🎓 YouTube Comment Analyzer

Advanced AI-powered analysis for educational YouTube content with comprehensive insights and metrics.

\n \n \n \n

✨ Comprehensive Analysis Features:

📊 Educational engagement metrics

❓ Student questions analysis

💡 Content improvement recommendations

👨‍🏫 Teacher satisfaction insights

📈 Learning effectiveness scores

🎯 Actionable feedback for educators

🧠 AI-powered sentiment analysis

📋 Detailed comment breakdowns

\n \n \n `;\n}\n\nfunction renderDetailedResultPage(result, videoUrl) {\n if (!result.success) {\n return renderErrorPage(result.error);\n }\n\n const analysis = result.analysis_result;\n const videoInfo = analysis.video_info || {};\n const summary = analysis.analysis_summary || {};\n const metrics = analysis.educational_metrics || {};\n const scores = metrics.scores || {};\n const grades = metrics.grades || {};\n const insights = analysis.actionable_insights || {};\n const recommendations = analysis.recommendations || [];\n const details = analysis.data_details || {};\n\n return `\n \n \n \n \n \n Comprehensive Analysis Results - YouTube Comment Analyzer\n \n \n \n

\n \n \n \n \n

📊 Analysis Overview

\n Comments Analyzed:
\n ${summary.total_comments_analyzed || 0}\n

\n Analysis Method:
\n ${summary.analysis_method || 'AI Analysis'}\n

\n Processing Time:
\n ${analysis.processing_time || 'N/A'}\n

\n AI Model:
\n ${details.ai_model || 'Google Gemini'}\n

\n Coverage:
\n ${summary.coverage || 'Complete Analysis'}\n

\n Analysis Version:
\n ${details.analysis_version || 'v2.0'}\n

\n\n \n

Overall Grade

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

Quality Score: ${scores.comment_quality_score || 0}/10

\n \n

Engagement Rate

${(scores.comment_to_view_ratio || 0).toFixed(2)}

per 1000 views

\n \n

Question Rate

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

student questions

\n \n

Learning Success

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

success signals

\n \n

Teacher Satisfaction

${(scores.teacher_satisfaction_ratio || 0).toFixed(1)}%

positive feedback

\n \n

Content Quality

${(scores.substantive_ratio || 0).toFixed(0)}%

substantive comments

\n\n \n

\n 📈 Detailed Educational Metrics & Grades\n

Performance Grades

\n ${Object.entries(grades).map(([key, value]) => {\n const gradeClass = value === 'Excellent' ? 'grade-excellent' : \n value === 'Good' ? 'grade-good' : 'grade-needs-attention';\n return `${key.replace('_', ' ')}: ${value}`;\n }).join('')}\n

\n \n

Score Breakdown

\n ${Object.entries(scores).map(([key, value]) => `\n

${key.replace(/_/g, ' ')}

${typeof value === 'number' ? value.toFixed(2) : value}

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

\n \n ${metrics.metric_explanations ? `\n

Metric Explanations

\n ${Object.entries(metrics.metric_explanations).map(([key, explanation]) => `\n

\n ${key.replace(/_/g, ' ')}: ${explanation}\n

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

\n ` : ''}\n

\n\n \n ${insights.student_questions ? `\n

\n ❓ Student Questions Analysis\n

Total Questions

${insights.student_questions.total_questions || 0}

Question Topics

${(insights.student_questions.question_topics || []).length}

Total Requests

${insights.content_requests.total_requests || 0}

Requested Topics

${(insights.content_requests.requested_topics || []).length}

Popular Themes

${(insights.content_requests.popular_themes || []).length}

\n \n ${insights.content_requests.total_requests === 0 ? `\n

\n No Specific Requests: Students haven't made specific content requests. Consider asking what topics they'd like to see covered.\n

\n ` : `\n

Most Requested Topics:

\n ${(insights.content_requests.requested_topics || []).map(topic => `\n

📚 ${topic}

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

\n ` : ''}\n\n \n ${insights.teacher_satisfaction ? `\n

\n 👨‍🏫 Teacher Satisfaction Analysis\n

Overall Sentiment

${insights.teacher_satisfaction.overall_sentiment || 'N/A'}

Satisfaction Score

${(insights.teacher_satisfaction.satisfaction_score || 0).toFixed(1)}%

Happy Students

${insights.teacher_satisfaction.happy_students || 0}

Teacher Rating

${insights.teacher_satisfaction.teacher_rating || 'N/A'}

Praise Comments

${insights.teacher_satisfaction.praise_comments || 0}

Complaint Comments

${insights.teacher_satisfaction.complaint_comments || 0}

\n \n ${insights.teacher_satisfaction.feedback_summary ? `\n

Feedback Summary

\n ${insights.teacher_satisfaction.feedback_summary}\n

\n ` : ''}\n

\n ` : ''}\n\n \n ${insights.sentiment_breakdown ? `\n

\n 😊 Sentiment Analysis Breakdown\n

Positive Comments

${insights.sentiment_breakdown.positive || 0}

Neutral Comments

${insights.sentiment_breakdown.neutral || 0}

Negative Comments

${insights.sentiment_breakdown.negative || 0}

\n ` : ''}\n\n \n ${insights.engagement_analysis ? `\n

\n 🔍 Advanced Engagement Analysis\n

Engagement Level

${insights.engagement_analysis.engagement_level || 'N/A'}

High Value Comments

${insights.engagement_analysis.high_value_comments || 0}

\n \n ${insights.most_liked_comment ? `\n

Most Liked Comment

\n Comment: ${insights.most_liked_comment.comment_text}
\n 👤 ${insights.most_liked_comment.author_name} • 👍 ${insights.most_liked_comment.like_count} likes • 📅 ${insights.most_liked_comment.published_at}
\n Sentiment: ${insights.most_liked_comment.sentiment} | Educational Value: ${insights.most_liked_comment.educational_value}\n

\n ` : ''}\n

\n ` : ''}\n\n \n ${recommendations.length > 0 ? `\n

\n 💡 AI-Generated Recommendations\n

\n ${recommendations.map((rec, i) => {\n const type = rec.startsWith('🟢') ? 'success' : \n rec.startsWith('🟡') ? 'warning' : \n rec.startsWith('🔴') ? 'danger' : 'info';\n return `

${rec}

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

\n ` : ''}\n\n \n

\n 🔧 Technical Analysis Details\n

Processing Batches

${details.processing_batches || 1}

Metrics Calculated

${details.metrics_calculated || 0}

Insights Generated

${details.insights_generated || 0}

Processing Date

${details.processing_date || 'N/A'}

\n \n

📄 Complete Raw Analysis Data (Click to expand)

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

\n\n ← Analyze Another Video\n

\n \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",[],[151],{"_103":171,"_95":172,"_152":173,"_154":-5,"_155":137,"_156":174,"_157":158,"_105":175,"_100":176,"_161":162,"_163":177,"_165":22,"_166":-5,"_167":178,"_98":179},"c6eb7018-8cf5-11f0-b7a0-0224a6c84d84","main.tsx","2f26960a-865a-11f0-997f-0224a6c84d84",27,["D",1757364768055],9,"/** @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;",[],[172],{"_103":181,"_95":99,"_152":182,"_154":-5,"_155":137,"_156":183,"_157":158,"_105":184,"_100":185,"_161":162,"_163":186,"_165":22,"_166":-5,"_167":187,"_98":188},"d5a85978-88b7-11f0-88a6-0224a6c84d84","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}",[],[99],"files",[149,170,180],"counts",{"_193":32,"_194":195,"_196":32,"_197":198},"pulls","branches",1,"forks","envVars",2,"contents",[],"file",{"_103":181,"_155":137,"_152":182,"_95":99,"_163":186,"_161":162,"_100":185,"_154":-5,"_105":203,"_156":183,"_166":-5,"_98":204},["D",1756898359328],[99],"upstreamProject","upstreamBranch","emptyEnvVars","isNew","flags",[],"routes/_app.x.$handle.$name.branch.$branch.history_.$",{"_93":94,"_95":96,"_97":43,"_98":99,"_101":213,"_201":218,"_221":222,"_259":260,"_270":-7,"_271":32,"_272":22},{"_103":104,"_95":96,"_105":214,"_107":-5,"_108":22,"_109":110,"_111":-5,"_112":-5,"_14":113,"_114":-5,"_115":22,"_116":-5,"_117":32,"_16":118,"_119":120,"_121":120,"_122":123,"_124":123,"_125":123,"_126":120,"_127":120,"_23":215,"_131":216,"_134":217,"_146":22},["D",1756638234448],{"_93":94,"_129":130},{"_93":94,"_133":130},{"_100":136,"_95":43,"_103":137,"_138":104,"_139":-5,"_140":-5,"_141":-5,"_142":-5,"_143":-5,"_144":96,"_145":94},{"_103":181,"_95":99,"_152":182,"_154":-5,"_155":137,"_156":183,"_157":158,"_105":219,"_100":185,"_161":162,"_163":186,"_165":22,"_166":-5,"_98":220},["D",1756898359328],[99],"history",[223,225,231,237,242,247,251,255],{"_103":181,"_155":137,"_152":182,"_95":99,"_163":186,"_161":162,"_100":185,"_154":-5,"_105":224,"_156":183,"_166":-5},["D",1756898359328],{"_103":226,"_155":137,"_152":182,"_95":99,"_163":186,"_161":227,"_100":228,"_154":-5,"_105":229,"_156":230,"_166":-5},"d2424578-88b7-11f0-97bf-0224a6c84d84","script",6,["D",1756898353631],22,{"_103":232,"_155":137,"_152":182,"_95":99,"_163":233,"_161":227,"_100":234,"_154":-5,"_105":235,"_156":236,"_166":-5},"23e3837a-88b7-11f0-852a-0224a6c84d84","// 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: ${JSON.stringify(predictiveComments)}\n\nProvide predictive analysis:\n{\n \"studentSuccess\": {\"probability\": \"High/Medium/Low\", \"indicators\": [\"indicator1\", \"indicator2\"], \"risk_factors\": [\"risk1\", \"risk2\"]},\n \"engagementTrends\": {\"trajectory\": \"Increasing/Stable/Declining\", \"forecast\": \"detailed forecast\", \"interventions\": [\"intervention1\", \"intervention2\"]},\n \"learningOutcomes\": {\"projected_success_rate\": \"X%\", \"improvement_areas\": [\"area1\", \"area2\"], \"timeline\": \"detailed timeline\"},\n \"recommendations\": {\"immediate\": [\"action1\", \"action2\"], \"short_term\": [\"action3\", \"action4\"], \"long_term\": [\"action5\", \"action6\"]}\n}`;\n\n return await processGeminiRequest(predictivePrompt, geminiApiKey);\n}\n\n// Continue with all the helper functions...\n// [All the remaining functions from the previous code - processGeminiRequest, rate limiting, YouTube API functions, analysis functions, dashboard generation, etc.]\n\nasync function processGeminiRequest(prompt, geminiApiKey) {\n const enhancedPrompt = `\nCONTEXT: You are analyzing educational YouTube comments with 20+ years of expertise.\n\nINSTRUCTIONS:\n- Use EVIDENCE-BASED reasoning for every claim\n- Provide SPECIFIC student quotes to support analysis\n- Give MEASURABLE recommendations with clear action steps\n- Consider DIVERSE learning styles and backgrounds\n- Focus on ACTIONABLE insights for educational improvement\n\nQUALITY STANDARDS:\n- Every score must be justified with evidence from student comments\n- Every recommendation must be specific and implementable\n- Every insight must cite actual student feedback as proof\n- Analysis must be educationally sound and research-based\n\n${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\n// Add all remaining helper functions here (analyzeSentiment, analyzeCommentsEdTech, generateEnhancedDashboardHTML, etc.)\n// Due to space constraints, I'm including the key functions. You'll need to add the rest from the previous response.\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 generateEnhancedDashboardHTML(video, analysis) {\n return `\n\nEnhanced EdTech Analysis\n\n

Enhanced Analysis for: ${video.title}

Analysis completed with ${\n analysis.aiInsights?.passesCompleted || 0\n } AI passes.

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

\n\n`;\n}\n\nfunction generateMainInterface() {\n return `\n\nEnhanced EdTech Analyzer\n\n

🎓 Enhanced EdTech Analyzer

\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}\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}\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

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}\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}",5,["D",1756898061085],21,{"_103":238,"_155":137,"_152":182,"_95":99,"_163":233,"_161":227,"_100":239,"_154":-5,"_105":240,"_156":241,"_166":-5},"23bddb2a-88b7-11f0-b90b-0224a6c84d84",4,["D",1756898060841],20,{"_103":243,"_155":137,"_152":182,"_95":99,"_163":72,"_161":227,"_100":244,"_154":-5,"_105":245,"_156":246,"_166":-5},"bc15ad5e-88b6-11f0-b46f-0224a6c84d84",3,["D",1756897886896],19,{"_103":248,"_155":137,"_152":182,"_95":99,"_163":72,"_161":227,"_100":198,"_154":-5,"_105":249,"_156":250,"_166":-5},"bba2672c-88b6-11f0-b0d4-0224a6c84d84",["D",1756897886177],18,{"_103":252,"_155":137,"_152":182,"_95":99,"_163":72,"_161":162,"_100":195,"_154":-5,"_105":253,"_156":254,"_166":-5},"dc8c5e6c-88b5-11f0-b082-0224a6c84d84",["D",1756897511902],17,{"_103":256,"_155":137,"_152":182,"_95":99,"_163":72,"_161":227,"_100":32,"_154":-5,"_105":257,"_156":258,"_166":-5},"cb71ab46-88b5-11f0-b66d-0224a6c84d84",["D",1756897483207],16,"versions",[261,263,264,265,266,267,268,269],{"_201":223,"_262":225},"previous",{"_201":225,"_262":231},{"_201":231,"_262":237},{"_201":237,"_262":242},{"_201":242,"_262":247},{"_201":247,"_262":251},{"_201":251,"_262":255},{"_201":255,"_262":-5},"versionNumber","page","hasNext","actionData","errors"]

🎓 YouTube Comment Analyzer

✨ Comprehensive Analysis Features:

✅ Comprehensive Educational Analysis Complete!

📊 Analysis Overview

Overall Grade

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

Engagement Rate

${(scores.comment_to_view_ratio || 0).toFixed(2)}

Question Rate

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

Learning Success

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

Teacher Satisfaction

${(scores.teacher_satisfaction_ratio || 0).toFixed(1)}%

Content Quality

${(scores.substantive_ratio || 0).toFixed(0)}%

Performance Grades

Score Breakdown

${key.replace(/_/g, ' ')}

Metric Explanations

Total Questions

Question Topics

Top Questions

Total Requests

Requested Topics

Popular Themes

Most Requested Topics:

Overall Sentiment

Satisfaction Score

Happy Students

Teacher Rating

Praise Comments

Complaint Comments

Feedback Summary

Positive Comments

Neutral Comments

Negative Comments

Engagement Level

High Value Comments

Most Liked Comment

Processing Batches

Metrics Calculated

Insights Generated

Processing Date

📄 Complete Raw Analysis Data (Click to expand)

❌ 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

Enhanced Analysis for: ${video.title}

🎓 Enhanced EdTech Analyzer

Error: ${error}

API Quota Exceeded

🎓 AI Teacher Performance Analysis

📊 Statistical Analysis Summary

😊 Sentiment Distribution

❓ Questions Analysis

👥 Community Engagement

🎓 Enhanced EdTech Analyzer

History for new-file-4421.tsx