: 'snippet,replies',\n maxResults: Math.min(100, maxComments - allComments.length),\n order: 'relevance',\n textFormat: 'plainText'\n });\n \n if (pageToken) {\n params.append('pageToken', pageToken);\n }\n \n const response = await fetch(`${url}?${params}`);\n \n if (response.status === 403) {\n const data = await response.json();\n if (data.error && data.error.message.includes('disabled')) {\n console.log(\"Comments are disabled for this video\");\n break;\n }\n throw new Error(`Access forbidden: ${data.error?.message || 'Unknown error'}`);\n }\n \n if (!response.ok) {\n throw new Error(`API request failed: ${response.status}`);\n }\n \n const data = await response.json();\n \n if (data.error) {\n throw new Error(`YouTube API Error: ${data.error.message}`);\n }\n \n if (!data.items || data.items.length === 0) {\n break;\n }\n \n // Process comments\n for (const thread of data.items) {\n if (allComments.length >= maxComments) break;\n \n const topComment = thread.snippet.topLevelComment.snippet;\n if (!topComment.textDisplay) continue;\n \n const commentData = {\n comment_id: thread.id,\n video_id: videoId,\n comment_text: topComment.textDisplay,\n full_text: topComment.textDisplay,\n author_name: topComment.authorDisplayName || 'Unknown Author',\n like_count: parseInt(topComment.likeCount) || 0,\n published_at: topComment.publishedAt || new Date().toISOString(),\n is_reply: false,\n reply_count: parseInt(thread.snippet.totalReplyCount) || 0\n };\n \n allComments.push(commentData);\n \n // Process replies\n if (thread.replies && allComments.length < maxComments) {\n for (const reply of thread.replies.comments) {\n if (allComments.length >= maxComments) break;\n \n const replySnippet = reply.snippet;\n if (!replySnippet.textDisplay) continue;\n \n const replyData = {\n comment_id: reply.id,\n video_id: videoId,\n comment_text: replySnippet.textDisplay,\n full_text: replySnippet.textDisplay,\n author_name: replySnippet.authorDisplayName || 'Unknown Author',\n like_count: parseInt(replySnippet.likeCount) || 0,\n published_at: replySnippet.publishedAt || new Date().toISOString(),\n is_reply: true,\n parent_id: thread.id,\n reply_count: 0\n };\n \n allComments.push(replyData);\n }\n }\n }\n \n pageToken = data.nextPageToken || '';\n if (!pageToken) break;\n \n await new Promise(resolve => setTimeout(resolve, 100));\n }\n \n return {\n comments: allComments,\n total_fetched: allComments.length,\n requests_made: requestCount,\n completed: allComments.length >= maxComments || !pageToken,\n had_errors: false\n };\n }\n \n async sendToN8nForAnalysis(videoUrl, maxComments = 100) {\n const processingStart = Date.now();\n \n try {\n const videoId = this.extractVideoId(videoUrl);\n const videoInfo = await this.getVideoInfo(videoId);\n videoInfo.max_comments_to_fetch = maxComments;\n videoInfo.request_time = new Date().toISOString();\n \n const commentResult = await this.fetchAllComments(videoId, maxComments);\n \n const formattedData = {\n success: true,\n total_fetched: commentResult.total_fetched,\n valid_comments: commentResult.total_fetched,\n total_requested: maxComments,\n api_requests_made: commentResult.requests_made,\n comments: commentResult.comments,\n video_info: videoInfo,\n fetch_summary: {\n original_comment_count: videoInfo.comment_count,\n fetched_percentage: Math.round((commentResult.total_fetched / Math.max(parseInt(videoInfo.comment_count), 1)) * 100 * 100) / 100,\n processing_time: new Date().toISOString(),\n had_fetch_errors: commentResult.had_errors\n }\n };\n \n const webhookResponse = await fetch(this.n8nWebhookUrl, {\n method: 'POST',\n headers: {\n 'Content-Type': 'application/json',\n 'User-Agent': 'ValTownYouTubeAnalyzer/1.0'\n },\n body: JSON.stringify(formattedData)\n });\n \n if (!webhookResponse.ok) {\n throw new Error(`n8n webhook failed: ${webhookResponse.status}`);\n }\n \n const analysisResult = await webhookResponse.json();\n \n return {\n success: true,\n comment_fetch_summary: {\n total_fetched: commentResult.total_fetched,\n api_requests_made: commentResult.requests_made,\n video_info: videoInfo,\n fetch_errors: commentResult.had_errors\n },\n analysis_result: analysisResult,\n processing_time: (Date.now() - processingStart) / 1000\n };\n \n } catch (error) {\n return {\n success: false,\n error: error.message,\n video_url: videoUrl,\n processing_time: (Date.now() - processingStart) / 1000\n };\n }\n }\n}\n\n// Main React Component\nfunction YouTubeAnalyzer({ url }) {\n const [videoUrl, setVideoUrl] = useState(\"\");\n const [analysis, setAnalysis] = useState(null);\n const [loading, setLoading] = useState(false);\n const [error, setError] = useState(null);\n\n const urlParams = new URLSearchParams(url?.searchParams);\n const analyzeParam = urlParams.get('analyze');\n const videoParam = urlParams.get('video');\n\n useEffect(() => {\n if (analyzeParam === 'true' && videoParam) {\n performAnalysis(videoParam);\n }\n }, [analyzeParam, videoParam]);\n\n const performAnalysis = async (video) => {\n setLoading(true);\n setError(null);\n \n try {\n // Get API key from environment - this is the KEY FIX!\n const apiKey = Deno.env.get(\"YOUTUBE_API_KEY\");\n if (!apiKey) {\n throw new Error(\"YouTube API key not configured in environment variables\");\n }\n\n const n8nWebhookUrl = \"https://n8n.vedantu.com/webhook/youtube-comments\";\n const processor = new YouTubeCommentProcessor(apiKey, n8nWebhookUrl);\n const result = await processor.sendToN8nForAnalysis(video, 100);\n \n if (!result.success) {\n throw new Error(result.error);\n }\n \n setAnalysis(result.analysis_result);\n } catch (err) {\n setError(err.message);\n } finally {\n setLoading(false);\n }\n };\n\n const handleSubmit = (e) => {\n e.preventDefault();\n if (!videoUrl.trim()) {\n setError(\"Please enter a YouTube video URL\");\n return;\n }\n \n const newUrl = `${window.location.origin}?analyze=true&video=${encodeURIComponent(videoUrl)}`;\n window.location.href = newUrl;\n };\n\n // Analysis Results Page\n if (analyzeParam === 'true') {\n if (loading) {\n return (\n

🤖 Analyzing YouTube Comments...

\n This may take a few minutes for videos with many comments.\n

\n \n

\n );\n }\n\n if (error) {\n return (\n

❌ Analysis Failed

{error}

\n \n

\n );\n }\n\n if (analysis) {\n const metrics = analysis.educational_metrics?.scores || {};\n const grades = analysis.educational_metrics?.grades || {};\n const insights = analysis.actionable_insights || {};\n \n return (\n

✅ Analysis Complete!

\n Video: {analysis.video_info?.video_title || videoParam}\n

\n\n

Overall Grade

\n {grades.overall || 'N/A'}\n

\n Score: {analysis.educational_metrics?.comment_quality_score || 0}/10\n

\n \n

Engagement

\n {metrics.comment_to_view_ratio?.toFixed(1) || 0}\n

\n per 1000 views\n

\n \n

Questions

\n {metrics.question_ratio?.toFixed(1) || 0}%\n

\n student questions\n

\n \n

Success Rate

\n {metrics.success_signal_ratio?.toFixed(1) || 0}%\n

\n learning success\n

\n\n {insights.student_questions?.total_questions > 0 && (\n

\n ❓ Student Questions ({insights.student_questions.total_questions})\n

\n {insights.student_questions.top_questions?.slice(0, 5).map((q, i) => (\n

\n Q{i+1}: {q.question || q.full_text || 'No question text'}
\n \n 👤 {q.author || 'Unknown'} • 👍 {q.likes || 0} likes\n \n

\n ))}\n

\n )}\n\n {analysis.recommendations?.length > 0 && (\n

💡 Recommendations

{rec}

\n )}\n\n

\n 🔍 View Raw Data\n

\n              {JSON.stringify(analysis, null, 2)}\n

\n\n \n

\n );\n }\n\n return

;\n }\n\n // Home Page\n return (\n

\n 🎓 YouTube Comment Analyzer\n

\n \n

\n Analyze educational YouTube videos for student engagement, questions, and learning insights using AI.\n

\n\n

\n setVideoUrl(e.target.value)}\n style={{ \n width: '100%', \n padding: '18px', \n fontSize: '16px',\n border: '2px solid #dee2e6',\n borderRadius: '10px',\n marginBottom: '20px',\n boxSizing: 'border-box'\n }}\n required\n />\n \n \n 🔍 Analyze Comments\n \n \n\n {error && (\n

\n {error}\n

\n )}\n\n

✨ What You'll Get:

📊 Educational engagement metrics

❓ Student questions analysis

💡 Content improvement recommendations

👨‍🏫 Teacher satisfaction insights

📈 Learning effectiveness scores

🎯 Actionable feedback for educators

\n );\n}\n\nexport default YouTubeAnalyzer;",[],[174],{"_105":182,"_96":183,"_156":184,"_157":-5,"_158":142,"_159":185,"_160":119,"_107":186,"_101":187,"_163":164,"_165":188,"_167":22,"_168":-5,"_169":189,"_99":190},"d5a85978-88b7-11f0-88a6-0224a6c84d84","new-file-4421.tsx","cb71ac2c-88b5-11f0-b66d-0224a6c84d84",23,["D",1756898359328],7,"// Enhanced EdTech YouTube Comment Analysis Tool - ValTown Compatible\n// Multi-Pass AI System with Gemini 2.5 Pro\n\nexport default async function (req) {\n const url = new URL(req.url);\n const videoId = url.searchParams.get(\"videoId\");\n const format = url.searchParams.get(\"format\");\n\n if (!videoId) {\n return new Response(generateMainInterface(), {\n headers: { \"Content-Type\": \"text/html\" },\n });\n }\n\n const youtubeApiKey = process.env.YOUTUBE_API_KEY;\n const geminiApiKey = process.env.GEMINI_API_KEY;\n\n if (!youtubeApiKey || !geminiApiKey) {\n return new Response(\n JSON.stringify({\n error: \"API keys not configured\",\n required: {\n YOUTUBE_API_KEY: youtubeApiKey ? \"✓ Configured\" : \"❌ Missing\",\n GEMINI_API_KEY: geminiApiKey ? \"✓ Configured\" : \"❌ Missing\",\n },\n setup: \"Contact administrator to configure API keys\",\n }),\n {\n status: 500,\n headers: { \"Content-Type\": \"application/json\" },\n },\n );\n }\n\n try {\n await rateLimitCheck(req);\n\n const [videoDetails, comments] = await Promise.all([\n fetchVideoDetailsWithRetry(videoId, youtubeApiKey),\n fetchYouTubeCommentsWithRetry(videoId, youtubeApiKey),\n ]);\n\n const basicAnalysis = analyzeCommentsEdTech(comments);\n\n // ENHANCED MULTI-PASS AI ANALYSIS\n console.log(\"🚀 Starting Enhanced Multi-Pass AI Analysis...\");\n const geminiInsights = await enhancedMultiPassAnalysis(\n comments,\n videoDetails,\n geminiApiKey,\n );\n\n const completeAnalysis = {\n ...basicAnalysis,\n aiInsights: geminiInsights,\n analysisTimestamp: new Date().toISOString(),\n analysisVersion: \"EdTech-Enhanced-v3.0\",\n totalAnalysisCategories: 35,\n };\n\n if (format === \"dashboard\") {\n return new Response(\n generateEnhancedDashboardHTML(videoDetails, completeAnalysis),\n {\n headers: { \"Content-Type\": \"text/html\" },\n },\n );\n }\n\n return new Response(\n JSON.stringify(\n {\n success: true,\n analyzedAt: new Date().toISOString(),\n analysisType: \"Enhanced EdTech Educational Analysis\",\n video: {\n id: videoId,\n title: videoDetails.title,\n channel: videoDetails.channel,\n publishedAt: videoDetails.publishedAt,\n viewCount: videoDetails.viewCount,\n likeCount: videoDetails.likeCount,\n commentCount: videoDetails.commentCount,\n url: `https://www.youtube.com/watch?v=${videoId}`,\n },\n fetchedComments: comments.length,\n analysis: completeAnalysis,\n },\n null,\n 2,\n ),\n {\n headers: {\n \"Content-Type\": \"application/json\",\n \"Access-Control-Allow-Origin\": \"*\",\n },\n },\n );\n } catch (error) {\n console.error(\"Enhanced analysis error:\", error);\n\n if (error.message.includes(\"quota\")) {\n return new Response(generateQuotaErrorHTML(), {\n headers: { \"Content-Type\": \"text/html\" },\n });\n }\n\n return new Response(generateErrorHTML(error.message), {\n headers: { \"Content-Type\": \"text/html\" },\n });\n }\n}\n\n// ========================================\n// ENHANCED MULTI-PASS AI ANALYSIS SYSTEM\n// ========================================\n\nasync function enhancedMultiPassAnalysis(comments, videoDetails, geminiApiKey) {\n try {\n console.log(\"🚀 Starting Enhanced Multi-Pass AI Analysis...\");\n\n // Sequential AI passes for deep analysis\n const [teacherAnalysis, learningAnalysis, behaviorAnalysis] = await Promise\n .all([\n deepTeacherAnalysis(comments, videoDetails, geminiApiKey),\n comprehensiveLearningAnalysis(comments, videoDetails, geminiApiKey),\n studentBehaviorAnalysis(comments, videoDetails, geminiApiKey),\n ]);\n\n // Additional passes\n const [contentAnalysis, predictiveAnalysis] = await Promise.all([\n contentEffectivenessAnalysis(comments, videoDetails, geminiApiKey),\n predictiveAnalyticsGeneration(comments, videoDetails, geminiApiKey),\n ]);\n\n console.log(\"✅ Enhanced Multi-Pass Analysis Complete!\");\n\n return {\n teacherPerformance: teacherAnalysis,\n learningAnalytics: learningAnalysis,\n studentBehavior: behaviorAnalysis,\n contentEffectiveness: contentAnalysis,\n predictiveInsights: predictiveAnalysis,\n analysisDepth: \"Advanced Multi-Pass Analysis\",\n totalInsightCategories: 35,\n passesCompleted: 5,\n };\n } catch (error) {\n console.error(\"Enhanced AI analysis error:\", error);\n return getAdvancedFallbackAnalysis();\n }\n}\n\n// ========================================\n// AI ANALYSIS PASSES - INDIVIDUAL FUNCTIONS\n// ========================================\n\nasync function deepTeacherAnalysis(comments, videoDetails, geminiApiKey) {\n const teacherComments = comments.slice(0, 60).map((c) => ({\n text: c.textOriginal,\n likes: c.likeCount,\n author: c.author,\n timestamp: c.publishedAt,\n }));\n\n const teacherPrompt = `\nAs a MASTER EDUCATIONAL EVALUATOR with 20+ years experience, conduct detailed analysis of teacher \"${videoDetails.channel}\" for \"${videoDetails.title}\".\n\nTEACHER PERFORMANCE FRAMEWORK:\n1. Teaching Methodology (Score 1-10 each):\n - Pedagogical Approach Effectiveness\n - Learning Style Accommodation \n - Cognitive Load Management\n - Scaffolding Techniques\n\n2. Communication Excellence:\n - Verbal Clarity & Articulation\n - Technical Vocabulary Usage\n - Explanation Structure & Flow\n - Student Question Handling\n\n3. Subject Matter Expertise:\n - Content Knowledge Depth\n - Accuracy & Precision\n - Real-world Applications\n - Concept Simplification\n\n4. Emotional Intelligence:\n - Student Emotional Recognition\n - Empathy Demonstration\n - Confidence Building\n - Inclusive Environment\n\nStudent Comments: ${JSON.stringify(teacherComments)}\n\nProvide detailed JSON analysis:\n{\n \"overallTeacherRating\": {\"score\": \"X/10\", \"justification\": \"detailed reasoning with evidence\"},\n \"teachingMethodology\": {\n \"pedagogicalApproach\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]},\n \"learningStyleAccommodation\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]},\n \"cognitiveLoadManagement\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]},\n \"scaffoldingTechniques\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]}\n },\n \"communicationExcellence\": {\n \"verbalClarity\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]},\n \"technicalVocabulary\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]},\n \"explanationStructure\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]},\n \"questionHandling\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]}\n },\n \"subjectMatterExpertise\": {\n \"contentKnowledgeDepth\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]},\n \"accuracyPrecision\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]},\n \"realWorldApplications\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]},\n \"conceptSimplification\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]}\n },\n \"emotionalIntelligence\": {\n \"studentEmotionalRecognition\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]},\n \"empathyDemonstration\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]},\n \"confidenceBuilding\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]},\n \"inclusiveEnvironment\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"evidence\": [\"quote1\", \"quote2\"], \"improvements\": [\"suggestion1\", \"suggestion2\"]}\n },\n \"detailedStrengths\": [\"strength 1 with examples\", \"strength 2 with evidence\", \"strength 3 with quotes\"],\n \"criticalImprovements\": [\"improvement 1 with action plan\", \"improvement 2 with timeline\", \"improvement 3 with resources\"],\n \"teachingPersonality\": \"Detailed psychological profile of teaching style\",\n \"competitiveAdvantages\": [\"unique strength 1\", \"unique strength 2\", \"unique strength 3\"]\n}\n\nBe extremely detailed. Provide evidence for every claim.`;\n\n return await processGeminiRequest(teacherPrompt, geminiApiKey);\n}\n\nasync function comprehensiveLearningAnalysis(\n comments,\n videoDetails,\n geminiApiKey,\n) {\n const learningComments = comments.slice(0, 50).map((c) => ({\n text: c.textOriginal,\n likes: c.likeCount,\n author: c.author,\n }));\n\n const learningPrompt = `\nAs a LEARNING SCIENCE EXPERT, perform comprehensive learning analytics.\n\nLEARNING ANALYTICS FRAMEWORK:\n1. Cognitive Processing Analysis:\n - Bloom's Taxonomy Distribution (Remember, Understand, Apply, Analyze, Evaluate, Create)\n - Cognitive Load Assessment\n - Critical Thinking Evidence\n - Problem-Solving Approaches\n\n2. Learning Progression:\n - Knowledge Construction Evidence\n - Skill Development Stages\n - Mastery Indicators\n - Learning Obstacles\n\nComments: ${JSON.stringify(learningComments)}\nVideo: \"${videoDetails.title}\"\n\nProvide comprehensive JSON:\n{\n \"cognitiveProcessing\": {\n \"bloomsTaxonomyDistribution\": {\"remember\": \"X%\", \"understand\": \"X%\", \"apply\": \"X%\", \"analyze\": \"X%\", \"evaluate\": \"X%\", \"create\": \"X%\"},\n \"cognitiveLoadAnalysis\": {\"intrinsic\": \"High/Medium/Low\", \"extraneous\": \"High/Medium/Low\", \"germane\": \"High/Medium/Low\", \"evidence\": [\"quote1\", \"quote2\"]},\n \"criticalThinking\": {\"demonstrated\": true, \"examples\": [\"example1\", \"example2\"], \"level\": \"Advanced/Intermediate/Basic\"},\n \"problemSolvingApproach\": {\"strategy\": \"Systematic/Intuitive\", \"effectiveness\": \"High/Medium/Low\", \"improvements\": [\"suggestion1\", \"suggestion2\"]}\n },\n \"learningProgression\": {\n \"knowledgeConstruction\": {\"stage\": \"Foundation/Building/Integration\", \"evidence\": [\"quote1\", \"quote2\"], \"next_steps\": [\"step1\", \"step2\"]},\n \"skillDevelopment\": {\"current_stage\": \"Novice/Competent/Proficient/Expert\", \"progression_rate\": \"Fast/Moderate/Slow\"},\n \"masteryByTopic\": [{\"topic\": \"topic1\", \"mastery_level\": \"X%\", \"evidence\": [\"quote1\", \"quote2\"], \"confidence\": \"High/Medium/Low\"}],\n \"learningObstacles\": [{\"obstacle\": \"description\", \"frequency\": 5, \"impact\": \"High/Medium/Low\", \"solutions\": [\"solution1\", \"solution2\"]}]\n }\n}`;\n\n return await processGeminiRequest(learningPrompt, geminiApiKey);\n}\n\nasync function studentBehaviorAnalysis(comments, videoDetails, geminiApiKey) {\n const behaviorComments = comments.slice(0, 40).map((c) => ({\n text: c.textOriginal,\n likes: c.likeCount,\n author: c.author,\n }));\n\n const behaviorPrompt = `\nAs an EDUCATIONAL PSYCHOLOGIST, analyze student behavior and motivation.\n\nPSYCHOLOGY FRAMEWORK:\n1. Motivation Analysis:\n - Self-Determination Theory (Autonomy, Competence, Relatedness)\n - Intrinsic vs Extrinsic Motivation\n - Achievement Goal Orientation\n - Self-Efficacy Assessment\n\n2. Emotional State:\n - Emotional Regulation\n - Stress/Anxiety Levels\n - Confidence Assessment\n - Satisfaction Markers\n\nComments: ${JSON.stringify(behaviorComments)}\n\nProvide detailed psychological analysis:\n{\n \"motivationPsychology\": {\n \"selfDeterminationTheory\": {\n \"autonomy\": {\"level\": \"High/Medium/Low\", \"evidence\": [\"quote1\", \"quote2\"], \"support_needs\": [\"need1\", \"need2\"]},\n \"competence\": {\"level\": \"High/Medium/Low\", \"evidence\": [\"quote1\", \"quote2\"], \"development_areas\": [\"area1\", \"area2\"]},\n \"relatedness\": {\"level\": \"High/Medium/Low\", \"evidence\": [\"quote1\", \"quote2\"], \"community_building\": [\"suggestion1\", \"suggestion2\"]}\n },\n \"motivationType\": {\"primary\": \"Intrinsic/Extrinsic\", \"indicators\": [\"indicator1\", \"indicator2\"], \"sustainability\": \"High/Medium/Low\"},\n \"achievementGoals\": {\"mastery_focused\": \"X%\", \"performance_focused\": \"X%\", \"evidence\": [\"quote1\", \"quote2\"]},\n \"selfEfficacy\": {\"level\": \"High/Medium/Low\", \"building_strategies\": [\"strategy1\", \"strategy2\"]}\n },\n \"emotionalState\": {\n \"emotionalRegulation\": {\"level\": \"High/Medium/Low\", \"evidence\": [\"quote1\", \"quote2\"], \"support_needed\": [\"support1\"]},\n \"stressAnxiety\": {\"level\": \"High/Medium/Low\", \"indicators\": [\"indicator1\", \"indicator2\"], \"interventions\": [\"intervention1\"]},\n \"confidenceLevel\": {\"overall\": \"High/Medium/Low\", \"boosters\": [\"booster1\", \"booster2\"]},\n \"satisfactionMarkers\": {\"frequency\": \"High/Medium/Low\", \"sources\": [\"source1\", \"source2\"]}\n }\n}`;\n\n return await processGeminiRequest(behaviorPrompt, geminiApiKey);\n}\n\nasync function contentEffectivenessAnalysis(\n comments,\n videoDetails,\n geminiApiKey,\n) {\n const contentComments = comments.slice(0, 30).map((c) => ({\n text: c.textOriginal,\n likes: c.likeCount,\n }));\n\n const contentPrompt = `\nAs a CURRICULUM DESIGN EXPERT, analyze content effectiveness.\n\nCONTENT FRAMEWORK:\n1. Curriculum Alignment\n2. Learning Objective Achievement\n3. Content Structure & Flow\n4. Engagement Analysis\n5. Accessibility Assessment\n\nComments: ${JSON.stringify(contentComments)}\n\nProvide detailed analysis:\n{\n \"curriculumAlignment\": {\"score\": \"X/10\", \"analysis\": \"detailed analysis\", \"gaps\": [\"gap1\", \"gap2\"], \"improvements\": [\"improvement1\", \"improvement2\"]},\n \"learningObjectives\": {\"achievement_rate\": \"X%\", \"clear_objectives\": [\"objective1\", \"objective2\"], \"missed_objectives\": [\"missed1\", \"missed2\"]},\n \"contentStructure\": {\"flow_quality\": \"Excellent/Good/Poor\", \"logical_progression\": true, \"improvements\": [\"improvement1\", \"improvement2\"]},\n \"engagementLevel\": {\"overall\": \"High/Medium/Low\", \"peak_moments\": [\"moment1\", \"moment2\"], \"drop_points\": [\"point1\", \"point2\"]},\n \"accessibility\": {\"inclusive_design\": \"Excellent/Good/Poor\", \"barriers\": [\"barrier1\", \"barrier2\"], \"enhancements\": [\"enhancement1\", \"enhancement2\"]}\n}`;\n\n return await processGeminiRequest(contentPrompt, geminiApiKey);\n}\n\nasync function predictiveAnalyticsGeneration(\n comments,\n videoDetails,\n geminiApiKey,\n) {\n const predictiveComments = comments.slice(0, 25).map((c) => ({\n text: c.textOriginal,\n likes: c.likeCount,\n }));\n\n const predictivePrompt = `\nAs a LEARNING ANALYTICS SPECIALIST, provide predictive insights.\n\nPREDICTIVE FRAMEWORK:\n1. Student Success Prediction\n2. Engagement Forecasting\n3. Intervention Recommendations\n4. Learning Outcome Projections\n\nComments: ${JSON.stringify(predictiveComments)}\n\nProvide predictive analysis:\n{\n \"studentSuccess\": {\"probability\": \"High/Medium/Low\", \"indicators\": [\"indicator1\", \"indicator2\"], \"risk_factors\": [\"risk1\", \"risk2\"]},\n \"engagementTrends\": {\"trajectory\": \"Increasing/Stable/Declining\", \"forecast\": \"detailed forecast\", \"interventions\": [\"intervention1\", \"intervention2\"]},\n \"learningOutcomes\": {\"projected_success_rate\": \"X%\", \"improvement_areas\": [\"area1\", \"area2\"], \"timeline\": \"detailed timeline\"},\n \"recommendations\": {\"immediate\": [\"action1\", \"action2\"], \"short_term\": [\"action3\", \"action4\"], \"long_term\": [\"action5\", \"action6\"]}\n}`;\n\n return await processGeminiRequest(predictivePrompt, geminiApiKey);\n}\n\nasync function processGeminiRequest(prompt, geminiApiKey) {\n const enhancedPrompt = `\nCONTEXT: You are analyzing educational YouTube comments with 20+ years of expertise.\n\nINSTRUCTIONS:\n- Use EVIDENCE-BASED reasoning for every claim\n- Provide SPECIFIC student quotes to support analysis\n- Give MEASURABLE recommendations with clear action steps\n- Consider DIVERSE learning styles and backgrounds\n- Focus on ACTIONABLE insights for educational improvement\n\nQUALITY STANDARDS:\n- Every score must be justified with evidence from student comments\n- Every recommendation must be specific and implementable\n- Every insight must cite actual student feedback as proof\n- Analysis must be educationally sound and research-based\n\n${prompt}\n\nCRITICAL: Return ONLY valid JSON. Be detailed while maintaining proper JSON structure.`;\n\n try {\n const response = await fetch(\n `https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-pro:generateContent?key=${geminiApiKey}`,\n {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/json\" },\n body: JSON.stringify({\n contents: [{ parts: [{ text: enhancedPrompt }] }],\n generationConfig: {\n temperature: 0.2,\n topK: 40,\n topP: 0.8,\n maxOutputTokens: 8000,\n },\n }),\n },\n );\n\n const data = await response.json();\n\n if (data.candidates && data.candidates[0]?.content?.parts?.[0]?.text) {\n const aiText = data.candidates[0].content.parts[0].text;\n const jsonMatch = aiText.match(/\\{[\\s\\S]*\\}/);\n if (jsonMatch) {\n try {\n return JSON.parse(jsonMatch[0]);\n } catch (parseError) {\n console.error(\"JSON parse error:\", parseError);\n return {\n error: \"Failed to parse AI response\",\n rawText: jsonMatch[0],\n };\n }\n }\n }\n\n return { error: \"No valid response from AI\", rawResponse: data };\n } catch (error) {\n console.error(\"Gemini API error:\", error);\n return { error: \"API request failed\", details: error.message };\n }\n}\n\nfunction getAdvancedFallbackAnalysis() {\n return {\n teacherPerformance: {\n overallTeacherRating: {\n score: \"Processing...\",\n justification: \"AI analysis temporarily unavailable\",\n },\n teachingMethodology: {\n pedagogicalApproach: {\n score: \"Analyzing...\",\n analysis: \"Processing feedback\",\n evidence: [],\n improvements: [],\n },\n },\n communicationExcellence: {\n verbalClarity: {\n score: \"Analyzing...\",\n analysis: \"Processing feedback\",\n evidence: [],\n improvements: [],\n },\n },\n subjectMatterExpertise: {\n contentKnowledgeDepth: {\n score: \"Analyzing...\",\n analysis: \"Processing feedback\",\n evidence: [],\n improvements: [],\n },\n },\n emotionalIntelligence: {\n studentEmotionalRecognition: {\n score: \"Analyzing...\",\n analysis: \"Processing feedback\",\n evidence: [],\n improvements: [],\n },\n },\n detailedStrengths: [\"Analysis in progress...\"],\n criticalImprovements: [\"Processing recommendations...\"],\n teachingPersonality: \"AI analysis temporarily unavailable\",\n competitiveAdvantages: [\"Analysis pending...\"],\n },\n learningAnalytics: {\n cognitiveProcessing: {\n bloomsTaxonomyDistribution: {\n remember: \"0%\",\n understand: \"0%\",\n apply: \"0%\",\n analyze: \"0%\",\n evaluate: \"0%\",\n create: \"0%\",\n },\n cognitiveLoadAnalysis: {\n intrinsic: \"Processing...\",\n extraneous: \"Processing...\",\n germane: \"Processing...\",\n evidence: [],\n },\n },\n learningProgression: {\n knowledgeConstruction: {\n stage: \"Analyzing...\",\n evidence: [],\n next_steps: [],\n },\n skillDevelopment: {\n current_stage: \"Processing...\",\n progression_rate: \"Analyzing...\",\n },\n },\n },\n studentBehavior: {\n motivationPsychology: {\n selfDeterminationTheory: {\n autonomy: { level: \"Processing...\", evidence: [], support_needs: [] },\n competence: {\n level: \"Processing...\",\n evidence: [],\n development_areas: [],\n },\n relatedness: {\n level: \"Processing...\",\n evidence: [],\n community_building: [],\n },\n },\n },\n },\n contentEffectiveness: {\n curriculumAlignment: {\n score: \"Processing...\",\n analysis: \"AI analysis in progress\",\n gaps: [],\n improvements: [],\n },\n },\n predictiveInsights: {\n studentSuccess: {\n probability: \"Analyzing...\",\n indicators: [],\n risk_factors: [],\n },\n engagementTrends: {\n trajectory: \"Processing...\",\n forecast: \"Analysis pending\",\n interventions: [],\n },\n },\n analysisDepth: \"Fallback Analysis - AI Temporarily Unavailable\",\n totalInsightCategories: 0,\n passesCompleted: 0,\n };\n}\n\nconst requestCounts = new Map();\nconst RATE_LIMIT = 8;\nconst RATE_WINDOW = 60000;\n\nasync function rateLimitCheck(req) {\n const clientIP = req.headers.get(\"x-forwarded-for\") || \"unknown\";\n const now = Date.now();\n\n if (!requestCounts.has(clientIP)) {\n requestCounts.set(clientIP, []);\n }\n\n const requests = requestCounts.get(clientIP);\n const validRequests = requests.filter((timestamp) =>\n now - timestamp < RATE_WINDOW\n );\n\n if (validRequests.length >= RATE_LIMIT) {\n throw new Error(\n \"Rate limit exceeded. Enhanced analysis requires more resources - please wait before making another request.\",\n );\n }\n\n validRequests.push(now);\n requestCounts.set(clientIP, validRequests);\n}\n\nasync function fetchYouTubeCommentsWithRetry(videoId, apiKey, maxRetries = 3) {\n for (let attempt = 1; attempt <= maxRetries; attempt++) {\n try {\n return await fetchYouTubeComments(videoId, apiKey);\n } catch (error) {\n if (attempt === maxRetries) throw error;\n await new Promise((resolve) => setTimeout(resolve, attempt * 2000));\n }\n }\n}\n\nasync function fetchVideoDetailsWithRetry(videoId, apiKey, maxRetries = 3) {\n for (let attempt = 1; attempt <= maxRetries; attempt++) {\n try {\n return await fetchVideoDetails(videoId, apiKey);\n } catch (error) {\n if (attempt === maxRetries) throw error;\n await new Promise((resolve) => setTimeout(resolve, attempt * 1000));\n }\n }\n}\n\nasync function fetchYouTubeComments(videoId, apiKey) {\n const comments = [];\n const maxCommentsLimit = 1000;\n\n try {\n const timeComments = await fetchCommentsByOrder(\n videoId,\n apiKey,\n \"time\",\n 500,\n );\n comments.push(...timeComments);\n\n if (comments.length < maxCommentsLimit) {\n const relevanceComments = await fetchCommentsByOrder(\n videoId,\n apiKey,\n \"relevance\",\n maxCommentsLimit - comments.length,\n );\n const newComments = relevanceComments.filter((newComment) =>\n !comments.some((existingComment) =>\n existingComment.id === newComment.id ||\n (existingComment.textOriginal === newComment.textOriginal &&\n existingComment.author === newComment.author)\n )\n );\n comments.push(...newComments);\n }\n\n return comments.slice(0, maxCommentsLimit).sort((a, b) =>\n new Date(b.publishedAt) - new Date(a.publishedAt)\n );\n } catch (error) {\n console.error(\"Error in comment collection:\", error);\n return comments.slice(0, maxCommentsLimit);\n }\n}\n\nasync function fetchCommentsByOrder(videoId, apiKey, order, remainingLimit) {\n const comments = [];\n let nextPageToken = \"\";\n const maxPages = 5;\n let pageCount = 0;\n\n try {\n do {\n if (comments.length >= remainingLimit || pageCount >= maxPages) break;\n\n const url =\n `https://www.googleapis.com/youtube/v3/commentThreads?part=snippet,replies&videoId=${videoId}&key=${apiKey}&maxResults=100&order=${order}${\n nextPageToken ? `&pageToken=${nextPageToken}` : \"\"\n }`;\n\n const response = await fetch(url);\n const data = await response.json();\n\n if (data.error || !data.items || data.items.length === 0) break;\n\n data.items.forEach((item) => {\n if (comments.length >= remainingLimit) return;\n\n const comment = item.snippet.topLevelComment.snippet;\n comments.push({\n id: item.id,\n text: comment.textDisplay,\n textOriginal: comment.textOriginal,\n author: comment.authorDisplayName,\n likeCount: comment.likeCount || 0,\n publishedAt: comment.publishedAt,\n replyCount: item.snippet.totalReplyCount || 0,\n isReply: false,\n fetchMethod: order,\n });\n\n if (\n item.replies && item.replies.comments &&\n comments.length < remainingLimit\n ) {\n item.replies.comments.forEach((reply) => {\n if (comments.length >= remainingLimit) return;\n const replySnippet = reply.snippet;\n comments.push({\n id: reply.id,\n text: replySnippet.textDisplay,\n textOriginal: replySnippet.textOriginal,\n author: replySnippet.authorDisplayName,\n likeCount: replySnippet.likeCount || 0,\n publishedAt: replySnippet.publishedAt,\n replyCount: 0,\n isReply: true,\n fetchMethod: order,\n });\n });\n }\n });\n\n nextPageToken = data.nextPageToken;\n pageCount++;\n\n if (nextPageToken && pageCount < maxPages) {\n await new Promise((resolve) => setTimeout(resolve, 200));\n }\n } while (\n nextPageToken && pageCount < maxPages && comments.length < remainingLimit\n );\n\n return comments;\n } catch (error) {\n console.error(`Error fetching ${order} comments:`, error);\n return comments;\n }\n}\n\nasync function fetchVideoDetails(videoId, apiKey) {\n const url =\n `https://www.googleapis.com/youtube/v3/videos?part=snippet,statistics&id=${videoId}&key=${apiKey}`;\n const response = await fetch(url);\n const data = await response.json();\n\n if (data.error) throw new Error(`YouTube API Error: ${data.error.message}`);\n if (!data.items || data.items.length === 0) {\n throw new Error(\"Video not found\");\n }\n\n const video = data.items[0];\n return {\n title: video.snippet.title,\n channel: video.snippet.channelTitle,\n publishedAt: video.snippet.publishedAt,\n viewCount: parseInt(video.statistics.viewCount || 0),\n likeCount: parseInt(video.statistics.likeCount || 0),\n commentCount: parseInt(video.statistics.commentCount || 0),\n };\n}\n\nfunction analyzeCommentsEdTech(comments) {\n if (comments.length === 0) {\n return {\n message: \"No comments found for analysis\",\n suggestions: [\n \"Check video ID\",\n \"Ensure video is public\",\n \"Verify comments are enabled\",\n ],\n };\n }\n\n return {\n sentiment: analyzeSentiment(comments),\n keywords: extractKeywords(comments),\n engagement: analyzeEngagement(comments),\n timeDistribution: analyzeTimeDistribution(comments),\n topComments: getTopComments(comments, 5),\n statistics: getStatistics(comments),\n emojis: analyzeEmojis(comments),\n questions: findQuestions(comments),\n authors: analyzeAuthors(comments),\n breakdown: analyzeCommentBreakdown(comments),\n edtech: {\n teacherFeedback: analyzeTeacherFeedback(comments),\n learningOutcomes: analyzeLearningOutcomes(comments),\n },\n };\n}\n\nfunction analyzeSentiment(comments) {\n const positiveWords = [\n \"love\",\n \"great\",\n \"awesome\",\n \"excellent\",\n \"good\",\n \"wonderful\",\n \"fantastic\",\n \"amazing\",\n \"best\",\n \"perfect\",\n \"helpful\",\n \"thanks\",\n \"brilliant\",\n ];\n const negativeWords = [\n \"hate\",\n \"bad\",\n \"terrible\",\n \"awful\",\n \"worst\",\n \"horrible\",\n \"boring\",\n \"waste\",\n \"stupid\",\n \"disappointed\",\n ];\n\n let positive = 0, negative = 0, neutral = 0;\n\n comments.forEach((comment) => {\n const text = comment.textOriginal.toLowerCase();\n let positiveScore = 0, negativeScore = 0;\n\n positiveWords.forEach((word) => {\n if (text.includes(word)) positiveScore++;\n });\n\n negativeWords.forEach((word) => {\n if (text.includes(word)) negativeScore++;\n });\n\n if (positiveScore > negativeScore) positive++;\n else if (negativeScore > positiveScore) negative++;\n else neutral++;\n });\n\n const total = comments.length;\n return {\n positive: {\n count: positive,\n percentage: ((positive / total) * 100).toFixed(1) + \"%\",\n },\n negative: {\n count: negative,\n percentage: ((negative / total) * 100).toFixed(1) + \"%\",\n },\n neutral: {\n count: neutral,\n percentage: ((neutral / total) * 100).toFixed(1) + \"%\",\n },\n overallScore: parseFloat(((positive - negative) / total * 100).toFixed(1)),\n };\n}\n\nfunction extractKeywords(comments) {\n const wordFrequency = {};\n const stopWords = new Set([\n \"the\",\n \"is\",\n \"at\",\n \"which\",\n \"on\",\n \"a\",\n \"an\",\n \"and\",\n \"or\",\n \"but\",\n \"in\",\n \"with\",\n \"to\",\n \"for\",\n \"of\",\n \"as\",\n \"from\",\n \"this\",\n \"that\",\n \"it\",\n \"are\",\n \"was\",\n \"be\",\n \"been\",\n \"being\",\n \"have\",\n \"has\",\n \"had\",\n \"do\",\n \"does\",\n \"did\",\n \"will\",\n \"would\",\n \"could\",\n \"should\",\n \"may\",\n \"might\",\n \"must\",\n \"can\",\n \"i\",\n \"you\",\n \"he\",\n \"she\",\n \"we\",\n \"they\",\n \"what\",\n \"where\",\n \"when\",\n \"why\",\n \"how\",\n \"not\",\n \"no\",\n \"yes\",\n \"my\",\n \"your\",\n \"his\",\n \"her\",\n \"its\",\n \"our\",\n \"their\",\n \"me\",\n \"him\",\n \"her\",\n \"us\",\n \"them\",\n ]);\n\n comments.forEach((comment) => {\n const cleanText = comment.textOriginal\n .replace(/<[^>]*>/g, \"\")\n .replace(/https?:\\/\\/[^\\s]+/g, \"\")\n .replace(/[@#]\\w+/g, \"\")\n .toLowerCase();\n\n const words = cleanText.match(/\\b[a-z]{3,}\\b/g) || [];\n words.forEach((word) => {\n if (!stopWords.has(word)) {\n wordFrequency[word] = (wordFrequency[word] || 0) + 1;\n }\n });\n });\n\n return Object.entries(wordFrequency)\n .sort((a, b) => b[1] - a[1])\n .slice(0, 15)\n .map(([word, count]) => ({\n word,\n count,\n percentage: ((count / comments.length) * 100).toFixed(1) + \"%\",\n }));\n}\n\nfunction analyzeEngagement(comments) {\n const totalLikes = comments.reduce(\n (sum, comment) => sum + comment.likeCount,\n 0,\n );\n const totalReplies = comments.reduce(\n (sum, comment) => sum + comment.replyCount,\n 0,\n );\n const avgLikes = comments.length > 0 ? (totalLikes / comments.length) : 0;\n const maxLikes = Math.max(...comments.map((c) => c.likeCount), 0);\n\n return {\n totalLikes,\n totalReplies,\n averageLikesPerComment: parseFloat(avgLikes.toFixed(2)),\n highestLikeCount: maxLikes,\n commentsWithLikes: comments.filter((c) => c.likeCount > 0).length,\n commentsWithReplies: comments.filter((c) => c.replyCount > 0).length,\n engagementRate:\n ((comments.filter((c) => c.likeCount > 0 || c.replyCount > 0).length /\n comments.length) * 100).toFixed(1) + \"%\",\n };\n}\n\nfunction analyzeTimeDistribution(comments) {\n const now = new Date();\n const timeRanges = {\n lastHour: 0,\n last24Hours: 0,\n lastWeek: 0,\n lastMonth: 0,\n lastYear: 0,\n older: 0,\n };\n\n comments.forEach((comment) => {\n const commentDate = new Date(comment.publishedAt);\n const diffMs = now - commentDate;\n const diffHours = diffMs / (1000 * 60 * 60);\n const diffDays = diffHours / 24;\n\n if (diffHours <= 1) timeRanges.lastHour++;\n else if (diffHours <= 24) timeRanges.last24Hours++;\n else if (diffDays <= 7) timeRanges.lastWeek++;\n else if (diffDays <= 30) timeRanges.lastMonth++;\n else if (diffDays <= 365) timeRanges.lastYear++;\n else timeRanges.older++;\n });\n\n return { timeRanges };\n}\n\nfunction getTopComments(comments, limit = 5) {\n return comments\n .sort((a, b) => (b.likeCount + b.replyCount) - (a.likeCount + a.replyCount))\n .slice(0, limit)\n .map((comment, index) => ({\n rank: index + 1,\n author: comment.author,\n text: comment.textOriginal.substring(0, 200) +\n (comment.textOriginal.length > 200 ? \"...\" : \"\"),\n likes: comment.likeCount,\n replies: comment.replyCount,\n totalEngagement: comment.likeCount + comment.replyCount,\n }));\n}\n\nfunction getStatistics(comments) {\n const lengths = comments.map((c) => c.textOriginal.length);\n const wordCounts = comments.map((c) => c.textOriginal.split(\" \").length);\n\n return {\n totalComments: comments.length,\n averageLength: Math.round(\n lengths.reduce((a, b) => a + b, 0) / lengths.length,\n ),\n averageWordCount: Math.round(\n wordCounts.reduce((a, b) => a + b, 0) / wordCounts.length,\n ),\n uniqueAuthors: new Set(comments.map((c) => c.author)).size,\n totalLikes: comments.reduce((sum, c) => sum + c.likeCount, 0),\n totalReplies: comments.reduce((sum, c) => sum + c.replyCount, 0),\n };\n}\n\nfunction analyzeEmojis(comments) {\n const emojiRegex =\n /[\\u{1F300}-\\u{1F9FF}]|[\\u{2600}-\\u{26FF}]|[\\u{2700}-\\u{27BF}]/gu;\n const emojiCount = {};\n let totalEmojis = 0;\n let commentsWithEmojis = 0;\n\n comments.forEach((comment) => {\n const emojis = comment.textOriginal.match(emojiRegex) || [];\n if (emojis.length > 0) {\n commentsWithEmojis++;\n emojis.forEach((emoji) => {\n emojiCount[emoji] = (emojiCount[emoji] || 0) + 1;\n totalEmojis++;\n });\n }\n });\n\n const topEmojis = Object.entries(emojiCount)\n .sort((a, b) => b[1] - a[1])\n .slice(0, 10)\n .map(([emoji, count]) => ({ emoji, count }));\n\n return {\n totalEmojis,\n commentsWithEmojis,\n topEmojis,\n emojiUsageRate: ((commentsWithEmojis / comments.length) * 100).toFixed(1) +\n \"%\",\n };\n}\n\nfunction findQuestions(comments) {\n const questions = comments.filter((comment) =>\n comment.textOriginal.includes(\"?\") ||\n comment.textOriginal.toLowerCase().match(\n /^(what|where|when|why|how|who|which|is|are|can|could|would|will|do|does|did|should|has|have)/i,\n )\n );\n\n return {\n totalQuestions: questions.length,\n questionRate: ((questions.length / comments.length) * 100).toFixed(1) + \"%\",\n topQuestions: questions\n .sort((a, b) => b.likeCount - a.likeCount)\n .slice(0, 5)\n .map((q, index) => ({\n rank: index + 1,\n author: q.author,\n question: q.textOriginal.substring(0, 150) +\n (q.textOriginal.length > 150 ? \"...\" : \"\"),\n likes: q.likeCount,\n replies: q.replyCount,\n })),\n };\n}\n\nfunction analyzeAuthors(comments) {\n const authorStats = {};\n\n comments.forEach((comment) => {\n if (!authorStats[comment.author]) {\n authorStats[comment.author] = {\n commentCount: 0,\n totalLikes: 0,\n totalReplies: 0,\n };\n }\n authorStats[comment.author].commentCount++;\n authorStats[comment.author].totalLikes += comment.likeCount;\n authorStats[comment.author].totalReplies += comment.replyCount;\n });\n\n return {\n uniqueAuthors: Object.keys(authorStats).length,\n topContributors: Object.entries(authorStats)\n .sort((a, b) => b[1].totalLikes - a[1].totalLikes)\n .slice(0, 5)\n .map(([author, stats]) => ({ author, ...stats })),\n };\n}\n\nfunction analyzeCommentBreakdown(comments) {\n const topLevelComments = comments.filter((c) => !c.isReply);\n const replies = comments.filter((c) => c.isReply);\n\n return {\n totalFetched: comments.length,\n topLevelComments: topLevelComments.length,\n repliesFetched: replies.length,\n averageLikes:\n (comments.reduce((sum, c) => sum + c.likeCount, 0) / comments.length)\n .toFixed(1),\n engagementRate:\n ((comments.filter((c) => c.likeCount > 0 || c.replyCount > 0).length /\n comments.length) * 100).toFixed(1) + \"%\",\n };\n}\n\nfunction analyzeTeacherFeedback(comments) {\n const teacherKeywords = {\n positive: [\n \"great teacher\",\n \"excellent explanation\",\n \"clear\",\n \"helpful\",\n \"amazing instructor\",\n ],\n negative: [\n \"confusing\",\n \"too fast\",\n \"unclear\",\n \"bad explanation\",\n \"hard to follow\",\n ],\n };\n\n let teacherMentions = 0;\n let positiveTeacher = 0;\n let negativeTeacher = 0;\n\n comments.forEach((comment) => {\n const text = comment.textOriginal.toLowerCase();\n\n if (\n text.includes(\"teacher\") || text.includes(\"instructor\") ||\n text.includes(\"you\")\n ) {\n teacherMentions++;\n\n teacherKeywords.positive.forEach((keyword) => {\n if (text.includes(keyword)) positiveTeacher++;\n });\n\n teacherKeywords.negative.forEach((keyword) => {\n if (text.includes(keyword)) negativeTeacher++;\n });\n }\n });\n\n return {\n totalTeacherMentions: teacherMentions,\n positiveTeacherFeedback: positiveTeacher,\n negativeTeacherFeedback: negativeTeacher,\n teacherRating: teacherMentions > 0\n ? ((positiveTeacher - negativeTeacher) / teacherMentions * 100).toFixed(\n 1,\n ) + \"%\"\n : \"No data\",\n };\n}\n\nfunction analyzeLearningOutcomes(comments) {\n const outcomeKeywords = {\n success: [\n \"finally understood\",\n \"got it\",\n \"makes sense now\",\n \"cleared my doubt\",\n \"helped me pass\",\n ],\n struggle: [\n \"still confused\",\n \"dont get it\",\n \"need help\",\n \"lost\",\n \"difficult\",\n ],\n };\n\n let successIndicators = 0;\n let struggleIndicators = 0;\n\n comments.forEach((comment) => {\n const text = comment.textOriginal.toLowerCase();\n\n outcomeKeywords.success.forEach((keyword) => {\n if (text.includes(keyword)) successIndicators++;\n });\n\n outcomeKeywords.struggle.forEach((keyword) => {\n if (text.includes(keyword)) struggleIndicators++;\n });\n });\n\n return {\n successIndicators,\n struggleIndicators,\n learningSuccessRate: comments.length > 0\n ? ((successIndicators / comments.length) * 100).toFixed(1) + \"%\"\n : \"0%\",\n };\n}\n\nfunction generateEnhancedDashboardHTML(video, analysis) {\n return `\n \n \n \n Enhanced EdTech Analysis - ${video.title}\n \n \n \n \n \n

\n \n \n

${\n analysis.breakdown?.totalFetched || 0\n }

Student Comments Analyzed

${\n getOverallTeacherScore(analysis.aiInsights?.teacherPerformance)\n }

Overall Teacher Rating

${\n analysis.edtech?.learningOutcomes?.learningSuccessRate || \"0%\"\n }

Learning Success Rate

${\n analysis.aiInsights?.passesCompleted || 0\n }/5

AI Analysis Passes

\n\n

🎓 AI Teacher Performance Analysis

Overall Rating: ${\n analysis.aiInsights?.teacherPerformance?.overallTeacherRating?.score ||\n \"Processing...\"\n }

Teaching Style: ${\n analysis.aiInsights?.teacherPerformance?.teachingPersonality ||\n \"AI analysis in progress...\"\n }

\n\n

📊 Statistical Analysis Summary

😊 Sentiment Distribution

Positive: ${\n analysis.sentiment?.positive?.percentage || \"0%\"\n } | Neutral: ${analysis.sentiment?.neutral?.percentage || \"0%\"} | Negative: ${\n analysis.sentiment?.negative?.percentage || \"0%\"\n }

Overall Score: ${\n analysis.sentiment?.overallScore || \"0\"\n }

❓ Questions Analysis

Total Questions: ${\n analysis.questions?.totalQuestions || 0\n } (${analysis.questions?.questionRate || \"0%\"})

👥 Community Engagement

Unique Authors: ${\n analysis.statistics?.uniqueAuthors || 0\n }

Avg Engagement: ${\n analysis.engagement?.averageLikesPerComment || 0\n } likes/comment

\n \n \n `;\n}\n\nfunction getOverallTeacherScore(teacherPerformance) {\n return teacherPerformance?.overallTeacherRating?.score || \"Processing...\";\n}\n\nfunction formatNumber(num) {\n if (num >= 1000000) return (num / 1000000).toFixed(1) + \"M\";\n if (num >= 1000) return (num / 1000).toFixed(1) + \"K\";\n return num.toString();\n}\n\nfunction generateMainInterface() {\n return `\n \n \n \n Enhanced EdTech Comment Analyzer\n \n \n \n \n \n

\n \n \n

🚀 Start Enhanced Analysis

Get comprehensive educational insights with our advanced multi-pass AI system powered by Gemini 2.5 Pro!

\n \n \n \n \n

\n\n

🎓 Multi-Pass AI: 5 specialized analysis passes for maximum insight depth

🧠 35+ Categories: Comprehensive educational analytics

👥 Multi-User Ready: Built for educational institutions

\n \n \n \n \n `;\n}\n\nfunction generateErrorHTML(error) {\n return `

Error: ${error}

`;\n}\n\nfunction generateQuotaErrorHTML() {\n return `

API Quota Exceeded

Please try again later.

`;\n}",[],[183],"files",[154,172,181],"counts",{"_195":32,"_196":197,"_198":32,"_199":200,"_204":205},"pulls","branches",1,"forks","envVars",{"_201":202,"_203":32},"count",2,"emptyCount","connections",{"_201":32,"_206":32},"unfilledCount","contents",[],"file",{"_105":155,"_158":142,"_156":117,"_96":100,"_165":166,"_163":164,"_101":162,"_157":-5,"_107":211,"_159":102,"_168":-5,"_99":212},["D",1757364971855],[100],"upstreamProject","upstreamBranch","emptyEnvVars","isNew","flags",[],"routes/_app.x.$handle.$name.branch.$branch.version.$version.code.$",{"_94":95,"_96":97,"_98":44,"_101":102,"_99":100,"_103":221,"_152":226,"_191":236,"_209":237,"_207":240,"_241":-5,"_242":-5,"_243":-5,"_244":-5,"_245":246,"_199":-5},{"_105":106,"_96":97,"_107":222,"_109":-5,"_110":22,"_111":112,"_113":-5,"_114":-5,"_14":115,"_116":117,"_118":119,"_120":119,"_121":-5,"_122":32,"_16":123,"_124":125,"_126":125,"_127":128,"_129":128,"_130":128,"_131":125,"_132":125,"_23":223,"_136":224,"_139":225,"_151":22},["D",1756638234448],{"_94":95,"_134":135},{"_94":95,"_138":135,"_14":115},{"_101":141,"_96":44,"_105":142,"_143":106,"_144":-5,"_145":-5,"_146":-5,"_147":-5,"_148":-5,"_149":97,"_150":95},[227,230,233],{"_105":155,"_96":100,"_156":117,"_157":-5,"_158":142,"_159":102,"_160":22,"_107":161,"_101":162,"_163":164,"_165":166,"_167":22,"_168":-5,"_169":228,"_99":229},[],[100],{"_105":173,"_96":174,"_156":175,"_157":-5,"_158":142,"_159":176,"_160":119,"_107":177,"_101":162,"_163":164,"_165":178,"_167":22,"_168":-5,"_169":231,"_99":232},[],[174],{"_105":182,"_96":183,"_156":184,"_157":-5,"_158":142,"_159":185,"_160":119,"_107":186,"_101":187,"_163":164,"_165":188,"_167":22,"_168":-5,"_169":234,"_99":235},[],[183],[227,230,233],{"_105":155,"_96":100,"_156":117,"_157":-5,"_158":142,"_159":102,"_160":22,"_107":238,"_101":162,"_163":164,"_165":166,"_167":22,"_168":-5,"_99":239},["D",1757364971855],[100],[],"upstream","pull","ahead","behind","templates",[],"actionData","errors"]

🎓 YouTube Comment Analyzer

✨ What You'll Get:

✅ Analysis Complete!

${videoInfo.video_title || videoUrl}

Overall Grade

${grades.overall || 'N/A'}

Engagement

${(metrics.comment_to_view_ratio || 0).toFixed(1)}

Questions

${(metrics.question_ratio || 0).toFixed(1)}%

Success Rate

${(metrics.success_signal_ratio || 0).toFixed(1)}%

❌ Analysis Failed

🤖 Analyzing YouTube Comments...

❌ Analysis Failed

✅ Analysis Complete!

Overall Grade

\n {grades.overall || 'N/A'}\n

Engagement

\n {metrics.comment_to_view_ratio?.toFixed(1) || 0}\n

Questions

\n {metrics.question_ratio?.toFixed(1) || 0}%\n

Success Rate

\n {metrics.success_signal_ratio?.toFixed(1) || 0}%\n

\n ❓ Student Questions ({insights.student_questions.total_questions})\n

💡 Recommendations

\n 🎓 YouTube Comment Analyzer\n

✨ What You'll Get:

🎓 AI Teacher Performance Analysis

📊 Statistical Analysis Summary

😊 Sentiment Distribution

❓ Questions Analysis

👥 Community Engagement

🎓 Enhanced EdTech Analyzer

🚀 Start Enhanced Analysis

Error: ${error}

API Quota Exceeded

Ashborn

YOUTUBECOMMENTANALYSIS